From e18794d504c239e4102d315b0f7b4d0cd863e03f Mon Sep 17 00:00:00 2001 From: gagolews Date: Thu, 29 Dec 2022 11:04:02 +1100 Subject: [PATCH] v0.1.12 --- CITATION.cff | 3 +- LICENSE | 2 +- README.md | 13 +++- docs/chapter/000-preface.html | 29 +++---- docs/chapter/110-basics.html | 19 ++--- docs/chapter/120-numeric.html | 27 +++---- docs/chapter/130-logical.html | 17 ++-- docs/chapter/140-list.html | 11 +-- docs/chapter/150-indexing.html | 13 ++-- docs/chapter/160-character.html | 19 ++--- docs/chapter/170-function.html | 15 ++-- docs/chapter/180-flow.html | 13 ++-- docs/chapter/210-design.html | 29 +++---- docs/chapter/220-s3.html | 21 ++--- docs/chapter/230-matrix.html | 23 +++--- docs/chapter/240-data-frame.html | 17 ++-- docs/chapter/250-graphics.html | 11 +-- docs/chapter/310-compile.html | 11 +-- docs/chapter/320-language.html | 11 +-- docs/chapter/330-environment.html | 11 +-- docs/chapter/340-eval-expr.html | 11 +-- docs/chapter/350-eval-fun.html | 11 +-- docs/chapter/998-changelog.html | 13 ++-- docs/chapter/999-bibliography.html | 107 +++++++++++++------------- docs/chapter/chapter-header-motd.html | 11 +-- docs/deepr.pdf | Bin 1929344 -> 1929739 bytes docs/genindex.html | 4 +- docs/index.html | 50 +++++++++--- docs/search.html | 4 +- docs/searchindex.js | 2 +- 30 files changed, 296 insertions(+), 232 deletions(-) diff --git a/CITATION.cff b/CITATION.cff index 4b1471b..b1cb736 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -31,9 +31,10 @@ authors: website: "https://www.gagolewski.com" preferred-citation: type: book - year: 2022 + year: 2023 title: "Deep R Programming" url: "https://deepr.gagolewski.com/" + isbn: "978-0-6455719-2-9" authors: - family-names: Gagolewski given-names: Marek diff --git a/LICENSE b/LICENSE index 722556e..79dc9e4 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ Deep R Programming -Copyright (C) 2022, Marek Gagolewski +Copyright (C) 2022-2023, Marek Gagolewski =========================================================================== diff --git a/README.md b/README.md index f4e175f..ff09cdd 100644 --- a/README.md +++ b/README.md @@ -27,9 +27,18 @@ You can read it at: * (a browser-friendly version) * (PDF) + + + **Please spread the news about this project.** - +Consider citing this book as: +[Gagolewski M.][1] (2023), *Deep R Programming*, +Zenodo, Melbourne, + +ISBN: 978-0-6455719-2-9, +URL: . + Any remarks and bug fixes are appreciated. Please submit them via this repository's *Issues* tracker. Thank you. @@ -68,7 +77,7 @@ and many [others](https://github.com/gagolews). -------------------------------------------------------------------------------- -Copyright (C) 2022, [Marek Gagolewski][1]. Some rights reserved. +Copyright (C) 2022–2023, [Marek Gagolewski][1]. Some rights reserved. This material is licensed under the Creative Commons [Attribution-NonCommercial-NoDerivatives 4.0 International][2] License diff --git a/docs/chapter/000-preface.html b/docs/chapter/000-preface.html index 6a007a6..9161eaa 100644 --- a/docs/chapter/000-preface.html +++ b/docs/chapter/000-preface.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -281,11 +282,11 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

+Also, check out my other book, Minimalist Data Wrangling with Python [20].

To R, or not to R

-

R [50] +

R [50] has been named the eleventh most dreaded programming language in the 2022 StackOverflow Developer Survey.

Also, it is a free app, so there must be something wrong with it, right?

@@ -344,14 +345,14 @@

R as a Language and an EnvironmentNote

R’s predecessor is the popular S system designed in the 1980s by John M. Chambers and his colleagues at Bell Labs S: -[3, 4, 8, 40]. +[3, 4, 8, 40]. R is called GNU S, a free, open-source version of its commercial counterpart developed in the mid-1990s2 by Robert Gentleman and Ross Ihaka of the Statistics Department, University of Auckland, and a large number of contributors; -see [7, 31] for some historical notes.

+see [7, 31] for some historical notes.

R has a C language-like syntax that involves the use of {curly braces}. Still, in principle, it is a beautiful, functional programming language: its design was heavily inspired by Scheme (see -[1] and Chapter 17 for more details). +[1] and Chapter 17 for more details). It is also somewhat object-oriented (Chapter 10).

@@ -518,7 +519,7 @@

🚧 Classification of R Data Types and Book StructureInformation Sciences, Knowledge-Based Systems, IEEE Transactions on Fuzzy Systems, and Journal of Informetrics.

In my “spare” time, I write books for my students (also check out my -Minimalist Data Wrangling with Python [20]) +Minimalist Data Wrangling with Python [20]) and develop open-source (libre) data analysis software, such as stringi (one of the most often downloaded R packages), @@ -530,7 +531,7 @@

🚧 Classification of R Data Types and Book StructureAcknowledgements

Deep R Programming is based on my experience as an author of a quite successful Polish textbook -Programowanie w języku R (see [19]) +Programowanie w języku R (see [19]) which was published by PWN (1st ed. 2014, 2nd ed. 2016). The current book is an entirely different work. However, its predecessor served as an excellent testbed for many ideas conveyed here.

@@ -548,7 +549,7 @@

AcknowledgementsMyST, Sphinx, and TeX (XeLaTeX). -Code chunks were processed with the R package knitr [44]. +Code chunks were processed with the R package knitr [44]. All figures were plotted with the low-level graphics package using the author’s own style template. A little help from Makefiles, custom shell scripts, @@ -574,7 +575,7 @@

Acknowledgementssource code is available on CRAN), was already quite feature-rich (e.g., implemented S3 methods, formulae, and data frames -introduced in the 1991 version of S [8]).

+introduced in the 1991 version of S [8]).

3

The author taught similar courses for his wonderfully @@ -598,7 +599,7 @@

Acknowledgements[5, 10, 35, 41, 42, 43, 49], etc. +e.g., [5, 10, 35, 41, 42, 43, 49], etc. Some of them are also freely available.

6
@@ -624,13 +625,13 @@

Acknowledgements

- Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/110-basics.html b/docs/chapter/110-basics.html index d9c135d..c36dca8 100644 --- a/docs/chapter/110-basics.html +++ b/docs/chapter/110-basics.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -287,7 +288,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

+Also, check out my other book, Minimalist Data Wrangling with Python [20].

1.1. Hello, World!

@@ -421,7 +422,7 @@

1.2.4. Weaving: Automatic Report Generat (text, tables, plots, auxiliary files) synchronised with their generating code and data.

utils::Sweave (the Sweave function -from the utils package) and knitr [44] +from the utils package) and knitr [44] are two example template processors that evaluate R code chunks within documents written in LaTeX, HTML, or other markup languages. @@ -540,7 +541,7 @@

1.2.4. Weaving: Automatic Report Generat There, editable and executable code chunks and results they generate can be kept together in a single .ipynb (JSON) file; see Figure 1.2 for an illustration -and Chapter 1 of [20] for a quick introduction +and Chapter 1 of [20] for a quick introduction (from the Python language kernel perspective).

This environment is quite convenient for live coding (e.g., for teachers) or performing exploratory data analyses. @@ -616,7 +617,7 @@

1.3. Atomic Vectors at a GlanceMoreover, the fact that vectors are the core part of the R language makes their use very natural – as opposed to the languages that require special add-ons for vector processing, -e.g., numpy for Python [29]. +e.g., numpy for Python [29]. By learning different ways to process them as a whole, instead of one element at a time, we will assure that our ideas can quickly be turned into working code @@ -721,7 +722,7 @@

1.5. Exercises
4

The idea dates back to Knuth’s literate programming -concept; see [32].

+concept; see [32].

@@ -741,13 +742,13 @@

1.5. Exercises

- Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/120-numeric.html b/docs/chapter/120-numeric.html index 2c21984..2078d12 100644 --- a/docs/chapter/120-numeric.html +++ b/docs/chapter/120-numeric.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -304,7 +305,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

+Also, check out my other book, Minimalist Data Wrangling with Python [20].

In this chapter, we discuss the uttermost common operations on numeric vectors. They are so fundamental that we will also find them @@ -319,7 +320,7 @@ More complex building blocks can either be reduced to a creative combination of the former or be easily found – should the need arise – in a number additional packages or libraries -(e.g., the GNU GSL [23]).

+(e.g., the GNU GSL [23]).

A solid understanding of base R programming is necessary for the effective dealing with the popular packages (such as data.table, dplyr, @@ -589,8 +590,8 @@

2.1.5. Generating Pseudorandom Numbers

Let us stress that the numbers we obtain are merely pseudorandom, because they are generated algorithmically. -R uses the Mersenne-Twister MT19937 method [36] by default; -see help("RNG") and [16, 24, 33]. +R uses the Mersenne-Twister MT19937 method [36] by default; +see help("RNG") and [16, 24, 33]. By setting the seed of the random number generator, i.e., re-setting its state to a given one, we can obtain results that are reproducible.

@@ -948,7 +949,7 @@

2.3.3. Natural Exponential Function and

  • \(e^{x+y} = e^x\cdot e^y\).

    • For more properties like these, -take a glance at Chapter 4 of the freely available handbook [38].

    +take a glance at Chapter 4 of the freely available handbook [38].

    For the logarithm to a different base, say \(\log_{10} x\), we can call:

    log(c(0, 1, 10, 100, 1000, 1e10), 10)  # or log(..., base=10)
@@ -1167,11 +1168,11 @@ 
    2.3.5. Special Functions (*)\(\Gamma\) function grows so rapidly that already gamma(172)
 yields Inf. It is due to the fact that a computer’s arithmetic
 is not infinitely precise; compare Section 3.2.3.
    
-
    Special functions are plentiful; see the open-access [38]
+
    Special functions are plentiful; see the open-access [38]
 for one of the most definitive references
-(and also [2] for its predecessor).
-R package gsl [28] provides a vectorised interface
-to the famous GNU GSL [23] library, which implements
+(and also [2] for its predecessor).
+R package gsl [28] provides a vectorised interface
+to the famous GNU GSL [23] library, which implements
 many of them.
    
 
    
 
@@ -1758,13 +1759,13 @@ 
    2.5. Exercises
     
    
-        Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0.
+        Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0.
 
     Built with Sphinx
     and a customised rtd
     theme.
       
-        Last updated on 2022-12-28T15:36:00+1100.
+        Last updated on 2022-12-29T11:00:10+1100.
       
 
 
diff --git a/docs/chapter/130-logical.html b/docs/chapter/130-logical.html
index a543f6f..cdd6f44 100644
--- a/docs/chapter/130-logical.html
+++ b/docs/chapter/130-logical.html
@@ -10,8 +10,8 @@
   
 
 
-
-
+
+
 
 
 
@@ -28,6 +28,7 @@
 
 
 
+
 
   
   
@@ -294,7 +295,7 @@
 Although available online, it is a whole course;
 it should be read from the beginning to the end.
 Refer to the Preface for general introductory remarks.
-Also, check out my other book, Minimalist Data Wrangling with Python [20].
    
+Also, check out my other book, Minimalist Data Wrangling with Python [20].
    
 
    
 
    There are three logical constants in R. Wait… how many?
    
 
    
@@ -485,8 +486,8 @@ 
    3.2.2. Testing for [27, 30, 33]
-([26] can be of particular interest
+
    For discussion, see [27, 30, 33]
+([26] can be of particular interest
 to the general statistical/data analysis audience).

    Can we do anything about these issues?

    @@ -883,7 +884,7 @@

    3.5. Exercises

    What is the purpose of very specific functions such as log1p and expm1 (see their help page) and many other ones listed in, e.g., the GNU GSL library -[23]? +[23]? Is our referring to them a violation of the beloved “let us be minimalistic” approach?

  • If we know that \(x\) may be subject to error, @@ -961,13 +962,13 @@

    3.5. Exercises

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/140-list.html b/docs/chapter/140-list.html index d4b0a8a..4f56183 100644 --- a/docs/chapter/140-list.html +++ b/docs/chapter/140-list.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -297,7 +298,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    • After two brain-teasing chapters, it is time to cool it down a little. In this more technical part, we will introduce lists, which serve @@ -1168,13 +1169,13 @@

    4.5. Exercises

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/150-indexing.html b/docs/chapter/150-indexing.html index ea3ee4e..7dceb74 100644 --- a/docs/chapter/150-indexing.html +++ b/docs/chapter/150-indexing.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -308,7 +309,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    We now know plenty of ways to process vectors in their entirety, but how to extract and replace specific parts thereof? We will be @@ -1337,7 +1338,7 @@

    5.4.6. Counting Index Occurrences

    Below we explore some common patterns; see also Section 1.3 -in [48].

    +in [48].

    5.5.1. c

    First, c drops5 all @@ -1697,13 +1698,13 @@

    5.6. Exercises

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/160-character.html b/docs/chapter/160-character.html index a97590d..a200223 100644 --- a/docs/chapter/160-character.html +++ b/docs/chapter/160-character.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -308,7 +309,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    Text is a universal, portable, economic, and efficient means of interacting between humans and computers @@ -429,7 +430,7 @@

    6.1.1. Inputting Individual Stringslatin1 or cp1252), but they can be mixed with Unicode seamlessly. See help("Encoding"), -help("iconv"), and [21] for discussion.

    +help("iconv"), and [21] for discussion.

    Nevertheless, certain output devices (web browsers, LaTeX renderers, text terminals) might be unable to display each and every Unicode @@ -1010,11 +1011,11 @@

    6.3.3. Ordering StringsImportant

    (*) As we have mentioned, many string operations in base R are not necessarily -portable. The stringx package [22] defines drop-in, +portable. The stringx package [22] defines drop-in, “fixed” replacements therefor. They are based on the International Components for Unicode (ICU) library, which is a de facto standard for the processing of Unicode text, -and the R package stringi; see [21].

    +and the R package stringi; see [21].

    # call install.packages("stringx") first
 suppressPackageStartupMessages(library("stringx"))  # load the package
 sort(c("chłodny", "hardy", "chladný", "hladný"), locale="sk_SK")
@@ -1311,7 +1312,7 @@ 
    6.5. Exercises5
 
    Even the statistics/machine learning oriented
 ones, because of their heavy use of numerical computing, e.g.,
-[14, 25].
    
+[14, 25].

    @@ -1331,13 +1332,13 @@

    6.5. Exercises

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/170-function.html b/docs/chapter/170-function.html index 1211672..f7862e9 100644 --- a/docs/chapter/170-function.html +++ b/docs/chapter/170-function.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -303,7 +304,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    R is a functional language, where functions play first fiddle. Each action we perform reduces itself to a call to some function, @@ -1041,7 +1042,7 @@

    7.3. Accessing Third-Party Functions

    documentation (manuals, vignettes, etc.);

    see Section 9.3.2 for some more -and [45] for all the details.

    +and [45] for all the details.

    Most packages are published in the moderated repository that is part of the Comprehensive R Archive Network (CRAN). @@ -1163,7 +1164,7 @@

    7.3.1.2. Source vs Binary Packages (*)Chapter 14 -and Section C.3 of [47]:

    +and Section C.3 of [47]:

    -

    see Section 1.5 of Writing R Extensions [45] for more +

    see Section 1.5 of Writing R Extensions [45] for more details and other options: there is no need for us to repeat the information from the official manual as everyone can read it themself.

    @@ -980,7 +981,7 @@

    9.3.1. Function Librariesmypkg featuring some of the solutions to the exercises you have solved whilst studying the material in the previous chapters. -When in doubt, refer to the official manual [45].

    +When in doubt, refer to the official manual [45].

    Important

    Note that you do not have to publish your package on CRAN7. @@ -1028,7 +1029,7 @@

    9.3.1. Function Librarieshelp function.

    Documentation files use a LaTeX-like syntax, which looks quite obscure to an untrained eye. The relevant commands are explained in very detail -in Section 2 of Writing R Extensions [45].

    +in Section 2 of Writing R Extensions [45].

    Note

    The process of writing .Rd files by hand might be quite tedious, @@ -1137,7 +1138,7 @@

    9.3.4.1. Managing Changes and Working Co

    (*) -Consult the Writing R Extensions manual [45] +Consult the Writing R Extensions manual [45] about where and how to include unit tests in your example package.

    @@ -1163,7 +1164,7 @@

    9.3.4.3. Debuggingprintf and the like) in different areas of the code. No shame in that.

    For an interactive debugger, see the browser function. -Also, refer to Section 9 of [49] for more details.

    +Also, refer to Section 9 of [49] for more details.

    Some IDEs (e.g., RStudio) support this feature too; see their corresponding documentation.

    @@ -1401,7 +1402,7 @@

    9.4.5.1. Creating Own Replacement Functi

    Note

    (*) -According to [49], +According to [49], a call “add(y, 3) <- 1000” is a syntactic sugar precisely for:

    `*tmp*` <- y  # temporary substitution
@@ -1741,7 +1742,7 @@ 
    9.5.2. Variable Scope
 
    9.5.3. Closures (*)
    
 
    Most user-defined functions are in fact representatives
-of the so-called closures; see Chapter 18 and [1].
+of the so-called closures; see Chapter 18 and [1].
 They not only consist of an R expression to evaluate,
 but also can carry some auxiliary data.
    
 
    For instance, given two equal-length numeric vectors x and y,
@@ -2303,7 +2304,7 @@ 
    9.6. Exercises
 
    11
    
 
    Such an evaluation model has been heavily inspired
-by Scheme [31].
+by Scheme [31].
 It will be explained in more detail in sec:to-do.
    
 
    
 
@@ -2324,13 +2325,13 @@ 
    9.6. Exercises
     
    
-        Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0.
+        Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0.
 
     Built with Sphinx
     and a customised rtd
     theme.
       
-        Last updated on 2022-12-28T15:36:00+1100.
+        Last updated on 2022-12-29T11:00:10+1100.
       
 
 
diff --git a/docs/chapter/220-s3.html b/docs/chapter/220-s3.html
index a902bca..43c11b7 100644
--- a/docs/chapter/220-s3.html
+++ b/docs/chapter/220-s3.html
@@ -10,8 +10,8 @@
   
 
 
-
-
+
+
 
 
 
@@ -28,6 +28,7 @@
 
 
 
+
 
   
   
@@ -295,7 +296,7 @@
 Although available online, it is a whole course;
 it should be read from the beginning to the end.
 Refer to the Preface for general introductory remarks.
-Also, check out my other book, Minimalist Data Wrangling with Python [20].
    
+Also, check out my other book, Minimalist Data Wrangling with Python [20].

    Let x be a randomly generated matrix with 1,000,000 rows and 1,000 columns, y be a data frame with results from the latest survey @@ -315,7 +316,7 @@ being able to simply call “print(y)” without having to recall that, yes, y is a data frame, might seem quite appealing.

    -

    This chapter introduces the so-called S3 classes [8], +

    This chapter introduces the so-called S3 classes [8], which provide a lightweight object oriented programming (OOP) approach for automated dispatching of calls to generics of the type “print(y)” to concrete methods @@ -1344,7 +1345,7 @@

    10.3. Common Built-in S3 ClassesExercise 10.20

    -

    Check out the stringx package [22] +

    Check out the stringx package [22] which replaces the base R date-time processing functions with their more portable counterparts.

    @@ -2014,7 +2015,7 @@

    10.6. Exercises
    4

    Their list is hardcoded at the C language level; -compare the list of SEXPTYPEs in [48] and +compare the list of SEXPTYPEs in [48] and see also Chapter 14.

    5
    @@ -2158,7 +2159,7 @@

    10.6. Exercises
    27
    -

    [49] states: Factors are currently +

    [49] states: Factors are currently implemented using an integer array to specify the actual levels and a second array of names that are mapped to the integers. Rather unfortunately users often make use of the @@ -2234,13 +2235,13 @@

    10.6. Exercises

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/230-matrix.html b/docs/chapter/230-matrix.html index 1a5f0b8..170ff35 100644 --- a/docs/chapter/230-matrix.html +++ b/docs/chapter/230-matrix.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -323,7 +324,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    When we equip an atomic or generic vector with the dim attribute, it automatically becomes an object of S3 class array. @@ -1436,7 +1437,7 @@

    11.4. Numerical Matrix Algebra (*)[25] and [26].

    +see, for example, [25] and [26].

    R is a convenient interface to the well-tested and stable algorithms from, amongst others, LAPACK and BLAS5. Below we mention only a few of them. @@ -1845,17 +1846,17 @@

    11.4.6. SVD Decomposition[4]), +(see [4]), it brought a new object oriented system which we are used to referring to as S4. Its R version has been implemented in the methods package. Below we discuss it briefly; for more details, see help("Classes_Details") and help("Methods_Details") as well as -[5] and [6].

    +[5] and [6].

    Note

    (*) S4 was loosely inspired by the Common Lisp Object System -(with its defclass, defmethod, etc.; see, e.g., [15]). +(with its defclass, defmethod, etc.; see, e.g., [15]). In the current author’s opinion, the S4 system is somewhat an afterthought. Due to appendages like this, R seems like a patchwork language; suffice it to say that it was not the @@ -1923,7 +1924,7 @@

    11.5.1. Defining S4 Classes[48]. +see Section 1.12 in [48]. In particular, in our case, all the slots are simply stored as object attributes:

    attributes(z)
@@ -2423,7 +2424,7 @@ 
    11.6. Exercises5
 
    (*) Note that we can select the underlying implementation
 of BLAS at R’s compile time; see Section A.3 in
-[47]. Some of them are faster than others.
    
+[47]. Some of them are faster than others.
    
 
    
 
    6
    
 
    For drawing random samples from any multivariate distribution,
@@ -2486,13 +2487,13 @@ 
    11.6. Exercises
     
    
-        Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0.
+        Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0.
 
     Built with Sphinx
     and a customised rtd
     theme.
       
-        Last updated on 2022-12-28T15:36:00+1100.
+        Last updated on 2022-12-29T11:00:10+1100.
       
 
 
diff --git a/docs/chapter/240-data-frame.html b/docs/chapter/240-data-frame.html
index e31b94e..e482634 100644
--- a/docs/chapter/240-data-frame.html
+++ b/docs/chapter/240-data-frame.html
@@ -10,8 +10,8 @@
   
 
 
-
-
+
+
 
 
 
@@ -28,6 +28,7 @@
 
 
 
+
 
   
   
@@ -303,12 +304,12 @@
 Although available online, it is a whole course;
 it should be read from the beginning to the end.
 Refer to the Preface for general introductory remarks.
-Also, check out my other book, Minimalist Data Wrangling with Python [20].
    
+Also, check out my other book, Minimalist Data Wrangling with Python [20].

    Most matrices are built on top of atomic vectors and hence allow items of the same type to be arranged into rows and columns. Data frames (objects of S3 class data.frame, -first introduced in [8]), on the other hand, +first introduced in [8]), on the other hand, are collections of vectors of identical lengths or matrices with identical row counts, hence allowing to represent structured1 data of possibly heterogeneous types, for instance:

    @@ -677,7 +678,7 @@

    12.1.3. Reading Data FramesSection 12.1.4) web APIs (e.g., through the curl and jsonlite -packages), spreadsheets [46], and so on.

    +packages), spreadsheets [46], and so on.

    In particular, read.csv and the like fetch data from plain text files consisting of records where fields are separated @@ -737,7 +738,7 @@

    12.1.3. Reading Data FramesRSQLite, RMariaDB, RPostgreSQL, etc., or, more generally, RODBC or odbc. For more details, -see Section 4 of [46].

    +see Section 4 of [46].

    @@ -3019,13 +3020,13 @@

    12.4. Exercises

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/250-graphics.html b/docs/chapter/250-graphics.html index 2a54a2b..8d8f6e0 100644 --- a/docs/chapter/250-graphics.html +++ b/docs/chapter/250-graphics.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -276,7 +277,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    The R Project homepage advertises our free software as an @@ -334,13 +335,13 @@

    13.1. 🚧 Placeholders for Plots Referr

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/310-compile.html b/docs/chapter/310-compile.html index 1dd5568..0175bc8 100644 --- a/docs/chapter/310-compile.html +++ b/docs/chapter/310-compile.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -278,7 +279,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    R is a nice glue language: it is perfect for implementing data wrangling pipelines, visualisation, @@ -315,13 +316,13 @@

    14.3. 🚧 RCpp

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/320-language.html b/docs/chapter/320-language.html index 2dde6b9..7d41eec 100644 --- a/docs/chapter/320-language.html +++ b/docs/chapter/320-language.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -277,7 +278,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    🚧 This chapter is under construction. Please come back later.

    @@ -304,13 +305,13 @@

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/330-environment.html b/docs/chapter/330-environment.html index 1affe6d..1d7d468 100644 --- a/docs/chapter/330-environment.html +++ b/docs/chapter/330-environment.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -278,7 +279,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    🚧 This chapter is under construction. Please come back later.

    @@ -316,13 +317,13 @@

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/340-eval-expr.html b/docs/chapter/340-eval-expr.html index 0bbaf2f..d60cec6 100644 --- a/docs/chapter/340-eval-expr.html +++ b/docs/chapter/340-eval-expr.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -273,7 +274,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    🚧 This chapter is under construction. Please come back later.

    @@ -294,13 +295,13 @@

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/350-eval-fun.html b/docs/chapter/350-eval-fun.html index 3f762b1..b8c54ac 100644 --- a/docs/chapter/350-eval-fun.html +++ b/docs/chapter/350-eval-fun.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -280,7 +281,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    🚧 This chapter is under construction. Please come back later.

    @@ -316,13 +317,13 @@

    18.5. 🚧 Package Namespaces

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/998-changelog.html b/docs/chapter/998-changelog.html index 55bb453..8e636b0 100644 --- a/docs/chapter/998-changelog.html +++ b/docs/chapter/998-changelog.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -268,12 +269,14 @@

    Below is the list of the most noteworthy changes.

      -

    • 2022-12-28 (v0.1.12):

      +

    • 2022-12-29 (v0.1.12):

      • First public release at https://deepr.gagolewski.com.

      • Beta (complete) versions of Chapters 1–12 (basic and compound types, functions, etc.) published.

      • Preface drafted (alpha version).

        • +

      • ISBN 978-0-6455719-2-9 reserved.

        • +

      • Cover.

    @@ -293,13 +296,13 @@

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/999-bibliography.html b/docs/chapter/999-bibliography.html index 646966b..7bfab10 100644 --- a/docs/chapter/999-bibliography.html +++ b/docs/chapter/999-bibliography.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -259,34 +260,34 @@

    References
    -
    1
    +
    1

    Abelson, H., Sussman, G.J., Sussman, J. (1996). Structure and Interpretation of Computer Programs. MIT Press.

    -
    2
    +
    2

    Abramowitz, M., Stegun, I.A. (1972). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Dover. URL: https://people.math.sfu.ca/~cbm/aands/.

    -
    3
    +
    3

    Becker, R.A., Chambers, J.M., Wilks, A.R. (1988). The New S Language. Chapman & Hall.

    -
    4
    +
    4

    Chambers, J.M. (1998). Programming with Data. A Guide to the S Language. Springer-Verlag.

    -
    5
    +
    5

    Chambers, J.M. (2008). Software for Data Analysis. Programming with R. Springer.

    -
    6
    +
    6

    Chambers, J.M. (2016). Extending R. Chapman & Hall.

    -
    7
    +
    7

    Chambers, J.M. (2020). S, R, and data science. The R Journal, 12(1):462–476. DOI: 10.32614/RJ-2020-028.

    -
    8
    +
    8

    Chambers, J.M., Hastie, T.J. (1991). Statistical Models in S. Chapman & Hall.

    9

    Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C. (2009). Introduction to Algorithms. MIT Press and McGraw-Hill.

    -
    10
    +
    10

    Crawley, M.J. (2007). The R Book. John Wiley & Sons.

    11
    @@ -298,13 +299,13 @@

    References13

    Davis, M., Whistler, K., Scherer, M. (2021). Unicode technical standard #10: Unicode collation algorithm. URL: http://www.unicode.org/reports/tr10/.

    -
    14
    +
    14

    Deisenroth, M.P., Faisal, A.A., Ong, C.S. (2020). Mathematics for Machine Learning. Cambridge University Press. URL: https://mml-book.com/.

    -
    15
    +
    15

    DeMichiel, L.G., Gabriel, R.P. (1987). The Common Lisp Object System: An overview. ECOOP. URL: https://www.dreamsongs.com/Files/ECOOP.pdf.

    -
    16
    +
    16

    Devroye, L. (1986). Non-Uniform Random Variate Generation. Springer-Verlag. URL: http://luc.devroye.org/rnbookindex.html.

    17
    @@ -313,101 +314,101 @@

    References18

    Friedl, J.E.F. (2006). Mastering Regular Expressions. O'Reilly.

    -
    19
    +
    19

    Gagolewski, M. (2016). Programowanie w języku R. Analiza danych, obliczenia, symulacje (R Programming. Data Analysis, Computing, Simulations). Wydawnictwo Naukowe PWN, 2nd edition. ISBN 978-83-01-18939-6.

    -
    20
    +
    20

    Gagolewski, M. (2022). Minimalist Data Wrangling with Python. Zenodo, Melbourne. ISBN 978-0-6455719-1-2. URL: https://datawranglingpy.gagolewski.com/, DOI: 10.5281/zenodo.6451068.

    -
    21
    +
    21

    Gagolewski, M. (2022). stringi: Fast and portable character string processing in R. Journal of Statistical Software, 103(2):1–59. URL: https://stringi.gagolewski.com, DOI: 10.18637/jss.v103.i02.

    -
    22
    +
    22

    Gagolewski, M. (2022). stringx: Drop-in replacements for base R string functions powered by stringi. URL: https://stringx.gagolewski.com.

    -
    23
    +
    23

    Galassi, M., Theiler, J., et al. (2021). GNU Scientific Library Reference Manual. URL: http://www.gnu.org/software/gsl/.

    -
    24
    +
    24

    Gentle, J.E. (2003). Random Number Generation and Monte Carlo methods. Springer.

    -
    25
    +
    25

    Gentle, J.E. (2007). Matrix Algebra. Springer.

    -
    26
    +
    26

    Gentle, J.E. (2009). Computational Statistics. Springer.

    -
    27
    +
    27

    Goldberg, D. (1991). What every computer scientist should know about floating-point arithmetic. ACM Computing Surveys, 21(1):5–48. URL: https://perso.ens-lyon.fr/jean-michel.muller/goldberg.pdf.

    -
    28
    +
    28

    Hankin, R.K.S. (2006). Special functions in R: introducing the gsl package. R News, 6:24–26. URL: https://cran.r-project.org/web/packages/gsl/vignettes/gslpaper.pdf.

    -
    29
    +
    29

    Harris, C.R., et al. (2020). Array programming with NumPy. Nature, 585(7825):357–362. DOI: 10.1038/s41586-020-2649-2.

    -
    30
    +
    30

    Higham, N.J. (2002). Accuracy and Stability of Numerical Algorithms. SIAM, Philadelphia, PA. URL: https://dx.doi.org/10.1137/1.9780898718027.

    -
    31
    +
    31

    Ihaka, R., Gentleman, R. (1996). R: A language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5(3):299–314. URL: https://doi.org/10.1080/10618600.1996.10474713.

    -
    32
    +
    32

    Knuth, D.E. (1992). Literate Programming. CSLI.

    -
    33
    +
    33

    Knuth, D.E. (1997). The Art of Computer Programming II: Seminumerical Algorithms. Addison-Wesley.

    -
    34
    +
    34

    Knuth, D.E. (1997). The Art of Computer Programming I: Fundamental Algorithms. Addison-Wesley.

    -
    35
    +
    35

    Matloff, N.S. (2011). The Art of R Programming: A Tour of Statistical Software Design. No Starch Press.

    -
    36
    +
    36

    Matsumoto, M., Nishimura, T. (1998). Mersenne Twister: A 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Transactions on Modeling and Computer Simulation, 8:3–30.

    37

    Nelsen, R.B. (1999). An Introduction to Copulas. Springer-Verlag.

    -
    38
    +
    38

    Olver, F.W.J., et al. (2021). NIST Digital Library of Mathematical Functions. NIST. URL: https://dlmf.nist.gov/.

    39

    Tierney, L., Becker, G., Kalibera, T. (2018). ALTREP: Alternative Representations for R Objects. URL: https://svn.r-project.org/R/branches/ALTREP/ALTREP.html.

    -
    40
    +
    40

    Venables, W.N., Ripley, B.D. (2000). S Programming. Springer.

    -
    41
    -

    Venables, W.N., Smith, D.M., R Development Core Team. (2022). An Introduction to R. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-intro.html.

    +
    41
    +

    Venables, W.N., Smith, D.M., R Development Core Team. (2023). An Introduction to R. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-intro.html.

    -
    42
    +
    42

    Wickham, H. (2014). Advanced R. Chapman & Hall/CRC.

    -
    43
    +
    43

    Wickham, H., Grolemund, G. (2017). R for Data Science. O'Reilly. URL: https://r4ds.had.co.nz/.

    -
    44
    +
    44

    Xie, Y. (2015). Dynamic Documents with R and knitr. Chapman and Hall/CRC.

    -
    45
    -

    R Development Core Team. (2022). Writing R Extensions. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-exts.html.

    +
    45
    +

    R Development Core Team. (2023). Writing R Extensions. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-exts.html.

    -
    46
    -

    R Development Core Team. (2022). R Data Import/Export. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-data.html.

    +
    46
    +

    R Development Core Team. (2023). R Data Import/Export. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-data.html.

    -
    47
    -

    R Development Core Team. (2022). R Installation and Administration. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-admin.html.

    +
    47
    +

    R Development Core Team. (2023). R Installation and Administration. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-admin.html.

    -
    48
    -

    R Development Core Team. (2022). R Internals. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-ints.html.

    +
    48
    +

    R Development Core Team. (2023). R Internals. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-ints.html.

    -
    49
    -

    R Development Core Team. (2022). R Language Definition. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-lang.html.

    +
    49
    +

    R Development Core Team. (2023). R Language Definition. URL: https://CRAN.R-project.org/doc/manuals/r-release/R-lang.html.

    -
    50
    -

    R Development Core Team. (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R-project.org.

    +
    50
    +

    R Development Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R-project.org.

    @@ -425,13 +426,13 @@

    References

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/chapter/chapter-header-motd.html b/docs/chapter/chapter-header-motd.html index 5bb3bd3..aeed7c5 100644 --- a/docs/chapter/chapter-header-motd.html +++ b/docs/chapter/chapter-header-motd.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -260,7 +261,7 @@ Although available online, it is a whole course; it should be read from the beginning to the end. Refer to the Preface for general introductory remarks. -Also, check out my other book, Minimalist Data Wrangling with Python [20].

    +Also, check out my other book, Minimalist Data Wrangling with Python [20].

    @@ -273,13 +274,13 @@

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/deepr.pdf b/docs/deepr.pdf index a221fd5dbebe1492df8ac2595d544806006c7401..74d0e519d1948445281bb8af30833e85786ec485 100644 GIT binary patch delta 111855 zcmY&o6N6p=0w8#5;x5eqjn8<9Q{qaqP2D=RY*qxgRsHV$?oMg<~Pw*Q10 z5i>UvHybxsg4H81XObQ;jX4_;qmr|k+y6Ci6aD{-QCf^hmyg+qorBqk)tr;r$jF$J ziN%D2jfs_s+mw@&ncIw&*;Ig!or}fD)YOQDg`1O=g`LTmi;IPo-PoAh-1xt<#>T8k z*TA^SXF$-Sx;e9e7#zs`hHUKp~E_{+Lq8>0y(gdO*Fmn<$ zk{*DCNI(GQuZy#pksXZ3=8cZG8rm89uUjZMhFe+)Nnk)d6%~7x)J(e5LE;O65GK^5yeA<3@v<7lz)PTS8=3_nY^X!T*J)=g@#?9 z=e3EO`6{{H?_d7Q>m1(Ku2=WGJx*94As~R#G%y2Dcq|ZMzfZZ1<{KnX8cgJZqh zZw-Vo^FP9W$e>+_lagPI0@f`@pT_3$Z`dt~rizM=VyTa z@(v!Vy&wo=dJnm;;i2>M3*b?!bUxIa$nOcRf(=&jO^w1~%GYt51fT12W0CG>1RVIy zXl3!mPbq<2H#%m=LjqHH;QI0z70&0^HwD-8crwC`2wz>Sg=^;U+CdwbA+_7BcwDh4 z64Ut}P~v-tqhf{&^kOJdwS<#I?r{M0Jtm)7s71he>iJ^>S&J><2ZbdFYDyxVS`oky z*&d8xoUB?qC7ldWgz&J(<59#as2sw94@1O*gGkU{_~=Uck+~e_a~uuzu0U)u{K{hx zVuJh_#2yj|8Fbanws68G&k|fsz_v~jxDk+KsXPWI z6I*CM?9fndMxZRk+^UVf!e|(IJ^ZW3Re&U+f`m|i?tGzu3Ha*joM znrCxdVe8QDMVlF^WRun{rnY2T02!<_GZ;tkN#jBG_`!uA?5mM|NTJNfauQ*-3&In% zH|ePi_t0i^#<;7K(!Se>D+L@`$QOB+Y%Sb1>|rHgcnufU0iklRZ_y%o`sYy`vgc;$ zZ;Kndf)HzmB_GY87X*jlejqF;VQyV!#PCtZmYYP9`Hs{3&|>V;cKC-P|GTUwiv#52 z4m1o_=oa_E{>mJi@hnuofkz(jUQ$e_`GhV1=~5@wk5oGbV`K6QJqGZh04vZK|M?;+ z3I~mB$C#ro59KnG8!+_?C-4C^mP>4#XMS7gbV4WaYR2{v5vxrLCCy?AVrg7sMSU1m z$TZ#|Z$qL!uMBr{Vw7k_okMd%G!3vsU8t4OyL%B^Mu=RlYZW;=9Jhux9OTp$$yW85SHF9kG2S)xdcreE8bav~_)DiEIJ{4~v(r<%_oN>5c@GS=WY=2N)CG|?|6pdz@dH?09iXtwVYA3IDo6GP=&jBV^hm{eiTg`!9S6uLA~S><7s8T}LcN?Oo)b z;CGT(f2I8#_Uo^@TkNX*Kn_Iu>1p?kX1y*lRtm zIlcAwx(+MRApy113dHh;Naj=_Mmc;hj4acvk`BJ&t(-QVgDSbV` zXG;w+ZO?liOxG<@5~)l~R>H`*>ni3Yk3Ozg79kjcO9Yhp=_*)NnR{2>QQWmSj?`a* z97+@5a|3Ve3g#5tfCa>B&DD2s7Ua2B}3S%q#fM+c+HUdDzz}56eDpXlPL?$V}!9_;~!Lygx zsR;YAqV>?>8(2m~l8@a{lkRDR*NIM`5fxqA<8w=1DHh|NsGve0!= znE`B%uiHw>!hRCqxq{h(s>OS|sK~7}Q?V)y!pGpDZ0`9jEIw6c%mj!yOu+I?ksZViL54h23JnvtvMQm~4^OJh ztiW+NH6f5OXH`rW6NfpdOy3A78J)X8{0(5ZhO6gKwy72?H=@bgj17Nb{^KZAW^!b* zwe7A^t<-hxgr;9zeSN@KhIoG7m;p9uMRJ4;JDcg8n3!PWgoOE`R%(1*_YNSPhyjo! zG)=WQ=h$;vGX(Od`Ar5ciZbMabR_Mk&&KwL1>Q)f4yYF8nmJzbQ4CC9x22 znx&qtEDedGPr$WNMooJ3WZ;;WE(4Nr@?~xW0$v-Kpddoj4^3LYGbD}S0`h}2cVP%iOr@t&FOQWxC7GXoQ6Qg zDP!VqC#fqzrb0fZBgx%`Qh`;*@yce7_0!NJB?6RufOBq;iBE+EPKCoHF{14g*et+J zpNtSQILZhK-{N|v^9Kx)E!^*^In5Kljj&X4sj!9y?aGHH3U@BCz{*aa2=NIPo^?1$ zPoXiqShvg@t^HB2*`6YVKL8YNOTVRN0Tte0=oA^h{gO(e*2?fz6xqG~J$iRiVZ^t|T8iK)E9^`m9iO+9+h_zh8`7A+NFpmn8i3chu%3P#k<{-6 z)ZGaCaMpzfTq#v7-8Yu24k4S=G^fZHRGx48vQm)uPcfjdHP0dMaGr=9GkWU7)}!pv zN!})W%yZwd5Nq(V6#~M6+CAZtL!q<$KyKce9VfBZ3^RTUw{TE*z$E^GL}3k6>(@oU zw~xHDj$**`u@VOzzb)!x5 zb8Id_^5ddl?c5IJV*BrW1eKY2g_Tu5%j5JOIi&jZbYoAv`l{ah0nty4GKv|qy0l=U-e$k-!-S_?U^(4#i zafVUo2YPfG7ZK<_7@(R?XzvlR+SyCVia=#n008f=IYKu(T>8RDIg~#_;v)MX?_4_x z$a8iXvB~6q>!=e%>FGolt;=Tlu;N5A5!SnPbY`s-8T!}9V!ZUw{%E#;_!)A6!&wXh zn_AH8g!-|FM!gaVVE>cF&>n?8$$TPs=Xs~6p7W0qhXoOcLXi@n0ODVHE~pp0$_|s% zz<}1&fLjBS9OJofZ&)?@Hci@;7W>V5>?PQHojwe>F>y!%=r*Fs5~aIx50TNC9^TbnuD z;GqTUkF`D7;N^+KJLzw(;l<(k!g5Sb?(0yCx1V3AI(v2x7pe%BuTQa43tR*PT;1ww( z*sK@f(!@~;03k@F$z&phzadora&;;6{a@rH0%79gXobD!1FS%EI*lJEqrr&F0%m>;pc+Yt6;cQ*DLXw4<0_bCGS)L0P>u_e>ZJnN?t?x ze;%bIjJhMY*qLD};h|=#Zq5R)rs`-v8yaqQI?Mnb=yjf~Yvh;ozSTcm(Kcv+UtpBK zOI`n)A_}5Ggf!$#EUZLEB4JfL$wt3DLuCirnxN8K%rH@8DJd2sZ+h9)O@j~u2+IQK zB5Y%<>Y+Zt3_}e=A<${2bsK7&%BrfW#zvODZZ-BKV@3)<*uiYMDVlo0EDdVXL82-J zFW#?5T{AzK=GfR;N*8At2B;ylvV!ttRr(-i^k5Iw(|b^S+C_ z+|(nGK{6#{qO<-;6Za5XiU^Vhn27{ zNhSjs5lLPIEM4Ek0u)gnm+{#`Hq@KHDiY56Dul`gjB-XFgF#|$Vbu&(aGxp>g>Z~S zOd$cl{dt(-w06HUes}6s+Vim#^qJozw2_Zqomg~OjPsD9DXtKZ_C4NPW+0e&5__GH z?$XLF-?4~tYs{Xt_)IdZBDev_cbZsPkIYXA0L-ohTYk=tHe*M9pNC8rergRA6i&-- z&Yt$lp08Jo{d}C3YyIAyTs${ljz455k_rJK%YUvM^vfQE$0ah#9QEo%G^gfr%PAH6 zqneTsEuxY{|HWFS)1}=Qm%6=f36@IUT%{?leAaF(O?ZA93+PtvVAlEV{JPy$^(?)Z zE*L26%9)?>DxQ^%@j{N>*mCO|-1D$KHgXsZzXg4Brkzc_EDc-_={@KQ zGQ@6ytKOFv`LBO<@@M2SVy0a#>^^+e`%aVPSHC{Iaz^|K^sg3GJy|tXmLE1AI2=b-cuy{fY(2_d4u*u| zagu~-Q%z5G?(TwspY81D@fExoL4F8g#WOxok2|&8F>*Dw`Cf9k(oumH>=VuS__3W@TlvmhXTADyiIvHyLCTjnb zy~J7fq6|Q!YfaTFK{w9gKm}}dm#&LI)k5Fio{A*+CXL6?H9!|Lubz)4%E}rD6;1Gd zuok;-D8ve>^C3PEDMGmCcJeyQtcOytf_;a30H{Z(%uea3=46WA1&ozJ9Ay@oFh3 zlu5cr-D0#(?a_B~s=llV*=D?O>78pdrTi(rSY}4aT&h6OkDT8-Mumbx-Z#kqdFG0^X4Ax z1@=TXMZ22OV(RuQcjTORtS5Y*mY(u*38P0!@`hzf?TyA4cjS6PGJgxcK0c@J6h9qa z4dBmPDNaWn0SssCVgPq?bpZ74=8T>$ZrcNL@#FQ|5I^5|;y(9>DNfbI2hQFxUWx@H z$)@~vi0{AiEySnyM1tlR&uHlG>|egV5Q?Q8y@HCe0DMps85@-$ZKAvj0oyx&!T3D0 z9(%kIPyQhW)jA$D;A}@{}vwVTaTmzSi%OG2dDM#^zrOYv&Z+15Q)`&f|*_or4 z2Tx8O9fbuUV_z73`v zsFMOOuk*`J4?uIvVPGgX^cc4Wl+q(>d_r&0_-3-SiXQg6t|oaMIn9NFBScI_5A6<_ z3j{mqmt)-m=5LG?tFX&RCWJRrD_gdauNFSEE)#3wW20|V2GmQW#s+JzMNE?f3{~YsD@!=6mv~=3cyPbP*tHm{TCWcgki?=t&rL~|M*nffO!@Yby`{OK;Jg9?bR%4ZxWT9 zF+KE!hpjuL7InIkGsM(NwaLrRX`Pvd-M(r+&@5A9E+GhST$(eMTjCk{&;85q5Dr6L zYbaY0-FrbsH@7OAr{}cHVY#;@?p2$}o=Bs^Bp_VP8T5^7EKl^3gGe$#2Nhb1M@8C> z3TOg=QK4Ibv=N?sEmYYePxXrK4;=Tz(Oc0Pqd1x9e$D4O!NZZcyp;&l{ye|Us;k|! zzaO(MMD}PEvmL)cu17LQR0}MWo#)J6^m*m*YZgX{wxz}1#l^3F$DDLmmRBle#=n_I z2)OCiR=}7V(`+Qt5j;)!;eTH?a0o48-~L>wj+mJ6QLa&T=&MeH)UR!PeC@huC|-*s zD<~JQ2-#jq7O?U;!&`@|KG$W@C|#D9jY{6%Y;${P+G+ zD=4SPfI+58rox0l+m$9jN2n)C%w0j;1<0>+cJAXZV|FaIO3wA>=u4-Ms4P%K7+e4) z{8I^j!J6i$d$D3V5Fr{XA(0`wJIvR&`4eiz4RCi?cFKDXi`9$ez$&kEowt!NwR`!Rck;hY4SgSn&l6e(-Y#H5Ild2`22Ov-q ztEhhDSY3y~Gg~r`euznjcWUUqb2+NClR0iybRvsCQc=X^igp%zxUHPc8~Jwx%q4-h z@~@=p?OQ_E?%y@q2c4d@=HZ~g~T9x=w-%(2w6Wj;f`@kK~Wr}CN zl6rd&#T&e-8gp8T2WbfY-u4g1UYn2a5}Iv1?Xd&zttPsSHuaJXhO&$|z1ppLKSTU~ z9}*FVeTQf{vhq}w-G3W2*W&*X-k^`OP%5Z{apaTv7JG*bS;Dw^cmui}vrVLe zD+IWbVK?g+ngXT-ny##&@43fDGXzGk6GK%WRbWaB4znKGX>W6viXHuhfSxN>hrfvjhk!VCMmk<;lZ@)fgb^^6K>#H2ZWW%RPb4lj zR6!HcpBY-DhW+e=KLKJr$O9ZS-W`&fNI)Fp&k7Bs;6i;!tK(!i+oFGhj#9|uz%Hnv za5vJ~*lur-a1+VB_V&^=W4_FG6b|qq#TRfuatj=l zKnf`>sWOMWXGMWC1OQnD=}HE;`RPb*h-U8TRsSsG9#}0gM&MW^AY#PPkX+XJROEKm z1~R#+I!<3RcnYG{P`;iaCNHX-DQ5oc!=8$edfz8lJRppH@0qOZs?)=CK7WJzr!-ON zCX@!Vyy^pK*fQ-tY`D>2()SM@p_2-k3Zd_S;(-W582ZF{S^xwr;=IR0fbh>a&-K$J zhysqbH7JCl@4LN4>)ysA{>*e4sbTuV#tUGtn1&N*o1nx_GshhAvl_VcOP{~%H-vyN z`y*>|1;ObISJeh0r0zg^j)303Vf~yNUo?*6WZ-#_jNC&4KT04`r2vyi47VXdfM$@9 zAZVlZrcb8djsjM)dP(APL9$6Xn)jPn_l_ydEcvFRLf^RMJ~igab`kQi*C1z7AhJ)J zkKQZ=Jb9x@PI+8HujV^Gkglw^lzlrnu6E2MJIXv%&efPllnSuFD{M#QxS`0G$CkFQQ2;|2C(a-2VgZ?EX z3F#;8i4}_Q^$7KK4fS;ho}gfkEx#=^FZi4gpYR3?m~vISX{W+=4gI4bLj$2U$;Z zQJ&dF_zH9mS@N}PQ*f?9!=HsbSm4xLrw)w0p&+~!4!b-Vg-9ZS9pd_Aiq78X?edei zL+{=Pg@eY&NKhvp1F14^hLDtb{2(zW?AA()N{)or;+}KB*zO;& zmjGEg{vdOlvgITv*Vfwk8GVpfgg61S3#zPxUk+Izv8?Z}`Y;ATMHn!a2|F;uNr*Fkl=t4c;)4;Z+B$RQFqPoo} zrl9|HKP)(}-h9EP^+U8Cl3;S*BU%&saIa8}p3phLJMU~QNi1_-Ia^B9n!d=D*MDMY#m?CZEvE!6*vX@g?*wvgz^ zP-lqp*H?PJ-4L0ZL|_>HRA)4#RJb>Y0u)`%O|uZ9N@eCOw#kpvN35R59uVHv0UOqg z7J?TlWhR-{=Syur8=Odo_;qhXDRSg`aD0q<=a|(`oZOM?D`RMyXU~7}t7(=`B*EUj z=8Hrg%Ts98&l^Z}_u-NhBdRk&N>kpUDpZyJNrfRtLe3eP%%m_=5h+NA0OwqWf(#x3 z2KF;B2~>a7T_ssbE5@u94uJRrWg5lN-`_=-yA|IW&SYY|Wc`Ec#w(KvbV~mbaEmoP zFOa!wJIYdAISluPV{YDFBt@;eQznJt+%h0rt3J<**r72SOU60dX5N}Em3DtNn9d{& z1cHUo^fs-&m{snfr8~03e#4>JtZTS->!F|T@IGl=!gc0Sp7+Zgr z430`zSU%LQX2NU`79bqOP+%(oZMJl##`nW99IuorC)6?|1P*!EOFKjnrsiulQTJ9D z_60Lvd8+Ayl{nRc7go$_Db4WmqCa1>>CS(w$@fO~j^6q?_-lQa6P(f@iP7+#SbC36 z{SM8AyaxEWmK#0)X>qYgA`VhLP2QVCpoQVALzMCQh{9~9$bs&De) za$zE=aAobDaOEhkB4`Gw=3%Oa=R_14p6_INC_0n>STlTJ2yCiwP5^JRme(vn2~Ce_ zwLcxEjH!t8qM<~z+Da%^hUqjmb0Y%@2Dz#JXf#$yi+Hq7vB7{^PFj0ot)0)Iqqxp^ zanGz~=#?w?u(0r{29u+V4x+l0WWK89?&hDu@~NVtGywG#rLid`X?b{pYYdICsXi&T zy;GpDcr;22`1!F59iS!syl0a}W{}wpfm|pskrP=+mO6jA+f=BRtOQC0W)54uFg6Y! zs|wUO42y2PNfgf9E&xk=eFh3zuPGU+2lc?f72cF_@yf`w|X+77f}c##!iVq@%X7ckj6cK$`5f z(b)0*agpR%X7A@>;!tP^3v&BG4IU-mbA^~tBiNBA$f?QbAh5^h!|X8A6c!iO^*Lmb zW#_ncFP-ISQEQ+N5Xi2OlJ_$}bn9d1&%80R`O3U$X754yMBWn1faZH5&W+}WIKiKU zIKnu)G-)%39?O}BaD@WPJjVTnUfH0V41Pbg?_D0i2She;g>&ibi4LL`CeuGZEadTu z`I5lKB&!EZ=hmTG_uHdnv@#e3wz|w?R38(x%9OM#)!E;85Kf<4*o1xCYSe^#Hne@1 z3AMSLf23Du-*>F9i)u<79AniK`2wCzsqa3aCvh01{wq?6={G*}n!;VP(+e8q4MsOJ zny`^tfSMW30d^RH3QmdLi{wHC7>qfFsOoS6$x ztsUlKu8rr6sDk~tJNN(W(a}C;R%gU8dC~h+3zvGoGyzR#!riBIo+4dgpzi0i5Z+(LTV~= z@_`VqzHuMER0`PI81}2S1%igN0U2nI(ik-}dAUUiexIUNeQ|YMm&@w3y4d;(AZou9 zSZ{Mg^y;+pw}B##2)YAHZtD+p|d{O1#?+kTgok<`*+%HbJIp? z&YED3aF9L9J0tyTH{_Op{6`rAfYr8nu*>}J#I=t1^1biwUbh><5Idiue}1@1&}B~L zVWVi+#BX;)Y};R zAa8Mz@hr1(kuk8K>h#LmtrDDGsdIO@Rk~Q-L#()Bdcl9Z zIDNXj&+{SJ6Rh*=>lNG@9yw?b77hj#1rswM9{f#c4R1sNBN1jrAWNPoSN^& z+ZEj2-qE47nqX=*8Snoq#e>OG=>0`f3EIuj?O@h0q15cdMn-j*t)BFo8p=`$a zza6?*h6IF_JMAF=74yF)4WD!^g9_NFCF4f+J)?a@CP-IcL~bq7kc9$cgd$ESY}b#n zgqDx$O~ygTywXQ3*R)T{3?RnmT8m51P6oELzemybzx zJV6)09Ba`Oc@|6h0ZBh+exbfQ`gv`vIW~R~xIz)@*s#ii;ngD^z4tx>F;-Uyo3H6d zSPeUaFKG=N-h>>mPfEiC3q~mECQOnfS)Z@}PVWy}XwK75f3BGe8m?Lus~9|D1p&?0 z(L^g4W$m<&jea@8JvCQIybJL1!?+P)j8N=9{D)I_cqlLCZ~uVBTx8fC*DZoFX8lH! zKp1VVCidqK1}+5!mpMs1kcg096RBr4t~dVtd~I}SaP=yD`d_wZ8=tZ=qws5&fZ-bd zy*uqkih3x%2m|3`ss<(MGf$Wg$qFQLQ4tLWaP)Y92>bh4cGA|T zr%-3u`|~{X5%jb3c#t<0*5~v6aP@ex^myQq_SF#(Dz+hl7+b?bM;s7(d`f*YlFcy z3X2K&M%liS_|*TjpWb_2`2FTyuaISIl_KlA!KQ2ha8c987uyVK>*-k-<~{9NNNx3g ze(x_ILDoqB1*;D1{MGOM{)}&`E5{DI+D1k$E>VfGxSZyS zesHPJz|XJ8CrL;ISS5{!n}u4)*+V6Wt;+v$UsFX%m)67pt1*2AeiuKKnI3K>sKG`H z?aCe?j6i#mn0m9O#kv9&ncFn0QO(+GoC6JVs^1&&&?3v+C1*F#vJ)~K0+tnV&QNKp z*YHP_B{xPx@W$BhThCDj4Y!$&iS&kfgN%U0_8gLbgv7%m2qcvZfmhj9ZdGkXCTAUA z+iP}muceb+ZGaz_GhowouG5jmd?{L23N04U=YlbO7F*hp!ofvC{I~6#yK;*3iTyST)k3btB6m!mxZ7JxB4HiKm8Iw=EVMf0U&GUQ^+OCvgYZ zj7XbWzwTrVP#OnwhI1V@qL{kyxLp>jk55bPg?i)-rlhm%QqT)P4osC1m7S5J*gf_x zbi+_CYLb^YbVkGNupLb(NL)38K^C(XiNoP^vn{#11!u!f>E^S>YQ?Q!0yCrw(wEnJ z?2?ErIRy@2R~Paxg@KxfX;3@VxOut`gm_h`nUm7Snf5=*m$`iY<*L>FN3C7S{&NM>b_ ze>)uIPK>pqsCLnhQ^cc0ti)T%Y|4X0Ryx5|xh%4j^y`fVIbO-O^2ta`-quK7I*#ws zb2wY2&bV*2ri?ucOQsOn_zo{Cgvt!aB4@}xBwh@e`18S_}tC^!=b z!n%9`2KfQr7Ya0d61asbC~PAnR_W;VWUDq-zIw1PYB(GrBwVEa&}h_jQYtQHG_I2h z;YU-+EEKA)#fArVDtD>=iW`F_YrJyWBwVch(6XIfL?ufL+6l2dKL~)Cl#;3VqS7JF zD-zl}u1eA<1l7l3w1N`IV7QNP_USEgH_Tno>YObWLrU~c1)AyMRBGy$Zr0NJk=9tX z0wqFk{Y` zJjd!tktL8oy+LdY0&Bo}V2lWVXv~!*==d?z-TuD(G)oA@RvJW9^IPEs1IY7G@|+_c zkr>p?hx?r#cm|{)RLX#JEsNG{Touu`jL5|!&%hF?Iuf(N;3{mPFWdDuLwyKOGBw%0 zb(%7!!#2%)S~G?Oc<7To5Dcq#Qb^wIo(#Q4Y653sy*kdY#SUQDpTOc0=vtc7=r|ZQ zNJtY!d<_@F>^*mNq&3(^KhdHnNoJEe^yGI$BIa2kJJFm>c6o7eC!{{2E+Y7M|WiP<3eui=3Wwg-LtY2BLjmxsFknupSlD(z;1ZrSk)@f2I-?u^3KRr|L zQoqykql_*xamOJ zgqWJu4tI)_Dtk)?&Y${ivh?TnlN7s?8R`Q0nek@9wh4$HArtRQN6tAIhD+3VLhAXT0rp>&il9 zxy=YgePFEw(m}%0l(uzo!_CVlwnmb!a^{S4-VupNOpIU*<>qgCJg_a)wH4ddcI+pQ z6=F*PtQQDkut#%S&r9+RLyBsD;E@17e1h>C%RS*hw1~NKpIx0NjZ39j}W#n zqD8hu7T)pp`<=WPR{-iu=FnAS%3{L|am3Apq=_a%biv(yhFJ9r!I^KdGm=*t6+=Ud zviMz+!)R9$N2DKT8LZKANBtHLNjE*@>ovo_)ed~jypNxs*J3N#%$RKZo+{k+O?4?^ zGZj#W69u@AEEbOtNt#v-D9^THcYEmp^+|6%45>tqn;TCVlS;;geEatIC=M!lkPF^v zpaf22gtDtf^9mSPpe(RQ95(WdrotEHjmd|4$f0kKZ0V}8KK5~JjN`UyOLpWPw?ixP zTYJ=7myb*s^xnE#v5)Gp<9q%yM>hUoZV5=C^IyhG$RuF+E|giZ*j-|4hb`Ne2*Pxv zXea>t{1i^vHcl6EjazmnPxpdZl7XlnIguQ}Sy|9ZU&p}8`v$E@&gJZWbNp*XqN&Pg z&Z|AW)Vicfae>d-EksxHgnR?@XcTYVng+=ZkdnIs9clSYCI!d3D_`23gIySV+bwogO?z1v zG(yEzLl1l1IxS_nf*YRGdEgan_u{>|u%7So*hX~CP+c{%1pNdoGfArC>0_l<8MTh z$yRLWOX0%xIk6>;f(a&2({%_yt;88vsS7B(-QS3ik!=^@jJuN`p5r2yaRuO?uJ@=o zxvW#sIdk*$3R|kFeelgon}XqWvE%n=nSG>nNO$`RT9_pThGKqti2D*PF`0h*PyL*m zKc6$*ArKA0lof`Urd4jm<$m?{oS?N@?H^r8r#1`Qt4akXMN^}=X8gmiGO@R@44Fii zoREvGlw*ROrVj!a^KS_!?^J!j-^zl4IOkAy-Hr-W=#Y{dTPq=N9g^?bUHG~_!xasV?E3)BBMS~a4#75o3tmqg*%YkkRr)c=C7b;5Jm z6fEeQYI85-JjHc0-XVst9DV(+>gA@|>gnf*sH0OytFmVbj+^9-WG1ISoTPSm?K7cB zkoCaD-d_|UQfY$}DH>dh#z~`-T!~pONQME1Qh>XqHZN5b5xj#>^?4^#PP6Vf(l%;~ zMb!EVqQ$ni5dUX^Y^jmB+5KaQcCJCj>PRTKUIK=-`-VSDz7PdfF7OfU)8^ae)sg4$ zwh%tqGjB7IVnxtdDa5npBjyiR|GfjAP)mL6AMMcK^>=ZsO{0GC5& zbPLgxw*NE*$1~#WPVD)iM@SZ;|E1*6)ES$UmuV#t}I05Od=-^F#^L-lq6vEN6tI}JHp@k z5x{Tr_si#;;-2E%|G==feE`96(D%;EL*CZde?aWu>gE0E<>4-FPeHJkBx4eavqA&jx^SHLcBw(Ln8O3wiVGug4+sNDnHS+O1UhuH9ew)ppv-{Xrl&1O{Z zHtg%y10FNl|BbWOP%>kFR8)lRCc2;lJ?ux~9&8AX9!Qhum05 zIVilbIVe=`8?|_zRY3xiWTY5xpXKd>{SniBomN7lw;$PufN)=6;WcTRv_;T9%55s` zMvC#`jbaB~Va)GD28@*{vFLfe!+GGtoJE~#ktD?LiS8B*_gaoFYA4!YIS&QuVM$Ze zOa+LbcOj*Wn3qhV$k9=82w$6yy)L`wutq(f_=UVyj-8LB9&a#vV)aZ<;MO=iWfxeI ztmH0-z%!kA`WlI=91iBH{>&2SsKye@Gf2UrPUZaf)gyN47ohp*|0IUbFP==#pE-{L zwVO+@T6{8+QdeRzHykC-ljqiXx+@jeld#*9uv){}Si|Z3*MY6|#lo2Jx_6x`G3pIv zD^jZ>HIK4bWx;Az)@muCKvFoE7+7Rr|5?mO8H@%uTDLptv|BY{5Pi4M)2rAM&8<~? zWfxwGX@q_p7|>w`UL!rfZGFMqR9WaeZJv?8Pk&w0Kdtjru<|u;*^B&lhR_D7=w0F# zmU~nvBD#CNW-3bi?sXa6q|qIt%f>4Sm*qP0JP3wAnxq_g(!N=H0qzCY(V3Q*i7N`r z|B3n$WqBK$qV5Kt0YC=lx7(EHepF5LE>^kphqEET6~Jt+35WXn{#7@YXP~%O`(Hu6^nN#T5voqDYHrz#$CUn zRVw_+t>rv5oi8aTZ>822YHn0!U28Y`_U| zy@U{zghkefXTd;9G?e;km|YC0`%K?u%-V{60@#09t`L*|eRwjtLQ1=wSoN;{bB~eQ z^uyECa{M=DMj#0VcR^$A{k=G%l$8Tg^G>QuUwfgfhs<%H-4xLzzgn-Jl5Q}=_{E0D zz*<~iU%Dqc=%)*dlAT$Bp5HCKll4F|2C#eWM+s56d{!DN!3ZB?H-vhnD~gH{3c*!Z z3()=Ks;)^${DW+P=3q!()B4(TxT4oy3MD8v71x?= z)UmQA$?S&JiUxbg0{F|{bZxPX5T(x!E~(8PO6{TUUhCE(op~pPB(?NfNN@o4%t>z5 zuc=PQw8(gTAx+%VsfC3FB5IxP7I&1j2{38Tz*DgK3dC~{k}YCq(lO@8(Z|yo?rwE` z<337uJZ&!8zus{&?2y93H#FcNgOWQc`;xRO{UkE0eVjH~z2uXGr@HBdEK(R-@qla(Fd(tg1?71rN?9!mHl>}oF zyAw_Epto@dRcvvn0bkqC9Rh4V06?cXo}Rqe`F&Zen1HINYl(FTO@;2KZy>cRMXYQf z&BrwDSV^TaW0EJlGm=^VW?4Ifw?B@unG>>$)t()bA_QYKG+LtKb+0|YbJiIp^VgH( zo%G7Fj_P1Gz(;r7iD<>6CuZ3}%0ERiI!^mzd6b5<9uwrJ@E+SgjREdU4A^t8uJS%_ zl&3WRq;#$0hpV=M_9&3Oj4JW-+#-m|!`id=9m)x8$|LCOadwq7j>*5E7d23_0V`0Y zsLBlALcql_CbJXCI#;@4)A1uuhBN7p1#*M`vyncxuDWh5m@aLs_t$Ow(k1RDk?yfS zB-vCHdlTNw(!I^c;mF^H8DPWF8D+2Jy0%7R@PTZ7O}1sbRnb~xKiyOj0p)WJ?Mnj_ zYo%0PLpM(^YD^~RzIv@ybPm8FYDSnL*k3e?Kwl2CX(x|2xus^`Ls(~2!UGX zN8bCio}-8%Yrwa^PQ3)*;QP~n=*4zES&7iF_s76iXd8{I%||7>@?%xjYeHLOigP}L z^*wi&*DAm00xw8 z!y*VQ3%hhlcXxM7OG<;JbO}f=AgzEBu7rdLNViLOiXbT0lLy{!gEf!5QEZmfiRG}beiRGT!rQhW7@3guS>b&f*v1Q zRbNa+p!M#1ok_gfaV<=E>DIRH%e%y4`7*g5?`sopl(4d*cat+LtO6_Ll)=XF?rF=z zyAv8HJrD&3x}cabrdxFqtOeRcEx1)Bd^lj^$)uRiCer0eUW3gYwG)d;oJ)jU)A2y( zuu0RqQS+JO*(A8{PnW$msBB1-nOj2_Z&bG!Ajh|bd)*S{Gtdz`6*$WA{gB|&y8X1-}jKN=k~?Ioi8Ld>D9a9Q2XZCK6VgH zY=3$^)@JQ*>k6!)g>CoT=?Kp6=K)|i^;1=SyGhN)Wys-9MxL`)7gd^40(w(9s?D^T z90R}{KU0>jv4hsBm=w07Zv|(zI}UD_Ugzy$-^}j=&o}hJ99{N`0oUfnIJZf4W zJ-q~NjO^C? zrFp)#oS!%5{LYI*azAiR8Ge7M+@>IYtIoC*^78u^DJLfv1W8EXco>?(z1bK*YbZM!k)xl@G;}N zJ2ishvex=&5EGf5EwdFXCe0zow2hpIY2kg~yZMTU_q4BW;hHowf1_&iz*MabB6)72 zOA6u4P2rj}$Vryn=;(v=aeb;lYx6VKa$TmVXME&(?AW!7weH%f)D<0DJm6P%BS(L0 zw~O*gmX}#I$+s~ujg;Tpzy>u^UUxMX;rBBJ`JLNUimj7&lh););8T`vQgRIv@{f)7 zp-pX~o%tWmosI@|H}#S%&{>onp5Hh0G>eBk(?00P(~>{(W3IllS)mYIbE2n3BdXte z5Ucvp2;J|C2)Tm5X)-6XfZxvktx)0>Hb)HiS_qqIyJMo&?L^^0 z)nId-fS#xU^f)hPlW#$}j@uP`U1UqJX|417wX=y4eZ*;v+J+X2^ZZgqMm_ z!Os1@2bHh@-@i_7{l*55=xT8Sk4gu#om{I+29erZEG(OeEkA!l7WbS(;^p1nPx*EN zV$M-j%6U=|+ZtYMpnJz=xGCL5N8pH*AdMZiE|9JPon# zDHU?Z+zs_<<#q7(el-8C&YJG|f!mG8R_b!jQ~>oTZ#7;tu?7;770l2{Opb{5R5z>S zuLGe^Elnr9`*}-^y@4Fb5yz};JL(Z;yM(Q^kBJCCNl~&fvXOGs1R+yBoDQyQw4zTr zWzfl8T9SxZ+8|Xm``4*7f>qc;cg=U*oTWlAoO7fy_9q!YWwF?iE}~WJb`wD7iIGji@`pUphF{S7G(=aDgjwa6y=r?- zWeA!FEPDGR57^W`)^igWWg`g}x*6@*fOM~YOzuJ?xRN?}z7gIYgDd7y23B6h!nv!H zoTP#&C;D!)ou4rtPHi{)p9V@aK`u_0sg9*7-fd6xNlx~`k7(yf0p~rY7Z;~q7kjax z0I5dEcQjLP(eI3}IWM6n-)8R}&bv1m3ymL_r`<wnhrcd*>5z=$T0M)Vf#$l7ZiDm|sX&LM0)AXBSPxxsf}irG0vp{@44=Hz-r6+o9w`0$xBCWnf}X`=NfZ`q&7rN0Kv zjM3yjw2gevw;s;GH%w0BQO+flCC1>Ie3EzSi$V|xYIb%79SxL1;0@PxUt$PLl4P$H4Ld1jMq-Ccg~R?6Ix59Iym-fm zS5!8|Tk(O^ob4=Gw<4YKMzj)#IyqRL-{GE!vK9PhBdKR3T#;uW-|jDTXVqFv_fd>| zRilgdf^Q$0Ywh(6mS<6A*4>cCKtIW5a!BZ!k!z)aD?JO)*&gUj3Un?iVfP--OcUTx z=#a=#FC?yI9#-D4Ac!6_7B?_#^|U^h>+T57B*93rmaiL3<( zKfJR!bao>TR%i=jem*!cf~t|)7w5I|yeUJWtr?N(v8C-y2E4NN^>)N!cw}+>h!J@Md&D@p$lEPgC-4Sh8DE z@=$g1P-1d#Rdn!sP7*SbZCDu3r1@h=$hkcdot>K@W65WAjW| zFPSP&eoJ9z-pmn}wl&4PW#I!=Bp-^ddbu^A%C{<$DR|ew-W@*T zo+Kl~QM<<2VoklSfEOyya{t>{DxpX5@(bc-??Ro`(9Or5XI5QQ@oOkc&pd?o zu(zo1T-VGuSxo#~*PqMvv^1L(!gO$M;#QEm2X@8#sCpZ<(;|5MoJkO$L*9CGm=Ekc zNK_&BDWozq1m!6I01wG|?XG<=R_UWP4Wgm`iR;KoT+HGQmY?jEf-7F-dd|<~zhPke zU{y^+?!bp8fu^jlK?}%?N)Fd94=6>NDkomvE343r^+k7}h|Y2=R(~$@xE8f!Bn|tMZ{cOtVV3SjnYig=-BUCWsY$yxHt8FH z+xbk@%JsNk;y+b8-gZuI3)VB!&NCzViO#{tF}ezxJ61fPg)V|4z8(w zV^)Px=-k-n=+=W;;q=uO2tJwjoq9_On5nUr@gi;2L$BmZrbK#kU_B3kXdFO2#%8NqBRu_%oI!=X_od{n&7&YO@eXQ#D{8}eZaEue zNIXjO$hoDs3cEEZ!P3xJFf>pNsA3i5cI%#j+?#&!i%IE+FGEoC81|zWJ(x?#{PX&( zQn1FYKKNS_(GIE$J;-CM>hoLP*LiL#|GBNc05Y&nbx0xfd@xI43o_n7Vu*PdAf|*G zC4PNCb!U^Y=Wbl=UTEl>PKxJb+n+O|*49Nuv+}2Kn{ROjVw?8U+{k9cQv+7f`?dGgpmSRA%fo;o+D85rfrI3l19GUZ;AF}Q)cr%+Veh(q zt!TyPMhzCr-$nDo1L{NX8e2Y)SWc?U`9}3&cjo(kvd4co{!6gPBAyr^@HaE zSg#&Wgk)kY)jg~5Ev$4A4~6nF*O%YPo>I?%k4>vnW%udIX<#>x1x|PD8ET}DwFVN8 zKZm70(JD~92bu}CYO88m*nAUQ z`Vn>h*wu`OSF0KV%~tET9S@v;CtSh0Idwk${vB_X8jXp5uVv-zVt9fJkMXK3X-{-? zX=COC-t+;`t7nXR0|CZ`q0f`IFjl)*3k&T5LwJC4Q97%c-uXwiJN}Cdw`CQTgtknj zjdN1EMmPJ;UP22`b5gwoHLGb~MZKf$b~zWxO`#Ni(P118;d;8cVX|vsP~utMUDO+a zEHZXn@G)nz7^=b~5~`Nm!zERu3;Nz$r>= zBcTs{N54h&&OKV?Lh9pCxo@ht+mmlotp}glbi64*j%FH+qw+P}Z`e_Ye?} zXy=L&;1l(Z0-_Q)y>VA1z`XJf~=2TS>SkPlaR1yuQyQfQ&@Ovi$@2pO;xitSc})>1xXA+wO%#8Fp@< zq%G|e7 zql~j*9w*8ej78<+o3(ATQ>Ov3uiM~w5u~c+u!da?{t(j_kZt%10o%kE-3? zw5qu!tGJE0jN~j$PPQR`Pq~oz_L32w*NBLvQur(svd^c{tYyFS{^X=4bpYA7j)5{X zf5`{?h}A2=4{Ce<+2YR4&$92|ct@4IE0L@2RjKki9BOX3T^){zx7dL=bNR%^1g`joqMw}SO;qU&zH_m z-@}?eSVKY#yH+PVbPNVrn2VN`wKpw3jDD{_Bi+yotxhQAQ`z7QVEgPLZBrro!BM#(Mj>XC?WyOxsVXPy zG;Q1BK|ulA$e5!Y2V59+mi~HNOItu5&ik-)ePoAZKIP4F$%_S>o^60MxA_Pd9W;=+zonO3c+tnmO#ba)DT1 z(g@^|3CGK}YuE4uD(|xzpx|JX#7fIl3MJ}WJRcj?j(EYmgxBHfZ)X`_7OLCIrD)6a zIu4>`X=rEL?rUB-u)lprff7eAa;NaXpl?w?^# zc2J%$ZnoO77Ay+x(*xySg%zOjF+kvn?&xYjg< z@;M-J0=Frem&#B9dt|TzCJLz8*N9;BhIMea5KFLFydfji5k@k7i*FoS^|CFSuDHqQwE_!8XDn)`u{GRubayxrz3XzHqn*MG(eL>|( z7)JE#CRj+DL1PGwFyvJT&6kX%47pwVlXa0gmReI*$r&oVvyP}*AxfG_eRXBFOAOeFTg zvezW41nm@8k%jKR|LFAL(PoxG~hp!aFoV zv^fVOkClSHT92K3MX`p)+av7UB3~iCBe6KkZ2xEdy9H|`V zS*mYS`E}JT1~R>_(<}Js+ws|?=Y;`eQC`sUn%JXAesJFM!+IP!<^CsQIN3+CpyT$$ zb`n$jM@$&b)e2Cf529v^`mv3uGViI#_O{*0xoq_YmDHY@F`*e1lgMS@n((!e=(OqG z58*{Nco<;KMiX~l=%5$bqczqOtKyvh8X3@e9v$hL(E`iyiVP^0phl|Hx-! z>pk(!uEZ(8j^1TW^*tu9#oia&^@lPfsA5|<4eeRH8wbL>8icU5#5+0(jpJC;H7`9+ zPcT=*s0f^N_{IH@wC3&f&dHpTy2;;0H$Y@y*)9<;)M|&<83RgTPbBLL8rf}H4n@uO{((>F%v(Vki8dZev}mNl9Xp;13E)Q;RT+CE z?;yQ#DzCEUr5w7tFJ94ytOqWsjDSrRXi5@m6Og&j2pj$7Jc`h&>slw{N# zMQTf1AEV@f?z1P9 zmTYd=`LfhK82!Fc&>O~;YN!zxe_!l_`_%9zHCrJvyFaWhr`)S$2uwmzc4|nGAO_H$I&eOE=_ug{|F+0xp^K^Hr zop#c~aM5n~e{lDb{g{=vxD^fwEv}03ikXzCpDjDCVMQ+6*^$oh@+-J8`HU~!V=}m= z6Nu%L((E9+nI2e({7Nw5&ZedoAHR>RawUIXudtWc=w}vX4K4q*vwDvf9v&yHT&$eE zx94~fan}!(f=n+07tr4rRx8^G?ZgMgDu+DKRkUi-7h5#>_IC2(E5_GANSj;hEQG6_ zJqp=&&gDf1EfBi8mR2^QZXiVT{8hxOm_X2{t=KlL=Y^ZE%O#NBp8+&hSC+IoAK~At zd`0y1OQh=ez8fM%Cm-ogwa$$z>M-V1*`BgbUgWKH(-LAm{=V%K^pzolSvZ&%WlSdk zprBjv>gl)+XB?FcVV*g6^|)V$Em)(u;+S&!%Cr*n}kWI9OL zU=&1BJ&S#T6QE_OQ603!ArI?acE066nv0LR7|)}iW?gGXoyQZ?d(F#B#sVBC^tVP*%;0ZZEhgPg!91@! zcQ`TNwEZANb*CXeYtWw}NQF7z^cJK(yn&hqIVCb(q8w#pvtvKbNkmTE`sU;Jx&YDe z^eDf#O(e4wxW|bvc&Q_9zb#@amc`3yoQt-^325JKIGZ(n)_j4oVs2RO?BipkPR-er zq6LMHLo$jX^`;kJ_rPiRqimFzjt)hu1|P(WTzXG^>uca|SuH-8&)w$aXg`2ZM17n! zOC;G#B4JkHWj|v}vs#=V^#NxTeSL6Y+PA!95j^D3ZbkrERuOH_-t07}`Eb{~%Qr4V z>o_$?$L_cRNHp3smZBrhB|kMhof@I0OvMr)ufkMl)+tKv5 z6n+wwx~fL8yKw!saBHonOgSE;PLHmw(kDEDJ>}i1s9JF1ljSeY*7r!H4_!f8jYcGm zhnfuwO((4z$keBpBF z!6rk-LrJzMbQ6@u>Ro3n-5N6ZwRblBpKrQkj@LOYp*c=(C~Ub0GG($sHe`s7SXk>` z0GN$~d{@X72`E6#oVF(0$E|rh+Ul|QGQ&0PKZr`sxO@Ut5wVeeq*Y_1IK6G+ z;xAL1@q}#;@SZjw=MLd#*AZX3#%E6)ce6^%j!}y2x4CY36(mGZo73es65Wt(d?e{v zC~|@=(Djb?OHwi((fklt4RX*DpBC4(LLNbHxDqYD+DPTDks_Wi1I zzyY`XgeAO@@OOEvHl>PQTDEVFU!hVTC_3;Z-Icp3?}lf^W2RI=@zD_i1Ls=QJIy&8 z%~Eui_T$C2zIyJ3S`cSCDpE-N28eIB$>L4q>SE0}c~7DRr;@oUGC7VFs0HyT6 zXr)iNB|N@0SqUq5V?s0`nLZ|#<;U2iPZHZ6XcuJTykQY;*b>`qN&4V>wAPTx^-71- z`VpzeXmBZ7<|r{}lxYp1E?S{!TK6?A?LV9+UyQ zdGdr+HXhXMThh_Ki0KC)?mOk46b8fxR2pG@d1^nSwWY(vc&3mH9*HCW9K9Wtcj&XY zhB~0c!jIy2H}mV7B3G+tf?U%M5UKpVe88jK!fU?QERDEIs&NhzM=c_eVFrQ=5}!_P z%lDQr8-~%&STQvgghEi-Ka~J|2P`R$sI{GLg$liJtIFsvOnt7ly5+?IJrF~6PmV@b zto7=8J~cuh4%pFnZ zn7nS639D{MucYLMw%x5{Zd4SDviV{w^C8 z*DMp2DeB>)oBTmdI7|~$H}wf#)6O<&k+Y{HdTs1b79jh#PL%0(leJC&`QI|sm&Zx1 zu+CFSDtOIhsxiO-;Q=}_d*7q7?X0c&=(*|*2LRsZKP9X%4ogR>yJR~&NLMWtcNOEXhTZsCRmxkjLh#`Tzw0_>lfhlU4ku>dU zu3qY5oLt;D2Y`Npl;eKAWN2ypM^r_|NbIfod8O*@`t`x^tsXa$q3vGEVa2LtS(b?5 zNqS3tAVW+L{29RKvbkLygKC7C<+~5gU3DkkWTrifM3Wp&AO$EJ6DMt*Mg1r^Pw`jN zEI8aeFncgOk*`5YjZ_&`Xtj6j7J!>}QD&p$*D1<&ze1!eHsr=_Xy`ok5|EBZ!`Px) zn~CE+ygXi!JB=CpA=lsP`hYAh8H7pUv3dF;oV;|xh#2+$=b((ppsE$RaAy6JZs}NX zf1>iKD?=><6QloQcMG1@h!_Ty9kZZA{~`v%<}9oUVAG-H0B#WjG+7wf-gTRzjQqAR zk7v=~ln;b%RgwWnTq%tb{<Kf;ua6hj-;fJ4L)IaxiMRXWQ<<$zDY?)OL5b6L)17oOxtx>VpzBD zi=6$rs(H7n(zdKEnNmiq6bCtH+GITDBYrc!AOxVjMpS7?vs%v|=kq5K=qgTF*oMs&=4+O&ERK zND`GI*ijMNPg8v6z+p~Zx?9TVYh`asP{5%(g#1OUSxGjd|772RmRdL+^*3IO=$^&^ zpjKRwxO9fVM7c`iKnI~8XTEw9s`ke>ZdrvleBwmHtoX$Jwe4I$>e~cs&_E_zE0Vzg zRLi&H%1-j|C&qbg_>OZgI)!6bzTTfLRXfbT-x%cQFJB72?}WUrEs%rnwhsdx`rS&x zg2ZS^nn#?}DDmD^^3SE5qI~ZeHzamFMe^E3N`9@g5J8>}YcnT9Rmu)0KXGe3mK5^$ zQ{+`-G~;pV3t5#}W+V%yZ;gh0AYM!N53j@o=}Gc?zU$wmky3CeID(|Cq>sER;MAP> zA|jGl&EI0!D=Py3q+QrK%!%XMhE#hr5`Lr zg37*U;98O=$%F+F+Sjj}aA_QFE=)fdr6Yy|7ThY2eBeBOLf|Heg1z&_xDUF#_5BX=T`aUOb1v>Hii== z&R^T`M@+yUR1x@L5&d?IGCa8b0ptI)|NrC~3A3EQ2*v$h9y{B_hz0!!f^}ya*8s6x$0) z`}fg!(+dd1fWD7`OBD%%OZ|y1^JAaEhJt_>nDC_z#=!Oc3B1Y+jur)@hy$)*!8hHF z7eFESFL;cZLR~|Ve!J5gV2tTNW)d91zY_1ym=S~yO_E5%Uc!JwxIcLOGfsa+TqG>A z59o#gZ5Ri#K${s!^P0v3(dyDWcoL-6NFg>fO>Oc;z1u1V=_W<-V(a} zqRb${B*OT$ff0T!ql5R6aD)4BV*c9NFgRoy6S}5|i4Wbqj!6%XpUVyW7aM<=j09#b z2K?r_BBsy}*k1|pGJJkvft4{GfN%@>>B2exISs;P`NJCSV6uRqqOO>@&||9~OLF`x zBA!}f7F_NWF;_Sn_&)lFs4F4HJq=G*&Tg1HfWHMI^trsR?~h3UfUnd!49;jMm-wHK z{!xVy-Z2+h`A5p^gNrGI~Z4S z4lyecH5h?ofr1qR{4Wj^0dm2{3c)}KykzEb6YKb=ct6+@BUU8%e+Fm-3@n7@j41I4 z>zyiMIbUs5q*aleU`x7K{Yk}ZB6M&`k&*J_M zrlvxP`FF>h( zmGes;O3EM&YYtE)BTyR_G|>l6mTd{V((}Uyu;i-$<9rA|m4?5`>HfZ{@zl!S(ssULXW;Jq3OGk+6QR0Kp5; z7CMpuV*P}36ua~C zm~csU1p~q3Ndvaz)p~~j8T4S2APOVmYI_7b4Dc(Ac4x5lt`>EKlRj-=KL%eSBCfuk zVq5-!{~Rig`qko%5LQEoV?c35VRKm=e^?qnP6rkeFARQRLv;m36O0Qlh*mh)uQEn} zX71ypUhN7Hpz9BDh_23B5TNWQI75E`U8LjqU0ol73b_y`^s0>zAeC;C9LpT(UnX)j5w_LVg*p z2p&7%apnHNqX~>hd09|D-NgIDhC*dZ@bI7%3V4ja_B(=B@)n*g5K3VIr>)n*WBC8%48&YS#URk{TH<{L|2|V7;6@&J2AELqIJoqlAh`6OB^3dj3dVbJIS%rP z`^z|&;RuJoUr{f3c~bnO~VTyZ0a8n?7aj5`AE**~`_Z!Ab2SJZN z!^zp_;p7#M!4A+M6(W>hp&_||R}1elSV`cUWebn#2gZ|Wbll%3A>l806PVC;AU*+< z;p~^Ae~+tuj^_r3Mv~#sO(Xk-@q2E)Ft z9L|BicQp$kK-b0ae`Eo~6|NFK%hf%SC5mqWE7rqrxSF640lVyl?{js$f?&87i64HI zAp&#^#eej7%D~LVcSocX1njH?-xraa5LbKk_~r;q#MNLIzS7lfivVR0&NM;0E82=X?CMG?Y}B|q8x@0B>f+M@~Ah;Rh{qo2@^S-|;A!bN=OcrRSR zuQ0fR@HX~mtBx@GjatG%Y-rd7At7|L_c!owZwaF>C!vuOaJBwRTs%qW4uHBF0CAz* zi-b%GJc0bspV<(>U4DsB0f@MLIg|W-$i?pv!pEOtWJG_M5hEC3oD*UL|3>Y4r0HC|^3>kOKiAX_SlJp z;e>w>gJ>yeIEh?=P+c+jlo~O|#S?`WDCkFJA_6F<7!d=sj1dREL=ga@6u=|P55^}> zly_;|X=S3zPln8cfX;|QatT9HCAyCRB~T$k%vgi#h@4^CdPEBF0jv`d9<=B#5#!|n z3vnPr@ai`wD!iPD`Zy6G4rITnhL>z>or&PHd5?IwErk5wN>y-TB6uJKsQ449VgCD8 zSQODVI=ox)jEA%RiHs2VI)UgT2J}-AoYS*(xHdFOn12}PAkaH9h;Cv*D?H(&<=rA8 zrb~2}D*=JP#4RD({&~29n*#<{4g1GI;Bo<=w?rj~1c<;D9w$P^{?kDWfg!g>#Ej^5 z5my_BL}FJHCIVD;op|>TAXYFj)z5qYAM}wC2mL5Im-=)v5*J-90|<_1{KQy)s~RRl zOmH>xArR@*h+%&aZEZljf3=ZBP%YXK?;%c7@GF0qwg++AZ+ZB`e1nLE5$YqHOdCtA z{s+YKWMZwK>-2}c%Y%QN>%T67J*_03MJx*bhd=B~3$f?bQt|`zmRRRX0fK3c6Oa7H zT$i)S%w=NiEApV_#YE;Xs$F8pRWaq4R5#CvyMDv)(lrhM5^IF2h;>U5l9c^{ha(k9 zz*WgZ_9Xr=4>pqStLKDE$$2nwlBCtl0@+8A`l?7coMa%LvRGBGleAKDhLro3)v*$KZDs9wp2ng!}6c8vJlr_ zV`bcrBzA)E2@Cv_=$kMo4yhvEnS7_zRp&{+ zSY4b@V!x#@zE#^S34a?ww%eyWC@$%esW%?E39MM8zyJRE+O?za65s7EymP-s7RYfY zMm}>?G4IZ`)mEybs0%YhwX0ZTHChPaAbkNzi<`XrW~}}t2HU5nTNAo1z`MtoJ-18t zA*ddVEplg_Uww6VHztAzGgVm*u?}uXLc|XsO_0e7S~?)}>rZtJhgL^-tNCmB_HVH* z9N0)bJ}aZ0fq(hPS%eZ4#HjBi5$lt4GSw}+nyiV{tFDqr9T zB>2IMbME}uP<4VgRQwsoTeYk$K4?vMjS;^?MOoil-F5x5c5|}_8{P&qpADssnM5Xr zL`2`K4vu-{akNQ0-Quf0bryMYA1u2pJm*hW_le9elcd^TPuZ2u%QjD_79aW^Z0&gLx%uiqN=_(;neSxl4uz~H7jk3`1)J&89&JzDwo)uT^4wHuaI zWPDAK=5N1jj%`6h57BtLGPZJL3c3&C6wnRfz{Jek(DuZk*YK)l_7N@_qn0M@W88+g zs6_BYCevqgp!L?Jhsiq0*TV`jiWwQpPsgSdXF~SD&#-IPZ?D&hFC@*3N>~7l;Qu!7 zFnWmCF8%g$XSgd#N4m4&b?xJ&{ae_CwB{#4rY4_)xV~ewz21~Uk8WMfy7O>GJQtO0 zCLBp5_3`)%56zTX9u)cEfD$oWi;mN&_ftB}QlZRu3T?5HrrYc+%&^f`HiWJJnK8zgIFbMQ! z(yZ$n`B-^lJ$08C-@&;(&{FuL$~f1;a@l1;?8IIuuo@CY-SjGNdb)VS^U(Ar`<5J{ zYn@Mu2@F4Ls}6tzRF|yYF$g>uKD?tS{tfTx{D?gmNd~>5HoBv+9J(I<^No^5BV)&s0qQA* zJt|M!kDq6s3gc0d#nTOlaq~z?JrEV8Gd++eLc<(fq#6h)!&4IL9)%M&tcZm_ zt2y_KrGx>$~(rUO(Dftti( z`C)Ibo}2eGZBoL9MIUF7WUYP^kqJG_DYG0ApZ(Is_tCo!vSEw29=nETCUsJgv{}VJ z!`}Ebe9D(=MobBdCOemS@qlf-i>FB$KqpulUin7o=uvS{mgzR0%#^(g@-FKZq$=X9 zIH$yut+;CXg}31B?dESNTZRYMU>7{3B$QC|nwvSFVyZ9NYBNz_xcjwhXhclT+e zc%-}pcR6}wDwgYe5f2xPK6I2Aji>J?2DqA|SJd?`WN)O26n$BSb+VCue}`+n%gyF8 zyE`s;er_l+`_bh_`bAEu8LY6G9m80l5AsY_{jIlth_-P1UVt#2ql0_nPU-S?A7{WB z`ddgQ`?<1!)|orC1A(R8#bl;H?vP^R;LY`vyusV+XA4!Ei~+Nmo;eYj#UW4Xs-2-F z#fR8btUXyq+tkF_j%8qu+R9N5tY;kKGyOFs{wcdcrx~VD$&1bj`U0|Q15-&tbVK27 zLPZw#((UiwL#NOAClXM%m(TVYX4m0g(t8O(`m}tMYV`f&RF7w3@~gs08j-aL_WgO= zUF74a>GSucCUUW}Vxsj{NysQXUR-vqVHQ+n`LkacLvQW(6+A0jRy?h zJEmoV7-;hALiuK8-j^~>>aY<+Wn{*sXK3CNJ}QrGl0%-E^kjSDeexXxL$5PAJ*(V8r7?&_ zVn5-%UgOQcUPZ>r;Fs5fQ47w-2sIAvr3#Vd>|YyozUIa+ehm2hp4)yFcw^0}&qebZ zcTcNtn5M*i#RjOXs~#F2O2BJ}yk*Zww#rzUY#~|WgEM>9m6HMbm9OC^FR-Hxat6_` z&nkSzfq8CJn}l*>lS>c#t`&f82`XDbbQ~I+;}U=>?_zEyW=Bstnfea zx3DEZ(F_RZKaHK;u$?$`2KyB@!2cW8hzUj4E2nc?8AhhhD?-a-!g(pgMY#kt^f?O# z*}Kmqppc1e>Y}Xk*;8~SyHnjLl3CYn#9;1EogIEwO z5k1ml-5vfi^1!VQQ$6O%hKCTpz!%%t@-5TnYhfiqe6H(Z4J@@fkF{y6xH@o-@bxb& zbcjg%W;1I634mJlIBrIY$SpcmA2iJIAQfS1L^_(Hg>{ z8%M%EB#A@RaS63Ib$VIQh=y4uWl|df?vZ2kqB>>c9nnJsf@9X%9gC>sWvXi14r9{z zEb|lkHQl)$M2Bnj5u@-23l5ZTJ=C|vd#GROhMGsx@sUC(TU+FCRISj$GwKb5{rO<_wKQ9xquxLebAvc$Awvkx~2w8-nsw4hLfUz zA}-P(fN{5w>`PoH-Qp`ryVPm#3a&2#wQ*y5>Kp^?1MYqy?>|Mej2gdfb0xdhNRHMv z(v764*m>;zxHSLe3!K=qZb1%+>CDSLEtwM%k1tOK*wyiyxt%`UTJ_(MAVei#L}!&$ zSvL}HORgqgo;BfF0t^VMJ!+JvPY1?Au2)U1OiSqLuF=rgUi9UgdU_AkFo5 zf-3=OTIoojwii`;YV08DbppR`8lSV57F}&uclfG1vT$$y6LXo24iGQTo$YuZHA+0F7R!bn|dD5t?@?hu0E8$w%@) zsH{w5aB|ot^~yAegI|G88uD3AzNMenSu7(Ya5THE2B@X%0^WWDKAQR9ns&)r`QW9w`bqeAIw*) zG;f_TBEfL3$a-I$@{OV7bEvKJY9}k^vP&mhxZ@(@0(r@DMv8L59;zjzRI!%>$w~J! z!|f%eZg$wc>ohR}%qg4S9=+v!*zkcWI)0+}RDk($Mqkl)W~5l!Kmg8lD!?l-(b-w0 z(8<$Y)NN?YIv|Uwu>>Gr>!-%FH-i@Ta`(B7k;yZr=@qCK!|T)158v6POekIZu?gUB zd%#(!z9n6scWRYLnUqfT?;aK%v>X%qn#O} zh_SoJG_9pUZ9Mvk!na6x;z_3G37|%))WJ2OetfR$0cCh<`?XLU=dRdgu#f9-w7u@# zZLyfH0WKw6?pxh*debvROI=6AC1b-!D0o!icXd=NBqhm9dT8E;32T+KR2TRq-bYnX zyrBGWn);axv`vp5tg5@_b$m-PYovf4N)!p$MWR1jp9}pp#h+6DITd_l4?NXH9!a6K$ALS0J}D-O zGXZEyqcb3{@p7e92bkC@8I-=jzCyXG6aQmrBeb9B47YyviYaz`A{VKaUw4O+*17C5 zDZ44VRnXG!e10BwG|N(zF%nL~u>MuPcazi5^-Za!{=SiRK6lh?Jt4lX$oW%S}&XyC14)Eule&U|1@!)%EkUVzUB?roRerdRiEG~hec)FRtkDPWo4QzBW^Ab zneBSghYl@mCQjm0emtO5YK90mSJ}YZ`ynyy{DmIyN*_id=9>m&fQ^!Nr-RLvwqt`0 z4{$RgM;4M2B63`n*Sg9GG)#~Z0D}Mg2=OdcZA)1{?|=T=eG`4xo-uR$b)6jzfDcoHu7arU)}+#3Y$|aW`_N2U$JKm&4Lt zkG|L93~|GB`(*KQvqF3t+keN^IpTjfC&rd4Lz$P`xoV6qICex1Htvkfk@S4YBuTn| zWW*ZveK+GN#rD{!0n!G`uH2c}r564|W?-2VpgRe%g)vFE9}8uK@u24aa#bKq23RL6 zja_s=Q{`h<7Kl-pxHD;)&r&c;JhTXfgv_cZ5XuuW9g0*)LAJ2U9hTQraEaR%DJpCv z5{lbi5G=N40=3kb3D}l#i`FQf^eh^|TH8YJ)wUt}-YR9x@x8)Y5mfxO!0!&b9fp7u z)uUowhoDcvs^hM>e5Nk|63Wzl2N*0`^9RkI40|f)_eVXH8kq|uc;PB&ClKb>jm-G> zl7-B!?3xScX9=EK&mqpPSjjxL$jA%mmvPUnEaB^(o8ga@z5$BgKeLqCY+dNKvt8sW zXQCG`pd(T_=gy>-e_NLXIhFf|E2SzxxyH9&R-#%F8ktcp3dQL7^&A~v0jB$W#XW>P zt^%c9*)QmR9&wRiYqjsF)4TN9TF?i8%B5iyCWl>pgI~SBemmeHjDAqQeL=8~R~q~;xGB;M9pQ)p zy2P{f^YR0gguywjAB@{gb6`x6@OqN+yEg&aWRnsAgp*WO$8`GWCYQ4 zBM}o1Jy1!0^q7+g{C+l=VzuCGJb^TcAR}aCA{u0*Qh7{1#qb0X#RSK{Tk3K|K}95g zi3Fn=SXG6~j5z`iv+_Wr85zh40Tsap^AZ32nS5YxvoYr3T&#N;tXLTVC<-t~S0{xA zb25m2C}H?Y%t%!u#i5P;A~pICycKsWMD5aHq9eiHp)Bn zWmiaVB5^^TOkaDk>0^vWLWg&e=?FLU&GE&b6TL0_{;%cq;8Z&eYXVN}11hg}RyDz_ zQdP|mE+7;+|7n3$ZrN*1xI9;&KypDSAzL_ThEik1=Hk>=m%LWzyf3HIFjMrNAD{|=P}YAL zGSLVdHSIP4g#=)ms%w3~g&2DCK<(2p*(kEpSO99H$rWtsKG_=Ld_iV~ZIQHFit+U_ zn!AESc@5RP=P6!<6;m9MYPVI3@ZsFheHEA0&)AFd;7?1_XeE3-ypmM zWEtV)?YjLqMuwz&Y;F5?=Nw$T-@4G)*`bRz{N8-FKlv_tRkDwZySpg=x^8RO!FL-@ zgK!t0*!nnoMAkpp)2Sb}5?ydS?BKLJ*r?bT>gB%N-w%b$Q*}fMov}hf*vQx#xVW=? z*nDE?#0H2llTDy0!c_{uFZyf66DQVNt`ckEFh_W7{CpBVITHXO9L<&?%5wa8*PL2=QPtoyZ55EOvu z>eiVjMIS!ppFZh#7j(hEs$K%UUC!-xZwcra)0Co&Uf&g!6C+>x%Tq%o`t6 zLxyZB7pXh9BoTGahE7sza~~Pc3PZ3M;vC=8sEVP@#duI;;-jXkr<(QBi=WH(_*^Ky z@Y=hEzklTE#+55Z|Nem>oha&HYL^CLfQ^)Um3<(GIavQ5SBvxd}T&F)(3#*zIk{uqo6M}D9tC{+JNf?k;bSD{NdPygK!E` ztMnfck+8!UNPCfiFud!3B)2DA1=)bG} zHRrfp&BklK82EsYV~xT6FM*AkW1}TG9uTMfm}5f&pz*n7(eO*I$Owy55h8@!tZWgu zg^ak06GedFzg|GPT;_?89$#Je)!jCWC192wckyb_$uA4+lABl0`k{lN>tdWff0_Ja z+Ro9f&vV#0QA~-i5w*X)Fm907rCBL_Im}AYzr2&Br8!^Q3m8pxoOB67;^`EZd9N62 zmum?FP&t2HuXwnwY;e=KDXG6Q4fEBAY?M>e(2YkBmG!6Nw3d6_W^T4^1Zn z+g8+`ifp$Vh2J|4!&AM<0}hl`Y5k<6*Y?t{JOl7iN@Tc8qb=nRn_7)*hu1S(X3Zzk zflIS32G`k$`Qs)o)<*NLXiGeAbeIn_@e=yD_6#QaeOhJwkfFh=*0vsDc-fGr#r$LH zL25Z!%`?xOi;e2tY#8BkL)o7?6kmOC#Inv%ef!4Ji}wFhQ_T_^Ev?|?e}zTT|5I3` z1EItdk$eZM7GJxmu1nj4lF=v`#S@14dS(LX%?gG^po8sjX6}aQj*o31NG}tYywhEfkCMAY?b;S1b?S8ah(9&|Ir~1}s z-R#%sOm|7CJt4^QAW@b7s4!3#5|}_oEVeR}K{J;EvMt(b(Eh0pq6jKOsyM-$ViK9* zPhp%BnS$FcH+M!LJqaQ(4Js3I1o`>L3DnPwGcXL|x`L<_SCJxvsC3o|CZTy#2vysT zaDt`{k$RHWq~Qp?anlLL)1V_HP+p6MXxC?dTCB%nYegx5<+@C`0Qw4hr}{|5BYv$51PCibj9{pA}` z)I&>2gfEn@@{EDkst6tyj7ueES(OyE02Xp;6WcrHWhR-J`PBY zph?~HHDK4x+|{Ei-3bwJ1>7eGPN;cM2`De?H`K3C6V62Twp-BM zm0IdQPF*2XjvLu*5I-Uy(?p+`Gv%uVgAa9VmT{Gs_h^NkcWRB!N0z@CAF$H;o~jnd zM_}fPjl#Ox(hi>>a!^P8I{Iu`1zXJpPn$*S>0T&9Pfo=Xb07aH^kbnv7gpxeLg%K( zOh%Z0qb(U2J;Ai)q0YwVsg7&>Po)x@f7x}*Ze0LT?8XyXzqFF5+uD0Y0&=_$8N+rV zk;mVdeo=`bl@O!b_b!)EDhPDm(A@m^gXcmQeZz_SG0otOC1*XS3-rV9l+2y4N4^F| zZ>sR{5jMg}n3 z!P_viG6$yRp?zI@62)y7_C={thap)1=`8KrE3>jocp+DJz45tISK+M8|2r@&&FJK3 zt>+(+hr4qRIXG%+q)eG*C6~(`FKbzL%E2MZ)#Jk^(AD?D2Hozow>m4{w(jHEp4k^F zPjZU_*7!&=B|emj;=UM#B9w&b4i$hiCV<|k09TTWJl=S3VxkXTq5yxSus1%@i<}6Z zQl=tIF)@}AjL3=dXi5#~%ejv7c=VW&Ul&hvT2&sOUl&R6sHz0yo1$|2p4@Kj<65$+ z9)bvu4Y${F*F$l)KBNHjrl)f0OeG5DxQz*^A047#;$tqA&3?&@oFRynEDV^Ba@UJk zDGi=A?|z^XO}Lw`ik67tyIU{hEeaI1jm<-E;e3*6L?yJgpm$g)?1>~?RHJAtuPFw$ zqAndRY)zF|TwXJuIp0S)oBb4j8SAp=qA``aeRA79G^zOD?8=i4!X*=zN0nl^NO*Um ztJ$}-+$maW66RXO9ypO$b^r)sC8KI;4V^*kOp^IxDw+5g|=oTzOb#DF@w^M&epi8(A{yAlYgNA)_Z zYc;uAG-6D?NHX*~YtPSn);TAD?8lk*=`6R|JO(|7wcl$!F3nJUB~oM}g8=a*)RG*SB^=_F8HXsUGeKf+3@v-Rlx5H7b|i~Z*4mfkq;d_w3npBQAd(ra z=ApyER2ddj--nfxC__qM$P+vCx4^s9#!+qi?3zc|M(KG)@l1Y81(psdaUqg24sC{_ zu}x@2rPL%OWmGbAHp40A`PYSxyog#!#eJdQPxXs;U^Jg~aH@#i-ddlRC$Qmn68N@H z2);S<8&p$slZowkRLKzX$Xmsa{$HKuj*S;q4?_XTH zwUlW{j{i2#g};IR{o@i9|A~wE|BEYXTyr51thTWy+{UQg%4_B1CL}8qjqvrn(A63Q z#_~Dc_3_iOFcaCWP-FbvwNwZ?nyDrU(}P$2OKq@16%Qf9CZr3wS5zHqX68A?vxdvy z`{nz{`s2-`8saFlN6o8u&Rnzod^7UxuKs{AX;xtvuxI2SqE2^zKhJ#%y=0L}f@l0a zN-@jrZP?VZ$jT$rz)s!YdOl<}T0JDeiRl~)pKKhER=OISBw9fFSc+^w?Fvi}HIme5 z!k)VbLi*#Yuc*2eo;P9iZ1opD&>@3}7iCz2M_j8q0bRTJ2%Hi++^I0$B8){3h1XPq zk$k;SCa>!L{`g?#8GHd)2}=FYU&TX45cyz{uecXR391N3R()t(&4qb<43d*z%93Nj z>?R5=sO2Es@vFVta=Iq)1K+4Qqw@9*%xJmP^MA6Uq_sQ!3*5aq_bu)j?7b{noc9xyNDRSP;Sv@Lv`9d!KJSqZ2Yu&U=~cGmqd z*xJFYp%*>J6)<3}iUbG}zrJuu-xn~inp9d5!s7mNPadD1{Z&7QDHD_AU-;=)1u|fc+it^F?y$&j%$xZzpV4CM?Mk*#(pmG0M+W`DduXh%$D_L}ERJ?aNg0S4LF_QIRLb}A-*A9f!)M{iPX(nMX zv6Zw4uL+T@8J4bzA*657X$=KUEe3(A4#ku;U^Q7>^^-6QzZzvPgS6p4pIxt=!}xTu zbV@lDTN+(f^Ta6?(|4FM#Fm_c#%1OC z!N%`D`9E5>b-H5v(E_tGr8RgX5(8qqAXJps*4>D5K~u(~f5!$7Si|?D)mhK9ZGwP6|ElIdJg%MgKU_Zh3n@KcC0Zhq>HipY|3#VGr#&cKFoc z6_PA{_?Fp*!$4(q5z??R5;1ySuF8wY;c|P5>G<3qhs*9o`10d&+v)81-`4j6jLt6l zIO&*ZSQ>7cYa;d>v)UfvumRY)>6m>-4~)iaq9p$yh*-GT7|dio)~m-uyF=lx?Xp=x z>|(*-ac|DPv-N#$=d;j14xGLmEar&jsOISAZ01Ph@l6RR!)p^r&WG8$*-mm`WwFlL z&an^a54f#@_;gdaL%8EP!~Z-FLvV+7`(jSU9Y%Ic>ix6_Y7W#LPk>F7O|xs1YvpU| z>zB=)j&hW_3TbkBJtTVwd-A$;^#SUmtNoO_2~RX1d_Q|Xe7-^aKlo$#BYA)F#(pCC zQ~2}x{Og`kJq;{g%?Zs7$$eNOoD;I9dp0aXAod!X9`dIFh}021-2tDqpT4;{JUP0Z zuAH;39xFLpp>C7U(11s;C&e-G53n6bH(#E8lsb8MH~eMYo39jh>C(s3Ib+Ybl|{Al zKCjZJ?rm$^x+uPkUS{8{5aW=T!tp}b_k?tW7qvL7xah8IEDu8U`A8_V7+A?8*@FhTMXWMdG-ot4IxH_KAjSZX5e z_cNS-Mcx3vX2IWRv68|yds#~Bq@<#y-U&}o?>Udgqh9E~?dn$K3(q|z?S|o9h9f4@ zHYnjcJ?E5i4?v%s`UI-4EG8*Wo}vF(l_Y70Phm`M!3y3XLHD`ZPdIS3Y49h z&qu7Y=7{I$U6La~vu~;F(mtGSKyZaXksL$35A=iAbr03b5+lR$iudkP@9pe~DC}Ex zN$1|F>Yn_9Tmc`8XM$+%`K@daERAgIIEE$~Xm874JV4b(dPm}7`b``zBq^^Y~o0)CTG8@+0(gEzh?p#B{7oQh!5Jj61-qfSj&m$qp8g zZWWQu-OcCQPivOQ_gKnjm^Lf{&p}ioe;=H%o?jPK{SVX#U|ar#Bx}uDcb-Bj*}F9&FkIP z{d<0~m=vqo3ckOUQ*QR~ikZHI2IZ<#tUtUJ0LZVK8+uDpOw*+7FvrgjGzqGZ3D`E; zCPZebZzH_q1KrHCe+s3W1xe*6132IYsxG3EGHN7d$99WGrKBcB1A!xsON-sB%EP4HRIr z02D-8A^hxS>kLt&Xq<%XXXZ9UN>Za;qpxk<2l!bnD+1M~328>_GGoJQ1?gqU9I(O` zoR&RD9f#EGV|q&5{C|9-J!*B=3f?d$RHAh1$*~Q12 z;^xE<5l23qltaoJWCx9QrMUa$QbuQs0FP?v-#|}MzdZ#y*MWi|Vts(Mgv^dBwYD9Tj>H2M%X)Af1=0 z@1vnzqha;`-O&3iv80qXY5qlPMBm={y%^f9L|*oHR4$83RCT4f6P%r_8W2GPW$a{q zUj+7T2$o3rg86L18LK&^F_7{%Bp`E&FyQ@(h`oFZfRS)cKTNc*yJCBej)UIcPxN^) zO9B1P!nOs3U+|4UO_G)8nP?36q^2FTcG3T=T3fR6cg6l}Hpl?xQS;~~BrzDEH4hEu z_Tv}Qei=B4kxIkYCF3KmL-I@qP?l<>^P_TIlZ%g=4$xe+i)+OGO4C6Nw@v7%r{sD*y%I0*O0r^23+1&o0VtbbNBo2}0$TMh)&E8vo* zotY@^fj5jH)aV79Nd)nt@yy5j88H6U0Ji3ljI!Hcl1&abIXJIVu8ydPlFtb^c?+r_J&z5C^UpuFYE%Te6c1uAq>GivL{uGPa_^G+1c{+DZ zlBKD6WTt|0uH{p2UZ9IvW(Idj9otQKqcJjoyAPni?(61Z2Bec!sZTLCMLR{P$~99x z%&)+d*ngY}B`OIyvS&-zr`eFh^9-eo>`fE1DN#!+a9CUL>X2RXbb~#L3NpZBHSqJL z^0}0B*FmHiCPV0qJQ<)t7Vy`ePa{*R)y80%I0R zgQ=X?Ee2`#weha0hVXZvW=iO1fkV58i2Terdi)Cfs=~V~ZrgS-dxy}m8l|h}4c=?m z0g_ry`Prdg`6YZ)WMk%`StAg~7rCBZLA?Tx7yb2;0FSu3!j;z&V>s`8lH2$1pZWVK zm1L2t_a~sqv1iJL05+5A48DeEw)^}mAH?6Dzwie!_kK$GVvYw>nG@tiPQ5wa`Y`v$ z3AwAg5h`AK-=f%DFb9rgO7f!?yne5|JSmpQ;$+;lH}cwX_?*=u^6*&;5nHs~<7E`! zkabcH0%YF``_AZKiX0XHbkeKNJ6#@49y_&wJO<}_@>etolBV+p$)ZXD0Wvo)c zOumTVA{Lz860=Sh@Y`FkwSCyF;K*_o>cuLfk(F95iDWBA{~Z#5u3_dm-aXAi?WFkffsXGK_bzfw z4A?TwKvB=>X98}yALA9yVajlmJT9x`?0umH^(4jV)X13~KYepU1O%#Z=}E%)CGqti zO%px)1rskka+5KtH?-#QcOeX7S?ndnu(Dk+lG|F6j%{52UW%-*V~9(bVKza&lnZJC zP5Q+)>B>HqR$F(Gvn3uQatk&Zc^~I6O8zE0;=77H1XLsL zI8*FWdi6tt)z003Rerai!$c1Oi(`BP(K}LF2;?mlFfKnaRL(+}8A3j}X&-q*!n9C- zl^Q@wu?KtU>9#s)FFLr8+F=vB3S%C;x2tI!v$SYgK0rVope-!N4kDsr4jAeRhSCnK zP_UL_DHS2IBTh-bjx-q`X{4>_0Sqe!Kig80(DZ|S?tpy0yl>4F{|v(4HWl~5dV@je zd)x%p-f&>q3E|Nlzyi@H3bS=~m#EYj-`owXHxuEThH?;VHmfG85BzhlhX^b~+Sl=f z@eq&H#_7nM&^MYRm#{)aJ%`JwiP9LlXe;b$5efB@GKp}!W$)x9j%WIt zuV0;sn4qS<5+Y@2wtBYC|FSazR4l}hDYcD@jS>um#kjM*p@xmFkKD6G*h{r|NaFDb zrt%HO?Ei!y&3dm3A7g+97QoNL%JOkn1vs`dQVuoPT z!a*S)uNi3W4sNgHE-(#=mA+1G(O^zm#wYQgy|HR1va*9U24v6>*P?A8oZJkfPm_*e z*eJ}=usCt-=U1fX-D8+hsHLlnHfu@=H`6EH4=N|Jo6H9q6x)I9am&rV-raC8Yt!om z&$bSSG3I{(VEyGC(%vx1{CBBu38dxPi)*1&o^4Ys9i{w9^e%944XrpmOHLc1&kGxxhQqupYS~aUeA$ac~2n?r)PgJ zgvyo@@?@)E+%4Q9$L>*X$D6eK7E9De(-_HgIHl!K&nMwX#pFpuwaZNvKj@4z-S>sg zt_R60h0W$(-vVF5mssAKZ>UH{7KD{5c%(49nXIl80b@B&!)qm^+!g^k3yt+qblssH zWmQAl?EZ1SYZ;rmUa5)nByKqHXOok07S!F~T$#;gLWD~dBHC!0OMML|u;v+w6Yrln zg`v2P-&|xUvczML5|UQMiE1B6rM%)Yq=k*dTDqjh_RF1;xguq#q!Z3o=|x}+#d@y< zx4Yr(fHi9NkU2Ar>t8pQI@zv3Sb0+D)GCv{G8sd1dMUzz%5)*}*V`1b2&3BqYc@^R z)vxZD*S>I}1dYT%exbd!3yTF4mBJsbD%IM!xLBx4zc-}eZGX$fk%DGf1DZQX=P5G#ki7BR2vv?Ek%E4SdFT)C z2jlMJ0Uvb64y)pG#VeryMn%K=M>_xh#r)cr=}`FN(tI{2O{k)6h`g;E;4YqBqd&&g zI>T(1wzjacaEgepNEslVIbk+I{7*O-;auO8&$pG-Y5!S zb8i0V`BqtIyCkI_Mke2-d!t#+zi$$L@+v*&-R0pCxw2v4Sw0)MkjF6dCVk@CV(qp8GLo)cmsKX%9SzSLEW(8l)dRFpTgkWI;Tu(wk$0F z`*|Q!Qd=oBmTK)}$l}o*>bU!GWV}er%R^{^72{dbu&Fi(eWbC%2yh~e`EyKIe(_3`t+Fj3VRt@M%W7?AmT*Z1u6t&ZZR~}@B{of3WF#3Fm*9}Hyakb(1W_K> zrLJ|^B72x!(OPoEMeXo6Q=2*gV(Q?3x9hili}%5fejz_ib^{mG18f>wmMW0E`v!hJ z!kJTm!Iz*bKNNg$Bxhr6o#B;8#wKvPFC1oExuy5dn~IXYaf@(IRls1fORt(+{iEx= zFyQo;VhvlT*=ixmRLKN?`+s4!rsf!kN0LigEJ-yb8svCsw+J_;idDT8`*p}5SN3y& zOWFTf$Z8L{3Ze^l2SBfU*qKoK#C%P8d))~tyRhE#49Bypp+&(+2a|R|yWwv)&`Ojf zH9lI>^sYNGegIRea6{gM<23u?y;~&itd_7Ays*t*;Xo@Lgg`Zn8+yDy#ntpy8v`${ zGaP0A_0X3F@5hU?cgIhV0CGeN>2odgYA-dFD$-NKi? zSmN6bI^{U_1Ikhnt%!MfS})Gm{gs2G7TRPD16oP5G+c)~U%1pV)Fi7z$y0WCQU^fB zBIu7ZHJ7K50O3Tk35(&xE3ZN^^BG8#LPS3)p~qItIWI>_Hd*4*@LB4%(t|C-4YGs# z-gJYe7|r3>W=JiDIo9%Vs^`=WC5DI})TCFuj&wrbJix439mCstCd1D{NNrBoR}Jh? za!<6n(WJ~)tK}FIOYpb@$_-flCh4Xf^A+>lGjsa|z-a#~#>p-@4-e(0B=oP8u3{wd zMB6L=RXNau9Zv!*ABMxkK3{=iw_}$CvW&s zC!94#N16Yxq{!7_>V`_?wh#ojp!kQef@=J72FNO;pn6yT*?MQyhe8Y^#K@9%%1g)6 z(be>5z?f?}U{gju+8bW4kjD97+qzH^|07JaDcPADy(2;W40@ZmZzI5`LQcm8^V`+x z&C$Mx8YJz*fx#&BrKzNLKQXn$c9gZ0!B|Mqr07PyZ|B2QUDngmv$pOixQoAL*`{#x zL52EuSIum}q}aSzIx&684>SYUCstx6&HMx!(9}dz!h&VTn;GG3rC7Ry45+TA`jc;` zfLgKw_O6HbG(5%{P_ge3QAY&%5n#)phSs)MYRwzn#2`n{eggS`kV~~8%Pvd!8@Wh` zGI?Urkt>r%y_yL0Kv#GgJbS=z`+Pp}_&`FGcTUd=07=;1p8Yaj>9#sq(@K`t{L~2v zn9CHsUeIe>s`TKtscb$>35Ukob!+A4hB2xN@pO~!2_PHoZEMzK*JRE5mWq=trCYI0 zI}-U&19&36-Qab)-Djhrq)1iFv?_mtH5)8;x&P1}==hE15FhA7RyIcT==L~|9~UxF z@t-Gy#Zo&zgtz+aHa9YR2nY7x@fTN2-yP|tfA{xXXI zbGvN-xw8BQeW!cm(unxv_qrwB_IQAMW~_VWpCCR>4EzoV;B{U^l^<_{)fGlWSR5Y2 ze@^Lp%~RdPE5>0koWr{iVMGDyoq-wU9o7XwIC>ab1AO9-c(uTfqFH>pA?zR%5mo zKXA)F-S~(_(LSkXipJWB##%vlk((!CklHQAq|yqtMF91(>@7yiz}gCc-fnG(d-#tp zAQNOyBS^jgWqdC_0O5y}Q~oOsmDlXNFjzxo4kTxmcv5!Gc=5YYAVg^27@lM-J1hwe z)N7jfpO;O}6}^14>WfRxwUoyN|AHew>1=0|E7CK#;jFVkOvPKgig#ppsWld)I2lzp zlY+y_yO(NI~@yfPZyz-wFx!#>;nD$Wfn# zD*ZD?S;w$*#t+Q?HZyzroG=?T9)`D=K1_bS!|C^W7v&s~)TakPXTd`#pIk+M{kpVc z#GuGVS7nlV;ko#1II-K`K93EWTBl8D{3Mo-uB&;mc<}S~b2Jp|h-1^q;LCtJ+K&&9>cNqtarC@&!)=90el3dmmmES1Z!G?UPy@(Ih2_YTTfG zO+%MaMr0s2cmx0}C=il>Fo6$VSo1KppSk(Gj-#KP)#l%r8Fjf-I{J+2EN-T23IqwA zZ>v9`LTNGYo2);jZ?b71L7WI4iS)ZMh589}khp%__)d3MjYcNO0lg}IyF-+FtUo~q z<}omc_N6dpdskG}&loCE&&hT%kWo|Eq8|pr9Gv-c*(g2GH+no z6vPEtu)8wRK*}4Ah0SQcmT2ZTpwHMKc`#Ju-9;#fLBz;S5Rp{4BrMmgXYksZD{SvB zqNsG>I*&YVDBV&ua-svper+Mlj-oVy9m*!(M;E@u9WT%858xBoasV(!a6awfp_-1 z+&=p2-lj^;iAb^8DX;oI`?#NA-^P*U+>SG#Q2YfTJP8`lu?vZ8WkBZ69^8SPJ}#dq^P+JISu|xJwYX?udF#JZOic^Qe zOGo(~T05G5!EflhN{Ejd;~BI=gfdya_?qCQgH5Ed$0@yhRK1DbME}@YP-Bn5-G&&5 zHGcu9-QC!J0z`uYKafl_5R8$>pMGP$dw$rnt6w9O8;xyvN5$f`)A_I*4RH+pTvjzK zV6Wsw7mt%)3^gtLk!9Z!>|)5I$98Zm?l+>5iU+rtrohE4F#=t*k&%?_tq>^^x3Dzt zz22?Q=XCsiJ9WOJ4i>~A4zlPk6W|Yw_ud2`+xVZ&PJtxTQHOZRq(^s$>f}5TC)t-z zZz-FkeFVq+Sds15(P$hWC?Nf#2)r9)aw$VDs>dae(~3VW-q(kwrru|wn7h?wCzmE! zkjgmuxQG=>_`kOk4Jp{4;Q62YL#+1{JZD4{K1?fDD_D}V)g;wdn@0FiqVxqfYE}b2 z!jGP)-5Um?WrWcCYfVEg&mIpbAM4C2RlV0oplRKRipcyBdi!V`J)vvH38-eJD!VPz zX?xL@5!VDJJsBHB`U4YFILP=X%2w}-RAZV)S}Xh^H!-mz-H+4kxe5ARAaoP^F@IAU zx0@R_Lp%oZoLiVa?S;NZ=Bv&j30?rCjNq9q)K7|1Si`n=qI7zCN!}UY1GE+qtlH}w zgLQ?z%DW)!b?i}cW2@jdekWxnOIVYN_({3xbThD+**ehV3}EC7(L{Lv{h~y|KrVln zHd{Gg^jUPyVkz0Zf-OWoD<`(2ghCUfHm*Wj;hEYBOrMp1XH8>%+DH3j8yH2ufEdUcS9NqrH_OOocbh|Jf)tB5e1DF zt~Dj7g_qtXV4F=Fo*_&Id=3^N(YxPjr2Aqu<5DkK9FzWa_QVl_1j_@P>7b}KHYGU! zJvPsUMko<7=AJE}V^yi6i04h1?FDQIj!EpasdShxYgIfyS!%f7jGPJ(#<*6j_hjjJ zf;K66=Ehn}Colo8v|!=Xykqqq zspg@L3xgRYarXBujHv)X+O1z-HLJ;Et9?Bw-Gr?NwEfttw}V~oqSx3_)V1u@-f!2s zqvNvW(Lsa6g~49w!n=lIFU7i$50A0r6ErWQ8()k1=N4bM5BRG^%TQQ$jZw!)d2vfk z(I$ba$GNV(=J=;)9R73kPz__-;oKQuy6pY{q1x32gCIx;fd&r-SLpou1*-}f z{eQj+8yUuK8yUuNxA>nK1tXCjG);r__V%7lzV2hBM%*BTvk3kRKdeS(RS z)YV0X>SXR#2HSEDQfA#?mLL;7M^Hda0a}ZRlxWOyIJxmv$GQ}j4{n`-=g-MH(-FV{ zquF=@1^g-_GJp?3hFZFgXn_nI9d?(CdM;iDLRcP^87h75uLY3>Ec5a#%49S~zVUCe zG%jy5BT%7D4ao;F{wm;HjsEKXL*R1li`xk*vz}u0%ryaJa8z=VTaC%=;xi5L%Ypo5 zW^)S#ob;xIQ;}mH0Wk7(7$k;l6FtB$X@^KpEWuIBV^%)6X$JdPudo`Avt z-{KDL&m_=6QocYYs98{lLFxBIY)tT;JA6HH1vot5&Z%(mLMMTO4ei2553E%+oiInC@ zfL%a8!C!xoCZJbC&caak3~hunnq<r zqA)VY91Ua(M8)un3%Wt{F=fIyR?z@flnMzf28pz17?Xf}mT3|C5!Tqk@^Pp4Cs%d` z^Xn&>H0j5DjZ+MJiyH8V+z@`9uPF;H7v4T+PIs8ipD{v%6usc-}ss%2)q^@4FVLBbVip28#8++T;o(uhSTDS~>2SLQ?_A4H7K7wQ5~d}1QWEy5s$ zS1=qBF9Jk@%V8r2HH?;#vk!h=U3`S6<^_ru{quhGcDqw_(W`IUnbZ> zg)w+%*OP9y+;nEzQc*@vZuC9{;$a9Q;}@EyLF&JVHHI!_-X3Ip`v)fMpJ#!&*1rxt zo5bASGq}&c;*Z{$P}Cs6ks(jtRW}ZUH4e;UH?ci5Nqu`zron`A)UrdN-}6Ne{gMEw-ldw{E+S(!LBHa_lV4t?8=PvKh8~d8kAKdZ^{NtLiNFD`02N zR}+L(18AMj72BX#*5%?y(~&%f-vKbcc>rFHO=lM`Cs(Rzpbzp!OoSfI!nbgau5&i; zPjKEYY&Ue)$ba2hw3ct?Kz>PZ$?q^kE+B(v?ssZFZE+m|e4zIH;4u^5FH8R&+r5*K zhAw)SQ4Lk#y-{)Hel>V3{Qa;d@p1g4`=S8>u`ge_^w6oPbJ7bE<;|w(@?xV&%O)`! zYKX^w%@=rr0>^|B0tz7sW6B|cx(&yh%Q}f&^+k~Mc!QUF|8g4UGBK}YZeGB=xg#s0md zb<)XOH~det$IO z&E#h99Py(%cU3RzGcgd4V5g_*v(-cR=WGsKo}il@GNOYU`i&3Jh%`4b(0(_Dbaa86 z5j^Guc&@uB=m|Je#$GiL54{wMEKXu-Aw8>v;aXFXXic>l9Vz~y z`Zq+wDwJh2P4Xo3Mv~0aZKO|mhlImOP4i&+EehDut*gr%c8fv7fpJ@C(MhSE*~MtP z#lHp5?grrjiVFb7PXKN`Ac~NWPq7L9Lre6=eE1%}0)hN1j3}Y#Q0pV%1D-UzxG*2A zBX?G(y}2vPNH`>aqk;iBfl4S?1d}IG&slOK93F}(Sr%NJo8;hEO7L4^tC>aGtVOK_ z00}UF0_<;r(O;PmKG9kyv(6o_%okZL1@I^n*7FU>e;=G2R;$?bczbu<%BP_7Ul91>Q+ZL+de*W~?_V*RAmHUFq(F9Itp+A!6T+N$ z3%5usp^Y}iJ@cT9j*3H$XWpO6dDGJ#OjB&o2wJIRLmQQ1=?GIw5{Ek!e!PfFqU#+7 ze`7e+a!3IyL3oX{791?++@fxqdbZqd`eNp3fpkCanWrIR+Pf&`UeTG+4n$@jfuS9W zQ*p29ueX=Um+ZJVhHna(ByA}nMTzN}93e6o9}8ArUv!3*L149YP(O_@Q>i3e7f#}<(Sm10r=K}S$vrV-^5UfrykB-dO4H66q~>sl<-mo$^U{y0MDHtk7T z$^b-;B7{R|OO8^F7I{&b#~uVC9HiqGUPy-&ZJXn^o5nB_PrIuTe53+AM+TlbsjxgI zbtvUzNq)QskvOTWKz4jOPR{F1f3s-$_Hx_y+q7a|fr%q{=dr$EouNIlROu>H!JADr zALFAORkqo&1EG^olvuotA)Um%KTWQDy{*@M)i*2hKv&JIN<6IF5z0piAC-3Rb{*l1 z%*Z{*0|pkQCj$ftHd5s?j5yMI2ew+JPr^O~3LPojW@O??TQT8qt2R=Ff1WO9TT%MC z1F>UVbUY%;K8kU-NAEwreDkm0o__l}ndq-w+wChd{-g>Z%CS`d-o`JN0o;$}bTt5= z^s4*m{OPaN>K1z{4X{FdcB)N&`rgt2^=Gqr(ru|6z_IDi&3rS|dktKp>Uz2&o6HR< z_GL>isx@K6qdVmiFRDeoe;Ll!>Gvk|hJJ4{TwT8Ud=2?Ja606|gOCd_=!Yi5RS$z6 zz*T#+nYcEe0K+W8eZb5>kV2Z_ngN;&&}4un12h?+%>ZrIDxzgGNSkTeOw(qXHq*43 zrp+|7deJXRhO7K+k_RHmMB?yK7Dp8F^GV+;4VQts4AfGE4@fB&dEFM}WWe;3k9+X?jLTOu3xMXF(m*6Q$1kdZMAiX{gwf zcMFQB0&POSZFBTvC~XhRi4^l$^au4s_dDb}<$6-@%87!%x130cOJN0sCLG!o{+Wl% ziT(#Uz$FHkVeuOimqj}qBbQ;92^g1vI~*T>+m75e5`EvV;G>PjP-O8Q1O~=-e8H|a zhA;6hf;_0F+bZES=0aHmP2s;jHqHs#_=Sesn(AX;B48}=T z3x{`jAmPSAtr0Fner1K@K9Y69tH@t}dEp6Ik`2O}fDUaG-tp*|t@m8xAmqq3P79v` z`f((J##E9sA{d3wofW|bu5r+W;Wl1`2z@0NL>Om^xkZ(@CW&Yu(FB#o@hh)I1P(lq zh#~TW5s_z*pw^fY=FW;yz?-~hC38(+y`sa>6aqi6^jW#wsbM(>%~C_-z|!Y`DF?&z z=Nik?=7(|G{E8>ZeT2Yp@#)y9;+n(=@M%=s7ha98F}W0ZJk~Pfj{HSLr-?^rs~X4Q z-Z6{6{rID(P6hw}QdF;BJe~f#b3P24-49iDwyit4J=tvg-|*6f$yQX^W<&c4|vf?a(73>kNa2s zSMcb=j}P!@PZIWEU62}T)ZR%2gS0+K!cv}%$roUx9eQp1PHKs%7QixINe|~?ypfunao~R*W)}ZSP{KGZH9I4cDQWh#GH9Bwx=;Xz zpe%!sqhU`5v4xzHhT|80I{j^!?$^8KQQr-s`p>h+|NiOC-(N5G-LQYwcm2uze!YA; z)a&*PsGHqc(=F?6;MO~TjLs2Hi5EP~Pu*F+Y`Yb}Et_s=hpUq(HwNcn6^j0K*P>wq zzpchkGoW$&Bk??V`taq|ZfGu^c5nMpu0ONj7{r|eh`TJQRl6IuSK`j;vR^bT?EPl5 zZZ6OQ5Ln{q=~e&u>BDFB<~@E)_zlOs2^>#;+ir$_JNnlV`t|I8@IANTsnF+U^f|4^ zA}6AyLIBVS=FE%&CTN)~DExNEn&MdtJZI{asU98)FwXHYjS3k5%Yf9D& z3{t}qL4zbO7MCOkPYs`JeL529+jh0z0xO{MS}qZxF%hd4^i09IfW^VN$Uqz<;9!C- z4qnTe4e@QeZ5H)^dM&$VsB$3NRTuU4-Lk*zW`r{^5X228ITFf-!bwh)QG!m)_CTq` z17!%&NYBJoIq4kJAL*UHZA+vQpg`!LSx7L(ASfZafS&mz1GsOozME#Vm8*Kyuba!= zyH=j{7rAn?d^?M`fJRGZgc5`pR2pJ-X||4yDiGZP10)E46>Fv7eIm1acpLj&L^oq) zL@f;+q=tkFF1B21y2RizhDmCq9U`-zBef413?jQM^2l0AWIOP9T86-MCP>avO$5N> zR>JK9WA5U>_rO6V=Yj;YgYZxfIht}i`+dK;f@4|N3%PCT<#66C`?H;F`>N@x-B2&q z%^Z)cBhZ0=C`7P9H}ZRrd=hyw+{}DdXs9sBm_TT0k&A1OjEs|a($WEJsU+L&yJp)p zYq@HN^ZkNFI45%?8IfY!6r{3a05%Cu1_6Y3H)ad2Xl-N=HYMp`atLfP*Z@%YeRSIK z5nZtbz`*ByN@MEbnN1<+1{Dw`kfUi`hRYTCIIK~Bb?tSrQaSj~bGv^Q{fiWf)d@fj z3n5yh-*NOTE`o)sV|{UkC`(o-^yWO{fX{WjeJGQG)d8hSGvSnoN3)~w;TjLjjNpmO z0F`V>=wP8JIsoF}sX{6QWQzcKcqv|iC^I77#xvlLF4MF>LPoU9DI&o4dPKY?`6(SG)ZMq#@}%M@9PCWLP+fXKUs_-T<=Idd$ejE9Px zsx?oM@ zB(F+?)qQ-*ej9+`TR~ZYKxzxO0IODHg)?wle!g*&v}HjN037`R{@E2~UsUV4s8!Cj(_*BTcG4BY@m8j5^MeRtVgVd0J z7t9K&C2T4Jm;n#;VLmVq+bRl$Ucps4k)4B4O7gKUXg(jH-ZF2d!hO=nfe;jxXwt05 z;xtHmLv*(dwM3>G{)11RiFa7SNMZx$ObWWbb(t1z--A>T((?mQP6qgV>w5q#+S}D& zJA8zF0LrAu>zP1vpwLBW0dL-VX5sLEcXm4Ph#&T}UK#wBw#kNQgC-#%)X!5`um#HipZ~%ktY0&Pu+^L}Woerz3UVZdJ!+U*8X( zzs_36knQN(v({h7dslog%h#@^GUPJmGEF5-XV1U!H>7hN<`ZpJyA0WX>92?)PL1Lx zq6qFwxLmddm(4j_DBq2{#^kbkUB;Hpmp4kkY-TZcbSS6(v@%BsE#Lj%n|M=6Uz_~F z2tV#WezE_UCzNjXd&;+0FcWlCo&K?U(=Lbe>3#=aBxweye}Ypzs5eiVc6FW`PxoF1 zaRQX3wc`j#+D*4%JnrA`{|lTagkeu~;0ug==Wuj&{Qgn9ZV0_+xLozG`l9)> z>n&4x+O5_Nx&@AxLv!(q7(u)ou29RfdR}+^4v&iekXopy;B=J7bB%xY-spqhUrD)f zj|H;&A0*|^mX~4i8xxn1MI0lSVma%Ev{ z3V7PhTH8_^NfLeEuc$|R9aPu-GBM!@z{bd)@pu4_z3bpXhDLO(P!m!!nEm=aS>26< zBxH$}V{L^|sk<(xGP5#IR#gn12^K?O(rSE1rek0+3g)!Lw`5X?h=O8L8HIvoQU`is zsDBC7wM@EzPNHKnD2sw;G6sV}U`ht66PeN`btagyQcy`U<(#IHLW#N&LNgV-qmp4- z%2cvU8w`Y!W7>sO@=OPtN`VO~pmg-&lR z^D0m;$}w*xVNsr8u=FgjAk&OgWI+pRs|5?jcq&O2Y?_BwEci4xtyu^Oi-xF0{S4Aq z2`QjO9nv$;qP6K6G~pFt0m$ery)~qLMZG{hG3fLRdJd@tI)$RCg)vDz>2=bSO@B{a z5-t5rI90-J>S>UYO-%EkW>%z$P~9YR9jJv(4FtWb@gyyz!D}-~jLEZOFQ~ z@sjEv-+Zm^u5*_CR*e3`vXfNa9gWHgqa|Q_{YidMjw+VDKHNKa`})Q1FdvNbyZ&*1 zG}$@I2RFn17%xX><#{n0u4Sq}JgN3CQ498xQD3j}$=SHLu7ApLTIGTr z0YJa01i?;W5g>`L^5dvLe>tqIu3jUpfqg2@tINr~OqPF?qJgm3uz*eT%)suAr*DsM z1A#P?-kqG~=sCg^vi<(`VO|U_t9s#P1fE{*XnK1v><=c))KK>J%5Q+NV_*wAD(N@b z2AZALH4ge$#qf?jYlX;2ihs|Wcf~NrGV=8V>B;;4RsJ2h_p1J|INKc!hB?}0$5noH z$U;;4E0w0Anvwg0cK_Tz?!9}zZS6)mr(KEVy+XZFJW;)ZeD!x~(8v0az8$=Ufm3|6 z9+rBl2Y<4>hH+|*@gB5*Gx#Y?EY6$QO67Mnv3t*Ub_t)BkGa%ce1BSSTu^w9iYvrr zr7WjttAynq0emf=b`NQC^L2uL$coZu8QHUo7pC(#9t z*4z_4vfLr&5E^MBS4ut=O_xYyHMbOi6hMJEMaLbulGL6nXE%*Q2Zwv__I`VDl7D`4 zH_lJ;@l`(gykxGaTM#^W=8c>Gwz)n_TIjIaj_$I z#F_*ERD019L4UW`;CIWyeaqEM3dIIlQp?xGQnp4p$xJA%e`3VrykgI?^f0?9{?4J8?%jYv;H-rFIX-;zp@;6}`bt{nE`(j6X@6o(Eh#W^E!>7wXj>oS!f^ALpZCeo@t>aWbNBv$i6UZ8yduwImamvlgmgoJ+mW znTwq_mxuaX(_CD9#9Xq^&BSQ~XlleSpx?t<1SS%#Q zt3Q-GZDZl;6dQoTw3$>uzGEdavsmj-D+FFRd@UoR9hjdhkCIZ(FW{9nv9(H{6yXgdPcdGsh=1_^A0_JrFTG0q+sc-=$-O~gjRyAy zb5tNLS_kfldrQrO)jt#WR+K%fv^B#uT!gZg8}L;VE#H`Ye-EjNT|%5vT-1CN2pxVq z?k#QcYvc=d%TQIP%)vwdwBOZ0C3_G*3~8qwYY+7!J{uc&It&RGW&q$M>!Nmd!&R0e8EyKs4Q2C_IebD9c%&&5I!FD>OapetLl34OP1Z<-txidhL__(HYqQv zTX4;6Fd1g&s=#V*S8I_)EddJ_Z|#RZ+E!jV|njn8*+!rDqsCz!?x$P4Ba z0vC{*aXM*qLq`Aa=E5y47O?HzR~7uG!NQt7O<{yRPJ(r}D)U!dN3F+gI~G=)=!kWmV^B;|wS`e{-( zt>*1-rDbf3)z3t(PJYiIC!pOG+S$>Dj#JXL2X3DnNlh2p4w~i!B@`f<&NFynG7Hb` z=B%v_q5tf5-h{ZM5H_`SX}^gsK7UBqy>{Sn+B`k5L*Sh4H*SfjIXci9zJHPS@1Y`@ z(e6h<)txfdfE3Wqs6R?%uwi|uU(z*3ibZsbvHq_4;%S=3etCm1h=};EI8VpdzNyq6 zVt=56iHa`H%`%D){Xsry`wvZjU()4ADyO@T3xmk}QPOR@x}xz-!M0Cqm>WC94xoe9u33x@D17S-_6mX!$M1UP;z?H?BP%OcdC3(zljC3 zXW)-e(pHjhlQQ<@86ACLbU$^m88-g9?_&e^hf0cMM3`*{#%&I z%)gh(i9bfiztBZ$x*J^}$e9yst;@y`eCgoIzA)lKr;y?Q0M1nX2$w->921vCP#h$e zq4y0Jmw-?lA%ELO68?U_Vm~G*yxiH@*Pv0^n61E?@y4VUE1?9A-UGea_gl~H7ZQ{<8mUa=t|f^yyo5mhizh@_(TLS&W8 zGf`eGOA(ij<*8^Dg;?&gqHL{DPFeCnD6cGAVH<<8u75CyQQ1J{Zc;Xe@Cs2p*5E-7bYc{eNPtjGle=S6Xo zNx4XJH(TXWzsAZN5`Nh!kIf0?m1h!uIVkUn4RTaI6#a5iKKgPuE1z&lWDLycf>5La zK@cdbf`1KVjX{Z4WSj~t@4~X6L<3kH6oi9jo<#;66=6!DAR~Br1FyyC)hE0o!)9)JchkqRV8RB!=O| z3@=*GIv}kPyyy@1;_SMHmVV1F5@|0gfqlmZg8zH_e|!!0WDF zw6pW&e9_>&>TTEDT&Ofq|1Q*n$F?G1C(i!$_luw2{o~8W89$0MpsBrKmW~QDmJDvi zr5<&ek*WmRh*MpXa1g*I|J`52$?>t1_nLpAlOGaq3z#uv-zw*PcG+Go+JDu2UEf}R z_`1EaVG;sCMF#{+MrR-_;9;GCK(f9LJ!T3(`b^*P^!E@i~yejtfH^cg4u0!+7lg*fx<+*!Kj%=AUOf@ zpp<5mPW&bq%$@`QWzt?;m4AXpcS8)Y!J-#1l?0_7 ziV(LNkSWm(Q#fQpZ}D4tX97}0Kf<{7;aD3@0b(4aBp|@io{4hENe*@j`S`d78|^1` zLsUG3o`V5(7*L;L5N}d;C$SMFE&V?#CSWs6hUAELn|;)1+)t2_P=6Y=hb@5Zb&#P8 zQWRx)(p%vDgKPv9etq-0|M%>=>uxt+SJk}juJ11OY;{x3>-lQY{IRLJrk-5`%$!}- zU0rqSrm1cKS5PBw>UHz`^F5nDtFLG`uV!D4C*wDfgEkQ zUov_*0yuJn>yS>7#eW#h8p%W|gwkGelms7@2ZnIw=mRmSNCO^ZPxtc*^gTErM~*AL zkdbgit&Hser~ow?$t+3d3x7&ib96F;-+2D;K$(|0x+9dsz6kZ76?BU3bnqb{ zJtA^O6iN}t?>G=TYUC&BgI)n04HxtvGgLxKlD=Eu!{Ia3tvWYl;!H`-7&14oRxm)K zu$D)h!im>QhQp#;}wDfDu6x9nhNuc{y0E189)Y|9Lxd~_&; zGyPNn(c2GQ-jA$)uIJ50SQVEIH@EoOd#>bN&%=k2#m~S%OBsy#k47^e^BmqX!}RKX zzZ%BXxGQo?CXI^AH=ltRS1do$W8C*+H6B>|t=*)-B7cL4!aaZUcze?KKDoWLy{o*> zexoIZ`RYdk;*$cR+u<1=cn&kP@*%8ep2r3Mx!d@pve6Ix;tm_KPb)jTC0{}ZB927b zXPea9gc2VlZr9#h9!`TYX;2}Jrm+WkIGHUEk9x}I+JV@6X7ccS{=~kX_IVo5Oxiv( zX|!pI`+q_r`*E8+As-xug>=xq(e$03x{sa$U%rKWRYZ?=ms#qK(m&(@_7?*%h z93FpKYj4}e68+v^u^$r@TJHN%6aoCWzINNBsh!>gHwX$^Vq_w+C`eR&{qOIYB`L{~ ztwv&s#s=)+k~=%EojJ3ll-e-Cq|}y4qls`#1y6)$MyHX$Y_LQ`=CuT21PeYAfh*Ar zDf|hE!W^xMr!nB!jA6QK#vGGABnpc}Wr%+YObJg6Ok_$aJR+@N%34~(N~U}yL9Ajb z8k%c0(^3*=YnWD+xLC`y5oxYt+S)Y3GwovH5||D)&4^6LH0A^|GSZln(3OOgPBCL6 z@pGD)paM~bSs975v&@>LhjYw2OENnT^SJa}U{1(17MY`mrSyWihO?Ip6X-5fbuNF+ z@S3@x)0klpl-BT;`D8lj9VnN^Jo8GES9}0vNdiya(8LAi^xBEW0p28k1O+PDAZX^T zNn-|7vNPQ28!ZFYa7j`)-8-N7VGWQ(VGSS1RuOB2v<3|3gD1`rYs4fe+~cDsE@0|o zq`A?uAey<31yTW&2Ne^Sz=BGage!l77LZQ~gq5bd3YWpSG^SXv&0P(OxF}&*2qt{@ z;xCGyEtdr z1ysqzO1c zu;?L8^c+rL#&acUTPggP2se&6-%p<5O+KrOIoCa;ky3D_EVhd0R>89-@+cslm7F}i zr-hc+Ya)%OgQp=Xk)bMWplSD4Kr+H`r1KdoMz;URzEEuCcqZ&AC8!(Oz(kY-y$8$V~s7 zTt;%FVB;gVD{Gmkxv=|sa3eXnUY5e**my>1PPI}?2aC~$#C1@In+gu-WhxYX#IDvDrNP4IUUIy2+`6$1d>(QhYCo>DhCO_FjXDri{h-B)+~E>_1~Aj{q+6O zq!`bO`}``OE(VvycsYN`=PdizbXbkb>6m42%jwZ{QLYEh%K4%`xxrJ|Tp95?Ef&Lh zIjgIA1DyrCgamo}6f(qGE|N&%U-kR61j7QQDK^hHvNocQR%1Hr~ zp+jRg8hVxA7JuQ;i#nf_!=veVQea+oRTsDCK*$aCpG2)au;I|ZWz#EUMH{HYi9EG@ z$lP9Gj{!2dxNm>a9hS(}ty~#;tHE`7Jt?d4JfGd%|4@#k=p$-G8bBOq3DM9SYC&)T z#Sfc~GS$J=CG-#qW<#H=T;M1rfCjK2ik)&j>I#ADUWEm5%q{vzLuefK5}rGB4VJnY zd1z(n<2eZlfS#DufakQoAPO~u)(YVBLpzvW8C*f6fVO|wXqRe=0w_i=PDzFDEzwuR znh_-q{WHb5q%#MjctDS*mE{hN`JRR4>X)-$FHgUJck$-xWnSM5j;qONa4|wMEbIHh zd6ybTIdT~$EE>4flz|VMrDt=_g9;)xD~NY$tAc!yOt8qs>DB!L3Gib2u}XIRm5fG< zKkF8MPF8;!my3E%`FK=a7i8$=Y&I!wDZh(k?bEkNUShi((z!trZY4j~q=z~+HmhE9 zxImBp6^!TyZ~_nLON|D|LMBrJP*qX|h4)?D*W2f>etP}e%dZY2I;XB+gmpV%gbfG5 z2&AbN7CeLzba04b?^DV5=G!Rw)_-2|cN)KE$zOlF_~i24%geK`?_%?ri_x3x^sy5M zLd9?K*8pr9<-d{0il0Z;PM?1jFp2#2`{hOR=h;nN&lW#q*|@B4me+h(-Dcx_Tuq9* zMOGL2@CE@j80B@I&GWnL77+uicbm_PPg${?=gZMR33O^uyCIwwe7N}Y`Ht);kRRnE zcn^O~7M)phi7uCk+7 zR~LU^m*lhJ56W~0M6C*NByD@mbx=&FHz|L>y+(brGQ-_ba!P>!B^_c!6)-5p;xRV-N$&BVN3WCz#`jf16kFx_D_^)q`PRR6s) zTC?iwC7NU*{egY`hG%;no3%pF*}0|CsA76QW3gAhp4Mq2+}cIbrwfUn*PXHCmn!wRd~NvpN7#SFCvD?G zr+k+Vd}pAJQF_jI!P1FKpP#gf*p6@=vC=VgMBFfK+cbHEYj*VKICX>cp-XeNQ`Gd? zNF(sNrAiO4Ix33vwxdG#B&~SZRz<|efZqEk`l<*ms9CjDsde&g?%HUb9zSb(q-R2> z6o|UV5GnIIpH>Tyf_~ss5rjz=8$T~n?R%=TqF2U{*em+J$EW{3eSUy6fqMz&L%a9% zO-*~pb`#o5|KQTmrL_de;L(l@ny`CnhM+n@5;}GM@ZJ9b5NCw%mqBVA6PI&h93ufV zmob6~7ngug90ZrLVjLTPU5{fm5`EuaQIGI|udB*-*$5#4D=ldE0S)jp;-RNI^aO@Z zlum2Jzu!~Ny-h? zgv6qY7bU6LXOl!4V}CD`a&~l5NO99gzJ$YXD?yykA&u0kBhX0N)TJm>;^^~CGz!=u`mm>j`uMNvDtv}5|7P}NI#$wkC z6k)OTQ6^*SPYapEe$Oyc#|#0cUC%JBY1dkbWXTOGZ~#l)f-sMzjsS|VT>5*Mqja0& z(uz6ef;p_CFPNjo{tL`eyHgd+(V}C)Qn4UkFZ|D1a|9-TRAcumQ;fRqEy4RbD$5vk zKfpv)Iw~`aQvAmkU(oaw`R70Blk4?<6|Uc2ZTG9))LQ%O&HBx|_2zbWwSD`?=j)p+ zpVIULP5;{bxS=n4*9Zy!`9(UpLfuRCvDMTz0 zE*lg+snJ4z0Vcfv!^4~XAKMj8|5@MtM$?ad{MFsvW{=s9paQ~Auf98ceDZd`-`;;d zO*gC6b{B51Za42%@9%$GhwIJn^UdweFQ2}E7rMmXU-7c$;L(GC3hMq}aSh)Szu)pH zc%j;Ff7xvIc(4jXN_+$%C71_Mt)ao&5oy61|4)>Ec)IGOm4I}`t%l@jCTmD=Lgc~F z>VW2SKy!~EqJ)Y}p}7P^1wcvH=-Hssh&ietl9#SJ7@sn&8pLjV8~z~1Bf9z)vNxl zD2xPv7lG`BAC6zVIEbqbG^hk8G8aZVVruY~P*Jx*-+~hgu#FIV`Hw-fog1ok#QP%L z1hpRQ2X=1V8x8bIYl5BYxsXP*q>)h^6@l7+LUh)dQ0(D?Y63g!r43p}pmKzkfDA~% zhLmeCuqszFsli4KHF*#iNZ zAv7(WvpIXJ=R1{+00LvP`X@<3@7*)*c_isbQ%C?hRA(6+$$PJatXEJQJSL;t5MJip z_l2_^4>k^lhE@gk#5XrUbSo+6Tlw!6)*n6an5a~cOEFGf=K#KvC5 z7>L1Iay#Gm>QIrGL2yAU{5m_=dVl51&o$9SmC0_{PAPzsaiLR7B^y%| zh=gw=c-v-v24e?%YJ*(XGaD0cZAbQxfXNS;6k_~TLD7Dtg3{?b_xb;Sv9FLz@bip_ zR-MowW%zc}P^6uyAT&v1G1vUms2sR7Oy%b;Y$sFcBlV0>KSdwHo&@x8w4!~}@8n~Z zOQGo}jtGBmj6z12?MEr)&l&O5AYhARU ziv@LY1G4^Z`fpDug0;|D>smsUDw1Dyj`moQLGAG^~30=+J*GM7PW95$EW z(GD1wfKVI+my>E7A%D+T@G*HXn`E(g39A}p%j`Q_7 z#c5iyb%Cd8BZ1*j^^H7T*HdI$7n3r|x|o$^4pdI3*ECMPd=WO1KOG zM<$k20Y8pJipo+f4<;G2T*ZLV$`curr64nAtDJG=oKwyQnSV2ra%7`OUOAu2IaV$l zp9l&VWTG4aQYOc*B1=xBtVrI*k}-Cb?>jV(WrPRL@H5v0zY_E=7k3&Z$%q0Me@h{qDq`Z zSCmu=Vh^IMQY`xOm?K7+10dlzVh=z|*_U&qvJu~a&3_Ls2Qsm!D)xE%htq0$!?t9gpVFa9ok7$nY zZBE*W*M9}CZGbmNt7EWo|Iate!`p4Ix*vwkrRshu^7GARJYcr>k*zKk+e5!=M3l4< zM2@w%EcB=0P>zxg@PT=Ns09#{hHc*A$#lfm1Sm8Bf@wUw4SuGPrj)f-8vuj1=}0Hy z`R=!IJm5mFgKdChozargvePC=dUINGhruDz;D2mLEq=saOY9=fwUd&dB`q!>Jxd^ODROy2j($uQDarXR2efC}m zY!|D`#d-g)?dAFDRs~(u489LKs1tZKApsJz_MmwGG^|L%V9PKuEFJ>lLtvBk`G51I zmN)&fdp$_;n^WDQHt1hm3>rii9TLI@^cUTiM$a%mTw18rEeNBT1r)(Yb2-l`&#!QB zdEFAnB#j=hSm|Z8^loVTkeq2I|FkU;96e}VlrC6%sk359D}ii4MEMif+uW3DB2o*# zL+VT@Wp@VBhht*5*nAKY%VE>K8GknG5kYZw7{{wQvB6eLqneXuL~@KJS34_g+RYD) z*kbYt1DKVpMj$+5EQoSy&w}gzb$>N(;g*Z-_Np(m`j6GP?z>&TA8&T6zCnqAijEs? zZRSw;mTh6rsfoc%AQJ1cloZ6iLIQF8nVOQ_R8H3Y^{8>fjPmC|U%XY6V1I0>CsO`0 zI2h%BC}JssQF>xnpAqozP)bO@X>PJ?NkNXXP6%S@&N)cAL$l+Oa^7hBc~a1Rx9UJ; z54&O6J>Q`xecjIpAClz-2Hy_Sg%VT=?(ol;w-+=)6cO*-rPBV(2^iM9d zXQF@e0m*z1XbxGukQ#79fO|vu0VqaUhl+ z)hH62bUx#Wro}%ih(Jh}QpE8$A3;gDw`z0?U5%@m4b?G)I}jg6Llu)2}Ih6JHO1HaVDNlVnwjP+u$wF6200T`enY6$7Y&Z1|M5 zW?9L?A*J?UyjpAyH`iCC;?8j}p#W7~)`Py-PoS@+#e@oCQkZ3_PU(|r?Dw1PTcH3m zBN8+ObV=6DGRp>{)qh@AhNJ*A#A8b%d5gi6GA_x%%6=Bg{ONi1?p73f+$LZk>Pfax zCuI?Non%XJj|~dt`;%XYd~f7Ri8y z2G_7_S)U-?28@y3t@5A^DG4w%tIWzvLi28>`EuJrqX)H-&41V|c7tbSM5An!p-##! z`Rw>>Sz&^;v}{k4bfQ%9RT4cJ*?0Xr8Wd?tVKC3EIhO@uS?u&E+t%lnEgf!32VhmQ z^FTpcsfVBoS-y<$V#+w%om#SiV=!V9WV4A-{+z7NWcdz4=f~3APIE&V6v1FK8`k@>W)RC& z`EsM&rMjOMyB_yog5#wL$WI`>`w9d-&@>ZQAygq&AyuIQ%@t_2_aKE^NHo2Mu!4e( zrXl6yjt@bG@F>Xa>U30v3OiTWIXtBtq6q+hIIn!8@_*>ORRg(dAWs^QFNh|gzN2wf zpj(>>Kbp>R6+#uNGEBPrK%K$X8El=w))_2Sp^k3r=(dh->*zLBp^oh8$j&~gv*Z2p zNzTXXOg=xF27ka?Z$~d*@Jzl?0akT;b8klZ0O_F_Z^!0a;C?dpG=qE>G|d$6y@~ga zzlncJJ3@Za4&T?#H1FeB?}P|fQ?i-Ht5%w>d@NXg3M@~W;0F|t9v?H@@k>{g=+aX& zg`+ws&`C4Zm!8c0@{7L!EHMH1mqBVA6PJN=93ufWm+^rU7ngug93FpKU5`{Z41Mpf z$RkuDH+GyjK?sRbsi5`&0e!0aupiUiDX_De9aQn}dz^ctowDr0%%z$Y(yZ@SeB#*0 zb^^teTyPXqb|lpVbzGwf#YrqCRF{K2%E4)|movGV$OLv2s+xpPSdvMCpW0r-Ws2<{ zM$g3_WV~Er`xawYZSQ|o$3&(Im(1DjDLEEmlh|=eHi|~axwiMjacSB#0d8&YWfy6@ zr!J0j(Bh&4#wk%k@*B&Q~+lM+lD z29=sjN2xAR2;=k|R2**EC^flE!7P7Sv&*baQkTaiz@&3x zLshXDNpMe~C?~80Byu@NHi=zUZucT2i6)85g~TN2D6A$yM@elI=%`#xDo(@rZFNdy z-x5}wgWV&7Bu!$c(N;$Aibg{(7+z)kB0-AnUWSxR8>!R8rVWd%DFu_DBURJO(2Iub@k&z~^=5st6^!q~PG6!l29xQSVwNwx8{GXuCvnr7ynug5_lyvpWj#iSF?>=1EhC2{557U3@Jymq06Y>Yc}vz&5wJ*yg7rckl;RU?wjZE5j+C)TaBa!eXOsXG1Wb!W41!^--rlQL zXK}5-$e?}1AEOpv%>Wmz#_*By-k?gD0ZQTBFbscHZp;f7%Sh@Ra0$;kfG42>67p8F zlrbwN_AI==b!g6#fqzhhy43szmtaoRf~n#%?aG{27<0M0@JJkUA`N9C8TX*@u^_W@ zLVPW|`p?zJ;|>V!=i{6u3%sAjKLD#Cd}HfsgXmG*U_Fw01}k+xM_6)Deh2p95c z_jG^vJ>Ypj!b%iptc&mreZGao={(e2ji8x`!u~aZgL4j__P}{p|*_ZcqYg8F? zAc29bph9XRbROuAd?>9H4WS;+x6!Y`i4pRI94qi5WH>?SqhkV7ro-3@ttdcQYv@}q z1v)Bde-aA3tZ{#rnq#O4m$C`~ZJE#2YIc7Z4js851eN!0ZsxH!`YW^z$gc^=7}ZF% zT?H&9rF@8D5)O{ePdcI)kZ$XqfVP|*Io#)2%?uda%5HP00&XI0l?iyttLXj?HOt9C zlm*m{Kr1NytquoNeN%8I(Hd=R+cqb*ZQHiZKelb#wryu(+nHpdiEhq0w{F#a*t>Q= zbX9jh^s4V$>sw195UZ&^1z{3uGlRN_3;kCrldzKY00?2(t2nSDJQWED>VzMopbj8R z8OvJ!RY|ztDohxw4Cpe1Lu|`TuouPo-<;oBO-BoSI2OGauE{`91Sk@ug;1&g#5Jg{ z^}F|Z`2y}%+3EW0kKIzjXHfuktDKfFIb4~bn|&`VG)_&$d+9J?;vWk&ghfhxuiUNM z#HXUsL?($24S#cD!$P3ESjp|NW+uQ$8;eQ`;+aK^C|XTG#V&g-_E-K!RL;5BgI^O- z7Zc%92dQZ(A|2H}3bCkYrjp$JMyu_J&Pdyr&Sp%GFAc+{z4;FHkD2z%8sm6Ar?Uc)1|}tWA)R<{rsV42QRmmhih904ui&BI_30es=%JF=QrRU;VgiYBy0`F!aT$EEVZN(KBxbW)xNe%WN)U7tujYOzId(4#^L$|Cu zEQ{&c;_76?FViO@PQBb~dm-TiLHCIyK_YjIFq_6SkW`SmQT%3o>u>6e#H#tL%$(Yn>HE9o6;=u)}johTo+^wnAL)}JlA;Ijs^G+y8q zm1U_2k4ic};|m=%eMFTy`c?U7@o8Do#G4m(;>Xy=i)s@VyZ9aaaAN@GKm4@pj{dd* z9R_WR=yWGu9;sZkg;}TR8yTXV^&O4(3(Wrc|fCg9XLAt8^;%3}#yQ+J(b^8Sx<;}St$|XL= z1;L`+CT2T6#GPRx3WdB~F8H-10EPQuiLWp`5dTa;SVE8c(is!iRb<2J1s-?z7PmF{ zy3Y2S(h!AvqRVb~Gw`=BsNAkFOJVxtsk@uBuV zy(L(BM(|JDe>zT=4Qb~QU4ICqT~7g*xCDtT$S@F!XM`l47(1}6c+zxm&t+;Sk2Q;| zs2(!5NVfZ~_lCQUCZGG{md3QQgyy)?J61?$h7W>IN(HWi%p^)k?v?;l8h_qspb{e; z>i}`FBXa)!Agi=$glP!=v0?aCv)V)(>tZ+{MU;&IfLs|_5$aYbYT}J7U&5c4EGiGI z%&LU@7)j2+Ruf5Chrvmnra0!p*BEowLe_@k(MsWtyGG?CpnF6%Ius_2Qgu{EQDe5< z8ZsZ>oj1a&Xcg=c1|ORLuOU#X6~R|Md1)X>04HuZBDrdOQ#R?}J)x{MZXdIZy5-E_ zWL4}L00&RNH?*Aslm#v`^_8y3tnPrV+_YCShSO`&Nh4|bAdA8xR%<(nHk3_t(XM7q z=Rtj}HE!|Vg?1A0kxldi=|UXKs=zu&`(R)Rj5NBHIHtDcUZ#2F(g;H#)>hXB>!~4d zft|qJXK=#gR9__-<H4F7fr5C*T{zTS{ngU_xzG>^}|JtQ6;n^+bV z--_`YEzp|2#wsv2j>u%B5_4(3?~D6}p!D@!@88Gh$*h?FpMM+K+0j=&ac9$K>GR)R z+x=bs&!=d!*Dg40i(X%RHu=V~x%YUbx(SzV z0qN10939g3T8+BQljyf)6xi&JJIy9M`)}oUd3zt9rzAK2T|NI;Zv63&Bs4VMaW#1m zt#t&aVqK1dyrh$GieEs%tvxw8hJaFIZBELh{^@QcTA&cn}wLX1qH4 zr&2VEtg?7C<10=vYSeAqkFgug#r5rj0V~dW0jjuWqOmlG;D%|m7oMrj#m~<>kCD)I zb6qGrHe9bu`&0{fYk7^}LSkA#4kpaCK*sc)0p{TT%qx_)IZ9n*c)u-YmE5Q&$$zqn zR-1#0p{OxpBy?SBdsfxjK%}JAQ+#M90t;wNH9;3qgEWzs?X==%dzv0;oXkh$0JF}) zQ~{2Yc%f~nbQNZ}pDifd6t-L|G=Tn1G|9JNvDCaGUKOWREKX%%r|xj;@WAV^1~{WN@!c4nJhuIhX)Lh60@BO z`Azjr-zq|DPZTdh(3Uq*MG-vR09R=#J<53-((KR&@&Djp_^5aWZ%ZJDf_?9Zpe?OT zH7X1c4x7UFAw={+1Er^nw*+&Dz6bSFL`L$%&nF4rKjH0l3)1R1p=z}`01y&_9O;?p zbs=h}X?$)8TttNe;3@C7c$X+V#K~bZxSX^>Fvfc@fBAh+6=@bjiZcSHZOE|0J@>ZR zSHuz#o=BcVd(cc%ZP6INX*`-#Zx^Jsz~z{*h~v=jrO&_7jj`z(@iBW^M^4b6ViniG zR0W+VfC|6^$U@|7wt^*J0E+iz?M3@`e^>l~K|E;Bt0>4+@jR*63m8UbG2czZMPwx% z!?+Rg$18$MgJE#MkgnXN4Y=0@QH+vDVWrN|Y`ch)g3B;|J)z4QQl)SPF|WbcPTZZ_ zbGin#yq`Xos$l)Su5*G*)(JIsh_H?CquqMz-G7%A!JYFO4Gz)M1UNhj;6PU5atwS* zVmBlgd>TipAP6H8Uv|28p8aUOYzQGWqk2Suqk=sa(u?m7gA8qVq5VqD$UP@Z;#I=! zoq&{?xrYRQzq=!^|5)gW6D~espu*xr+T#k%{?$$_U5tm(_N1v0TC{XK#Z7%S+;Tk|s4f7+D6!7qY8~j8-EQbwM9hfA zEuA@AeDS%^CnA4Uiv6`Z0LcyBz?s=k4$&7;IP z?gi^0BJ_zuq}RRd^7r?IcZ;dQxhU+UnS1RII+ZiT;@EnAHsS7&x;Pd-y=QHo1AZ4F z3P)(QdmzI20AImh80Bz(KG{ZqkA4Wa?|-4UN1xr**`ii2M<>(m8M4;lkp_nrKY2LG zA0OBMK;~Bp3OZbKPR}gr8Ft55`|2BM@CG4l?@WWa=diun9L<&sxa_U9GE!Uap`T5BhQiw>-+9(4v3;7`P41hsFVldZ z^c1y3A%S1$AK1lz4!6sE$>CqXN-QQG|ATm~;Ga60>;DZ^{1@c$01jmB$h~J8_ZfII zMt+H6!@mr9eq16Tho9{ZhW)A93`Lq3tP#InyhiP(P^Y^ivLGN}YdHC=AD)h?$E&Op z(dEb!(Pc{LA=sSKv06%&O!g;zeOFabM+2lEoIeYo>h7rLIqXxlP-c0Tsq0 z9V9hZ-K$A<_7<`kv}P*u_*=_`T+Et~1AE{v~^)C~PsuiXORlDxr zDzyYJ+ET0IV?d@i1e*6yv11GwC1V6UFdcGc+eVce?hbObQuh}0t@gLm>GI#40KkvZDNo)Y?{05OkIc==i#u6J-)y4Y*?5GY@M zG5HwX*?9xD`D83v6X^AQcXY{*!~_CH3?H$cC4ec->Xy(=uUU9x673pFXu&grR5B0$ z-Qjc##RWx5EBeJNYVdvL>py_W(YXe$C`zwEr77wXjdYwuOs8ZRBE*ll-2GBtmWB3h z3XBOb#=yv+jTsigor!Kt)IH}UqsdGs+m&(0;=SfZBvhq>jT={P-iP9Zo5AQbzSjE5 zM%o57h(%&uXL5gVJYNJMs_#6|MMa`8^4oS9w5k+qS_3a^M=zueiQ9LX9HypD4la(1 zFB>O*gDKfh6uLej3sUy}fX#Tld*eQ<0LoQ+;rOVAC{{Xdq;PkS!>jlRvvmUO^6c zzcz%h^7TY*a245xe?0C3iA+DNKfzFEh~Ozmz_3i17VjFLPkU2MW(*~0X(9A-q+0qM zIRcMLV@?yE@I1&=M0k*;USNaaBD>b|94)-J%}mFu8ZJ~EKdm^@1P@1uf-ZW%~3xn z6N`+d!}Xq^(EnNw8Wt#ajUSFrRDW8kGl4yjBd`-yExsOrqRTC2L}T~HFL%Z}Me|$P z_TE!=o>#kCMWGsmD}rtXsiFmljl4w})TMaBQD9jy4*5$$QS4G}HbJ7f21ce$fkvK# zFiB48kd}1k6t5wW3M>)4yUZCHV#}Rc5{lD;V)?WT_13j$YrtS!Cu*+rz`yDK^(mle zDCMJ3>=%Dbk3JQSj~L2_I@@IuO}8#0XCwZ{r461{S>!onCF@ha|CS4wl~JWt6=OhR z48{r!0|mc~8fhmI(xjTQsw@q%Ef7t_j#DhORif%4sUJS;Yx0q~@j)Ut+T@|R-G`zP z2)lfu2f9%fc-j^4a(ll_-+GLHVch%rdsW`j_t5#`S+>_q{I_Is#VP8R;mr*WlnaEp=S+Y#oM()1umsg(yz)YD65n!&=#WO zifY>tsEEp!2hsyS6)Z%B0p$wJw; z;n$ZU>8@Bm;LP|^NHECV+v6+AlK<}Vdt}hJSkXM&y1DU(Lo2^?FPy?M+;q_2-P>m< zfo5m8K?OWMjAwf={fWL&5O3R(&JE^L`onep9x%oJ1Wwi$K*ode&KL079D)c;w0Y*+ z_z67KmoyWo?{5bn)B{))EjItIPluhcD1WM{SxWp+M7+_9^Fvv1L^Al_{0-Ox@V6Urao%xgYO2ac#fey=@K97zL>^gQswj@zAybo$!)wEA zIGx%mJLx(Fs^)@;WKnTOF6JR~9c<=_QD$Ak8dGK_Ngb91@JQ}gCKV1LDn}a?!d130 zMlCCDVxlWAV+N~C4U#$IR7xQyVf9VOXUe(&&?FZZj*95KM2bMtq&6zYp5fSIen~bM zT~agI9vj{bqG!qYK;V*Rn1{tC!LtmDTj>tQDlX+^4p$pN$QjPrIyz}u`KS|{HB$@% z7jFPL60yvp;J0LB7=?4pFc?!v+4Wb+Y+@xHD^L9iheX`|JF)RZ>2Y@RaP8fDU$4Lb zs7tGMA$-*1;PY6Xug0W(xi8H2*R9>7`+ZAJ^7~7_^Mc9Vvd`&8fg%tWFk}^8=zcAd z%N##B7t(xkd-W>1zb23pHc(1*yd`waq>X!oi|`N&$d2^GpM=YZBjJa}C&=eXKo%m? zZ6z1$_y?bH4u~-_IG?mR;Hx$YPfr}VaY?Yddp67Pc>M|5T1wGhlQ+HBait&Fd0l&TPT)qCSIlHy-cY3}Yd_Bx6-m}1165|@fK#kmE zD6!ZsNFk@@$JO6MArdhB*?<6NHJwyHRNAcNDKZ8t174d_Y@FDKrh?%n8WS6WGI`8b z-6mBTf5pKzL(yh&+{iFPCBZRnqX$I+a~T2BA;nMRGAU|oi?9?H{$*`50{eGFmys< zwYvV$mN6BpZNDL0mjM;|op1*A7N(5jH&z#iWH`z>teW^3a3s!*i0hVbhYPESXD7no zhcx!?*<@>21SmwU1r2A=FY~WH<~^gsK1TT zCx&lhTW3>eAlfK2*um*M%Ri{0R7tea(9^J%X`zK z@6#8z1TDaxRvap}n$=N_>b{MjG(2BJiqqkCTVIG36Uh--L2dfTN%uY@`g6}G%?5Su+GWqb0!VS7ZfI0W2i`*U;X860ZPQx0aeQgN)D@;7TQyEu8!_Vy-Y98E*Lxcb0O-x z;bH7|w10>#t8BAZHkK@Ye=e%>Oy0Q8^)$^4Az-8MJA4(}19r5<&RRs&yPUQeCYAaN zJfd^gHzK>QN47o6U1sL5LJ^`Ij z&&a?!NxY>I`e0GLfTiGyFRd{@I6o4S`lu86fj4yr5yZDQ_nh!gva}(npFI$}BCT^l z2HlGB>1?R|kk#%dJ~D~VEsMShb6y99GedaXXy!)lc%xeDPtewzdE3dAquAKnYk3^2*pDYDh&?GYhNgarN(65vx z!@SrOe@ZvBY9h`)NPwXcL};aKkaaU1dI~UjS^?b&Sy#$8GZrj30d@M>0I7&!!9Xy$ z-_rgdNo&bq@Vi!qCM7mYRtJ_gGlVKi-x$i)&@iWBX!xH3Q3mKL!;BEc#Pw{zgFVQo z867I5EI15rQ2HC4rzq*8)_nxS$Ibg)ayf&HI960T$%(U6$sRnV7_KGC0jstyzrTYeg4OP!z)|_gL*6V2Oi(`Hyt1aA=)v z_|Hea-vpcGx2|q|y3DlmXYCP@d!Bf07)1Pg?i>Q9e_q?~KCt z;($w$Os)<0-WIuO7T>J_s6+%57`7-w03BJnuFE?c8)DHfSx0I;xKh9$+{ zUsjugM)LCqd7EOxGdz?#lVThKI_uHLiEq*&X?g~L?4OoP^dW%G}{?eoH%rxFN06; z#%#;6^TV4n4>v-99Uk2@@zw|XHO+QwwFKLj@}eQM16d!OR$1-6IXmR2vLgh#k>Fg@ z(l7dQY<&*ZjxQWVgg4(xb3R@AD#SA+*qME=PLP!9#FR!TJfSK3(5%I*ni6Jag7oWr zXltmWsg)D~aZ=WyEA8?Yv_FGYKn4fMBcvcJ&&CgI1u-fB0-hD>N=f*VR1etMar`sED=Hl`Co+L>kJQU5%9H zN@~%ou9}b_e?e6N$BDUGx(u<)E2k9@#BM>X(MUoAz$sBkJiGcx>q_`;d!3)P(3xJp zon6zD^Wt@I@(1P#0qZ#=@lWhm+Zpwq*>P7f-Ts zXX$e9XBSc~Tvut;r%$9ZOPVQfL6@itB2O3;2?uzkdE!k0tXGU(MFH325#y95pflK^ zltop5Nj5IySOtS(LG`-Qz4!pDlLpWu?(lT?D>XYfL6J7ZXz_o<;o!zl6+OO&lI$0dF=^PN6TLNF9t zH{lO2q~dW~T?2!e;Uc*keylqprPqpLRQHqvL}d5bm@N(#PE?&~O>M&MtBm3BxTnac zCHWgT5*LOvl`f4NH&rL6)FxrDSxZj1kcM?MxsHP$E2z_~aR!r?S!^dr1!l>|(`U5g z?Maz0bcrb=x*4Pr@bu@zKxHN68;HrRV9%luTG!OXOJrgRIm^sLrmy`)!ixd>w$SLJG!iHG&=;jPxio|aSRm7WwWy%Z z#%Am3+LRkGvF4r;Gy-?XPW!t`cbsp1BHMi&es}U`4pIS2&yz*xeM$illiK{B>qQC; z!~!L?YREl*f5O#u+Lk0tJxM8|jb2g#hdwO*d9@SDk99n$VP2A-(B6`tKa!ERUs{s+ z8xy~`&RYN(Iju68r)ys(_?>EftJL+WixuIEOK<#_0z(%Ldk+Y>J@31K3G>&Rc=oAw zl9z#3$U#vKXIv%t@sE?Eyg*6PM2R3slGuvm4b5q)_^+WIov|<|7p(nqp9(I3K!i7E zrMDof7ZN;T(Lt-_&|1`Kw5Hd<)JwzEI47d<&WbaRS(bQanXd!2Q!sh_f)5FT3|0P> zYK<8G;N_Xi%i2T4wnVQ*Z({|owrv~fpNzR;c~A#`ggagw%Uv`}0&s4e1&V2%yp!fq zeaB%7Mj{CG5~C|W3h9>+s-KAg`YfT8G5CHP^c{nIuXXz4p3WMj1z!7K?D3H+a3r57 z)2~D_KcS%Z!5s0~R{|6RoVEWeqph<4I}t~G1%;VjlKr1D+5z{!W%N(Sd`QnZ%s>c< zNG_1V5-~72F9wfHCozOue^|SHqW=z;ff_coMw3Ap|Z@B8skp1YDg*N;V{)oS&!^rumGz!f7HpwDkTFlNu@hH(7<^ z$CFE63t-ZOmeRW1S3#%np42oKjd7a_-wR||Y&-M54pKLXLe0F)j~D3uqo_Ad&-W7R z^B@5i8$59+E@HiriIV#rg!&i)RL{gE6o5#hr$iQp)&wTtgr+(-Z1N_`APA!+ zqk7Fk1Btsq4y>bDAQTi!#Q;sft~>^LlvCrm1Q-@KUi>*ad-iD5wZFvzMLzUZW9UhlTrn>^-NQNSihII1zU&e z^~E(3NlP#!J%tiqkDwL^j!hxOG9nf8{_|XWxl8-@q1L<2JHruO?Zmfjy==4eSK7@0 zp!%|P@1}USTX~y)@a64P&ybk=@FM3%*zn8kkCI!yss}Lq!-}UI@@~Amj5c^RIVP7_ zZUW=_*NGATSC3A`ZT!=XLDhTK$xD0tFqFwRu)30#9qunJn9bp%87ZF*;I}Gh1`CBv zA_|LOYv&X*d{jZL@?q5zoYkR}mM2ORfOibhQ9U^3Q*Yb^^;KcHL?Cw#D!IAH0x~rK zry+hX+-L+7)^44(K)NPz^7lR=^)X7}7#(khV$m6?wN%xB_G?%KD~$9Y&m_!f@a*?biN%I^eV3Zy^ zbQ9B`!x2q+s`yedTJu!}S+5rO)S9gu7xP6=`r^r#uU`vs`h8>P@+|wQ^-kvydM@gm z%e1A18d9ANM0IN=!K{vLI)uw?UGP~2MC-31{eTJBW@uPM7sjdZB@1`63$*;u66w<- zF<;ttl6fEbtg!rB$iHMGpySI0z)q;CSrr$dilsA}O*Hk7bH4yt=0eL%ylJC3z+W4? zSWe|JQp&_sC^(LLUY=_{HYQbDypRQ#&3Bh|@h=fLBWkg``l+QSVrvAj+{i7}?7Luu2%Vvx(8BnlM6LUemLaep02Mnt+xb!l zYJwC_kJNpp?A}sOt{l7>md+-LjCwFH)As(qfYuQCCVU%fqs0|*%>pnPEQjM$(D6yL z72`T+%J|Y!YHQSN?g9}=(fYt_tadrjqy*fY(FAXb91P+1jPP7n>|k{`Z6JZdE5j^c zuPHE3|Fr4VYBLhHb06nfK%)6@uk3Wj@ub}3-BIWD#pbO(R;B60RuIf9(3+w@b1cg9uqfkb-_eR%e$ zK(@W^Or84G*2&e?2Iti&$8gU()7HccXAG^cf4|nxUE&6IU;b`@W5JFMS{Fki7jA5; zi~W=j7lf>2M`&|92V4mFHC76Bw2pSI&c-Ko3D|ThTwI+wJ9R{WqG8Jn9uxdutc}%H5O$ zjXPoLVEQt;bNu@OJmx%dZId~sJhvCF@!XX;;ks}AZrZ+e%LvA$L8*v_@Cqh!KAIjR zGpo_NXeX8Yj&g>bczMHlINvQMm5je_c+1M&J%q*&FQ%CAa!u1--1uo```P3hf@*^p zg|}hFpDvc|Hz!k-CHlY={cY(Wo`bLR5uBx34~YRYB5VtQuYmBwZ=gLXJcDTZ6kEhp z+8`f>hvC;KO5aTtl^(zXutc?Q^dg_e*`Q%42z`oh%ob^RauB*luo~zb+f%3YNtW$T z=%)#nF0Ui!HyKo2%_LjGbv&|I4Vn6E=@4GxA$9m!abVPFvz5SmbTi^*%}FPDy(S`h zyIa?&0mnFe7nj<+Mm6IXxU!r|RQg>Z9{Ufe`k#=$|2iwDUuxpP09cs*KU3vZZ5x-Z zG4#*>xYXpDcicg?B~Qj2OXO0t>TSp`c{3A4fKh9b4FC&HUWR`?=XC>F_S(vnY)Xl< z93Hy8T=$;!VJH&2$TFid&$l?ULd|%}1jlq{ED|*tUMQ!~(a3?0rZE5294Tyc^$KV8@~@OZif;u`J=>V2441 z#L_83h>?!Vrm!adosmwT1CMF?D>_!glqjC4RWFP<5w>qtl93#DI?$8@ohBZ}m7a)Z zmI)izAjrfp#riNaEto_+Ws{AO!Q{YJsF4Wpl9--%JP$6f)@CAP<11u?m0q&tgySY& z!02iXQQ*NKO89{a{}V+7R*59Hu>htWOfB;z+h2mGXj1G^W`%@SX<|(#=5W!>*aMmv zZjz+qMQ$aaM_PZQkTM2HsNqQI6s4t*Bu$jdEa=LTrV<=sYb9%!wFZ(Y7!n> zT_pK=DXYfJ)7`qPZ=ISab{ed&R#5*(neRK++`J8l%F$7m+EFHBS(0! zX3tFR*i3Uff09%FNC-=Nw+AubiPhWSKsss9O(jTr$WUGH7ZWd&&DqtE(ka-n2$JsSVgea6P4B4b%{->An`W*yo!Q_}sRaxf*WfQVZ43ix$6^Muu%m%!o zQ!qwi_6|Ah6*?JcdRU0cV^5$`lFNr#qgq{ro)4n_6^9jub7H!C> zk_cyp8*Q4U)7acbUGCAf#liYzP##e+%-_*-SSiXL0ydinCdg`3Vcsc0?M`VL?xn+9 zT^$!${{8RF0O0#}GuWibIx6k~Ww}h(!)^J+FbN-6h<`hj`5l!(xa3}?zg8NGPBWpdzkhsFhV_q*-NQ-xUn0Kf%!2Wf# zbXcOfSc&#k^A-CPaD8jaAyADr3p^XSs?+4N*!cC2E0+J_D(RmC)?0diuiwMJ`-529 zdTg!AdQC3h(JAitrd*HDW}x5kIRtZHd^wXv*k^(t1mA#iA74N`DT7yP26_^h-8=1O zm}_ncj}#PqP%!Xaf-itF=W&heMU4G=veRxtWKO%7_mgF>d=`$%aDfIZ5+a;k>AsqT z7ym|-)x(x0UbufSImHp}{S%M7&8~M?2H6N+d+4^?I`X%bfymJFKj@#DM{}{ zW`N$_FQ>tgENIzPVKh{7RFwyKC6-3xB4guWFbaMXV}zk!z=@2RoaTojMc+v|!ZVVH ze20LW84k(!$NG8%gT5e|6}BZBKg=Z>x7ZfThFfv%eC&kZC~Re zzy3=0p%KZ^+^fQr$tx|i#I!k3+iD*vYnBdJ{ec7bf!9jA#HFdSs%Ae=S-;2Pf$g0G9WAx(mmWx1Iw4-{A|wp098G$Q@poKH7670UwEeRYZNI zW$fKOvy~ipcXoK>HkUo`NYIyE2a&?i?)W9X(r10n=&~D|qw#Q6B4N=%dSOt2Dfw5A z!kkgO=qz&kEb?5>Iatg1!^v0x?}!wYa*|^oXcDAm&G?S9xNn0zv>Z9Jm>hGzv6)0#8%%XUCdmN-Y^?&aL*L%(+@K-eNjAAu_0 zDRgcR2hXP!kStAeR1Bdoz2mNcw&W`=*FW9iL6u)3ZV_x)(5e3JKv5s<-AngMb0_b~ zvsVC%`khHoFPf*(?4BNmV`t@{J$nHF2ftC$yfSkC?jFXm#09@^!P6%Iv&0xb$FJR* z{}Q?Dzp!~;+cN*`=`Fd@bY%K|aZ!{R+1{VX!ngM%Ym1 z8cj^ZvsxjGZ+?F?Y}J;JyZYz4#z$zz1x{Ss8Pbhg+EMfqZE-+!4!QA|$tDKqv%a!k zq=-pr)Bf}K&vbhIt2g_eP_ANuC{XP2JJnlmm`J7S!~4vw&HIV@l*Oo)iUC|(y=1o; z8!i7svVH6JMl-K*3bd6%R#fUfXK$B(#BBc~g@n5Vw~m2sbOVna2!#E4Z3~?4zl<&z zG~Mm1>lethwoNL_!5eBV@c0SP_$6++tJIX!p+U9XVF0 zclJ;}*nq$8a@_Agovl_j`l>gkUP>CiyAg<6XE=*PkkoDYoaFHe>lLgk%bOf5q}W_ygRcV zt897xJ)4I+%F8T!>o`};6rIH&s=K#Xto8nk77eo@Bj`BYFJ~76%Im}O@o9Oh(rVrQ z-VjR248a{r%qXTw5MY7;8EYNe5yw%Ot+GAUMJsB8 z;rQdfr}sexUZ}w2>UZo~A;(|ItuoDy#GlaFeT@1G{2upL!57wF7k_ph2}^wd}4 zC1bk#$0%^2{O{fcfVJ+lKNd&`8GJqs#7`_~fKi5f0Xt-r01rx8U;OZUJL)po*2Bu_ zQy-9E{mOO(cG{);Z{<&O_3T*c$blEN1A`Th9oDW?h|${f6x}85`6oG(j@w@vc_@Yp7Wb!jSb?Lk|ApT%ii(X@=7 zonf&!IOv0=#pFQ_*P{@PIyFOwW@#4`vak!9+Qgt#42`IUuo`hEMiR`ivE?&zcLq)+ z8H024odu?gS*mNkb-r4tWK70Y%9b9Dnlc$GY5fH&=_VXrIkHP; zGJ&&Nl?a_p)v$O|2-a5B+M1UWMykw25lK%8wZs}_P{RddOT|=AN9>b>ny09SvI1Or z8Fl3{qWm)eb;}=~z2lO>F_7$X^GDio4ig{}dhOGo1eXMXJ9=-^padTbfjj#v01zai zEUObtmY@xlfEJ8VbX0+5NySM6L7!k!RDmM0#L`ZbkX1Vy$F;Eu^7D|kj;*Z?iEIS) zL*md~AVz1xT_i)|iwkW~xTP0SP`GU9sUuPmZS28xQGTE~DCqAHL}Vlr30cV{Ggijg0jMp}0YHD6%GWY~?oe(G#>495u<3@^GC@w!YZlX_O~0JmN+v=%kyO zhD19HD(ALbZ1%E8VpA_}!r?Jjenm!wGm~}8Q%2p{*$;G6Lsmc{61jOY07{u9Qm-({ z|7BIf{(bXeo^bnl9utt^@B3%^&+F~i^v!b|DK3?}+P< zKgv`GMu$Cn2lw!o?yL8ko$Bt-Cx4IrJ^h}|?<**cIF2>Kz+dQ$8!*xHX2KaIZ(vJ( zaEJs$g2#jMwKD`>AmLF8C(U68&K}!-)>uWaMS6n630V@F`Vo+b03)bZLa|?|r>#eY zjb3Eq7JrRAyjpa5q1sbVJQ~X9I zOpOXoU1AwWg2R7_0-l+!R`i`-i`sz=er@?hq23=1ha>jF5~?^h!NWH)cd4;Nn9x!c zK7H@IQofQ@kzBCm2e)TxSDSpoKMuxgM%6NIKQjV8vzLW1gTcFp->+<5AhhB3`mM$4 z-HJB8sG-PUXyNO(!b#@7O10p8^GrPuiS;*YI6m2B? zy1P2LcR@!O`##@qZjd9c{otIIzZr1F{=DzZepS|QimBGRMzv(#mIep0FSEHR-kW!| zBEW3OrfaJ8WRkSG%2p{nW~}g=@87X(=J@5AXqWC~_ok?E7nq1~AzIxM$6iI8&bsmu z8d7CnwDD720?fO55Tn{MZy#hr!E2onEwvi3&|8LUo@9lcXPInZlQam=xE3rkjS|;Z zQOp;0M_I$b%X(m{{8xABA;>7G#Fxa59BPY)UVVg3taf*KPb=E^eN1NbxyOC{YFU_L ztw&4ws>tb#F`U|`&zzFM?cMM>WO~_^X>nw>P*<4K0Bwy#q9zxUg{Zv2poKp&?t~7B z@CD4X+m{sE!AF+M9LEDa4Oof=SAy=}Ch1Gu?rDB@C2366u`|-*OYF?F)KX8SHi{*) zfA87GSs9p-W3o>g>83E56Q^}|Btm2~z(f9t>ao%u_`8jnwdakpE`lsKMOFH*>OVn{ zd9v_50N{T0rcTct(g zxW3x@^o>*nB{9Ei<(~R91xI;C>dHJ&1;OJ7z@UQs-*(|{I%G++!b1#y2sXL;u&|ZW z?$crvUFVUcV%9z(EUXsFNMln1xsWY>DJFuUvnUtfZ+)r}U2bRou=Du|!VYhJ9Spxu zR5kXZ;~%cQJ1ZuU+IF9&ZFvQx6=xnkA;sxHRt$_LJV_HHrW%#CIp^!}B^2LmlQdH= z0CI-MV-7~K?;|s;WSLlhR{VpaOMmAM@x1UF(VoU4TH~Yz?7=ZvIurrIJ4~24_Q}Zo}7=-CKje~Tc_E{ z&=Gf~lU4nmaYR9As;4(1!-Jb5CTr^F+?;SPsnCeF-&hk-3KVZ9MhBk3EzBsN@8V%L zuYk6TT_}T<4{NSgYq|ypH{t?N4o`5G;HEuFV5ZwkGC2R`T^1!at}25fvkVQ5lid!Fo8AtW z;O!V|_JtY2k3}^&^R=kL+L-Po8^PDgV9=sRdZ)ppa)Ff=6}!bMQ}$jG<|HvxlEMr# z6A}Z>H_~9IwLTOZkNoz*bU4cxYRfh`Dxhcyk*t!9hUi-87KlNZe#Z zj2{{yWG<~at&OXz4;~z$-T3h+B3HDaY$8@0iG-J~`D+SC{WOO^jx$&@6G7oeda`H-Z4Cgc=Skg9*uxxzr$~T7XC*c0-;4p*vf#m03fTgspVVD{PJb?U= z9Nd;fL(hO`(6Qj*01Tx3l74@=w&x#Cn~@vv^teYT00{GlID}$U%8{Ci1nm(mZ?vXV zHpQGh0ek4S%-^8jD(?^wpJhE;NJ0erc0a{zbN?W{llk0i*SD~m?`yZioh)|==c z+0I87koI`VAXN7U#kM1an#O%oq~sw&b%P`|zU=f7`pNQ;|NX{NTi|_qv7}$bw2b^5 zxm#rstCS_xF6Dv_zcs`{TY5vHo@I%2U@1UDnx_Xx2?M0`%JRhSnFra8Skak;hTcD) z@W+x#=@CebnzHKmw2|ACJ(rS~evvpSn(J5`K(mzw-UDfVy%3K&uBx~^HC*r^qQoxo z@Agut(WHwEW*E6e)#af_*=5qzWM-9_Az5lBPRrV2l_vfYQ!Hj8>GMh`u`bLa0_(!?91r7!yxZL4temV+U(hN=bOZ z1yGi*&H``jw6v7MQIqo0|DowCgW?F*u7Thl+@0VM+}+*X-60U%7I$}dcUV{?Sa5f@ z;O_2x-22||N1yGfn(dmNsyR>fV+Yp|>)A?+@dQ9R`Sev5JDWh^A&$sy6%l0SiZ7V{HxU34VNZzfOydrmzQM4O=u@W533eVWtd{*^M}J2BkRmy{sgSsJqLxGL&Vb&fKv%9vOGem+6N_2n&TvpzCJrvUceQL@db z91v}ab`8cjWYxWh14<^r28%kiExVKW8CMf>&Xm1wCh>hTe+D<3TFNA0{NyqHE8}IDO~|=mORh*Z^L#r;K(g$h z^Wu{5OJ$?}O8|1&jG%ScVg5EGAlu^m_2<$MYoyE&tCQdoaqf9I*(m37^i-E%=TQwJ z!$(z|(Irli-#92!U1jo(9WyUW0HWVH=RV7yr{z4AywnRx@mQG^bL3G4O*R`~b9}0sZM}v)WKIvc zXM9=0aW)U?O!I;+ONpI)Xrh*UeIX+_uv6@dqLVl0l@QrD^TTc%H2D?@_h_8q9r^)2 zrkWLpB^!1{xUx}TVH#z=hBd|)0q`U(_C&iCk^0?xTS#~id??O04mTy5vZIX%>%2k8 zB~Qqg*D&U0kpUu4O%?w9?@N>ac|&&=XH9$)%>bHh-# ze=y?yrp7`IE7%^?hc;Qj$-U%=O26ofSiaW=sAv>G^^ye>m8-)-xtT#gT~r2^Q0Q)x z{PZUg*3l#l%br)JDNx&}pI6cZ+7vWu-z!Dw02bKiYc*0tOq(ld?nvA*97h z5Jw)WDN$ESF`bgmb-sJpWa^6V$z|&6l15xWKoPOhKqacX2auxy?XMEDpr^NrFk&kH zO6t1`<_o1vUpqq1+w=O|6>swR+*K#IJsrvCvHn8ptc9P+@g^z|7J;{3-brAy z0|dy~WM+x<1?M&G7*D%J^^$J|f2?hvN#_uIa(!$;!WJQKsT<1+efb&u=aQ+Gue6dfv66u+F* znU#lAYup@%?#VGLpI29H3F7&Cfado8SWqyFc=BGEk1|e@SIkI|{tcpJY{uk5TmQNM zf@bcvP1&z~bGB>WOmkd*-)@7nnVrW|dtAbQeJU1_qjkUTwlRCS_{D^#ab@6{{?l6o31cu!g6|Rda3S91XNuah4VhP=8BQuCwSi ztFGFIpgDkG0gQ&ut{47t7Lyc6r8^H|)=}F<;9s>(p{rg+suGjb(!QUMU>XFTJe#;! zR~a(rvfs!K0#gNqOSXLgp9d)S7Def_cI~Ud?Qk)iS+}t}EcNbJ{@+HcXP^}Ffo1DK zM8Ox%wb(y1Z=fb=Hj2h!xXQo_$~0IqISi*ptX6%5sfw&^bNzXk<^HPoIxs$U3KWU! zmkV!+VSCvyH>*N_nY`ypJ=HehKFMLNnfnMm4HsXswCkqVOoc(f+=cBb>bY|WrhE4D zJD>K1#B4~HRI*zEc6MSH{(Od1woUah1cSk))d;wrUC0u@?J|6w_hS7_&1>TUcr25x ztI=G?kS+0LB(zHc%Al(p%Z1$rVQr(r;jqC(&A>X-ooh^q-e1>C^_OsF*65bg4C$2n)BYhU zXAGfl#vQ)yS_*brYOce8jWLKw!#p8Fd#XgBsnt0;M5H>!{g$=H#pV%gX5S16%{@Jw z=_J~(tjS{4^=|r^n-c2| z?Sf^ya)I9&M=*7QUEWLb_cm&b#M_-~%R*g_MGSBHCt*5`g1byKyBuuN$i})OyRRlbGvCIaN9*IVy^C-A%QX>& zv0r$o3^X%Y741(Tz4;#xYUyEylV4F)VnYG(CX_?D>H{*d{8f?6YCgi)rsYq8jDt!U z3SXf*HO9@`_IB{QZNF6OkENo~f%h{o1j>=qIO4p`&+CKkrwMSpLG++U-b5;<2$q~=a>vIX@0O0}t3URD!hPi*uZDGk0)p?I??YEVyNB&{+Rjl2 zzx+_2XHe(Hm!IGWGm-mgf2Il8!8wwC?c)5`Na4(Uot(yM@i`GU9_gCSFv@HD!zi$X z{qn`J^_!6zhpQq2vS1vN#6P;n3O5$l&h8bW8=OnC+beluia*Eh>{T=vaK?$yf^m}eRVQTno#{&7S8euR_ zHOT%(_!v2`D`(>^RzFraM2+ZB&ox#wNZQv=1OOm#od=?qne~lA(dGmGyE3!O0#Yzt zgyQ1FXG|63@R8JlHIZU7v`RDZ05LrNccln+pCez{p3)1o3h3lLdpvVtV#TivZUn1n zn&T^4>wMvsx{vCx6)z-0@oq zqK!XKn3fV4CJ=5M|D-e!+G*MxgCa{bM|B#t^t-wpelM6fr6|sk1w3xA5S%jYA4po< zOvJ(x+)RI$*n{u$akG4Zqe)~V8YLIixPWzqwt|f=Z!B6|R{(;0_vdxl#RLZ`sn3%$ zfH=2GM}KAJWSYNbwyWr1T|I4HdpU_}`yy@bb?&gc4|w%n<<9h_$Z&fl8hqSM%zPSm zxP7sNeff`%o0r&@f zMBt`<&}hEzO5~<4trb~M&YWuG9t3wfFwA9lrq%j0#?zW;=CtEb9#zs2yQ%4OMY_GI zm9>%8JZ_e@@zv-M;+qHIJpQIRm2d~9)`y(Z$GCxDN~#9u@9CYf3#lcgaXhzq+Ai90 z+41SQtxlk2E_O4QVlH;tN$bBVC%+q-#4e@>Ws)-pH7k=_AQ?&;I?pT7-`VO}dq!9< z0KVfi?Zhf``fhlZO*!s((z%n}?2gTiz0M7_pfCw^z8;p%*^Y_*<5(qgHBxG=-(6eG zeXzl8avNUau{zf)x1U~>R@t|$p2!f)GgzyAZ?b|H1e+8o0Zz}hO*uFd0GzLJ^-r(J zTZZk4iC|GNM_#>T8m0w&Xsyw@zVq`nHoKwnPwqemG5_}BBxrKm`8k(ijf6L6)IL6YOS)tvznKbC zI%rYBN1K?QBLH$x%2jaM3m_X=Bg)!oFFu|_pG$2cy|F|t5wK>0M9v4rjb-~Qca-F| z$CEZ_{M%s#q6X^MwGkBfQ2D$;JuVH}8G7Bw4@yUrf=tztAgCVs&t?Orzh29o42$Fo z&?vL3Rpp2(C^24cGsM79Yd=IB;GnhNPaI&WwVzt6!IUnyrehlhz>OQ*&D+mIZ|XD7 zBz%mg8;<9<9O1OlKsrwf^nE(@`j@sP7Tg(0`Do8(Y+$9_ZPBC_{VAK^TeNnIwI2aq zW3Dk-XK+0C&|<~>Lu`}b;C*F0{JEY8kmmCO@3yCfSFL+A=V(>vry{*@QU1%utuG(K&HM zG-zn)=vHv-2Jn?<=;R3aU43H2LRNXi4hUyXHsF~Z6IA}jU19v43)0v0`Z2WdjM!R@ z(yg@9d#<+_H&={Zxxb%v`d|(qOl|jBe;DiR2hI2KRI8ae1?q;`|H1blpj_rl&_CV* zOzYpq8uo3!DGrdAh~{3k&qheQ=pQ#wZjMxV_&qlXQlU=uQnuY7xl>K?W?{}BujViq zI#~HgZ#!!Xy$|A_O+I}>%r3RR<`_2u+K0cZ-x5^y4R9Afg6q7cba zP|EmkqfiY0Eu$DDitcB|swX6G_$01m>zotwf}1ig)3Av&sgP0@V^L8MW2a)gZ7B{l zlnFXuDih%gC{{UzWOwRQljSpmkQcEJ%r*06O}yh?aJJ!-w3}H3qizQ8k%kjW>>WL5 z{?^3i!MMy81Av~M!vP~tLA1<7QqMOj|2DH;qrmovq}m*VZr5DeI|jnl0ohosxFMi= ztKZI8;hY>4sgvB!@Wek)LzoGu`HxFpCP}UVaG{2M5W!i9i?(@hnW5v~N3NL9k_v^A zo)Fod%}ES|@iTpT-DZcz7C9KNcWOh$#w!UL9-z9sgnxR9wP((5LD z4SBt^n&q#uWHhOYr3`1L^Xf|Y;2cCg~Npf3I zk9j*|Om|?~Qx~FhtHyzE-2Cf#yN0l$Z-reFE-SO#I`jrgJ@rjDIBXn#IPBzw{7xME8qLS(lm_LxSMMJNiVvd zK1(Eeq&g69W%3LnAnQ1pHr0%sazUGOxS1;L-AlPQwuh3&gvTnAt^F;q_g#EQuJ$6g z%}xwSwozcjt(fmHiWjN*!#rG%1mJ{zwiZZS(7|z}{_}k#_BX{JPq@uKb-g680JgM3p%=QyYhqvLV4T**o3e5DfDWI&S%zS(h{vbXeJaXJBOQ zY{fi@cV{RUg*pzebE>rozfX$QNfs_{+J!1N_FV(icnK-FvQn&G*=Y~>*#HZ_+}4N2 z&ezMcZvvA~4fLeiF8ZN5UDFmIYux?|?kM8|^x@%!I+GZ*(IO!;t*1mJ?M@4mtz_{( zv%jPvIKMy#pRob%e{eyRj%1FC7FM|{<(ke0 zULm`14EZIUbGzzx4rA3#W!=4KRdyC~NiGQa519RBtQ+g4Wp>%lKiVMGn(NZ7UqU6GWkrP^|+C}$ouSZ>QAKok>DN4v@Z;vbn3Eefm*R#!Rt@;iB_S&$6x5YHj6gB;=ES9)hO_J<<}GznyAB!1$1nqT_0hWQpo=j z_(VdQr|uv{~?tFqT-4_O@9c}!Fv9-bf z!`Os?l=O*MN_NDMM?Ue?c?cdSKRekXPjJ*IZSW$4=ziE{wxD?b$06=E*Q#|j{0;ek zbG0(rtpa~`3Rk)I#hRrnpBC5-9H*qObyY}VWlBWV{s84>RBBN97r>cS)L|83NGM$K ztwmJRtQ%G&1E{UpU}b_xZA`}bbkLsg_#=b>(Zx`KNgS}!qo|oOld3D-C3oBb@|y7L z4GdX76RT(t_buQ}+sagymJ?)x6fM@Q2vs90z|95P70jz>g7U|Qj+739LdsZ(Rr1Hf z*r;zw5zPhIOoN}5o=~Nep=8igSQZd{td&3^y-HYOy;?P;KQ-1eN7WSPx7-;U|JJPn z@}RqI1iV67h?jMss}+s9o$(cgODqXu)-NA$4UpHkT!A52;BTiXF{5n-kRYdWTGo=N!5Svoy30-K^`#^E2tPQtoEOSx@H8h27oVGIf_; z(v$V2J`D*Pb`@Lx;UPYCTJY&^*Xe8ECm3^#^?hXIe}B5U-@ojh9lATu%LDj*zWL&s z{~7BlIlQ}@E33;h+z_fl_HA9W(iK0pt6HN~veaGEXy93U0l_ad@s~YbHdw`g)MPMX zRr(s<8-7KT6L{gqHq_91Z=yL?ZROg35x6(#7&LlieM-N*$+fN`Tq)gMzSB zRbLIuMZ)EHI^hfgFWvSx0`#y&0>OWH-)EB+#Cz}j#340ehpg^GS~f3V{Z7{wjoE0z zrH7-1(&WEk=LkR->m~y z%hZ{pevnZWs@jQHgkAH#Z_IIy5?SIFVv>imfb;J=#}8UuTa;7qCcqaN#P4G@uHO~l z$nr08)|${uak$CB;h3jQLrAPpHu=xsE50szrz`MRFY)iC_C`E6v=Xq(-i+wK%V z_#JsvuolxO^@0rZ4rYp{PK1*XL>@ zd3_N&E!9s59OLhR!+0L#id~`~>!NzcokV&XY~q9EWl+TxLtmrn1HSq$yCS?{6dy`{ zw8m$|V8x}*uI2Xlx7yEG=N}A+hEIcA@lKvcF~ZMXARo+4&zy(3dj}m3XHa8}#ED&z zeY2Y70fih3T#{Tb3nS@-4w1Cd=n(6e4{lm}&E{3dHV9C|cx`vOc7iM@o|Gn-wV3vWC@~w$UGyxoDu>XVGY^F?i}Q+|bbUX$&Zs&4#N^xv)DG(0uY< z279OnKQsQe%o=7&%)_TtK(3(~2D9$J`PpGyuR*{BRjusCQ7^%$ji5!|&S>R*DeJ8$ zlXZk*>LyU0!P9TzoiPX8U`F6&ED#MuNbg;aZZz|%$ z#+`)y@Rh+xdaVkrLVSe3AO%Z+7hAA4^oyXC`7Fa8Aqg29mNpQsERQMu3kND5^`DR!TQBZdq}pz zz?WT1v4FdgF4yKaLXAh|1v-X0pZX&lyn>Zu+=ni&gJRUfX8MBz=D(ZGa>BARJ#P=+ z{vD?*^21KlX5Yn^PySuz)9$M8frx3zyI;*I{?icY|Fdl^0Xym!+lHjwLF{zDBo%gm zg+tMiv`0ya&7`0OLv{%6?`9mk9ns8ZjYs@BH%;rV1Ua7Ps3($S|j5 z3a4ElQ;FGifUmS|+x6{hqC5T7XKMudAK*IwuREgR75n4XYN#^`k**YZc(u|6Dby%` zvFNiPtHzbB;!-8BZl}zE{~{B zFJGw^jiJgz^&9|FV$75bYKHeF?+wJpjuj??=z4waG!>Tf@d)Joyx<1tV zlKQ$}UxpLeee16f!(0}zVRy#|;9b)zuj?ylP!{)(S9?u#G}T}>D^I}Z`Dp=x+SYX5 z8{Zz-OStBdHE^-~W3Ae|=$x|CI}8r=>t)7GyHyuMu-VpWMpDmxFG}^+7@)x3tPzmAO`!IQqTpl7g4Fp z-)Z#S8El>zY)0p)H;XQ$N2Tj36)B32;Ds`qwHfdx)bk%ul~JKdG_Hs&L~kTcv5*j^ zrJL%m9Jn698X^EI#4)pUVI2_u+Ak>(H|7cK-Q6)8^mLy6=N;p(Hq8nYJvIG~J3DFMLB0DsQ4JT$#795>HeLne8Yik=EC1K^DUjI4-ydW|`?>OnW&$(3LE5K4iF^(eAu8L0GzljmICco|r zzGjcXXaII@`W1piI?^`h^QVT(tSfK(0}0`fy9_c8b=Ba z4uQ$GdMTC|L@aoA_hc*u0$rK>7mR8c;OzegHHKiF&|Ul-t^0FRZN?&DYfgvtlJBk2 zp$wP4)|vKAP2fS3iZZgD`Y(h34jgt2Okd_^8_O>2p+31on_mlLFI+3vB^f>eZR?Wn z*x2pXRcRc@1onWxwR-;-z;(u+UUoVYt9rH*!a%EBAj2R6@j-mJHz5b%PJdys zX??M`D!@Ion_QKgjINo`@B3C$u~SzX+MOB>rb7mP6k+Fo^2!26$q1Gm8Pl?mNbyZ7 z5ke`6+W*HfSSszersBwRerw{MZmVGl8r)fBg;1X+Kyj##nu;WSO$19|1&;{ZeKl)u zMOn`GDN$6?d`EH)yl^y3#s2TSHbMgklq60RLPVm7!=_e?0eqoYByk1sd(2HJ^L(Mq z@k8}rb1x!CYoa1-lDHYnVbeS0J;O=FJ!0JF=G64tVbAFv^L%A2x_H3P%Cj@e09tP+ zwSYH(o%tK^fd}1vj~SyaIzCdbeMo7KMM3!52z4zT<_4z*;#tyG=wntvNK_DFkNL&O zeOfJi6j4peKa>31$p|`Ocw-TSSS-eH2?e>}JvIi7(2i6lE+|=ideo-*!UsTZ#OvbwH<28zts6c1L@q;*!u779rE55ya9WI@64Ug z$A^ZqoCf9X%z)3=+rzsZlrT$T#rKpo)q9h|GJX$W`(j{cXRxr(E8?<+^=^9Nuq zO%d>(u~}C4`E<25P z8@v=a2|O5&9WG;(tFqiYa;3KYM>#k=`{Hpc)k|LI>Av3jwnKK?r#gZboQ8`>>At=N zqv3tdl!cLO>uZIb*?AZIMUgi_09x){8y|2%W!p~RmOK+=jrHbYK6{Bhl8)-;unDqk zVmNZ_xD6#sRf@B;rW&!?y=tQo-Ug&7YSu+yz_MBkd$>F&5Us!TTzFCH^p9e9YdF^c+FkNo%chIKE zaW1{wOi?Uu)4J5#`JVXD%IDFbYGA~%#y0RX%RbY@YMw)smCYur02j}G4F${zY0X9L zXNW`z+C5*M98<#m)=4t$&jpS)|8h_T6kqeiSbl}QMlQX5XC8%Qv()@qafmLZPi2~v z4QJxsog~_Mxjl<8r%ja%KuFgxtE(r<_r9zrGAGZ4xvGx8YGYOVPcv}I_=NHZjrCb` zQ}o7$%R~+NaTL>LKVf4$)|KGs`H zuLK2_zk_?VIx3}%=?&D2l_=`E)PIdsIbufc)inREHD;KZ*QcbQnZ=kZSp#hz!t!R3 zV|3AGNo`d%MnW#6Ei^+rrTiCaT3A!+lf6nX{`{G{D;B{BN*wb_goaDLr$9oBui=pr z0^N{+(;Rk+8#d1BZ6?K$%{PNs(K58DN(@Zx|s}w>)K7V8II;yab7hT00fRNTVBH<2)UKZwv*S``Mb_y5v zZ!%>8LyijAqQ()DoB`t=g)WpOrIAwjgshic5pqL>jx<#vVFobcgK5$eU8_oUQn`d6 z#eZ`Ir-WNAB8^z35=Ch$q(<$w}OQ<7ySz!K$^TR-P!mQZYSkK;V9)( z9FG|hmkA#gr)K$`c%>Y3mPGPAZ9ozv7Xn9pKpquGR*is0EUpKg1r`l^j%fC-g{mu< zLF;i!1qZDQt`7jlvyG8`4lhrKHAKQD=zMUq_l-8cBcdV;2D|N(?w^b5XS}6#l@Ff*IiHwWh2zE%lBnZ zK+D!zXCEN@56_50LnSXJX0Cw`mu^Q8|K*|P&+GBc^Uc*lr@Q0F`_tq5Xonp&(?!sq z*XP~C*RF-pOGY)(B>jiXT!S?S$2J2+N={KA41u;z zMT!)&eTfFyKvQ$uhFodQ{KbgLs?4=ag2e6aKGVI0JFI=ZtuWNcC5gT1g_3*S!W7rRBsI5am)yqQv_wOE03&17S641!{bJ1|a@}Ml>A?DYTl+j?;R!bd z)zO6f(oQcocDbH^ASYDLXWiz=xsCpQaABD!&FkJqPEocqh#hev)faU1lkWMaDWL=H zaU3tduiu09{$_Z9b2o1jgNm~%gNH)nw6%wbyaF`==Sc=|ESG1fbuelDCBpV3i8 z=?eU=wJiTV$YyWS>g~XdPC#9iyF!BiwA$~zGU~lT`%$c;e=0oD6F#I(GsL%@`etV4 zEp*CDx2MiA8@w?ja|uA9BWTdw*Wkgl_oCy%sk--ETckPnoPkAVRU}J3hxglzy#-v` zJ0%{dX?P;)McCKbG(t8^!(c`Q^<=hIxp#%u8k*E8-l(Cvo}qYWbwoAyO34d;>|O2 zuK)Yv@L)n96)x*5fPBz2-?C?PPy!I3hxu)ALI*TXTx~3ABdMJ~Sk+)Gkx9oG$N`B) z+gfRo-Q7S&JO6W7lNA)0p)-s2c2sFU} zE6}cr=~G8L-{I>6Y6MPR-&*MxXIYEYu`7HXj(?Ocv>e(pNz&GP@z@Xc&;i1BMJKTG zhpVnrpkQOtHM?^egnlxM)`=b)W*p4uWlR>ev21iwODLy006>x>RW(Puk@ogdsw``k zD_oDH+KEE4SXQYpW(y7vf5zgw&ficafah=1OK=$*FM|%6nZ?87l8ys~?+VddLOGaY937myI6q9;P<(VR|y~p$bvWu>~n^r-bIhsmxr6 zq*J(PM-l-9%%Pw5FUu&b+igNrm}RvZ(VDSh%OEX7XZzG@$k6gE-VG0p?o zK3l1V2LL}RwIxkh)uq6Uz}4ozXPN3l`llaO29URgNGNQSR_mADu{cFAc5 z6$Ez@+83Cpl}PBxT(FruJ$eXTwx|gcS?VodIiL_DPaJb#Jo65mmSZffUOS!qx>-A( zaJ=wzC}*OuDsFSV(2C#V4v$N?0k-`BcfF1=57jrdmVAOnW)WTlL4}3F1Q;L9!-6og zuF8xsQcWJE*7$NIMOhUGKOmtY3&NQZA!}%s)*#-&(!ro`C!lR|RwF&*}Rv_)S>*KKS(5`}-VHQ+r=76;3QKKpEYZ zZ5L#%i7s}mr!D%=6b+;Ly%>wm>IcfP)P3=-6GVblXGQ<2mcPezsI7nPm3)#>@?Ue- z0~VoC_mN!!aHmt3R6=T-`=?|<63nM5Rvfg4Uh^uo?;=wjG|ou|i_hYx+muoxsGc9% zXNRQ4Z25Ez2Oep+IqRewk5lx-fcQlcrdK}u05-;m)l#$D4zvFHy$*AMB|2aGuSCG? z7M`-;Ba;twsj>FXeT>;gQH-iuWNMqPq}NBxi#=rP7&g*ZzB|N%3>BJvl(t3M+NMX_h5j-{;s|jD*pyj4CeG%YmZH9F-3aX!H zJ8FSRAohwSsagzKOQ{P;z?w+LOl+~(wNRsE133+MB%!qS3uY7AuzZw*PGt`znzN@v zl+7^RWI8!|Q_MD=l!5;qE6HOlMZxexCk69S;(dG%c?7J3NLEAx>U;GsXdvEbZS97((5NOuS_n_AR!t{-L`Y3P@W`0)`*<|?KqPmL}!fGbug;r zRhYXE4j_t~L$hX*s*Jw0jp2%vYMk}a+``f^!fo3V4aaNv%45$l~*bn z)-dcJhr7Qd&dWUFawYn9=uPDHb!=H68Vh}jGbASZeBSR1i;E)`=<@#T%j-t!xJD1E z?g~Xl0l4O(>Sbz-6dWD}IFj||OW0fA?hCrG^|#5>`ML5d;L1+1PZaDXc%`xWFO?_> zaTE9WSZ-fNNcMP~8}rY5#@26~-k`5KR}=hV@{Q5;;F^y-z)kq|5`#%RJTC>YZQgT3 zYU1(;{mXG@sywXf_c&}^3NqeI!|YfV@^``|Bt}y1QvDS}gSQ9|#3S_2*@4}jNi)f+ zxc)A8R>01`=WGE_Y9>L!?A9l2EIlREv|n#u-uQyY|9az5(yHzWP}0`l2#^4za7rm- zg7Iot+WX1|d)otQE0etspOR=Tmj1GjO`N8cDEU?7P87c!v_#?Cj1kh$4dFuW3}u8P z-x0u_fx^g2c0Y{48Y;xVZJWViWK4q4q_B_jp)0L|u(%qKD1NS*DHJqL%m_BG5KI;X zOc*1ARA4Z4nvpVs{1q9&NnQcPmE;fF@{$u}5q@SM&zBIM2{(q1?E{$^CMsrP_)L_C z^OLWFqGVUKarO6aB~z;S>}!+a_OMTU&7@|xm8?HX`cn0OMkvOg2Rx zcPTt}MC8i&SdH}3_UTT96-W)2=whMeqp!35;?TIz9bDs&s|?$zpKcyLt7QR@a6h>Z76QL zbN42&s67&G;SpQ!S1)@;QEoK&p*7$~WG3kpm#xy!JuQqfa0@ETlmE!e!{GD5-sARm zuB@!ius3ge=t~LZ<7PXrPVv(>HlA$ICj+25MW)yLdUcT2E#TYQ+z&M_mn+oaqP`aB za;)MGfl|c?fbIgITyD0RvT%p8OYYwcT=StPNf#ar`QJvTq1`v3c;q}R0l%+F@i7Ke zF{pUwX#GBvv+I&PYv|wilU1ZjeKev1oe6i{sWgD!{`JbzGVFj3PM6SdQs7(&)H<;z zsO;w}rCZ$RvT9do&5p&NC9ghYINc{YZ39kPE5-pQ>tO&nu9M!=+Lr4<`?F)0!#thN z!`4`&HFym%$_3m@8J<`PP+|SQ)vN^&mTm0f5)2fJ|46NqcN%!LG?(l7Tn4+9)7?!lMZ+zvRhE;d4TD8(D|3%RY#jnP=ww-eE${7AK7FrH&>zhOjt83 z^C7=Vej^g+F@C=73{-Mffia)3FxUc|*wX%YfAf`XEq0=^&?bT7lo2#4o>DF#!s8fA z`fmwvVXbLB6)RbMLv$BD-w5L^c0zRaJ)_b=n)R3#PC4|)Z02W0rAZ7qqHNVS2C~?v zN+BJClW-<@HQ8jCNQaA@wPVgMd9N-GZ~LUW=T#W?|u;_a^m+1d*}ONeX? z>p}qe1_*x>E-t$zCGxnB{!Vx-79_murS1It;mgE@4d`SZgeLD2V=B`kMlj&^<=RZD zFpV(u;-n`=GPm`vm(+0EQtqIX4>M8DL}zl*jL=ArG^id8XObx?$(GddJRYeRKaliL zcbpAf{!><1cRduqAgGYLMRaFM+642i1$zk)7Q|vn*;sItRyHd(@8np}lBlVWt*TUa zr3WiveB5W-HJw@9XCFX}OX#Bb-37?t*LX@AO~t!Z*_UY7NwYy=(p6%7XRv^(TeYlX z{kCn2Z{leYW=`S~KzhvXCUsi`$zQkVoD(|xYd+)9ilVb0`IoK^NzLLF&&IRQ0Dm!H z8+uLCxP`Nvkj~?{PK7s`@jb^T?7E~|@4Vjm*iqYiKyVcipnDtemA`1%c|rRj!Ijtf z=+DT+qpijj+NEl-!ORWQ0eAY&jdYG(Jtgb~sND|;-`1%>v2Vp~s2zFObhl_ZP3Q!> z_!;+O3+vXZ*X21x)m?=Q`TqOjMR5v13ueF{Q8rf9&b~j53TY-7f16V8P3oDi|My3P z0qOi4rdx#^%!+H2YvUT$so5CT@5Wm-HPX5qvrI<$UwpzFCt{ieUL{)&^6+ zY-Ji|K@rXxm)#A6eXT8~VLEmX7urOpDDI66Q2JbsXAt2brQ!fa`T>#naXz2XEc0%8 z4sTER)J@kNR}Zj*_4HX2w6i1w5Xnb$uh`NUQfo{l7HL ziMOw#TU#SR3-ZJ}CL+Id6bTrkI^$>0Z|+}vB^VwEYUZy{ji3KujN%wawwnec80Qbs zNKiCxN(b>wq+)&>HRe&8f%4edn)4WxXi+JkXDuM0py5fOCO<-g#B}M=g6*5F;_b#L zVXV74g3$(o@!+F{tqRP7*g|LJ;#A7J;N%Nl0F24s225U6;l!9TisP5ntV5IK)3Br* zBS_=DnIC3E)TD;nO>?5bpMrLaKkuD(P6{K<%q_S zs-Mxzdq?*LK*^}GHEnfE6NFT%5rlZTk;%~jtr?doUb*4ttKOaImK|baMbs^Tx&^en zfL%K3xAa3ppFuge1qLt!}9@<1>h`B-Q+#5-BbD zJ40qs#7w~}Vq0G@(?lZI8oy#yul#cPSHkHJ5=Uj;H^zg=-@l^km7S2Kf`|WJuau)l zE>MV}2e3=QQbFXzqbkCIQ9!Dh@M7taf&g? znw6OrfiXJrtbZlQ=j5=OOn6I7wrzP!@aB_6Y=qHqGs!5J*}fOsyr{s#d&!$fnY<(l z(RPUhRsNyc&(E+c8)lp^;gzpXs9F&Mvn5@l>65qylCm~E=WaU$Lj$f=NvvYF{{XHo zUWxt0Saz^y6M79l->xM+x&tEign~P^mv6#l$6#iSdt7_lQom6VUvbnap8LxxzE#!r z{&5s|d)~f`+b+A>9|HJ2KfTrg08gKWVFWJ4Yd3Jjj@!N-kLOc>j}Nl|O&TDl>4=8c z{;ILB{)Ulr?Wv^)ao5Lc>^!uL62L`6A^{w|2-8bKB1>TmeWu?kl69B%d5dL-uE@Db z6DK7_`MiVAT#biSMAzbJ5#bFvNw@BqSI)5$sXBeLlY*x)$Ep+^>JZG<(Iwu%vv2m7 z0kTK`+&BmP(BC3XG{ut``)9tj)jpe#{)c0@HLo~P8eI#XwXcsDvn9 zgT7WVKBQiJDmH}X1BuSI#dioj`Vrvph9TKJ%?$FakWh)uG%(7F$$w6g+*Sp(u~v2% zAB=mYFf3}%F)X?sFdP`n-VA~W4*|q}z|QA0GygbI{b?8MleU9>mFMHDjk2;)MchKK zCT1usJ~;SM*d^{DGD33~z%j1=8f3?>49&pjB!eHr+C0wdvssS59^U;;e^|>H4lc&| zDE~T>xqKEGWG~aUMoTA-B|_d?nU2uJAUiJ@F3^qABq~^Xlh!~1i;-+Shj(RhDTl7 zw_fzNiaukphp~Rwj;+h3StA3F18n>8@evf#A6B&xP6$?#&2#mM zN;^Fws4AHna)?$AqGl-nWtsf%^?DN0*hi)4cAM~~Gp-y{`{`%6V_ zC(yiWt`oY|r}U~=^pcI)ilSIs0(`1u=T|%i#!wU8XU?bLT;vC?OR0sSw!HRyV0VxLHS!|_X+{PUuEuV`Osl!i$rrXY-&VPcMk9G(qA5n@eroFnq8l#yli}&NL%%x=r%pnbY z{Q_LhUR3_1sibuv8zhE*hIo+-(lX?1R@L6@gMG}QASbj%>5!2%knI!NoTf)$|)7=>o2TIU=LfA|l38kSR5OSs!5`h1=2}vqCAu=FE zYa;eXGxEkQhPFzU+|IHBJ*fd$e;}qFThv%5IrA){)cDoMvI2WfUgae|)<({x^v>Si zUUE{R3>;0e+E0x7ZVa4rCK%&aUC~ers8{tGl7eMLk#kKTrgM*4H5j;kelR78u6uva z0x3NE3hHn{;nKWP)l$=RA_{fEN>5Qme_hIPXNi*RzXX}#?!?ButlpF0MYttNWkXpH~={Z zf3<4KSEO_SH6vJq1B12G#?X?jqiGCD)qgGKXg6~1MPqPsR0m*>VJc#_@kAT5cn^)yoN*&e zvUbZxj@W)=8$b-rI$ca1RY9eWVn8rOf0_hPCv7Fx5_!9-C0~|`4H2@HL`y1~qN-6@ z>Mt#+WErimQjA=!Z`K&qn9LdyD|$PPQLEQ!3}Nq~F+{va3zWc7(UPOODdY>x8l18n zhpdyNlD)2IiM$rmv1%}}+}QH{aIZU&7}?QrIzF&dYzeo-pyfB60w z-u(3Qf3!y+;;1|Q`(GbEgtv~91cuz5Czi_ka8zC2F%{siFu+cpKjQ@ZXQ`ZaS21M?Y>D9o?gLjAA~z zZ(U(K)v;ubAm<%O&P)tNyPrKDy&yVfE-Afq`vGud7wti)t?*5ZgdF!D|ye=uy8z zYR3@xCDdbHs#Uj^DjP;Zw4nk*KbPkc^n)T1Wz5CH9Qho1pmT+bu5^$e%?Db&B=TqowM;nZhNy+# z;<=WX=^2qc5}9JocT~E%PR$I}E-cDRb?VHY`kCs}(G!IY=sob2Pn+_0@BeS}@NCBb zPhif1oCTt@&tu2iR@ptLf7Z=Y^5`jT_6+0}d1SrOh?`&OhavJfgp9U@Y=;9|i}jhx zb)v9L{7&h;sb^Lju`X+BJK(}5*#Va}r^%bgMc653^?`h|NHbQ;-4a9`{Z|GqL5WoE zh#(faX`}mrSv`K_n`9)jMb#eU(NXTnT(l1NT)No#LcK0`zEE#Fe|ko`0dn*Nbp?F8 zc>exP{75klH7}d|cIC%D`_e|dj<#N+9us7`Xk*u*ns&gYU3d2Zmv)7j-8s8x64M}HN^^2SpgBqz@o{r%i=Hp%;S^h&fjqt8 zME%0+wPkVxyW_l$f0NkUhM-2q=OoiYvfPvGN4V~K1ebQb(4$Mc@(#GP>uxOI(yr~s zu{odq%rDkmU#z>z?${4pudlOjBFo6IZlPWc)I#*mbIq{jacWiV0S=nB2;SqFB+}E( zDf67my}P(*+b-JT2czw-Q~Y4G-F1o|jD}NMx6EE`7I|FUf9xMrCARVaw`&JJz#+v% z_c)5#>2vm0`szJ>oxfeE#SeYkgIo#fZ0-$eITAP+h%4l-!tncT`mOZCtY>{I^(jt47!wMcNugk3qK;Z zX#Uh5NUrEOe{D*P$JB$1U89TMWT4%&u`?~2hVcWu>eUgRl8cK|-K!S;sLHNEbUDke zK@+XLy{z?o^p}{mz8?Ku=Gu+VG}YgU&cbQS`TVfG{W4>#L+ZTxWQ$22Tv+USIPL4= z-bU+^|k z;OGx}8&Hn^zPAB*^yj_}@Y9gzFWvH915ERGo)-PVC?3PdYz^4lHiMb}*k;tID80?! zg{C;;e@h>ztBXBX@^Cr7XPIY~;htna_W44Qe(v*yBwgFN?SP9r%Le#%!Tiyi)^Fs5 z27@y$ElkCFjz^f+L(m5K8NR&P>6MO03D@zNDvLd76iulMJ|%a)ljQq5NpI?p!5by6 zZP*0~oh;k|*EY}&xVC|>4cgwqyB+7#sqK~eG%VDI2Hmcfx%xlxY5Og`*gn1t-~QeE z$xR4*1@{5roNs}1%Ge4QFtAMVF%z9d3V)95)QS=PPtfUu20Q^#Bb2 zK!O~6$^$+Gh=CZe6CiQ^KSio%M~~?pUv@R3T9k^VBBc~lbit*V$fczJlgpz2*~JjG zAgG{S2Am( zxYBfHuC9Mo`@HEg)T;!vSdExBhNA9-T#P~eNkWTt4q;udS+Q~^bs!lnQRi4L=2Y+a ziSNw{A7a)FAH}?7_$aLF&hSypTZWHn-mutMS=R@wVlDOs;0cCCE@&B2*e^wcDmS#U zeo+EiO=m9A5s~^WB2wX_Sx72;Gz(Ydjx}26VEln|G7NMG8R8W~s48j|Q>Cb=DTv&3mWI!S)JKCs zERwo?v0XO&%(hF7Y|c818mjG5C#bf|hCeNu6;n0vCXv#l0SL6frw~M21d8c0C?v;J z&B}j{fw8s(E!`1?jFzsMLUGK|=Br?(qK5c5&Nd%hayCjw_{dpj#$YbWeg%S!q=fKr zi`EApjSVLFXu5ie#YxcBQ>H)h1^G3l5La42XR#hvgCy1H05?W$?j8?ablfGuk z4&+pCAhl%M5#W?k_`Bcmk8ph7yEi}o@+*Ik%*uU_aQ*e)=g;ng4nP#|1Hd1O9sm#a zcDKifkFlo^JIr^x>#+7dUW+t!w2{7-GlXm&mL60?~i7C3eA6~ za=ri5yo^?v5EeF9F3^@pR&_hyJkm-Ed)N0;{r z)@5U{_|UF54oUOi|Ft~=S9--B(yR6yeXdV&O=-ckT;iGxKi=7w_~;pJGZ>MXcY_g` zWj7d+InThBiEmIZFVlG}3m=0Ie9eDnR{#HRY3ukBRwEJkTyJ+_B4>nQO+kjv=gdEM#3XDT$U1l)&TOj5I<9dy;X+h3AGIr*3*$qbN zTz7+UI=9_mq%Kp&TX&YYOc^Q1MYv-^rE-l7?o&R$V&>-gHM=Iv`W)Cc150!btex1h zbJ3_+b}Evwy6|o=Ru|a~eX4vR%hFB}&NqE7H+?SURawrDc6o+v2@8L6TICVff%k-D z8ue1*2hq-XR*lpe(!gjRPhSnH*r@Qaj;GO~w5&T{Mu+U&mz}F*=b`SR(+lgmi%u`B zD^2VkH=)uBQ9`LR?y@W>0IHFnWtMJk!0ayYA6UJO&rp%RAtx91?18AL5` zuRyc|Umq~m4t#yUSUZ0dbyph;N8QDym)CX9d+WxiqFNj`K58$31N>E{Yf7$jYC~nJ z>O0sMl4`~t;jc0u11S7GHC|$ymfV-*65D=#Xgd%4^`Y%N>?L;F1*ezTZC9LLVz)W@ zEtgydtJ;LjLflw!n6B-(*!vtudz))E1aC^5u`Rle3+8iR7sY?#Yh3NLwg(I}GPeg5 zG%~k6-}Umk?HZzZ>x0Wj7NW#+6;8`SE|jBj{ayh(wbzU-BNDQOxsy3 zAK0Ung_m|l0H%L>gXRFJWXGrY$qZk+L{E`}_F3^&3lL+4_y7aY}64egd+}fX9ECX*=XBdYOwjh$CcYYVAW% zo1q+&s#VQ^T9~6!akCk$af!)LR$oHO6Q*(rsR<*66$^ui;@WKp5v|>QlC*Z)5g>jn zy83Y4B{rs8<5XWdmEps;Xc)b`P|TG!-|FgmQ*ye^p1=J8IMUFb82rRa~8CKPa zNpVr4wZj-WTRV)AZTT5v6kRc8j8P1lj4^6ZOftr(N!OWyPOznCfyFw5oM9EsjBXTz zW=497taHu{R?!|MIDo3Y5@A)%i~u0h%q79HdCd zE(K#$>x%$Y>x=Z%tgk{Hvi7JLC>YL_wYb(p%iN>r7JF0&>QN*}&GG>zCe5d%VC&Ja z1hyXfN32J~7-B`$@)Sd@VT_U$T}@S*rq@4}6#IsxH7gogimC}x2#x~)gB8KGY(9de zsZxJPj!9XP0>e_4q#&?*-waZMey|EGzzGYC6$D^`vXXRJASH`dCPj>qgSG>lT#7|8 zMpfRXh%u_=1H-u%9Roz-7RG+0XYL;;rNqv(Vz9|$aD`6$8aQFg+j zSxB4+>)I$g$sE7=2-553{ovmH^z$!3xB7pi(@Y*!{PW*G{%|ka26)`sWS5f%V7D+_ zW0*606nBW%TU->?;Nx5R@4j>Ie)#<5^VfgeNB8a5-#`8J_opwOd_Kls?Qk#d-H*S1 z`Ls7nU4TA}?s9ZNTHN*M`n0&)(dA0rFYf(&owUr8#+LQq%WYAaZt*BZR|LR)=8Jze z$dNesGR1iU4z%$pK8TACPjE{<9^)^$kDE0!L7tFEo{lchi#r`%tQR*QUAh;y99_sq zI7^$LfEf5;r4(dZDR!I37PyW}@F3+4DeTT$HA3^Er$_YIkwcpyM~u}&=u<9FA>|2D zRxIv8${kW(I0tt)`r)4a<>T%B)RyCY2kwnRf z>%w#fO>IngO zd8eLj?7UOY7@YI!x60(QxsAcOK0=g>uOlEb--IN9L!*-BSxE(_AUz1>&yVZmFRlU|3e5RH@XPt4E!sa*fQe6F39HRR|o6gVu^tw)a&+W!}Z+v;KTjfn>$J~5go?x6Q z`2;&LKM?U^A2n}3>-n|6&iuR{CN8f@PX$gw@qcG;{eFhz{{g!UD}GcY-1H#adk zWiv5kK0GxzGGSz7VKOo~H#0IdFk(13GBY(|VmW4FF<~`gVlzHnAU-|{b98cLVQmU{ z+U;0rj8sJsey?YkdH1{lyyAg?f^sb=9v~Q^AjqK-4iWG`4waA%vUm_=6{7-w5)s1< z>MH0WQ4s?xECzuUuP6}_0l|P^VuB_f!RRI=DDUfWzB0p42?2V4R4TRos_Xdb>+Vrj z@~3R8;yg=PmaP)$-39&cM7lBb^I>lXJ%qjldXz~26X+MhJ{)=u_5svg8~VjqGe424 z5!O6KdxZ5W(e1nk`%UVpWEms+z%bKN*yVQGmpInLr-F`qwnY^`jmRyt+>VtU!$IT0`YWz!urpcON7W3 zq}y5KrE|O`k&O=`ug78O1#duz-5Ee#ITVdhB%xvxtA9humW5ec%oMRYS0QM|RV13Om;O&p=0ZF8td! zC$iBP=rdslCWD2r0F4cQyNep4O7^u$Mmcm!wMU%iFcM!!f*yH)KnFg&--`8HMGY~MP+7ly+26wtFiENE;IFiR*8L&iYjd;-hwo{ z;QmE6aC>pzV6=#BsfcZmn5@pUdmW2*I~*(G|CsB&8ewnEnna&N9|3$;(H`iITm&9- z*g;>j*)UAUB3SwoKhb1n9UZ1UoI}svGU_^#LiK8kShb>h;-pYjtk3Re_cIRIW(DK) zroSG7QY?C`nro`rEez_BJ!ls1GY2 zql5PKSo01s?5!7!aUb>E4AwI@ll&I%EADGYm|3N3QYlVAPMb1I|uqW&KU3~vz( zKTgcccId!=Ms%mZK&|NY7lOOK6^Z6|B%?O{CO!(tX{i6ysM;D0Cc z4aSK0_YlwFP;y;7OT<4@>;;ZhsG&cH^^X($*o9n{v5$cxSaFfaeLVNgbr)FeFYwTW z-^Oc1{cmKB;WSYK1*Sr+6p-*JqvJWX*d(Y1EA| z6y7g?&|`f=ga5FFxRcDIf5*qSHzYYuy#xPUfdAswoyYm5rXuokvaXN!lmaH*E8u?_ z{pa5oJ*^P?4iosvh?;j`o&9Yh-?idgQ=Gf}vt&8Htc2^pNRhakc~_G2-7>+qb4zZm zz*`WCm)CC5i!FjH(&PufN^sg?;;`_h(70WHE#_rh5r?+-82tnt#axUeR^1P&2m2U< zf19Y)5K+%Vf|puwz3x<@{$GlCrZ8V`7UwINFXrWt*mpVYPAxf8pPTxn7Kq;Y<(z9* zpR;ASi#j6TH$=^k7S~w*O2Ka};U7N3eq0kR5wG1WIYHlN3TIg?Vpu>utIt!dA0%&o zJ57&|D^K4&aC&8!Ho(G7U6E7T8R_6Ux_!|J<{_^?7&rOE$x=JBd>JAmbPBw zg27z8)O@^#)JOEJnw5CKSLx*?JL(7rl-RLjgNett2m0lH7VimK_i@)v;k-+MH&Xak zY5so>I{YZS`%*u`jt(ka4b6&pU$=RG6&Ad|n!|&Y{3>F10Xx~>;1t8Y7MRe&6t}}2 zJBORFHJ$dZxSO@qOtpgco`Z|J-4-}WYu3eC=8fdI+(jGy5r(5nknZmCjpqy(JuvLl*K(Qi#liEGqVZ3z%Ch7CX3&ZvdJue*jb!4 zS)8g4&adqKkjGGG|8M{=Q2b72q>%~qO&!jFF0V3mI4$~EW9o2B_j=%j64(M RKPd3GeJLH{Mwe@F9TgHYf*$|? delta 111534 zcmV)ZK&!utGIWaIa zARr(hARr(hARr(hARr(wNkkx9JYh0nVmD%AHDoztH#cTwH8El^I5adeIb}FuGBGwW zGCn+IVl^{2IWjUbWnyDCHf1q5Ib>!zF*9N~Ib<+oI5aSm>;W55rveGaTR?(49mKi| zB$#%C2oQ@;1f;GTNQkThv6O%W2S_j9W)N|jfr)YXOOONu<0vuM38popVK6cX#`&XR zFdEaN#Ar;95`&Ha0FO2jM6*}|6b+Me4_pB;lh6-e0Wgy=5L|yZAU-|{b98cLVQmU{ z+U;6-R1xs&)Y#9v&tnTVQvr09qQQ3X$dv-S-73!<*{^rOzGcj~`|1&;y@}1xB zdwhQ1b0z=)1OR{88$bwv;4laP%!j)6gns}K)=(5L>fcEEwi0-FQ2$XM58(7cxrqP8 zN2zpu--D3}KVyoCU0B3MQ4=y9Z!M2a6m=lM_)d_}F8Nj%hE$kSjM8xkAfSa^&~yy@ z2T+Xo?!7lWl8#Mj7q0=eH~_B>N_1#G_Ct*#&hHg;7chURt`16fqvMHAJUJ!d5IS~7 zh-o?|%|)kSe>F|$@XZi+Ys2x$m!(Ze33fy_Aw_%-O#e@W%2Ox%U?2I?*YM81(K%2)xxasb72rslW(% z{5H{B$Z>!0cRXXJZ>iv>;L_1_rDQMqCTIr<;i5cLrCTbCH31_ zN|Cr#(1^DkjUaqmk-K2f^je~H9IC`VGAF0_gd^3&_ju|$(FNoRXs?M+kz7a5V{PVW zlh_}v&W|t*+GAFDw9J+M^G=~4_M+dpG2e*+bB;o zN|zuz@V}K$D2JXj9tT*`Ht`N&F#cWh z8E6vG31S)~e#mybR+$ET|Ba5vziG}0l%}E>aa=ZiofJcEV+MI#io}4N!HqQ;YkiGq zHhzD`Jk}uIir&F~Z%QxnQJ^mYGd3;XFBEx%pCVFJz8i(!0uN;>AzFiM!#irC2_G-? zU81#F(dC zL0>~9r1YCM$29Fe9a7d8qOD(`-PNEu9i|x$)12Q^=w+(x8^6*+m)BRI=?_=;nJVjz z#l`QyYfbOB#k-S%J~J3tss`dv(#O-f&G{Xo=^o zh4r^qHJB>f_mp^rtn>~m)|<4w1v;+?&Et9MYlZ4lH?+fHD@9G(zB_w+joX*EzW2ND zi|ZCuo@}p(*`3!PqV6AGyeYiw+Ku-;Z|OW$>Z_)*;h;Hd2Hx|iFWY}*PMUu%|9)0t zlumx`TzW*7Jj!ocqW)cVT~m4PR{7m)>bkujjCce`Ud#~A@LwIWd?aGa6zVJJSy)}T z-g|MNYODMaO5fU?t4q{heqAwEUH649xUGizD$X7#K47Yj$niemhcUORAcxFwl0$WT zN#Np(88PIVIyGD)n@O%|*;0Q{)uq~+8MwiJHIx|Bu%H)ir@qoU&=grV%_MHHPQ8Ls z(z1Zso*|qIr9&mR&ngMJUlrV27^u!k)c<)_Dk%;UKiAT`<}ylBdT1RaWDN z@dp=}sg<=##)N%##JO`Y1`U$umeQb~JxSf7^^ikpaNB1E2bwJ_XIp>3u@W-_X`U@M zK~WF{xN%=YZdLFJzgeUjF%3nKr^LdcNy8}S(JdfBre!U6i)gSJyL@PW3uW&W%i_~v zItPX4Srk*LudI+aId;HbjGzxZlX|(XQx$LJj`3)hprR z59yW4*DaKqq8u6-T7iGEKAUNJY9*uaY3LOPS{tjn#k}h+P#7F^c&;sS2R=bRGyLtD z1iIu*0W!wv*5R|X{v;;3N=H=>-Lu<>Iv@!R6mVHBfM+*%4ta1iwZHS4&veFhl5gcix zizf+C94x7f+vOh6>5i0paIt;*bu{^*+c+>prQJ%4pRlr@fwTCy1|;ual9Vm_0ZNkb0ZpceN8 zK!xFtY}J9I~Ixlv$!6b5(HU zB|1M?qu9XO#h1GbuIY}+!N6O}Q@K3$NA|HAsFuc7pzR!hb%JnZ0Mn@SyCUkTUNJlR z8Y$X7QL~jFMGNP`BDYhJB!?q)KdpAvgK=p%Fp8YqJ8Fp>QTCX}%ruT;Qs*e@s)BRL zddD;m>eYXor>PL`WGJPjV=<~!CYy@twKa$8dr^t6|I3e&hK0RdJ)HnvV> z#ln_jgyG?==aJTb`L;5d_h-MPSgaTFP53iksaUJWUsDuNYi=P#s9Va+b-cCz%lGN2gqnAPoSGuIQLkV&I%=ELNp<)R{paVF8lC-)^W1a+ zN>N;Daizl$yGv|g2P}K;e!{LML!)bxJUM^;naZdRH8%y;0-Fn2=Oa>qR3`m0a}!)Y z#F~=04WucIEnJcHjHio`LOLCB)}H4HyNl-XoF_auyvFI?L)4Sl*|wD8(S3|nSUCr) zV?4?E7+5oR5F6 z$(44E1lb19jp(DTFM9C}VF@d4so&Ze?^czrk7R45e@Jk~jvSLf|# zoyWB9v+xj6%FHVBl8|NO92Wp}s8i?IzZrqou!Sovs4}azV&r3@Dzk+`%^me5L-KlC zaf{tzm_r8Z)z|hlEb{d32!NVE)5d?E)g=k37b_&U7jJ%Fy!n0c=9hf)3y^<-ak-lT z0KV{V2J^!WKf!9x-$({-g-fFE0^s$-OOa{q#Wix-oA?lRP*8?83P*y%$Ckf}y@j3o z>LbC+o6P8ylcpf`IwBHGEF78Afy&WX-EU3U41D6YW#IhM@@$nCQiFv_d;%`#PMDn) z-l!VBlcn$X7RtoqdfsSQs;R?lKhco*05Ca${5c5#a`k@zmHp{G3YX#24-~Vr8?6GD zfy56Ze_fJIZ=)~}hVT3eAG=yr7z1`9MM!*vDu;GgOS*RglPpqVkRgZs`@+1mTGbLr zkLT;1@%Z_nIM{9y{%_Ye6;0yY+1An6-(5rEM3>Hbff8-kOe^ufxz&T`=dbnfR^LeY z`Ac>z{{Bp_baC{ktJ;pwS$}Px-;ZUWMN4ORe;*$M3AOT}s2<})w}UN4EWDS24m)=jLDS7IziT?ovikvQT6|hRLk9f+^KZu>@^FYN0@eOgdmv$f6_A ze;yPwMTpZ}A&6JcEtAec8IzHq9JIz2pbWHU+CZl+nO0>+f{@cdXBL4%rd)xbbC3Rv z20@u&ol0&{fo)2|Gh)@MM9vttG6ijT{Og>9aDl1{lfy=o2R>J5AN?U9Vacony6 zLKIXR5Smxp{|hcJzpU)n#x{57=KbNl6z0ubmZ-DzwfaLpEK&S@01rXax|iY84-~U0 zAi@p-Gm|lN7n1`oAVPB+H?n@;UxBx^Pf8=)FR7HPY%42!*WPt(C(f?R50o^LS&>N< zMa4(|{&athxrnADN>p+-sS$x04A5wFe|-VQlVmR@e~;nLsALq~!ab`@OomHNne6b? zE2|y%5`wZ;<7rgZrNE`6Y_Nq(S=nUKt|*%$6TswX^cU%mwYW!}ddu%dr>G}>Bhnla z`iu0Z$kV92G2AmX@wVVzR^HRhsZ?mPhG|Y(`4pHFG>|WjpC+q<&OB~%Dp<@nc@?}x zDX1Xhf2OEHl3tPuIiZ)VqV_y)Dk@q~khO{qGonso00r5q7z>Y)or>Aye8}DRH}^RVuugjylb>NL;ciTV|LmPGyhvC|+fGmspac z!y8c%@hH)f=fsqjta8CDOHoCG?X<|n7|$g`e2gslzE!CiJ_#w{P2U?eR{F{JYT3Ej@#p7t^JW^LUpqAOZpKHNQE@rPjWxcM@BQ-K z)6@23(Oyp8O=jmi&*rB`J1>vg*>bwP+93}r`OmW{HEii!T4a6~kJK&**_beT@^bIp<@vJx@^W@O zSNzt$7Dw%ZDR|UTKx}^7o=ne|i%a$B>Cyb4eas}Cot?H{s09uGgqC{m1Id{Y3V4o- z=^3vmbN~eQlb|uVQ8$-??%fZfe<p<5y?XxcRX>LvBI)9EvbdeM>At*8!Q9T; zYsh+F&PKnMv+i!3_3JtN%imx9`2N>n3Y&>+xj$R&?QC5~)1SlBa5tXDF;Aa@rgv)h z=eIBA&!f-F<=Of7ySrb%er-;Af^!y`Hi^2WZQkB-ZNn#%uqlfB*F2$M1eVxR@<3e_qdL^J*&AGIR@@ z6>ewfb)-BTGpVQd^Zl25uP0{%<=`;~uix_6-r#!Kn;H_!rJuxFrfy-z((O#WftvqE`Stgf-=9A` z|M24NfNmRNZVdP5e{#N^%j>E7Q}EW_&9Sv{8xKKlo*ftbv|*q(KE8`gC+bgWCd(ZsR`V;%W-Ul)_vf5|B+%h}}vFwvSODVI|d zI0HvspLaodZ5o~8y;fIUw(h^r zju^vgY)PFn5t@}r#5-1?Y#T$q!+m)ex8Y$&17S+Ry1IsU>>T}S?e0xe+J+|btpacV zh0tghsZNkgw2>>`+?h=kVj8mzpcpa=**NH>GeKERZdD{v3xqW3u1I`NolfVo#%yOC z47+sXe>PcOG2Y!Hm?IzEyVw+O@5?5?m1jp@rDr!JG(PYyH|&)+anhz&#{pMA&;8C}99@(f~mXiB$PXA{Z3QefUu zN-=QYjfG7q<;;|;x!hm>{U3JCLa~iivy0PH^$9b1HT^P066?|4{BY;pa^9Prbm)kE0TUPe8NZy+1EnR zUC!;+Ik3E}>05GDrqms7!%?yn>PE;0ecQ0MYe}72T{o>QpBzKM`h0WO$J3LG1<4eN z6wKP%?xhdQ2i8zXm2#)u3Mcp4a~cCjf0;&!x##nX*^;Ol`sCA0=z$L|)q?byOTVG? zX0qUvA;(RloF#8wo?q=bjEJogD1Tkow_oWK2dma~`cY2Y;Wbx}R^V)1E!52Gcv}77 z@+^Hj)aLXH+v;Hy(~}=JC4U`R^{{|hLs+<$2Qk(e$J7;aS17fRIzFY2PgSvSf1Ixt zI?knUIX6tZZnM>$pt={4%biv&brh$L;?z-`I*M~gaqcM2Re;e&?x@Zk)j4#9uJ_#a zp1a<2*L&%DFJ14Y<437es$1H*PB_;M!(3;ctsQacDQEsk{(0Bo>F*~Wrbo-qDv-rR zCca&=wAU4UJ~?~QPES79*0O1^e^fgbI~J#tlXJpxzyh-8&z{Zym)O4JNuzfxt(vi( z0z@4E^W5TZ)6E&WV#LflWL~9qC-*K%c@f-VZMvi5U`Ix*r_Me+6yW*xA5k zpV_(QQ>vU@<5VfR5_~^#c;YPDYi`dccR7CG_8eGIn-WmYxX=BwtbN4UT`uEY%PeG> z;PxDb@ty|V$DtB$GtduZ$8o*|(T4b#D=R6k)ClKVwD z@*IMTGG{zMl8(>ZQnW*$e;6oo=7Xs|*I&->AfIEhO-LyhR6K@&f5&XNB8o*B17S^=7nV^X)F_;LS`|6l9ZM%3FYMj;;evBe^@BH!(6RLdyJn!vnXbeF*0Z@qJW^o=8e|yXdVsCTkUkmJWQZP_W5q|kDe6+ZOU8>1I0-$!E4EOm2r%Ls&LGDZ@v5t! zgJt(YUhx1tn)Uc%>9WXcnH+c`d`vHDc_Rpv$^a1~;{3kBKqiTZL)L^ZrZT3hxLWCN z2d5h@Zo>Zv;)^?Eso_bI@FCz-dl9j*sG#m%}JxR-rSj zLg)HJtLtqyE%O7~ZUa~g9dJg=sMG^z6l*EK8GGP#_>iLqP9R?e&M*Kcl)i$cfE$!7 zLuo5e3ZM#5B1cexQlvwGQbeeNWEnsb&|N_?qyZ#Je`Up7RUibARPf{EtTXGuFWLe8 zh{j;_0Dj&L;8#ZAms}5i3?V)ERZm2~FAv}+V*vaD*j&L6baddC_~V@s_~jA!*%A1~ z0sLsxBz*|@@#awU1NcFUEBIlx1>|A{Jnn;5ZS1OOPORtZny|}47YT>Q2St2rEf8p_gKv7@>6YOCKUJZY(RG&i2-BmY7;{t}b!G)@TQjt#ph3t(J2XhQ0*QwfMF?4WD&%qn^3JgJHPCHZ*o-_f8iN(PYF62A(BuhaT8E1wn`0lCq#N6 zJQ+r*y5exFJp_ZjCGpq17w`~efQQFlp3!ssN*gF5x8XWp+zX2=pTEH;dzmd5lnctq z&$-Thgdoag`_Mxajo-mVa@)1(Xz6&+^&@>J0g7U)@@6MM!1K)#o=7>nS{67abqxJO zeceS$!yP7rMv1qE^FwMW)#To$ zo+%Hz;+f{^nR52kXgNhUHdJNRe^A|Y)_-iFc2e)4>hPe+C3u`=$Q+4|+ALrZd;iUe z3IIfG9{F5m6mUY4D$s~@Kp$K+D-baK&6-3SezYWuT0N8P^)g!$Xq8KcsNMHzL z<2b;;yDXmDkgA9ZvT4uPTNF!U_ zr$rL-v%yP#RnR*R`Blz{Bsb2n@)zwMDH8r97!xK4Kmfy`6`ur4`YtLSHdgVpqTS|- zcI#E`j;jKF!?zS`#W|-N^*h{CzgKM#v2@@@-rNQyy_!=tHK&Y!e=S49*SwQ>J2AflFEs{>odKIBh0HVb?Q}|Tn5&NE;oV$hLRhRq^{&f;1|@SvNi(} zNSG{n5@}PBV3bgfV`*vWV@MG=;B7nTPxe%_fSMSGru0ce&56NU9;| zZl0fzX79^pRJOMI%%2cmvBxi)02;0?{&5ct68K*n;bfIZf6|JWr#)b^W{V}UBA87T zxHOhe0%cs0-03bii?#JN6)Ozj^o|H*MySEBII%;y=A>&*M#9(BUry-FSS*fUyOt3V zpKNLHX~&P)u46GVtn$SVX%N!4vM(Z37e}!4gj$Ahm-RCQ`%pG9V5+&*Z z7zTm_Gm8X4ka#hZzzf4E!wuN(LAxEy=jV{BcInZoUbst_ltk+Aka{>o%Ep-xshHs9 zx0)328=R>uzutIC(jeoxNFx|uWk`sIh@`=WI7%ZKD%v@lm~?nCv1Vyh!)Cy!J9D z!)_)S?>0AIZ<11&~N9p!|Udde9KCGA(xN;)5GaFzKIY~(D<$0B@jqD2>9f@)!- zB(auYqg0s%)BCDRhl0ElpRp$L>Om@KCDm5If9YgqOivVK7A%k`iw*oCSuAR_=BRb6j^jjEw2SeDPSwgQ;o zzO4t$MH zM}V+gbUxTfUfji^5l^w^VI!#)3PeY>u#v%7v|ytWwMAnsIs!JTER}sW@Jy`1ao84X z9$Dd3OGpb6CNd!}f{w*h9G%Qe!7#Ioe?_8j_VJrPB&U$MznYu>{P%Ywly=#&`Sj(( z2lHChd{HADnAd`UTYX4m!Qri*B3pk&?Yzxbrbqf%cV)b%Y5`}b&%^4Niv@A_dKYc{ zYX8LxbMw>f$J>X`<`47j!~4_S{pq94mf|sdmczU@H$T7mczU9v7C*7k%lT-ve{hzk zqm{;4o{v^3XL&hV;S~96^YW!E$%hFtwy}?h=V8gHJGS~OdIv~*J&llMXKPOwaI-fL z%6AdnAsPli^A68&v|V9>p`l!6aRa%|V#OG>Z4xWQ(GO6bBd2Sj>MUv$Mq1R8%X&ix zHx*~4+DGeqNO(dtWQ!tn(dQ0Pf1iRysgbClraaw;Dp``cm#vG>L0dX#3nID0R;d&h z>eZv|q=Ojq9Bp5n#qMa^>@08n^MG#Y(8c~~WgE@K#vZydRws_py0F(rA8g2bJ+>Yj z{dLITEsdD*)0nl6dUTkVt3+kD$d#$=7r9cEX@qBVol+W0+pLdLC$8une-DM7d(u^u zUD*ML+MN7Yn?0}#&tjJb?7|j0O+#LZrFqCJvy`8_FiRuAc^0<-lmXB*?R4M@_bHa9 zy}*+#J=fA$*}Oxt_k}h4aePQpFgpEMn3K1@J_lzU&@4MNl~-xuo6;&RbW`XP&0`lYhSTmQPqmAu(qpcQ|Ay!}(W(5r?h^xn`K ziO-GvxKBM_zaE#Tfx~9rAr^uZQye4*;QdHrWRZ=%dSo&7hOVNDe}1G!D6!k@o{mS= zg4utjrvp;Yl{JS2O3i>A7rCZD=0&bKkWqzAu}o5OU7O5ogy$ zkHpCq+9Zb{h*|nQZy2AdO>&>=4&_@6^ME0_Ery!td8MgldR}R&Sy0?8SN0aah&2n! zu$jgFRET@Am3v<(e`7X>5f@zChP`~z16P;!dO0feum)a^0^vDK$&Z-w4pY(;FAM*u zfwb_Cl*eVMEbYcnmeSI03}x8R9#5-ZH>4T_*UO6gt6e557fW0Q`a&J2+h0KStYM?~ z2?0yW`naXDUJs=RyZS7+X#h8DvDI9yEB}Y&N`S~+Sx}eCA{O-VrDrvd`%l0zi~BM$>Aj=w93}d(3@}c$!?|P9V-v8M_ImKU zJ6CU^iz9Spe+yka+S}3$1t0CDX_lv>y*thFe6&}nSzeCzCN)4hSI+4UTl*c0y*!aH z?z!O#thiZsm(NvCRJszd>U{~_v%?nF@t_uI3u`^vv)cqmLwg}!6aveO+${G;d!L)- zbhOvH{t#UIJd^s0Jo8Qtp&hbaAM97SwaYcCe}a++f5Xd>%;}vYREHBv-)Fi8I~*x^ zuP0)go=tZiu&q02m6(1Zpz_i${8L)`WnWWP`lVoK)O>lm^zs=QeOPUc^WjsUJg=1A zsgTvKT|hh=qHr_1JKW(Pyg4?Ga-I?bAS5u&>m`4@ap#A!^ymOcY62E zIn+d#$+?6^O8AG%W(xBCa&hhR>FvYq-6!khS~B?dXfn zE80GtzhnE(!8}pU(bGq7G5|^rm$v-Iw`Z`#(+oYIzjFigv9Idm z_^so)wX=X;&p~*1?*HdGAfk`D+P?t;fO2J*;nNQklaNXx0yHp}@wf{Ym*C4B4U^bP z6MsvO8@Um_=U4EU9I|dcsz?HcfgnM034$QmKQNXwh=E|e@XiML`6;rS-9?H;Y9u)a z*_8UhuZs0%aV!{6i?U!)85`2TD{y%bl-Di|q6!E!u#3_QU8j*&+AKPajMCPnH(0AQ z+I*i=+WR~LrK7_%qW7C6rjb|1h5STNCV!eVm!%8z8XBcnnUF{Hdbgz6oKY5+bf2@z z2AYyabW4nR1j-qmu+T)#nf#kq&J!S;NO2MK`=SD!9s^huq0J+$05d8u3cSlBt006l z8#skTQW}9m8xkFW3IWp`;1&9ipCC>xOQIJd@eI?mxF~NSp+c=ZEa_Q#%wr-3=zpc& zXPy!?A2DAA6?8^GUxUq<(W?NNSM<{0W4;O4%6wk~R<*=)=!7-=?=lKd;p=4|Fxq}kjm#*t=oUMDh%RoaETjKoO|OOi}nXf_gm zorW|UNmfilnvIq&-$1hwGxCsT!-b@QhBOEA!8-~Mtry?y!m(+|rJ_IK*T zKh=l7eEspO`t(VC_}k^bZ-1+aSkyn%hrhpkyZn@YFxwB`F8@hi-TL*%FK_?8sE@Cg z*H;3s7m_UcoEKW9WicoEETkG}LFzh2MpN%x2C z_tW-1{$9G~<0qm+qSgu2`U$mgMeRA*^ZD}PH`I1Rq*p{cdffiE+kZ8;eSbZu%46Ip zG>i-7e!X3DiMoS>nZrE}n(dwG^Z8hT^e#_d$UtR0`8%w?A&j^N0@uQXYbeRchA_{* zq0W?sO*WSGzH&YPp6)jzl-QsYVR;FbT^W{{nWppGqQc7DEQ+v-cmDsfG0|Sb`uXMC z+Yh=y^vAEi5}@A)^?%{dU%vhFwtCr&<*zU4E0RmeUsnbrS-OV7x~9bRD2cTqWl>qK z5uX0_^7Gr}n*#%dD^PZZNEAU=-HYFg6Lx z%eq;R-Aef)W!tqRnR*1p%vonE)>&V%&ISSVw!Ve&6$#mxZhwlgbM3N9XI3OwO+;6z zig888hGIM$sm}M8@0%IhSMJi@-(l0QpBbmbWpgbH%t(6dVG{QxZ0H9w#bN|3AYduW zVJCu(#hU6`s0+I@OV5Y!cdc#>RdCN1Cs4cY*)XSKSIM}Bv@G_eqY$4vlIAz^-0`mB zz>3Sy&u&g@wSSfCb(8LY**^uaZpXXauqqk z5#O{T=xmK+H+rviY_zYbJt9UdF`8yrToZ@cW1aTrPJc}V3x`UXi?DwC;zSC4Vbqy{zDW{f9vUeuL`F&- z+qh7Ng@3I;yIwHkii?28Hu80UCVht;HF7NJ+MvXlJNVw(jy-T0qzw%|Ay9E3;M>H+ zS%KAi>}DIYcahmYGbFtz0OzC$cF^I3v|eCSdEt>HL6d~U+I#g#@kUOe8j>Vq=qDt> zz!-|b11C$fIIBebXXco=vMel$_l!JVv|vIjvVWymL)|YzkkI5{3g>JSstYbm*oF_X z4LBJk#eZe7&*k_nvGd9nnPZL{bXhDA_glAkm5$M#5#AUOEzLEVGOb;xASug0# z16DqxI@ghyd)+wwQk$W%_p(z*40TZhpz>aT6Eb^|gJdar^stk~6NBtcUwl7v|S%f@=pl7750_EZu!g(5g3 za1$s}SWs5c^Hl0|IH43@mXxuWsy+RR?_2e53HWqacUyaBN#gDsoJ1lM`)I8wUVBYI~nS+pS546YX3S=qk%Hj05bdEoh}8=q7=u zX_YZS6zm@^6Nue3e!{UT3M~o*M+s+Gc&K3uHVX9wb{uU0*(1W+Id~PbOrgp4rGLhP zlJaHK%>wk@l+SSNAVdhQ{^OIYAoJi0U1hL5RtC%aaTTOrN#HK86Fl8h1rg&VY`q}b zd&A!E0$Zp zw{-yapqsFA!i7Pgt1Ly=8?v%|Pk-uiTf%Eyl21mbl(b6>oBkIYHOf12N}81{QA0l)TM`DMtNkrY~0y)dVKb+M`YFJ^E+tR2@oQp0OJ+ybC{3; ztO(p`H0#`shdODGwV{i80?!HYXm5M%A=}M`L9FYBHenAi2q?Q9tG$el3k|ToLuk^1 z*lZNx;qP~aXku+HbbqA*&Oe`DLb?%xz^}5rD71X?E_-0xjfKprBo3_a?)3;(pUpM+-4zRjFVlU?3g9zhY}JIA;RwY#lreX zf*Xxqz*&|JB!Af7531l6W0*k2d+NIqOf!Y)Bm>yu@}pvn?no?5YzvIf{()3VKQ_G5 z$zN_Fm#XnP9s3FNA(1G(!?`9Y0AW$(VD1XJurz-|QWE4%l_ zx{s9i<*U#sfs45Gh@Gj36jY59ZDb$9puT@i;C5=LX<|4V$ zdHrhFrR=zjPGFe2@W#pREiJe2*3 zI)x-<3s)HIqa7gk9E;e2ipO#qh3E>+BUK%omHX3Q{NWmG>mcsxjBQiZiROVU?4Gtm zoc}42^p}e`Nv6)i%#|kLy?a*QgU&;~QQV$Qe~_u6!H;r=<*;&7ClZ;Z?QCg4dsKMH z2+kkKCNp9sw0pEC2l4YMdu(^v<7#&%a}EzldV0FMzPh+>u8#5A2q}!$R%oTtffFXW zbl`>aJ{^DvGM@=TN&JOJQ7CNzkBk(`LVAKxLU~Bv8ZA^*e zYx5mmXdm;pAawBgdH4Wn@^$!ymKu-J#U|nM77@D3Is64KU1yO{)cKqh_Cn1%VU0@Q ztrymXL=EBEkXf`r*ccKu8->%5p5ml%Hl}k<2?sJg#cAOpq^CF|yn@6Ll0^RU9ZujC z`3^5UWXukPe~$^IcR_%@97O?036H!K;9QcBR{|i@^;$qw`N*J{eYyiL4mu`|yc5A@ z^r(s8GruUN5Hc1YM2I2D#YYj9Oy8m^qRx^8C8CLm8fXzAOAT*}Axjd8$CzagE@@RJ z!pJK=#pSyJ50hR@(y5Zc=BK0HmCS-gR7z=+ZVRY+e{~T>K-Ht5@>zp6B2@x_dRJP7 zgaF~!J0)Ivgyhe!=AB|i+Q#cYnCks6w)`OU|V z;_(k6{r;2q?N6uY*Dv3`KKKXyJMs8W@%Wc-e?NQ^pFWAlKYsi9>#O)Zh{r#F`To=E z#Z^f05Apcdr~DB;K>ql*(|=ztZXkdB`_uQ+*K`8GT~2&I{U?2d%f}zSy#D(nKAunK zvy={5@=8jummlO?B2wv35=|4oH9La+l%KYu1%J*a`N0vDCh zf5XlGaKvX5J^brmkiH~18vTM33a)hR^96IopLrYZ0kg!d8Qh-1UBq0KG#9fjVvd*3 z32K6AUp6(|AY#Kng#}bMllU%_0#{u=1D=N}`D!_iXe5^BkZ0&33SK))b}hqhSg`A7 znn|$D#Gnc**;rgLs-nRxf^=WF7-eNUe?6x?>s&-+F4t?kRzKlST(ajF_TqxQ+4{E6 z1&SeB9a&xY09)@j7g1y*uHreB@7$p^<>#zbPsXwqW}2%~mz#FH`MWpR~r`QCH6ryTpw8(&j?8Z%}djm#E}Ff4Y_$oA35?MI`zw?7kqf8n;p z#<5)0m&I1qO0E37!zxvs;i8l=0~uR1$5vq7Sc>Jpv*>D=+2kLY_@CKe~PgsI?F9Iy(tV?c14Uyg_&j%)CrX^+O22?`wcj` zl@J)5RSlktDe98c+!-cs?E@}2k_ML)H#wbm<7^-u2XVAux8nobVl1H;cEacLzn*@4 zJ$=85n`Oz_ZOK{HEjiaOIX5gh*K(y&`pk5lYEmFE{!q{;vVyDCF@fC2e@E*&$aX9v ztYq}wauLQGSFfEsVRjjH>3I_KM-P4r@0&d%`<#2QW5BdicULi=w?ZPjw{ywC%-wJ@ z?!j6HXE7N&3zYU$#QjoKV($i%DdDVJz%+Z+rkU3^w#MyR+q{sh&~DOqB!j#Ii?`yjA3Eye?v`^<3w(&!ojhtkn;3K3k$4oXx@2JF{+ISM+IXe+gVLF2%z*C?^-< z35#^5y8Tv;*Iv=kSJE%@r2j6?N$)tPfuCvV&ZJ*0|9Nxx-EmO0Key{>%+k@gK0R^J zJDRX?G@gsG!=-DQ$iwvV=-U}?jKfa7v6)C)QCUEr z%Q5VkV6?@0 zG`l#kh>7<1A%I#W{xKv2&3zdcM7ENfMZkKbIfMe>2?&skG`nPsOSWjh0Zl zZ4XADj+gPU6UurY?$n*j_^=E*UUp6v^nTqwuZevz!1LCp$wKwLA+~_*#)!cSFC3`r zecy`keW37Hfgbct2Ane(&n&pgh1~OUW{bb0c3Lq)`fGjQ+e6DF z;Ewo_zS0NP`H|5zUa{p?TcT9Jw0yjWD`EG`{8%^me_1SUGXt@&^SqNS^TiTZ}pbnWgK=NdrM2)PLA4u>Se1g^i^c&GpC@L_&cS!49M!^%ePvkG>DRE7 zFfau}BcY@;(k+4@NJ}?}ba%-pQlfMWjeyc!LxYq`NlJHzv>>SP4!F9z&$9b}Kg@M8 zzjN->_o;y)W?|Zt5K6>Jfv=hOcnzaj{dV>CHHk&M=bXe-5;G+V@mv~%w8GVF%C(ZD z3Adrwo|WpXR6L;%Hk8>q{FVjv9 zjsIRwl~4`E$Ixf)C3SB~p5t80x{#e`c&WO%l$d2ui1nPkNFm@j*pM>!A0?D&Y< z;ki=qd{o$c{xkst5{WOVPLq@nfyw8ZDUxtvlcOk!e!uTTNJ<3oNK?!Sh&8NP`{6qQ ziAlJ7qp}Vs;!|Y}WB?cL?fsND=vjZ*VFV^Sd-&@Gg8)@s&Rq{lHmB()F(sul{bBk< zvD4QkLf;I29XJ7m*_`$@et#PJeSE3sBl!Yz!#g0xyz;~0mIq~-wT`BOc}F%c*QS#m zOdgkO&zsI$Q~-N365sQVZj0p%w>~nlaKWoCFWLT}(S|nQrj6O&2sej*I}Rl!CS^ki z_8Pn)&3axOSOg9$uRtpIdW$jKQl%Eg+Rf5mPj|6Jqdnxnq$Gak=^nJ&`YbM4H}vr% zsvn`;EmeF|N*j?Oyx;C`xOR23brg9sereI0(lxlUU^U>rX0i2fkfIA?&w-KhNA0F% zplExECQ)nS2fq6GAyv2;(gUCZX&10nFS8fibTlLFJzzIiDCKW(w)pTZu<%vi50Moy zE4MTw|J<;8cBko1xLZ^l?#T$Z=mCk{mw9im;iio*U5z76t5GG|A0uy$=WoJ2(yK!G zj?>FID|!(IgQ5;pX7~7Y80v)g(@Ob^i{5ypDp<}QBk0+Cc|G7)H7n)26gszpbANn9 zlMK0q^nYLIsCC=)LGX%g|C5aw29H*tfu9+fg)v&s4CnhAzIA%Ncg>-A)tg-_fC1PC z_Gxk72%}yKoF48HPK@$=x&8J@7=v(rh12_Jk0tYj4&lRq9TvSv>!a#IE&tYSvuiUE zVVY5<^{bN`_2xQo&>h3MsrKBFz0XH|uGE^9CZx>7>A?L|jS0l-&uZnc2f67% zg|XwcuI(AOr@tGjMhR%Ohdz}b(E^vd4|kt{^|m0)0~6jCJ~6Il z{xp@}JsCSjE)M&ot~Hz1(Mub9CcJyA)Sw;9VAkZv^;Smv#*`BSt&v7ydmqZF_LQnd z_ga<|=SQF2v_`#{)~kD-Nqmye$XL4b>FM(dmlOuQF+K*g8)@159oU1rXOau92grG?9&Kr0^cSu@Jf%qQ^&? ztNnb{audVo3av&Dn@G7w_c4ZRX0HxT4GqN~`xxGQjU$`Oa@SOY+jo`hk(t!$7#fTA)DeIzQ%$b0?P&0)SI(&29)f?bDreJ z0@S|41d-o%o=KC(gtGKhaP5MP#@S}buIdFaT6f)Ee*%%k?pfFui7ITxmBk|AdS(>Z zb(NUvyiHWr2cXjTEw9K~^Yk~=ZQgnSx%Q3i0(xi%YB}r(@FZYcD<{ja_q$` zv}&n2JZiy32ma@K5cvH`h4n|z>tuuFovM>uZcGQ(-E0&Ay5Em-m-r}82ec$nNmqNq z7_;&eH@wag|4l$AeZ{~W;NGjgS-*k?@Cg~&yd(c-pZY8A80_<{4*U`L7$yWIPo#=) zuMno-nh-$g0`E_PcyIW=s3W`SM|=Y+1?A~VX9he}PI7!+M}`gG)t&6Qq1j5{F8M5k zWY#XnjgQrl-+ICMZpjU5wbr>-tZ54N+pk*yEAXQ^4DZvY0cWQHKTcP=);{l#a47kS z=ZcrCz)M$}9{*Tl`SvwZ^z3+p!*F^ujmP_RV`U_5hWP%ZQHb<9?me}dS-o}K< z!tO#iM=^q94lj}&ezyB%Z>D{D{#}|_(~p%FF+GkEmK7aGyPdP;QeE?^)HBC4$d7|xZ8;OaApx3d@?n;R6M%LT7>4@@A5Vku zg>3T>prxBn2LYQkr(%A%O<1!CK>^t(gP7HAJFG?I`P%U|@FhQ%TLN5cCQ?2GL>i5= z;^ObJaBMi=W--~A%-vs9YN?TVQu|iIZgRM#JA$scI&jH(sDQSaPc3mal#)Wu@ST+3 zqv-A^MJ&mZTFxtoM#zRzQmOy93`K^40&U+H()0XNyk7TEZm0psW=X0lm%sNccho-# zs0ZfzQ(doBfGgZr?@+FcH;OXZfyFTncsPD^{dTRGs8UK32KqLqqaXKWh?S3+Ob(`- zI+_}f!LB*`ARr#c(Cy@?3yJL7h=x9f*zrNa<|+?nvkqsoc4s^C#-F)Uc6u(DNNvK_ z>Du2bMAGHr-6R}%nY@w|RUEYoqkt)4_9*wUGAF7lz{{;NiOn*9a8?Qh6x<5++PZ4! z!QQ46Kt)esr0qt;IXLIrmqs(|$N0C}_7f^v-N}fCBGPK! z@|p(PblSdq{+w?Zc@7KEhKTnv(*)mqG*bztcq3?gNcpH5g9BfKP=3cv(hiL6+tr}K z(lC^sRRQ0UA*5o$9z)*>v}$UvCmN!^`7Zalqfhzx=Is&h`z&Gpkg1oOb!3LsWV$tE z`gLRqH3{-8)NS9R-bU{F!eTz4Jyb79xI(w)I8Ia4t*BhpAIv*`c*`U8hDcM-q4TnV z)!2_XHreeZz@2hV)<C0f`rqPVnbbTiu;JX`K2>jBtKoXKzut%AFFh=ZxK$}COHUTuQ0t^>vea0l5E!f-g zR%+GY!ZAIcLlzsB7Ie52%xm#;leMw>y;=qZzql0-qQJs+v(-o8P5W zKQ-pNWk0+oM1f}Th?a(7ELd1 z*Gx{nnUOtnGrs>aJA|RBCTZ2=d*ju?wz4l30T`|@DjVA|JDah`tz`Z|a=BNpW(~Tk z2qgG2(ZCuK>-mq_>xGwDUoc`$Uw_ zHbHO=mKye{z_L2%c94R$^Vd?7eAzH>90f0&_`X6M`hu&lnBg=enp|#<_YOfNRy@E! z!NqDsgg(fwoJ@XkBL`b<3a*)&mwSS->Cd;i_DV}+M~8apX-nm*jegSHTQu+Mx{GWA zlBD-=(sY_=n?aP_q9w&itF?9+t)mzi>YVVKq7)CQzP!HesX7?w;4q{GBepN|iVWjV z#7M)S7sqZE8?kF}5s^q)P==SHsaORmBa>2P4J3>SCXccVDTVjNJsO#K_jLia;jSmlJ&w zA=;t&CFVAOI@{rqcyH{maH!g9#p|GmtU_Cb;&@)Ri2LLoytm({zm_}N^y*C}y%Dda z2#x++nZ2S?+~uW2{dPQC(7^eKd*uKIm*@-u{P6AT3Hb&$r>8@Yi+wm5x19nbucbf^ zc&;NP)hQ?YY!cnrV)vdgb)t_^eg(Vf1Dlek0{LhYEO2h%*UjvdU)Zd4bfNc(t{Mk)||gnW)bqEHF7_?)$`Q4%t}n4 z9j5~Jb}AR}dEP)&l%z-#KYPdSB+XeUxExziX*D8q*IEq7c6CK;S{C~`H#(T%>#*>u zQFz!M2w?kyn^SOROajI==x%oBfjgaVxV{f#t%w97r4MVU01%>ADl%t9p>GAZ6d7C* zd1Yf+*E6EyD6BbZ2sC=NWJ)!pY&~7-O7t!EW?B1(*vW`u^1?y;_PQ$xEP_^(6=0zy zC-tb5kZy!clE z-b%8Iu8mdbRpJXcoCOj#Y(GeWuN4Zq&ne`Y>un60S|=E;YwuSnv1@io3g!DGK9Frl z{xQ+DK@nR>vQ7WhDuR0Y8%xxe9Rfpop`4kAI`p0oj+WuW7QhfG(KrPRHrgC0w$4TxA$s76}A09YQFEl6F-}3nw#1lbDWGEwHZ!VJ35TVl; z>Atq0!`s&Fqv=6Zw^v)X2d~vr;Az|Ji}*qp#8LLP>#byJU|-Y@x+jJsu~MD0r(w5~ zdXwv5Dnp*4KTm?-;`h**Wwm`xMMgoyb-hLA1_}e#d7S`JGX-D4SA(I&wfePUUNx^X zBu6V=*f=QCF7^)9A*M;0-c5w3acPJ45Zvj9QS5ow+f2wp4=6B?yx@zmQ2wsr7DJPq z`VN7J0=vb>_v%-e>_17!)J8Jg*KKzbH*2v~laY~ne5KsW@})=l<2%$#zu~#0E40O>y@7sUhs&=Ceea1M7y$^fN_h`YsrEm;xtV02EAhqYbzQ*m-sg#>uH*e;CGmqVSy&Zu zok-{WvNyIbj!!Gam%D|}c4bxVuh_aC-;lp9ZO(92MF6l0cZMR+w#spw8PPC!1OyPJ zZ3MJ%o%`X7eBj3I;vH%x8OR0}p^p}gaPxH30o&-ax>_MbilozrnecldHy+j1vXno& zo1Wcqi(X91_jOL9Z`!8m`a8uB3fJ4$4lBhT=fayRn>f}J8sTYXNJ8Nsg8BuayZgzb6ImrDvnqBqGv`A9e9iKe@0+3b)cgC6{3+N6E(&5e4?gVE zY?*J?dLb;nZ<=V}9;VAM8)UGQv#8wke2)5j_ays^n)Um>k`5JZdY1gUXxEQNX&i%) zv%Loi_gx&lJk!|46dm1$TR7~S3_=~>j@s&SR4wM0cGZ>cl-hR$o-j-+IQjng*wwUg zO9IZeuy13M$7&Hv_{r%_t}B=I`q`8%=nG5B_y^5Ide_7gLl1C7f)zDyVOn&KSAn zm506=L(0e8ZXdtiB-~TvLQ`a!(atb#o#YFL$F4OC(0iCM=xXa*-asQ_X??j#=@yWS zF-CSUN3ZQ05v5h&JM{3yMj4ZHkeQV>F^_&kg2lTyh3CT-L)E z#raRIt-g-0t#B|tgNxvFbeXI~klX^`2G#)@1H)7UYKCc8zXll(oLU)0^%1I22f+Hr zvn-}mh=0(= zZ$2$DjhyAE7V5z0na?qPZmhwrMCq2*cM5CWeG@8s1F8`aDse}0*E@!s`yK{y6&$at zU08)S@^h3sxvhE0vt>Wgj;U~ML8Ke+SI$P<#pahh{urLBa#O5}{E-gocb)e+N0~aT zJcu8f+~DLDN~t+?oTdBt{D+%7G$w#af5i35*|5-8+cu_5#T74Rw)rX=-ysJR?_8cX zZBSf*dBZgde<@*wsNFA_J+}R04yN$RIM$hr8l8bjJoLH&@|&C(>s;^Fq%1M2+g2m+ z*RdpLX>VP*+8n)S&ajRbZWr*t3S6$Y;xe*+plAM8*9j+eq-=~zZW0hPN+9-vn?^?( zI@nh><4)kPmJU|hv3vgT373yro6Xv-oKCd*n48tp7GEBCuDaAZ;3rdXyE(_fZ}7&? zPXnh?$!{FZKbc;)FqVs9=ND#3r&}mJ>}+8RNMy`c!PeUC8O|v`es1zS=hUv$zuc=- z%E|YBsnn!+9?$dnF}Xok7j-95P0LydhQsHuojIRi(}zn;r3FeduW)6oov+R*^s-#n zRdN?xStcFk6l!X|@rswVO+v?b4K5UeaHTWEA|pFP()pEF21ljGabwO(dPfJkh&|zc z_uZt^Rk@bw$rVNhv7;yi?~4XVSRXwA0oY^i+s=AXm`zmj^lEivfX?%OGx8*j|suLt+*Qe%HN?wqS;ue?i$ zfz-+DV%tb5c4U2*ijgh@1s}WDfJrM@R$nu8DaAZ1`~);ndd^Nh2V|bh7kr!W)a}{h zN31u(zvtW9sE#E#c?!RS5K-m-z;Q`-pU>LZ&285;nBqJfF^L*MGAxhrzp;qT2E9#=$;WFP;SR zc#f6VA^PiER$W zuXVa)yTMieT51Q8&}y2yAb!+$QD#+O+);_^rw_emu?TJDCs7b%JsI@vl;J$PDb5}l z7>H3ww*4(S4kzndq>_TTOKA9&iFQQ1cl?X5oP}TwjdVqE>y1^MYzmT$&iC;OlC@N~ zg6X)d_J!3=_Jt|sPDp7B;nIoNRI%=%_d#E)y_w>OGobkIEVn&_JPHyll|u-}fo%3H zgU6)uaz|$9Ua+FKsd{rC!}6)CI9~7D@mC!7qHjdV-4_!?R~gQ=#?&uVOL;)XtlyD6 z*hr(X#1;pRB{}3#o1E%)ujVPMQq|(uCvNKQ74deic#Yp$dbCs31ScaHhuCREWMyaQ z%KZ3f7psR;o{RN`N$}l6HY8gERZE#rU&~02F1aSbGGxE#OQqmqUtDlZxu>`QyYcE$<%QjW7Xw1KQ z60Xy0cTf1hrG6@+Bo5+b2Y2V$} zVrtOd^~u4q!-!W5p@PD6#DGoy3m*qpXE$DK=@9qFa0FOOS~qFvQ=qEnqf_2i@25Xx zpBS9F&Er&US;clc%+jM##$wv%MZEVZ_2{TOi7o$uAYA_Jzu*TK|6&xVOMuWf63Ce&soSGvl4YY)tsXXf@ zE6mi${^9UPVI{H-_f~eLv#H{D0wMM%HfM1&*P2r@TqWH7lP!nyi#!nwH<1r^!jvM8ylQknx)o z<p!V3SORqP_-5MR$w#DvKO$@dHF6mWZa6sv0W)JB!9 zHtkjPJu21fKb%O7KHj2d{;WA-vfq)QQ4J1zEB7GrI=Nx5C|_y9tl*xTlWv(p*zMND z=fQ-@^QyG6j0~UzMMRH5gw5+dn_UGrc`FEQq7!Exg{K?L^p-)sDO<&w8MPGrF8@UH zl*Y`~JB}V$m;@Fz_$qUF>ab8gX_YhY!18qu*p9^`#%Xi0W~y>)3uEqW%bYM(e}?u~ ze)FE2OSCMw=Gol)?p)PQM^g8N$oEnQOqo~P-lxZpj_UE}noggX(# z>6STr6;Ob)jkF1GQGHln7rP`2T;N%^PTo7E>&Lc>C0w2RqjOgacPsb}lt~ASx2_JY z1@BXyh*^Zr;a|&U%&+6w77(PkOSPKqyueRg&DAZpvZZ$SE4FY(xv>h6E%LO@{3?Z- zdsd-rzvyAyezN$OiGbxmM*9M`sd0GPLjgy|QO2tap2?6VoYo=>bl+*aVYsaPdK8b( zaMX1wk~e)XT8-$z(xx?5y^H)Q-meoi^FrkmYO98Z0*~*yyN%V15>3?mx=_By#Q&D! zYZSF_@sXyNhgPa_2M@ov=kDY3nin|7SF(w-0dmKn!kmLy*ls>$X}Hf69=H;P z@kHkyKQO&UTII!RAsgx;(jf&e)u)#_4rw{IG3aS?5h$KWi0|-pvAC5Ef1m4hHF9IE zER|FnM^{)dtzD2y%z;;vcghJ36HCAC7BEi`#G5ka`{U4P$FPtmaSlMkmt&?>A}DVq zu}p3q>i^cPuvDy0T@@@6i281fdS^`1v{zT`wP_4`YTF}a3}d?NmQ`-R12~j1hU$C2 z-UYp~mqI@|ysCk<9*itjli6kVe?qDnL*hwJR`y-gJ zBL4&1+mcWxCSql5KWV#ydyt3QCQ8;q$dXO1p z=2L{e<@?&GQj9|5&5~fzcUic3J-&qripzOBeOk~fnyf0)vaQLqB)93nIrem&yNdH1 zN{^pB6}MP?l2-rNKds)|U!~!3#$dLC9|>i%CL=GQ`m+-G%1~rbygb~=pzEnDc0L7Vd2i#d#Be!m64NVa@ieryn!nC zvY0%yepu5F!3jbTeg4R&9rN2?)60qrIP2MsA=9nVH*l=979I!DB`cA2snK?6B-%el zFK1|Y_127589H(!qpKhONq%xTvQ#&dArv=v-MfvL)+{n>Vbed>$(PZpxl1kg(_lfp zRNY9Mt+pARao1gas#2I3(7>JIY_=+_2_f-5D)n7?VwGH#XiGQ*E zRe*ua>aM;WZT9P|lw&OKoc3zoN}Qc-T=z^?mmFi&xYfH8kRAGYIDdZ%jmx`~G?^O@ zipl#G(dn07U4iqmy}3P%p?l-V*EDCjgGHSvGj^nfuJJu4TC$B@)8K%0z&opqinm1H zaCtvYF4HhMtfk4wUfGCsA02rwjrD+(p$1}1aQMCdHrg`^>DfcPS2xtc^0eyuuFhUH z{K2J3eA|H;yI0RWBKj#juRW2`&Tsg!;8EKt<6W*R1!xW0^{x)7+t+k5F?Cz3I59~J zzmwM`r@d&LUTJcQ$$4R|P-O^+2-Y|qA(h$dOwVG)#qu|Bz( z(C&Ur)lV_kr)!kRKZD#Y9@QPxf9RWb^VdzIn#I_dhrKi~?C$ZAD6N^ zsUWDHKWE3%SE@b$j|$?vWlK+$75WI_|KaCjQm!Gy_)-LaeS2VT%%%ON=Yrim0VR=o z3X4*L?rHIS4(8;8GWZAQGG(=ON4WOLtu zih)ALoH_v!E6aepcN>+15+YJ)dbGOU?S7io+ek2W2*d{V@wUJ}j?Ae)qQT64%4|wT zO!_ohNAgvT+4kqB?v@%Z;Vr|}m8Y@nIa3&Sr+;4biY~&@ zDY3tcSvGiUe}%8e`Z(iI^q!0hP0|?$eFv4{6Axv-lm~mv4xOjYGVkV+XiYZ&B0S9y ze{Vb7rLnWvoox>I)nmvuG0#Hz^e1oWXs#F-Sb&>{hLc8>hC})mjR1Fa`iOko77;yi zgA%Pk3|&AFQTm*~8%d~-mP8H~5d4M7MI*?CFb;!wBLzIrVnLTeGy>83fR{iFgQBC+ zP%m`U3j-M)jY&|6;uF1_XAp!Xi-me!MZK_*Sh6^?{^tTb#US-TKJ3ML0l9>jH`09? zr;g?vPo)JAgseNm$p-%<=Y^aG1EPPw`AiAGgI-GEDLcR(^qYdG2tXA2i^44hK+NTA zmGl8Dmq84XD>i@tQYimVQ<<@Gv2oG}qQr~f#l4NJ4*)n)qVXfxGXWL9co@6})IuPC z+LoI}P>}ar8&p-O0IUJgxdjo4Zvg^`-AUkM)FC7au)?&9JuUyxEpG=Bu)UxxRSeiItVC}RrP;0ng#lixw~jp7Rbw5ku% z#unEKgy6TqB}A-y;WGRc{?kAtKDaL6Uyu0_C7DBWabL-dj`R!tBf!#tj3X$Hu=q^g^?q@3>45ls^vf z@Gktpi*QH>vi-EMHxdlOW5-2&!NVg&D3jnZ{OPb?2o9upF?a~SNbq^o{xmusJsuAp zLS6w66|i!Dkn$x&+#AC+N3w9?`Ge4TQ5i=J#SVq@=doRJyz3w|u5$S4F z82*nt=A4FilZ=4xk4*eCy>M~zbDal_1ai9?uaDrIjO|6t{v)egM95G#o+B>eX%rbV z(tZTb5DjHHl~j~r=SNY7_1?$(yPH?W@MiGNAD_Dem8HFr&C7Uo!1MDzZ`}V!OeP=T zy@UKMKoC#qfj&qBEFc_!#v85D1w-tDfq##opC|-SU^yUKxr-1nMh5(C&0iM3pt4C0 zB*y)1XOxsk)MH6JL^~M}h8W=lGX52Ip}|)!pfM12$92Sj0;sV1eaC-k7%C3T#zkn0 z0a2kT2c-Xr@|TcB8A0bh&;}1>xpx}Ce@&m>$g5gFRxs)YahsvA2A1$`en!fL5L)Iy z4qU`7GavyX!4b%G4*tpFl1TAJ);Ixo0TL3p}v&(QVj4K5Me9_h9L;kfsE(A{T&29d68!T`2pw8l@Sr{Xw-km z;DZz^0LEWD|DAo$@qLi}Rlw`O-&hWj@36gSCUgZscIU0Y&r{NJ zAiK-@85rV~08AIjsRB+q0)+C@MF((b3(CE`4Pk{^EHQ4zAcJVHp6?_$p&LfCG2!V4@oD_Z zH%UQH ze87UBKWLo?3YQj%E%I&%7y}zsA}*NeMS_24t@Gvti53Oc#`~R-E)~Ei6}*LWUI~@6 zQCgn2eV3wz=YR!)h%y&agNr+PDNb)C7!QcD*Z5l$rC+GvU-jxdi=4H9KY5sN_rRFv z9hOqu42a+#k?@obVvp=WgY@E{Q2xv|#tl$!q!%8<8Hlpr7766M$X*aQ=X(LfB7;=o zqVowN>S-ZAt@9hSO$Uj^MbyzkUUgz>j77w4)uAp~I5Z#{R3p^n|^BE8J0K1jUV zkZus7Qw&0g*ie8l{5vA462uslzPm{OHEH`Gopd0hc&PM$-weg_cSHMITwim@ChjHA zO`Rd1a4~N2^CLukQ3p+Wfq&GEp9V02LrlO35nq&uqoF7fQE+Qilkbe241?4`5N)9- zKz`~^z{UNzh{}dE$j*7c|I3FLHc7~b^aIZC#UjdNzLk*wxEDUi{3_I!;G*&UL>6sD zF?j2Unmo?C?o0h|)dqP5L8xRvVF=10ls6o0eqPrL&SJxmbO-`41R+8kETTxA123WS zM@nK_h8#i=v#5nLg8%TZjDOow^9Yi9?%hKys32l5pXhHEqriqXLe8K5tFQjxGfe`0 z4LtYAzZOd$q%A$P3GY8~{vbws3(9gn&M4hMiS%DI|G zRSC$1y8R7uiB5l*5mE|mKfiRpiClu}gPd%DieFY8eUNWHK*=tuC@M~UkRroSf50E6 zMYTIKP>suafInC>Z$e)}&XF$?r1*E}!^>H);-E}$saTk#_}WyLLRR?j+d=0$7at_k zUHpy98@c31_!yTF_C_+f;wN9;Ln!#;lU}~T*^0y;xEvz;3g724)x4341^5A%S;!ly zSA#En(X0I2D80uQzD!YX&o@$HZlrUafBA#y%rk|3fuPdszZNiWpOg_;16;fav_F)PGLZ={xGc zzqYlhKVVJ}gu!mB%x>xL2)&U5 z9E5w9XC(zu!k^jT0?$B>koh0?WLE*t7ipVR4u3^FBzUKjZZ_09(=-au${frNV3c6rL(8YFbSoWuG&q0vR2 zx*+v_i!ki6yyA_V`A%qmxp_taL|h=~pR?c};~z@mVB{+jqOW-WV@|w46s03t{-u#O z@)Z{m`Q?g8iV{7!Tnu?RqIZBx{hX|ZqV_KWDjE@O;{N{#IAcxp>OB7}LbPM<|T%A&ge*CZT`NAxOg+x%`e~X8ds39tc{*w{v@pEKoC(+2c z)aM_aAlpWXphQrCzs=%&yom7gtswmt(dlzkN7Nre3`6jH5dUS*#{8#i|GA<5wXXiF z(_eZLOW`AEJ%|Yriy?od^xum7To^!J60efr^Zp+p`G4*%WnUA|6Qb56tTn`_cG(8^ zS5~^X6e_jEeNe>B8e(Duf7dzN{{xrpCJq51XuD8it&Cj)KOQG`0w4$!@CXo(7m1mE zZ!dr4v*Zu+h*t1rZjaDDKUgB!7ZbS_k+`Jg0ONJAn0Yej;jlUxHKKBl1%#fnfO|NOuW_4&o68A-pGWCstW z|KC)!B;)6{?%b+6T_i;pS@A-ifKd_*=wDA=N;`awg!vZ*A0+=*65-1;={F40 zy~`nPP}1ucttN^qYGX)63cqMwFWwQ{B+b9PKuGhGg8!7YUy_vQ^1NuTNLqb4-x3|t zFPHb1?AE0F7ZcWn9a3FMQ!b~__LNlkB1xl#lh$93BArC4_DeZ$BuOqQ@^U=QO43Jv zsw3D!>UMc?5$GnpblgMH9wXHT{o^XXwIa1ceqJVp{DbX94`IDW`UG(KA&c*%?U$Rr z3YX06Le`5AdPzc7@-HN6u9N-COxDOo_5u12zA9{F_DC#oveSR+aSlSDK6!y5V-(1w zegzyVyXleDT<%1K4VlH|@&|j7mHneTxiClWb27ny*!=>c5>2M`k6ro&1d>b^`wz%P zH^ugbEa*IxQPt23$yq`+#r%IZ(*m4-Y^Dt+$SnC$xfb;?I0bTnfZXO9>fY^C%RB3A%{%G0%WvCT9%&qK`qCk`uGbuFBVJ2|idc_WhCCf%Nq8;R zC}!2I`RwYdM0Cn?!GwK^LW9-)H*kY2*Kem*1$aa~GiJH%CN2zEy7}DpW;cx}HKx9H zeYX?q*&EY#iR>+FH;>zSY|tg}*icRQ zPN5qvq8F9_X_)7@noepX`pk}>kz(RgXy{R+qSo*P<)P*LJ4NQ9j@g%Gl zj(p1|1|0BfSFVJ^8&9o#J>Tr#%ad}9@sG2)Ki8aP@j$kgYV;19B#-t%tf->|i2_`) z_ni&r#Jax9l^5=d!frSoSim&2;}5Z?AD?Ui<1Lyz4D6xyVIT{%PRvq!3)Zj4pWmGA zf9^7%ysmvu!f|7dFG|#J_|xJ*bGR1Wde2kR@VVQgfTKi;Wmhbb*5yI6wjc=g4^w8s zq=)Gb+g@Vq2}(Cd3lChsN4z^wu*+BouipTd1B(@lQrhaSmAa_g%Gn}nI%qpu0}IAl z>{v8oA0BLY6<~wvS@FSa*L?^nH!V_9%;{H4rfQNLlqc{(8Z!zkSniY&EB^bDz_ic& z4WQF2gWVep-h#dsx?z*mscIHWPY}y`>~ON{(_{; zz*z}bmt@;Yu!4IuZMij2tF71(L7`$ytB`fjX<4K4NZh1bde&b@QN|Q&SG{|mJ#+5H z!ahKJqqOOEs@#liVVF(o9@~uR>mwrQ8QsZ7u+I}FoHw@9w!RymIY)L(9?-A1G`r++ z4MSDX9%)j%->}>O%a(bF-G$Ex!PO)RSczQq->iEPfk!*t&WL=gQvKR?@{y5QSaXm# z(wez!rzz^)UVC!tQvZg91~cz>7GV{=*@q@F)gTiNe%q%vA3L3J-=`Elnf zcWC$~h9^wwSxLxi-xq=5?$Y;)h;x7vk*R4n3i$@USUJ9T_bXcFP?CH$OuXEy4PmN` z!c_bYTDyP8f4ocj4Qs%Na0-0Jqv}zZ!laubb;?pH?Mmxd#| z3u~J%22mI`{4ECtm3D2tLuOuBNM`tsaeTtFgAY?Pl^; zhLUoDdJDx=<3T;`TkE2x;`dTx6z?ScfT;Dp#DB@T6=}=N>?}Zi#9Cw z)lobr>byB^Krs%=B+#f?M8;LM*KC_onh`bBhS=QS4^!Y9gBxeOW7R-L;eTR>aA?+T zD~bQW$o-gr`ioU|au~9hhx{savdd`YJ(jHL#I`sYUL*ai27C@h9!1AzO2v+r)jnbH64SQ zv*U~}T-GIwpy~aUwNUXvOWwJ=aE$u>ZGPnG#ut0jlJb?%JwcAn+UDh!{&|WW%KQ6i z26e&L#Jg5EqtwCB_oHuLV=;z2RhGYtH>}sZ?Z)TcKa~^XV}DzwX_>@!^-ETzAet|O z?G3P)c4OS;I?r@heKGd?QkMbzO)t)gVJXdrTmdiCx~n0lidpX$cdN;JknnY(6tPdi z4Iwp7^g2OY7ifbd}pLWZWE1?YCj8%>86} zb4*x6M#lDWQqW|;W*@K4jT41phvlPVwMhqMa?Wd9dgVv;qdpVeT@q8qrm-1kT@e&J1Df5#8l+{{UGb$fEwL;Z7VG9$RdBeLUF{w%#@rb*IXCqv?OL?)h7*#Otc6d8xeQX9FuI zZ@!B9^A2qnLZV}`4DZl+q?K7M;l8^X^L1ItnT79VKW>8K3os^Sha_Cv+k|M5Ga-kG^#n1@U_q_A+ZCMlD3;Ec=`9PUM~d?-}AsfRCdRZ5mu2$$N1u5*;#3wSTkbEz!fNB+ef_yd+JOD=a`5?@ESqcOKru#vL^+PmYvTGg_S=n*lS%lr^y z$(MalpvGBc+$4SP;P-9nooz#WGMrs*>;KQDsY5FQY*N!LM+e= zVk_(iSrPoew@c4tc_7u0PDdF>@J7alJ9DPNfv^jaP-7HUsF3)=n68}M*ky76Uxl&I zI=Dx@pwd0UCgl!@pFaF6Q3;UrIoMLn`w?ssa9@YZUq^Pcxfb@|lNS@St`h}YFVEP3 zmcP~WHoY&miT!MKUcgUqEC;USumyE0#&4c#Rx$9t9Df~rKf*#>k~xbqcCeb${eeFh zG3Bavm_tF&mRvnq3hy|RRdYkdZMKu6l(}XWHRYK#R{2`Nk>nSh-G_pjF{4>>;iU=d zfj|7j$mVcp+25MC~A{a!Pkuk zG?AjowU1>cF%_Rmj9h70+YI?&d` zFD)O2Yc>mF4l$`GLzsv3Iy*+~v2WW?pzR;HJt0!%6|-BQSFaFlafE-<2+>65)W<3N zVx|bcc7B1;t|Xsy)bBawO3m`D3s#cHqAN2{>W7E3!pHSZKjH(&(Zu6b=FyFSh{ZM0u`SA-J&hOM{z zppz&0n*-bI;PUq;2osGQH*=1$Af`H`BLczt`t5zE*mi-BC5*HH?_AjM-eh0C-DjF@ zPvPnAMzNelzK?`~*yA_46A!Pbc%)T2Owqlkj@OnGZA+f$xNG7MYg1Ii)Dv0g_;IsD zpr{Mh6;W`{c{?b?YDl-31HUx_Uf9{8Xm{!_KEbZ@O<BYPnkZ%xG*1w8yr|BOv{IVSIap z?RTmA2Uf?~Sy58cMw{w4$LL=bhDM~EF*RXG2gT%0 z6*lC~Tp1(u2jdsGbw+owPb+1%AT|G;`a>oQcg?gw-I1Hk2&nc>=Yyx#4uh~e%9thU zr91Ol6JHJQN&U!?V(s^sq=MUs(LyA=iA1(Opc$u3wwk^G5t(h>>yo^HYq)fi2%9U{&L$+29+1<* z2`P@P`#%Y z7>iNQc5dvq&V{gM=*816;p*L;%1q|wyt8*!;=9MGw;}!dC_Q=2leEfUfqbl1D?H;< z;;VWjx7GGzwa-y0Hbd9oWNDp|yKxKw9^A4W*->=W_!W<$MTc0As68D?H#Lo1;s<9& zHWS}w2;mN%oE7EKV(%#osTrZ8{!d5z4;2fORWaRAA62WwE6n(VuZSNQWXl*YqHl3^ z12cWL8&jDhpN0Bv>@&UWRv=Ze+!cD+&CO|2!#RI%g!|gOBT3T8F?BlGDH+c2T zY+BCemD`hq=Z1N=u+P48sb{^9UGG~_V_-NVT*J{-7+qF>RdXN(!pa=-2U|>inDPqb)Aw21n+cLrN8s5l zEQk7A3nr5XJqnoisTJ^?)uEIJT0R-A6p!}kPO9P%*y7@zthUjemLkdRE0(xQyK~7U zLV~iNhEI=T1;11$mw>)VxKBMnbz}~Gg)Zw0D<^Fy&u*JDy+aQ?fe+JHs;`2#A_|X# zxwoNjmPnW$zq{*{6y@i#G&GjAS9n#e#L;jGA?Nt`j4I&lreGh5@|w!)R$E+~Abt){ zSuyzOARJAvM>-9G???_qgcy(u!6)qIIiZ2uo*{Z}m3hIR+Z5^iF$M44n|c;^h{i-p zoa@ijjAh@%Ia9G-rK(aP>21*WeG;MQM3UgGXb!lc3#NukSE-1af%i>mGcPJk4hQ z|B-Y};hA*JHnwfsHYT<+v29!L#I|kQnb@{%+s2vme^>qNr|+s(uU+a@DN{2m0u*YV zN{qFo&U|$3SIp_M;!-T#_#3&?1MHq@wlTGL8()q30~81!cBy=wsxogTo@XDe9${PD zQW6X0L9D8+0(Sf5`qc+@=WdQ{QucxiCiB~VC55ZD-BqDU#hcSaiJh+c^EW7PSMIRp8TAFFct_?`O;J-?krm7vsCOwZ#en= z!l#+>#0tbLhob4pNLD9Y@r7>kOWanp(E;oK=0vS-K&`a5sI8)TZi+FC zHLR7P+`EEL15?MNp8L!d!KF;aKX&^v9Uqkk6*E8)r*ndX+Ggjty!Ra;c-CTaiYV!L(ZU2 ztz9YK*Wb)j*WXds*nVPFa{=z-CCSr69f{LYPwDYqy2NuVlsvj)8OGHviU{aPO5-Rr z`4}jvTXcY6oUk-a7BaH(+eCSKa|E01{CEIKSERBeqZ<1i&@(~u?9 zu7h-kSw}UY%J%RGDVxd@8Ixh`mD@=tqVf zJwhK0etcP9^*y->I{?|~3giD!UTuhjo{Ag>M+(qQ(v2)+LJPV1LjRj(iY;3}fg#V279Zy zC%PFG(%p(z!E&zYX;5_MT^T+n_p2-JM@s{_=9`5jv%J|;xru*@Wj>g@%Cezz)#Q$2` z3fa44sL2d^3=aO$BZ$nnLP~bV3(q1RoFr zrbz-FA*7g8^-D2H*cMETS`9-;X;?F_>{l>ULQQ+up&eO zOawnG1eh-b`YNkP4)yb7ocXwe35fJB>afbhz<=+!q2#fg6o(W|Mun1z=B1HH0Q8UK zWd`|-!HgL1EYJbnaMRkSw8BV_=(7g-wYyof>IOUXkI8t@zNYVEo^AQ2!`@J> z$FRMWy8P2$2RUg$7}grPMBM)bguU7+)r6u;Ts4AufKi`y%!w{jD0-?w8ry;Tg7d)g zTOh!(7MP*hpJ19)XO-h;ID%$)I3bI%M4p&H4e5r<=UoVlhOWnErs?F2&TI&ytGlBQ zHm%COlu)(b`%zNbai~bzmpPd>$mS+%-HUhtd5ws*$PhABeCvujKsFe_;lUm zDhzFHRZuM#Zrok5_@L>Zf1Oc(Gh6<^eQ@D@h}<2Se@KoWe7t?4=oa;!h`EUGOL8EH`!*fyLP9my-G>WiRzYrEt zq*mE%<^%EK=_OEPvBnKz$N>`a;Sf&y&aw*KcuHJ0D1DE3a7s3;Gao-P`_UQw&J3KQ ziM6!FZqCy8iC26AZ^UCHYKZMYe)B?~XO^dJ~ z=a7}Xo)1Jrj!axz?kf6*WneSD%I3$36{v+CB!Ta-EmJQohk21yM@|5@G$^tOfwGBR2RL6-4 zM+?8oQ>CXcIfYh;hlHo$KZ?j011rqjCoQO`MMR#MEx;QRh;rjiSFi+{6xWLs%~Dc( zl6x&rsye;E#a-)*rD4RHe{+O1v@%Q$l);csn3b$2^JRukt4*DBi~L=r`9p=M&aRp1 z`a823pt*9pxg55+yuP`d!r9V!)=u;gFLXqDmIJFfMJl5RTk#9NjG_X&%%A>`R@{s? zzWy_hM5^g$zpU}zJptKM0i-8It(MIOqnHQa6vm5Pp)w%wZgO_rjXzQX>;9@Xu+gZJ#IU;rP9`Lz+kl8Hd2Eb za8SDgLIY>Zxs?p1nOBnROvOc|)r$b!!9vKk-lIjvHs^?dUatAcg6Dlf&ks;giI|&d zDvBcxO6slozxZXxDv$|n_{R5N{1R1AU%mAU%z8s^c$sAbQZlg+l?|G?>-NfAz6cYZ z?3NcG(4B>fanzkuO}@8ArRPuXN*nAiv;`086j+iB935`)Hyc`in-xE3h;u=(3KGT7 zH!E^x!FpTB*uZ2W`&`sgbLIZ%pDG(Pvf{`4M4A5}YbxNw3XkrwxC&ir;ZNMHdjeq< z_81A~IRqnv8w-dmEp9^_2D*4f$1?sS5q)?7oe1|iyc4;>Y*e6OgFjJpNn-pXS2i6G zbIV*4VY$Dh|74$cxD_I_S41)^wE&GwE?CZjBb6Q7+p9*DuHc9& zms`?x(d~6Z+zd?0aKk$J;7hF6qR4tD@!a|3E+uFNGOoashX)ZFY0J+Tw!D5MN7|cJJU>QDBY8;^L#gOIaDLQ;+UNMs;pB%m@UboKJt1 zZa+ApI2Ncs{eT`>3Sa-T=Z)1rdosKH3oR12B8r%hg8v_f(=2eq^Q$n?y9&H)mzTNx zhz8cpv@R0i&tg4aR>}N9@Kioh6;3fZZEy8l=YAO1jI3@FQ~lIJ596iC;Po%Y(cOCQVc<&YNd2{&p`M$Iu^rZ>^N zG?0=2DP(YB70IHOY-Xi2<|9!+hi$dNIx~J4i2+Tx@^v|x$|RU5_JwNIWv^?5Jfx-; z0gw}g0S%qRE@TSnE$aj_AHRbFI`dVS@E96%aEf+V(Gf<$suQe|+23FdO*`U9`qsFk z6zx&a33@c20HY;vT9vBy!<-1$6l&B9x;Gbe6|@$>H9zXDtZbU{hr+!+S

    y&XF5Efv8!$InIFz4|9Y6*R)E`VCZf&+|s?+>>=tLM&h};mmMQ-m?lHSz4 z_h()ht*D$)V)-p?pUY}|R&mWZPBgMOE-A7YSo-^xpth>TcxRF8(YhtCuuNliy6d%! zj?Y~rUVmCYGB6ZB+?{!C_JY^bLP+w=;1KDD@m$=wV4K}E5tDf$K+lsgdqY{W6A+`e zUjO+9%s(F6_@9*o?EbNs=Pcaxp=!*_f;Xqnx-kPm_f^=s|Ubr#OF0*b^nxj7) zp%)B-}f0k-yZKd-5p=23{MBgIz8@F2NTZ4vVhrk{Q8;HK5#7$6&uFV zMqZouEoO~sGa)8Gdx=2yh|FzV%LwO-?fcEkYJ2^~OW%M@_tTG!V94GUz77DPf6eP^ zfjYxFrkWSt^K^1SQ=g0swD91glvVfRTeT*6?Uzq7Or#2REL#nV9SgPKGY601KZ_MQ)BFd?-7c z%0T>RYN0TjI%gixt<#WKTO=IN%@Q!HE)D*etlW2@vR`wzlx(DrEzD)X7PK<_QZQ(Z zD#Cr}tyDi#j)p$yX-wq9j3FFCzF4gsHl|z@HS#%a&CO}EV~Y#YpC_=}W!q zs20v1NWuJ_cJZ`*Yv(Gpk+HIfdU;#^r(!#u@X29u$}%Up|A9gLJdyz|5}M34Hv3;{awM- zY7O5A&qs+vq@fIxsTXsoAfD}Ygk&VZfSeK-tSq_9FoSw*(basEdHg=6P{ZZ|w z=O#k$&L;|Yv?5gAK`#%Q%RZ*vH=%9MG%*Rni#z7a@@$M9ikMrs9BlK`+2%Wu?>j(b zUZ4E^`U#?1Q{wdhrlm@4v;Ma%G)^uu@Yg@1e*fcCx*;n;4WXcdHV+GTP5Pv+Xx2G| zMaQs%K0psoMDRcInK_i}zZlj`ptkJ&DoHu9$V-q$a(rv`ZQ9?lfF? zJb+zLUnXkn5%ZdQcmcV|1vT_vG;lXOuK((52e7PfM=bLC_gbl;2Z{r3Q+Z_W^I2C- zDy)d%@PXWu#-?Y1G8-*qd@@%tp~=dvRyX%I6FOJk!{KQ_c_||#JWuYLrk{999#<*EUWz!8jsKm|rh4QS8OQ$$Z@>r1mkHhnCY91b=rL zioqYtD!3D8o7JU&@%L1nAyEgd)?+*N>B8Y%-4XN0301Xa(B;}H<7k$x#kzo z{br%QA(&x8rb!=}K%&C{-yDqAnox?9-;o8QLZe&dgSw3Nr=~;eq@7mJxxC+FK~deRPX8up$*W1{ zFnkfob(&U%D^LXRi}=XY5yQ$HhXkd7g>-78;22pOs#t$3TAPmQiBvZe`;(vj0;wbx zN7aDGW^W-(z&850o1zBUh~;T&v3>;K(aq2yZ&!M%cTJk1FmibwTV;B@o~L{Bkgc&7 zi=AhadZa0C-!R+`DWAjCaZVFgZW5M&pAmGD>4*KFy<2~~NgooV1PowZ8|94)RU0Q^!{u`Uul zn)&%qhB^G^)%ND;S|~B|=lezbqF<|OfZP1$#q;Cg8k?iiS{);E>Ub(DdbNq0gx+Lw z1-gFknzvEcSN98xaa^ok2f((m)Du~$uHLjgaZsZE?`F=Y^$oZDX+ZkYpj%cTJm|4e znd#2)?Sj~!$k)^h+;U&k6Vbrq$h=sRNvrVbxtY8Tnhkr~L%thR8nZkY0r0qezLqzl zpe%4m*ha`+|D3%-qrO9mi$DIL$^d?*py!Yc$G*%<$RsFiw&w*s03IezPWve{BhedZ z$$04~JREeyb~+}~gU5$)hh>97a+x9=;=#dDAI`qFVLfi=i!eWRnqL}d)=<`P)(F-N z*3h(J&GG01(uUz0EX(q0XLzQ0M!W{!2{!TwGmQ`pW6fp^XG|FlA?rEo3)k*! zka?r&&DHBFSC=j!0MF2Fupi7H&>!Ra)G;(PuDW+rJreP` zx!}(~vDZhePGC=7O>dp74K1uyOSFP+Nx1FI8GFR))DqRE0tkcsnsQ&@?N3Gu1@7Jt z4Q7z}pSBmeuvxm)YxQWoy7o(Ne+u2rZZ3S6pZ=Z}K4)KTkYF)dpbS4Jzt~=Lmg%eY z0F;FmxxLu3g?i3MeyqXS z-)0dbnZz}LfX^t9#q00j=O{P}06_Oo?PkwwMekS8?pEAJ+5^*N%Y?{b_E!nw8d&U+ z4@?=?*FBdLH0GBcKASIi)QLs$%3UF!ZBLyN1 zw%ZLu+V~0X&=#cjYUcH7;q9qQ`<;3Q8O<9FKV^&{*U1)Y?XG;@I3`f4MR15j1p}d* zE_Ks(FPz~oH^fdJ48r%$Ad1|UWe$Qanpe+b>cv{ zPSUoT09@*=jqbsS$wwgS;xvUgg|r*|(sJ6G8lNwr1N;T*8K17PBwDiE?^!I~mqz;* zCbl=SCt6++Ys$Oai*T9r4o(Odj9`h$+)RzO-2Gj6q^Z0YV*I?^;F5xsP=c7Lyp#11-AS4)oKED5Ho7*sURk4ac)k&*VAJ44kE!C7?+ zzLcHp3x1ODpld0NA#^#Z!pgEUX$I3BUzEVCmBm#;A;o z9@Y~U6fGsO2^a!-7(aQKWiQ8BYm0&BCVx}DtRG}a`(WivOqf=dsN%`&z>wJC{&2#C zCthA!umwwD-JU!4Z9F^3=FR~ghmMRF5Fo&Lx-x%Hj)9%udU9sl?z8L@HE~?T>O$`ZeE)g( z%%NkF$?TntodVOe@>9D_LN-`5>9RSKgeM6$S(^M7Kjyb-$f9OBOzNP&3Biv$fyui? zQy%Z+-v`xyHm5^D;>c`7?}M-aFi@RfzirpM_g?o}8L9YBe75b^v#iW=>Cc5qA`A1W)nv$k^UJ)nysA750QY5%6whtr_ zx?#X$+)B`@QOBiL11(Pqser%>Tuf_4KmVt3Ld;#1oaAPl^N8$V-|Uug1Ny$h zd3Oaw|K@vbVR~)`KrjC8A!O6er6ab7Q_I;^$8pV5K89>mm;oKFK|AEf&`w+`CByNE zB=QK{cio@GYBoM!#j*EGqbed^%5^?XGEnj~beT@5k&HOU3Bhud2MMS#rC&>7zF?zW z2bGj8eGpt+gpD4Si8kEqx6m_%kQ13#m6pPodc?xO(m1#P;L!b@!&>)xNl!7O z&_z_b#n}7IjjLiuZi9=g(R-Aetq`34<*@H^I!(iIGm8FW3~}~7rdev7WJ9Mo{8Qh_ zSvMI>vuvlMx^8U$8Gy?w(QNjmiYh|=83ogyRXc-uT_3!&Dex!b{O`iOY=biQh78|Y-@Pfnwpi{X7y<|IR6LQDrG{x5dcsHd@ zVS44l-`Y7>A97Ue=upm~4I=Gp^5CLZz|>B5q|ZAGCGbhf&*aODYT| zUnw2z$+&~>-f6Ppi2Y4|Q49@Ma8n7%Y#;{!7Iblh_6q*E>X+o1tWKm(ow$i$R>w57 zTF?y&cWwGf82|;e4SNQe8CTNPY@#~<3hNHZeMQB4e+a>F4!z;%noFYme3Cqzyn8@x z9k`y+}6r2i|``*v=|7(sqbW~N$K)l;Vqp#PL!i9RNy+k#t&@#lQLxcV?668sqwJ?NUzORjPxRwaS7EcK>ZuK_SyB z$OJv(sk&7oAK_D{{T=a3nS5E#f^G^Az;OwihFlRhbdzvS|$KQLGPn(jgoy4f4$>f0bww_w?AQY?F-$`L?k zC_ZLxn-)PTzGts|`A-6V0{V#`5DJo;cM|pI1m{C9?_U3+uGfOj!RF4|!(T>-^u3B8 zy3y_r^N;`&q=-e`M#YYZMwRXnC%lMa8!?;1xih-9v3LP3G^=GeZa>$`NC!B&yh>&= z3*Zlvl7RCT7@SZHG2Sw|=|+K1G>UNvF)2iS;A}vVJs+=njJxL*dJ^v>0HDqN`&;Z3 zldzYw6B2*{E^rAZC~pw7^8W zKm=T6=534GdcE16(R9H8U|!R3Da}VorZV@L`#Lvv)X}1u9Zd1=nry}vpMye)4DGqM zhVO6KL9mF9Lp?EeTP#X%VIgoW^iw{o|Sr?Qdr04IY{ddThsb%STmfOJ?dx|IeEEW?M#U{Zpnah zihUE>V;9dG-g<&*EbxH9;c@}O@rUr^MSfTAl(pG0cR2PJ2MZPT&_?M7W@xdEx6Tg& zRFpv{{*6KjkdoQ~kR+fb_0927(bJWh1cR}9Twqm&3HBXg<1fiOLIqo5W7|v0t(Ze0 zW6Xg^i}pXy^s>6!pY^G&7m$w@urIgMuQuIT+#&k>%r55=t`J&VS4o>&nC!6_D&bOZ zgN?;9-ET6wuO79LM?vO5rjdW5a=xrwma@iB$p%^IYPcldbMa7+bP-!0i6Evo>l zuF{EAWChvBt9CmWexuR2!JrpZ_xxu7Yxa93a2IvcR3JpEHxq%tWDPoXkUc!tTiX&w z5)qBk%GdY+k2ozx{?n;9A!2s`x+y{CIt!UrT6PW4u!hxSegIxx8X%MMqM!Ru1R(yJ z`^{>Xa2E4bL0|cB;hTwoKiyY%w}}VFnfmvg+Y|z^rYDGir`N^Gd)4|N%z6;5`C7P< zZ*l(QX*ih$EWmTJdm`;PyG^nC;x>GJmK)8ln~K>AUQFPu2PgdYF;0si5;>?UBE5&r zOF{%-Y3I4-7D2ht#9$W!TWj!rh7SmIAK(oE7J>Ma;&e1!dCq}I>9V{K4emYD|kw&n;=_IUNR>M)Wva;lg zUW;=K^#ZNmL{ksnw+SkQ9f|-9A1|57eW?ThH4aCMx0{_A+sMH5q2l;Q=WqW=5rvzB z6`oO+)0vLbinx>-*)znrsg}-x7@$}3#+nH(J{$TL_R&52n6RRTyUAW=>7BiPt}nm% zPL7RaTW>#+eiHs9-dBAScwrwQO4Zh_fv*&z+p%}HQ(9W>7t=tieD7I(lEHm6N2@3R zX2^-t=;nYU$V$hNWVes%rcxs-Pi0diPj{uhZCwO1fkrsMxFB#Pm69MY^jm^e{xLU} z1MngY)U1{k;GTN0g-m+{YkBevKD-Izy$k_^zfa=lH9K#bgn{}YS%U4ykKjte(b6Tc zX4$%IZN>z)V>u=UucB@sZQT=EhgDtodTHyS9c9V%Ez zKQoG^Csn@X$m-BZY?qhn(@7in0r%DW+iqfA-M^AgJ!`k%opK(_h3)?owvJ&JwL##z z=nnHJ;9BtJbb+A1VcD9FQMp{55e?gA)2t-6cv8vI`1?Kz&g&2=AoQ7as)iC^ZnX`{ z&?~a|Ev^z=_a5gR=bp2mQP3<(x%rI8gvmY^QQ)cR+;}qPlRQzcGJ|Csk! zmn0NeGBtw_*jDfd%@s;@ufo4(!H?DCiku9(pnQX|iNkFPd6&tSAIu*tvM#3PiYwER zB))ICT37lYhG4fSVNj-t`TYTCU(sRaWYhVwj+UgAOF6nO*oM>}X&5L(Erqm^&yz2y zF3%#C%|K7WlCzEq%Af9rMZ7==z$VRz6D!|55=>ROL8~oRB1`3KV3xtF$#<|~N{t%9 zWnj?*#Xs5FC_OV7gE7}F1{Yw~Ep>u@Nm_!&l|lL3N`qoi!OTuZF1!UCa;H7a-bZ{@ zsi?PvYV&8&O}bX);98lN>|!OmRJglrK$aP!n1fRcE4S@_ady@h-2D)CM(8mK--< zrz3nZ?tNaxE`5@8;Cu%r4IB81^55UDOpxQ_!ry77`}t^AP|zVHIm!DI!6-$XkX1 z+3v}&5#A;2Qy16j5Jt8{b}}A};)cVzF35TGtLM=Vo|G>CBmnA;Z<)tSDAcqr610Ls zvr2o+!P1Ao60^G3rbMXu45G&U{oj_d@eMW3O{f9n`t5QGi)WW>$RKFrataY!IFy@2 zG$SRJ{be=c7>t9*Mdl8Pz2A<+S*TuL}R_&&jda^N7Ka zw$C()wbj@Ug1W2i;Hx_kM6zqNT&5hZ!^?65DTRhEEtwvSAVczf9GRB6;SITcx|pap z_Go|y}o;7_6OnfJ>hEWXGK-%cIUNb>v5o__w&c6_4rjWDmS@{}?sy z?@+Id{oMl}!q-Fou<;inwbT9;dPfCde+u&YL>05&rZ&-d=McmPaRb)lOgj0&0Gr;DD ztGTYJr)hWXQBa3q^_)!sg;Nsk-L9J9f{D4QdAQ0MyB}COu2ak?P14aZtdld{5gGv7 zlD}e@yIJ(Ab&-&^5{|75=ZIYMNvJz@#E03-RxyN1>5>+4*v|kbn!Wg{?Mw^tfKGOH zV$w69Kd_X>O=)TYDs+`f9g0l(cR&mY?NKH4w&+S-qkm~#u8NMHF# zKv8%n&}$}BfvOznEN+yjqL@Uwb=zQ(a#=CA+R}Df-T9jJ(d!p=K&>$LCyZQTUS~zS zQNPYSErs5|@=m|Ivs~aqwywC}TbW(=%~`;mvw--@b(JoLHi1ivG%-^AwpOL4UGh++ zNNX%v@S@>VNTs!DFJ4}FmH}kQGY}?It*J@zvkQ3A{2|X8;PGx8=a7-eo8f+Y5AXrL zVIhE8XG{qrdad^+`V-AH!@CP_$Gq~*nII7_@jd)78nZZu+iVf2xD$2~kTD!%O_{=s zHmv7jq^&~voUp67!9)CR#dRKGwg7+!b9(uOGy$JrQl;)%&|}K|GAbm0ntV_)>PQ2yjMHIwW`;yI*&Zl&0^vW1YYELRrHNEU z{q6Vfxj@h!`x|d|2=KTwLURuuRR7jqFW>eNqvjnoTxpvP$#r(tE^BBq-15aV4?;`N zXt`_oQgPAh(fyV1k>hFHuTm{&Q#RE2Zy9nH`1QH{Ipe|xEl$Klu-wK0Xw!|k|8GQB zCC&6XnB?4)eC0kV=mh0Ut7A*hIS8>%k=hGVUuEopq7VR%6z~ zNY3AI=S*G%4(nD?8Q54pj_!u-!pV=T;NqdRWPx=_v1Lgfjd~sGd79LBjU+G?Q-;a~4C;$N-PfhRmPfd z#?A*PB9PI(*-)QvA1uO<-Kfj=kGI{x0~t%&)XyX3BY;0@DcH&2USf~mm3f#XRS_z1pY|>=Q)|)vUY%gY4c@Mb<**wPHHls(fbH2v6 z-U}rq+VyrZ_hL&;tc|GVi48~D=PNrx}%h{@%z77k^KgoW>%Q?QOa6O5>g zqWw4nxk28k!@iSH?`NIVokl%atC4=XbYd*DrwV|~o%j)XRP>VP6j(p76!J2t_0vVJ z$>Tun@0R(@i+c_5i^Vx~t_`a{$)}-)<4(v)6aS7yB8;;v#a&+)c+#jrX)Mb?U ztg|mIbUS=%5b;8-xFdAR?}p9MyD~cfipD@o_>{qh?g`()b3)lZtC-nSI>_)4p2p?N zv0p=@b$y_Sg5(JNZkWNP4fJ^y8%Iel0{@AQ99>`FO(sl`sNLb)7q)-<^(wk&TDSkI~*;nqKGTM@;ve0NwL^i2} zwnS@;L1rp#j44&=Nq@6lU*Hfos7GCM4fnqNIvS&$r_hLoKeir2&uxaD)W!W&cgqMhs)#`juM5gdj1_^{k0?0qmRi z2hi01>|kv4`}TabZ1>63G1RiD@nY`0UF7CQtaeQi!y7BK*NzS7e6`jgNLLv2)g5uW zZJU8BTM@UOn}L))eLf<*|8X-&R7hj9J~4lvTL)mx0;6F4KqMykD9){vT?0AYAPP1)njY%~l~%E}Slq zDHmL}A2~tfk4J07QBjdM4*3Cr{$bO&6R|L)URee(p_N3q;?_Y9M4%+u~xI5#O^g*$=ZQmO<96qfAaHM|qqwV|IA>1dRsp)~ZC`@f;lOD-nI`&e-%2 zm=JzZ(d;7IoBC_EV@-}?-}cwX)egU2hu1wV4Xib-g)RYdDq}?jvMT11x|-s7z$}W9 z-mlZmqkz1OxPOh)$8UgO*UQQE)%8~G-WFr-miJrGuF2(h-C*0}DVQ`PMFmUbff1Nv z`5rWM5_8}mdhMTYH6JgR&z)^)*w`DN$X1MgfX_?Kpsumw&{N10<962tA2)PjgM)`? z@*UwZvPar1|20xCNY_C<$;j8;JqKdL)>+6!56zL*mhCK}Wcqrk-nJVYQ+bp*& zNKa&IhZOhd`#Nn2x7;bueYzS?U2=Ll>p5!}4`FFbWPd68?)@bOP4v(A)Qr zr~ijB$=CeN)Gk%T1qV45dj!W0_tpT*W%mad&8{{G6j3G+ENCF8Tn7jUS_~@ee{&nDAHuatF2@nc+|4o5OS>n6G@~{SZd%> zx!xsWdFuX_@b^LzC310eSiPzcm(q1U(zcC86`>J9*OvxKD20_e>@a5L5%)+heLe?Y~>QlI(cY*bJ!~%`%rl|^0 z(;9OGVkbT8SpQTrcyu}e5tqbY-sv@rx17&6D94bQShr$j$a<{dHDBP9e#8bHk=QA1$>N~nqhw1R-}<9Un} z>lCD6%Y(z1iwgaajU~@fNrn~s6=993e1sQ%$;7`hF_TE>$6;9QLxG9DOU^KbG$`f( zF-!j%4gw!mBnXHBF{V19lqE zU^hp%rmQ*m%@pu-=Gv&U^ zExNJw*TDEpPG_({Lbo~rSG=P0;sp7)!EvI%WcXZcn$SZ4bj$92h?3HxBZ77S7(vv} z_0`+$PUA(lzHN89y!nJ3@5#lO)z%l}z@1%Jn%#2anQ3!*sXe99`x2=~zM`rnEQNPtGjAG0dw~pOjO6iiAeKD_%}2!=Y1b;M;q}g;!^pCtWWn z?+H$gis!%fsj33?$e7>n+s$Zk)grHPaE9HTJ?%Eq>W2_*2Py8&*c0XSi8`Gk_TQAj z3BnFS&-v_#xAvvKnaX9_Fv&~F`yk{at3jOF)Q?F@o1X@Mi6GDRl78AjL=-117~Puw zX-83~B59Sr@s}P!F9>D?X&P*{z~%;r;?1fv31)f#OfWT>{9T}-0JMTu@TSsO58g)w`o;lrV?@Zsyy|sg1CN3uvYH){os)~ zwVr6?>ATv_l>Bsid@V%obPH%NN4ol|=&D|sIc=*?m~n9DuGsE8awe{b8naezcrHCZ zu0cEksDF?y>HFTjc`uITI(l^w1l9t{(?C+MbvN>iquHr_)9)zpBz8d{XY}J43-lBG>Ld}zUp6_(_dC33-|wYT>snZF{rOv zx#HT`Hth?E@nTbOdcD-3WfS)dH^2wj_63=t#4(|Ou|!e^9>+!U>ml^&v`S%D`-sZS z`D}bw6r3K}^IB#|VbA;ni)nDiXgL}A4KZWEVPDa*kw@(YsA_vS=@=Z*4#9Ik{v?tE zNK~0nxrp!tQV8=Z_R^<4^E&;qQWlm&MjrxWna7kAJcB(9vM3FMafH(ha|=(%KM5(2 zpfBrrW(!bTln53j=)+!T;g>jm=4Fw{T{l$F4_!DN9Vx|t`P$K6+6YT6M9r^Ki8d!@2Jal}98rh{Ty-R^c8pF#@l)_&k8&I|~eVD_t z?qk8S-b=wYBF#5T?jKYgvijr=|`V}{z(OWmq^y<3(sDuVueeh6AP2T5lGekEt=vE z1;ZYv2rR@;aQq`(z%QlE+Vo<^rru-?3D|=M{?!y|up}vJx}i>Sg)dqDH~)*zn(OL~ zn_x==A(>2gj-2%YrR|E&@2$m4kNP{JSJy=G75|>KLL_pKJb^NbZ>j&}BqZm{$>Vz#nLV*KeiFJU|0f zLNE;R4{6F@mw*BOegQgT@NG$qzobP)8g$Vwft)Y~I9n3T+qmdg%ZBB3x8fns$Y+Bf z+fp(j7tFC{Rh%?Z>s|X{q%J{>1&MI4WU)-MaZpzl2xG&h(qRVgo1vDkydl`7qOW? z96rmwT;GZi$T0Z8+E6G6k<)m@25l-L9cSRBuwu(?phAX1JpDm%@mNS@Wq{wzJIBBE zeRb3&x8j~^?5^(|2FFrTz$O(-z!Yp3efQdK zVaY-Ue_a&?qq$Vd$^H+CKz6@e7f9aakj2nuQ#;ae#4bJiAr%lO01 zrk|{;^#+0Rx~}H^bv^H98{Tx&x}7eozTWiHrk&TH_;vqbIij{BzW}~Rq!~&y8RYcmv zq_H+2ACY=I<9H*(9ie=b@=?k3Zr>5U$c)@|JYZl^+B`szU?Wu&!-ylTcVMek`XuZ_ zpwN-RZAPY^v>6i)H)|t*)#&MRwiP9yI}kg@MaLt;?4uZWd-(p#kMDka`ReO;$wYtZ z+HPNy@tHb+D8|+ScpINC1b7(B>8b!g>F4hI^OrwWt6S`;IKT?=r*m!c(+?I0sL##j zu^Q!d)!r*n9ub1UYNDhw@F7Wnr!mj~CI4dB`l8!X!GdGcADa1pW~fLTN*buDo~}rD zhX+!MePPv`YE3-EBXKClH`Suv45$C}>kN8Bzc(4KHeX%7`g{%fI%q`5B@!W*iqH>D z(x3-$)gEmos?9xMm_>L9m>CGt&r61D252%slL49x&}4un1GHJ|iI&YEZKi26O`B=j zOw(qXHq*43W;O$V`bEk8NgjwKe;kL-8Gp=jx-)6{(4<`k>M~H5fw~OTWuPvP_(xI)Gi@;pPP z7c#w&>4i)$gh%ja4ath}H2wn`w?yc-DM@abr7=$}W~hgMWYrU7?Jcx{Sk}p`hSA+O z)SWSZhSPCp?k-<_zGj$W;4u9VXt>G)PUV6p7xiJm6M4>D@Z__A4l15f=Y7S~P=htp z6w13LPgEl}kRrK8@DCO|DRC*RfY5|PyTU*7 zc)`>E00uPzBBGZXJsdWdAtehKmuNj4AAfCc+_(|`-e19w2?|r>@cnQI;3Un(Xs-?8 zqzClS4_dFX)@3a%cD3jF-}f1b>o{+|tmxnptR+zt`EX`9^9;$Pyig*kAhhRe6b8Sf zlCaK+q?Pc>;;Kb(8dnlAC0vcr${O5Qp~>-$6WS`mjThPlzCoLTxREGyQhbvHDSwAo zqy!P6J^aW-G)N@SjK_@;+A_>~bZ1ax7oaEvZl2f48j(0`UEh=ied!@b)mycdB6{K*C@?U1 z)Qddsgx4`efcFrD!YGsXtavU7tXIJBk=4mJtOoR)SR#fc#&8Y4=huc227eZf6|XWAWsPsGj!QWwRB( zVlwdm|BC9__@MD04=+W9rhi`J8? zX1qV`x_&@Mckn$Ik6ym(`vET+N$&B8_^19&e-9pgc=!m9_9S5+)&;2(CZ=~%LE+X1 zNifFQn0x^y3wgjwt#uL;9P*N^O3XG%P~dTpcKgK+t+st9wZu>hV1F5}q{rkm-bgla z6Zq$)hYtTlP{KGZHBWYuDQWg)GH9Bwx=;Xzpe%za2`?@Ud^b5I4aWyOI{j^!p4PkO zMc)m0`SQho&ffm@?PA{z`=9%+KY7}(muEx0ZZCkk*fj{g1Dk4 za6I^JyBYfJ=)Xqjx1+=NT!)83UmDSuv>uC`h?WWtRwtMCJerT6gm&_L!q=qGG=Os@Tm!!r#MwFHo0qQuU@7mRV z3#@?3bGbx>#zf3o&>scog76FHBAEbb4F?nSF~GhUyp}Z^;=6X+Eb8@IcFj=bK(?!{ z>h1ewf8EUpXMfs7#0@4963T|cNg9s5BoVG>d!SU}fii?>q-SENoODb>@aX(QTcRof z3WN@tg#;rA3ME7r&>x><0JkjGchhXPa#gSTb#uLY-^z>rDi>~+?`H892a{yRB|$iu zs=}kE**Z2QqB~%K1fgQB6ub{OH*`$SeizZrm>E$^Lw^UUktVpcX8l*;Gme9oJe{J;h`LI zH05^o+kSHc$Fi;$a@*9);j&rw7dzSZRnt|wpq_SfG zHVIA!0fbi%W(%%pZe$QPCFx*t2y8MS(RB*XN2eX1&=p$%41As!S~&Ia%%%`@g9?Ze z$kDVe!{v&69OkIH^}3j;9Q^0G-9L){u4GEUr+@HLi^EKa7WsD^U5ksLq3T#?oH5E0 zJW!nTi~~*=UW1L^!0dohrI~O_3}3US@ZlB@?2O=w%K(+EN$6mqC^`V*=&3>~1Z0Z< zdAKQ_g1BZx7MY*{fpp0}u&q;(GLr+RrICQRz-ggHYy#yaFSVhv2w%jA;8uC5&?e?; zynh}HpdQ`>0GX3NuncWsB%qNULEVV!CWdj*ht=)fT#r$du_6ZX;=Gmc`xYqR{|T&v zj&`(nGz!}-nx;roG$DRt0z_Um^t`bE0hwbVWjs{mRE_l`Q`ERB@En62kGBD|!#GRG zSdrs!EFb@Yi~)?-VGbF)V@X9RJA5jyb$?jRt_#*gPV%fYnBB+c><v;k2ax7dIw z{E6#nDoA4Eh6N#0il&*vS=hYf^9Yd^eD8aWVxq7qG-<=shxyf;Mm&@sEjjcE9f01r#N z#1cjl8#rlF(Dj4Mw20h-R1os>15i!|#@+ny0JLa(NrUb19`OMvlOnHY0?mO!mq`xR z=$VDX-`Q!$Bl7V9OdLMZFpqV_vVR3N4i9k28j%8WQbCUq)g8ynzPQkm*H?Hg`LI4( z4NZM<*>K!Zps@^v5t7gBg_sbJfq?A^Ay75NIi{0-tR<{EDrsm@w zpavFp0FpPJ`XD4jdVUP_MOj1!;lN!vBZKcmYDkzx{%EWG$ffHtx{yffXn)5=nUD}` zERE}!CL{#?SZoZ}*VpC8A)J+b%!9~+d`^4nyxyvg%f7xJK7X6Fjv?F8%&hejYE$HM zka#I=`5=+xLsi-$o#tmu0{bmng};tRuXxLtPhL$|pRXZbW4@+oL!G~&X@{K8T}@ZY zSCg-~O>+4g9{RI>-wlF9^?&zv$y@Yps^sEfqy81V1ZpH@?(V<8s#nb}W2KCZGB(QC zXu`(Fwr(++jLpzz82l{;pMi(zL!a9V^cg1l8YYv+Z1R{*mZQm7O}Iw}e)`D!Py5SA zzSLj5r@cIm&+*^WUY4D`BRi`<>%)EMW5OIJ%;6xi^z9E+)De@*>U9~L%h+7J$IN0L+~GR4p_Pf> zE;N@1olmFmS-g7&e=xpJ+mByu|1cHO-F8p;Tn$EohN{!wSHHB&;c_~8!be=10qUQs zSI_Fr%cfmj=E~EFoPR-_fI*7t#kyYYI5d-X)A^I9Py7D?=Lx~PpYXv*ANjQ5=;HYO zi+0@*TF-E~=%4jf^G647rt4|9S~qAGIL?RW>fd4naX#Fjlt=Zd?)n{W75^i(P*K6@ zD3ALZKl@~K#2*gJ+&N(bS^XbaOU!j;Ze(+Ga%Ev{3T19&Ztk>~1y-WRtrT9~>CW z)EN(D51Vkm{+`y%;K4SI%{X-l6?Tsr=-zlk(4}N1dU``D zW~B;L(#)!uN`_hEB9$z&PN$M%Hi-1pGaFs%B`}9cQziIOrU1_ai$9Z!o{#X&KdR{K|I1%FLs)Yq$g zdOj&`s&bOnkzmIx`)$xP0_g1I_H%W2le6p;pAui?`*DH(a@ICKO^<6}ABv0WYRW$0 z$>V}I>Lrm8czU>_ z>FL2}Fq|?|L)qIazXHY%mVX!9QKUqfJ|rs>tb}rp0z?`B*o{=vtpFPKz%(y zs(CxO&c7k|qiQfJ&UeSdQI7YrlPbSH!~&^Hf2Gn)R2{iD6P;=I&;665U*B$9yHU(( zS7Pn2P;c9QWA#G8Npj!%vp%G6hs9*zZXRuiWt7^%^DJ*+oLXbN2Y+wCcl{717UxZD zrSf~4*e;{bSM1sO)!?SeCtPZvIbqrB^0Y)F7-2cN$S3y-#ys}%L$*H-0fA-5`FTaP z!Er(HGb*kS@szTh;+PVadxXKWj&=Q3jQ`VO+Z~U~Y5~&p_VX0|7Uh^nZn*3LOcM|| zdSe_nk-{!~ixZsu@qcEZ?&T!XB6wl04{rmLb?a9fD)BNM>yGeeUPpB#BM{QEUKJ0mYIPn?|d#kkBV|Q8Qfgm{Zw3- z&;zOuJc68R6@Pgo#^^cmYi%^vwb~HqWih;+04k7@6n!5F%E+A|PbatoaZzwC8n&z? z9GCa&0Xz0}8j+0SIM(??NA)u^J~}--dh_PR<&M}9YZ3s^*hNbeY8`&JEZnzT&7@Fl zg1qNzVkuj*FsDu^t$$*~le}WjvQ(K}7Juj2WqCWv%71a5O^dHt^`*@In@`H;ov<52 z8+DzvE_srNZ^vGeBgP@ij>3)1oB=8}DECPu?= z>OyTlmL?JCksTYjDv-4R=0V#aBEVIdem*qxib7zGfp#+xbQEouz@=)ahHEW1coX?td)lu1gpB4;8yna`7E3${**#eYI#y!wxFr)?};onjAAm^PCN$akzn zW)^GxX{BlZifI`cZGrt*d6blLegUtviLK@8uaEw9@aAyqmM6tVTQO3aCnf7z__^H} zitq-Krx-6*MEL)YlJ$a@UM2o*Wy{;--k`8XgL{KH(l)8qfqUZKQuAQ-kHozdWzQ;Y z&3|z1XuI2T0}5%P$QSIEp(@))s2=*K{jLTo z*@O6QNKGH1dZ-`q+1S7hZF&a_GXQXs_0#uuJeH8`CBVo%QbGg1U?~?=mMcYjJ&MB) zHUS0*?~jk_k7rj^bu;}b%f5X1!iVEqUVl!8*|fZ@zJP0H!|5oyD9^L2>UxwtUx8Tw zwOq_%C6`E4w6>gFSa95iI_vhEuK2^tvaIkR=eo~|X&~sxtu_plFw!;vej&qpGN4}0 zCSX0#Ns5wb>4F(@M+Ze3zk_|cy-5j!>$MKx_9UGNq9^aMVnLj}jcK=2>!)rg_J2{H z*J&Ry)SDo%C@$!f5{|^metbUm+2yp7)7hZ00`h`6g}?>mW}HqM-E?R1WN+`_il;9kN110+gGvMFlp0zqoi$nM_qJuyxw7#N@uP0 z=j_0XZZcTnJ!$8~0Etzz6iyjJMt>>Xl9UgQ>xW6*w3@fSm6owBR^N$Sz5Jd*PC&aW zw6miP9jBzDer}%}Nll;ACeSn|D4_t+be_QrlUaCfH)m~i2>oZj^CrY4g|MluOZ!dI z81x69=)mK&d3s=nz99DsC0sPk|LgIvmp*Q=l25KE#$bUXviX2N>^PPaIUb!{s8)^R@Dv}xPz86&8i>U{sfVQLlD3QU2^`U-B zHw7sc(M7@fyXK2$X&U?GEq}rwBI2*bMLNFrO{4Y@`yCxjAc}?u+raMz!+hHI@0v3@mc|SVGjkUU9+ZyZVh7NK0(6g>>r)Sx8Qv;FBrenG;_psY^zi#=I z(iO-0HQ`nWOG@925*IsHk9ICwjIy0`vk90kKsJRIfNTZSjzzmd^M8;!0#Hros_9a- z9hta^0NNR)A4;qef@*-NB?Gue2WW6M1GIure%0J`BMaRq*R;yD8!1>?c)~H(}(%t3I z5Nr?EknR56oE$o1>uf71IX!7o(;59vjqlkvk%0Cn{2}`eUa=kN!LGCobPvnVore3c zuyOwFt1(M>_FrI`iPy-Ys*F*g2*ZYa~`0ztlqC%9+_a3 zQDg!ua!ClM*pLujIq!rBDwrrlRMC4OlFI!(86RaSf{A0fE8;?s4->7TY^_kNEcqam zQV7PirIV7nsGN=E*`%DaA~$8&D(V`ra*^a}CgoDUW|cQ2{4y&K1eYu*HPgxwBGu-GPjf_!&z#bH-U_*adv!FyPGOPm2vt%47(EvUM z1(Bc-3F)n5}lm9`Bt_ zNLPk_o{@whVLctL7}#o_pcuKV1A>dKtSxd98&tFGF(??3+6OBJhfh;1vSvn+NiYyw z$y%?ild=+ZLb=;hu|X?j$CT_cStrS1L@^_Z*0T;t3TD!N?+7yr>oi3pf>*HT zJY|3FCE>l-vd=xUmNL7aMt`*Pn{}gS&`X>}W=i}_)Kcvknw2W(tj?UvPRJ+$AEeo{ zdegjEEjv|x`{wkw)3Z-c7tMU#ysKZ=%gxEFW`47%*Q)wzIa^({%ekuFw9C`wroCHu z(XKb$^Gnw=~0eMCa}alyXNBnK3Umvj+BMG`#A0eSOxn z^UDrS!#$OFQ7)daTz#>q=NsjEhdg_>`WwzTacCDOR^R}Y{$E&^J6_aR?c$w!GDd$> zNjRSl*V;vct^@c|{47g9)K|@aWWdX=UbM5*<$TfLx$1S-T%D;jP`?)HE@E35u#;y$ zeRKBRo9{nOs`Q*GkU$m?Fy1swDeD_&X~I0gz6@dl%38Uf-2$b(jz(K_*+;4pg>0F+642~`RjGYx++zy^z6 zz>tTg5>3%3k&YMxvBv-t(Ypb9pjQ%O3#eB(_8|1*_ijU+ZY*Bzs&j3__nv7zWWb#EkWvV&2m?7>w z31TrgM2=+!Hx}U&U&#n=(Jc8G~3U{=6H!v#Ia z87iS9$=ogQVgEDKtv)wp4y7b}43!&LD;OYAc*`Tt5zD|w0iu5tW%TUF7nG-Rm>QhQ zp(NJ_DfE1Gv+Uq!uc~j`3poo(xj$JcFC7ZuOn<6??Bznd9a;TY&zp^~Dk1Bid%MNg z-f|`HdLBNEEPezATFSwQkK0Ex|K`~XEN|g@=D+uE;)d0*D{@PwjGVnGL?bb-SbI;8 z(eC?d+_Cms)}(*IBWCy>eP;4~^W8oh+TQOEk9t_`(vKQJ(ITg%xHg)y!d@2C9)s)NB^+Aa2OWi zK6a08lXuDkF*s1(C=bNwh5Wb|23C33@z%aqfjoL4Z+l@d?_o*S@L;pwOVXI6c{fSZ zmTTqJZSTrKC9-27W49Y&WBzNu(KhcfOhZ-^rLiQX-M|f%{XJ4-b<}22`J)^Te=#v2K0XR_baG{3Z3=kW&01}5 z+c*;bzQ2MWTP#eG!}rCaK+;|>*=u{$4BYU-n%onFi;f#n1f#i;L<|WHi=iraS^g7q ziv%X+e>r(R+w@^}-}GUk5Od25oyc-42vUK#6$KG_ZY4p^@fuDE3W84fB9jwlJL#UK?(1O?*=Wr&m$nTk6C}g z2%qvA!HUqBA~@D}9_!IEtd|f(uquy*H7qfDm?AjE5<#)SWj#af0bsaAXc5mBjR+y* zi&!JDp)?E|LPi>~Ml_57<`2>4`LISZyjsK>Dcb`Iiz=^?G+G&HA`x{)3f0AIWSuNp ze_2Y16{#8PMKm_|1+;vgC5mWOZo#cAl%olk(eYh^2+^C|hc$e27i$Ebg_IRZ>G;FX zKa1i(@ZT5W$4rlXGH5Y%t<@xucD4yd&cNa&Z zI2Of8HC&?CK&YT)GVCu-I$j@_Fd3daf4w?e-dt9qcvVk7i{f2wA55_-*0~F3f$8em zRAP!AXi|_cg0Ml7hQ!8tiVTpd3UO6O=UA@=jZcfcyW$ zWwk^IwjoKk(w0p|Dz~cz*MgJpr70|qjc3V7&Xq=cXpA=`t|RTQDj1-bs*t(h*GPmx zS|$zAO5)ssc@6EatI#W0IT@HSe~``l5Qzr5!nLso3Z|c1**?HX%gD5afX^{Qg15tj z(kruPP}kH4kHa*=c4$>bT}K;)3GSt*VBXPqQ32TSCC(sR=}G;9gFAXeAbP3qZrUS6Kx{8W!(AEXIU0B&G3kfBI4 zirE5kANCvvs=bp-A5hR5Dj@PvB9nj_K!M10qTapnao*^ea>hc})%KKL*zrQ;D@x$@E)7Rzld~i6Mj0VRe#KL-c zGdSuZDU1e>*c#qhnHnSlg8)R@R{8*D8>cm)2 zdd=AaKmIiq(U0Fm8Bvy61CE7AMhZ+-a{`6+ecIL9M{j<4`|ImRXAxe1!6KaB$|73- z*_A~gOtq}we=dvQ6GY_tkTZU;-$%xG;meG_Rrx(L{;i3hpL}?I^78RbY`!otN|UWN z_G(Y2_&xqwa7|0$JMpaarDtum`J-@2#IN5@j+;ME&X>!}#ZN^su9xRmXL2~ZD8}V@ zHmR-`#j+}g=WwXOs9cuCyu2~WfudgP%7f#)Nn zfcPr|zy*-%o!R0e9wc!cVvu^Yb&_8R89uc^p#^#(!)|QA`Hpf-bfQkn7}Vmzq$P(y5RwF9u9cN3 z`n|o;^{EzG49Q7;2^BO-1gKE)A$ormUSD6!t0s$O4WgKsFBiogIz!>$_!UfdR?YRy z&gayBFGgoqWxYm`taRA3tY5QiuT!%Y1RtF{e@=~*^6MFgy|VL3`qz#cdifw}BbgOZ zvQqhgU9F{2)YQ`S4Rsh7Ql?>5`Q>`9sImahXIG#PU=shTM~h~ue3!KA>aMrQH+V*K z0A8b6Z_9DDSWWIW=5%XwhIY<|O#priC92Iu)WeJTPJ*ya0%|3oO$kDLc=Fgyp0K@&9x&vy!NK8{MwwM6R4HYc3Mw* zCkeY@cB`>kv8fYuU4-!9viFH-9nH zO60nR?;0y%#8mOQ0Qr=f9_U* z{C&}Y-%t^M359Cet}4J><%KqOtyOvVAB){n-l3?A+`2&*3-h*|&K77Y{((^yf1R`T z^DHO7hl)Ucxedet8;U3&I>+1*hU}Wr zaG8{_sCu<+G<{my%i>5|>A093z*ZM;jQIf@B;Ye@$;2HxRw|SMZn| zLXk7%3>gFg(iCWl_E040DagSeimfKG1X+fWf8RIMuA@S>5iJD-h9&NjA|L1T4H+q9 z7hI$uE~;2V9aFYOajCYh>VzvAF*q&78qrm@F_Byhg{@^DoUDZpE;d!fkepk~W+$~4 zK8m(+#ZjPWt?KY^e=Q1*xXp(S%1qWGM^bDxVn>DBxa6o70|%%a$8ba&MXmNWdXo+D4AdOAVm_TEbTCPqFWF%}s zsc8^{l^X&fw5p90cAA>b1#9GBm?2`#4ZUCu;r0uxq0OcQYbYBQ!5Ssle$}js41r>e z((FpHMs2cJf2>g(Dr{P7vjfepgoX+hTY|J%)Rma^mlrSG?3J_6cW(C2+dsA+PcAo` z)%Ek)?0i07t^LKx#q!Ji_WJX}pDn)*FIVTEp1PMW-R#%p`h322AK(}E_tDK>w+D#J z9^SYaW_>$9+u&{F>gsB_ z!D>5re{)aXd|ECy=$QLVPumWDU%p>H0xFIV{|7aKAo0!OO7RsY1oQP;;~}7aScr#< zj;eUXfLM!9=DV4Ff@Tq1ys3GzjlK&9xVnkA7Z z3(YBGmxK%e-=qUEUEiEuW7@^?$`{YR50`pDq)It^gjPg(Pc5VPh-f|;R`$uq4p^o7 zVtG{IZwfz5!7CydA$Vkj?E|f90qqT@HLJBge>+{AepxIp)+ejWZ_gL!T@C;;;Ik1A z7``CsAX9r|8E{Tx2S-NQqiT==UyuxAut$zX9FJ@;q>-GF&n}k2{{(ZxA@Em zHo+JG@EZ|jRbRo}CdcU>nSKWWx5l@*H#dvKv&!^{nDE!do1*#*P6|5T5^IFi#K<}! z%h92fWJIN1n9N(jy%VBxf{Rp3{Z^Pkf1d{j=^as3h^i~lfe>*tM}TBdpK;@C#-7S_ zqtYHgU~F2xlOz#MB$^t_}O*?B>~Oz5Ev|wy-y)a6s@vNzE46qGhpYM;0KDe|5U; zm98W)fQW)p#=aHRf{78&IUhTp^$_=Lj%vp!#oMtC`3M4K`B-|Ws0D*AA3-^xa0!VX zm0%2(oE*qN3?0#=#}NpnLv;z1*v=jZ1qEjW;f&`pnKJcIV4y&_^-R5K}~yk`9tEDBOX$4P^PE)JZU z`pmYn9e;%C)lMGZlZOYgI~$8#Wfo`;3Iq`d3qU|ztaK^Cg9sg2oz%mLta5f%?3d~k zya+_xq{wn)kle$NP%#+)7+@ChMn)!~9CX_g&)}-YxFabNl(Q_4Kw=fYe^rDXBr^9! z5ZHXQvvK%kvIrusTsM5ozWL!;mQI+v+9U2rKlSmmPQuZWbmzNK%O>vx@_9mB| z$wv&b#XvQWFZhtH5@o|{uau^bB@ZQ5fhC9B^?{1FlpQfhaFk-CT0M z0tT5VM}U;c@v9s;D^gZY-iDkp%6VTTQZCpml2tAWQfHiUnVm>pdBO!qth~HAq=2_( zc?A=d52oCgl#i*5mzB>>u98tqHi$%uZ5f%MC~wPErExCHmVdz^z0I( zGMmdP#iB`%Ig*k00LYY!h5#+)EIRd0Wn<+Dcw2ua63lR#Y)v^AAdy%BFP&}C6-)~w zlye!9xSnI9@?)TVJkr$9~_4C}|^zENgLD z=ugAC)+HU_1Iqxp7C`JYY;%Vvy9r+tpwIvartt_J_?bqUQbeQ;fLR+f-0Uj;rpt@B8j%b%3$) zXWw6a`OF(2{1rWV14{<4fP|d1lnv4hT{2YcI4{>}Qz%prlTuMGbU>b3pw;)&Sk`~8 zDQB?J8Re0}?0)dOfaD(;E@V%Q&;eSS!?epezc?SxuZQtszuH~C`)b&bX^E2*kUZi& z(hM&Z_HjDYC;f7LJ>G8g{>5%T{)QR#xWDL5cRX^ENu>Uuyu?|rD3#<{3p-fsd%i_= z6$HSskc+_Di7I{2LYi7tcRq~kal3!HT_4B&LcJ9vQ!W&CVWfnL7M+e@dW*HjEn2G} zEJ78QG+yVzkZ>4Jj@ZgNbdw>G!8{BHT8jc2ghFf3UgbeWtmkG!zB+sPUw!so2<%qt ztJOvS_ubXS=~e|@)C|54I;azPwL=1Q%-VzE{nfA{34<-e#ISe>h!277w9tRb&yiZ* z_UGN3L5km!>K3&D&9*UU5M6Xg2pjZl=)N?1hUMYXLapvW7|kr89DFpF^PKYX3I~_h zEphCm(E}EeURF!*hV}u;*)8Os)DpqbgVsgqg0+`AE0!b)WCJ3~pSa$}rc@J=TKEpB zHKCN<1xTNciT!H(K}ehr+wOnuu-%LZinHT5UN4CaCM|7oPMQ(PF_v6yN!YYq9vCf} ztQf$oWHkce5o1A=Q+pQN^l$p>aR;|t?RM9Fq1C^y$4%eu`@?v^U_tm>EQ3U6zu9*jGp(jz3dVvY*SzroS0AZdg$MEa;0T~3C;<8Q%V(HE~NV!9^W0SJpX!<-U=&)aRpt8sP zaNfP#qbGgSF9;te%L@#?9i$6&P$B3U;TYN9#fCK0qRl%HAph3M(x}xeYisDAY-rC! z{Z_vnu7+K|8CDa+!4ZE(Ivih*zrOxyJN*6{&U&-jZVn6DDhn1MgqO2sS-`O%mLAn8 zIymWa#uHmQ(mN2rAzexl$KO1Gl5lU;=nlFX*9#k}DTP}QA4WqJlNRMciH4Uet7VyM zLVz~UkSsN$qe5UyiunYsz;J`4hyTO+YH8b!h!y{$EDfjB7fF9LDANWk$kB3@*`}g5 zfe2g!jk_x6j}|7A%qh4Gpeg z+p<34bQ>^6dMD*U8&VQrXjYk(mxSi+Li6Reg+>o*Bb$G*S?mVS%7{kUC_|l;UGl~8 z*RsL{YiZe@cG8KulCP5J$;iIzpV6R5QwoE5X3e=Q5X)kxN7*KyTeft#DII`S$6Vs~oE2A08yO_0qdhw^7-btcPq5IQ$*eYH6`mE~QRw6_!YGqUXo zSN|iM(?5StAJZ6hHhoMp3sePLgkQ>i@RI33-s07GyFDtax_=LwLs=$><*IzFQSMUR z_p5!6doV#Lr{=l82hTm!xzYB_GjSC{6=D@q6)MnNfo6IHDcnPH^J~Zl9|ha|w|v?0 zA;`cV1(|J~&Q+np&J}hJ&nd^b832DcZ$0(oyj6b#xoRNK8jz2MW}&{Lu~l&QHWNxT zpXDlqDpX~d^zeZ?1JxO*&Omhra#g6KQyrb^=u}6iRE0XSts`4{R%g@wPuS`ioyiwR z^WaZ->;35E^PSljDpH=$c=KpRn!WnN8SlsDd*FUHw&(fpo!5m&Z!+Ke6qg|b8xxmlbsQuCHkT2I3>TN*S{xsLO>Z1G z488YP=-3vBMx-cFEP??20GgmZ6iIpta`sHULJU#=9akP93rnYx5eSc*%6AM3B- zvgCdbqu1sSDqe26e~YnA`+F9Dn8;P(lDYalrNBb$5(h5DN6{R(T7ORhx2{bK;97sL zhD_r<4SAe{wva{oQwx}pe~TGlB!Ai{`wu*l#Ue8ib{Vf0k?bbL}$ zbRE~guo%@*2^7^T;u3|bR9xavTk7{RB=$wcWo^Dj0=U&Exda_1eH0Cv+|H6(P#V8A zNao+-Wo4ha5CzTLC5B|KjdD=`43a<^zbHWq^?MbP&r%3FD!Dd1(CW4qf(`(L#L%H` zD`Dtp?mliXHTN80=&+7|0LoiRt^)>Z$;uZGABN%E;J-hFFCYK5+3YSiyH!;EDh$uU z@Z;wBCOmo+hVM4pSF3G!0Y~?LFT?OXE@-}Z9EK-hc)GgS;VxH=45J9Qm|<9~VpJFe z>ku;#;r(at&v$=at-|p0`tpx3Jn!+D4LpC6JV&V)of$$swm2 z6GF12=#G9Ip0WT=%dsNNved|kO=6CU#RW}759|X0t+8Mes=>@2oUhN{t~al@XIF3j z`eyyAELlr};n=AswMb4zTB0I=h)08dUZ`A`Ky4|C2h|LRpgKo8Ps1XI$0csXpczR5=;nJUr_LgAo-Bw zm_UT28ViW?1U!$e?}1AEOpvtpJz3#)z5f(V$vd07~KAFbo-gcjg6)Rpe<-xP)h&z>`n` z2}Lgg+L#p!M;1QbI<#cTz&|KLL+O5lOE4#D!D6^9hcf3i#$0bMBNE4wNJE)O&OIo6 zJjlG9kZA2t|G9pDJ_CaL#k^$6QZz5_tVYyv2sVzXy0ubdqhp;YEizK=r0o@#A?0}v z;YP6>p6)(>2OO{vs&Ou;uDlG5Uf81B05{t4e!awrxM0PxR4_?n>&PnVE%WTl$GSDD zj3to3KweNGwGnzibVo6@UW%qbaS(ez0qHxZ9sl4K*p#> z%y$*AlvL^|ib*&)IzO2a<%D!=M*`Y&a^s6#*_YF>7`Lp5*{X|GJcQ&B~acc?{9 z4x((JZUkEMW*&7ocnZW&qft2}BWP!)jOJ9pRL%%ZsRK)Vn&KM;zz0AX5m-R(M*-S1 zl)_MdOTv!|`b{?!!muPzC%h^9E(7Y7RLf`XJD1f9g1F3{qMb2dLBs)wgR7uYKV|j- zF7fI3!lG|lGyK1@7dbhK)ca&X zbYn4BT zSJ&SR!^QUOGHxGSZ8yI|U)*e84}Y%ChpV%TKh9pSu7|75+x5kIbsgXA-o5?m4)h6s z`017&7lj&X0P;z|4=8G-`wl$&p$v*~hbyS-1OIYDLLBresp{BRbSP z_+QapPVG%`^cNbOnDf4hum-Yl0Znm@; zYhc(mYzx!=HomB5{~X=>gENg_P7dbmwBh=WJYsXPs&1VX#QnKIcE8?}x^1hzY#Z6e zPM&dOvJZ66^>n{1e8iHr60^hqk}~yG&o+0Nj zCx1`gcU3!bfz%**JaldU4-~BxEGuk3^%;Z#zg7L)HlHBAPYj z58&UvrFDb8n^|y)(Nb*JdEUBv{m6PQD;G+ZDi_KwZ_;QSR5hAS&=~TUt~aVH9bGgQ zEJKe5`$EBezCl{6wk)qisc4<`tTb{9)5T<3Tgh=K(B>f`RjeWe=vWcezf>v^QQl_S z6D{_J!j1g%$q!2pWT_MBf{<|lI=;n;7Fc)Ub+FL_!>(;^EoQB=Tc&V0CluzC+;vco z2QsK++4b75CcVHcwfCqa6xK$@XF}n5^qZENW2*IKC&gZ-C`;tXa8Sa1NF#adOR}6J ztAh!h*&24ru7s}!rE{@DqA-vfM8K&+ws?G za9?X+Ob8r)USrReUc>SNwjay$Vwtjupafh(0F!!T=910?VB@+%IABsqFkqdDv%rdv z6{wUx?A|0G24ks3P!PmI8#`;brokB5nmFD4MupogdHdY)@EUR6QSq_&Y+iF+ZHv(L zOrNdK|GoeAa`v=(zWx1i_g3^tjGJ9N@I0&^eR^Iqzne3>o}%7zx_y)P@@&oJ6~XS( z{Yr@Yl>{#jsMg!qrDC5F0N-qZg}F@R?&G={t0m<5e7L;t;MdnL8jxRR|CS8V|M!-W zk+F|!@(Fhg&Zw>lB(lgvgPNQ;;3Da{bn`~GYS@xO=n=qM6T_ayL@U5FX=p0K+ESaP z)gbIXn2tHN1yOd`4phcAHiM;lLY=Q%UAV7Gx3rc4XqhG_Q^;}=bz5=-CH(R5;_7(X z-XJd1__oZassYs{>mYW3@?bJvWH85vgBnIHg_cW;(P83+s85&239?{^NG|G7Ul&=C zA`;Y@iar$m!WL*H($EmrAf>1iDtWKOnd;ngPvT&HC^l;oeG^pK8PTgckQn54*HXm& zty3)y5DG@>eP2aPB~oP$AYX?mqY-eNS}O3hCjgdYD8K23ucm7$`Zlf>9QDH z2Q6b@{Y%a|e)aU%p@QhuGC~H{Nwl9_Y(=1+ZIE8Ytiyqj-$XC+E)GU}Jd(-Zz(|Yx zjB{|gdzqB9rqH}OUN%2n%ts8;6rYr-GXW0@fN;@8ERib^(Q6umgbnKo2TDcz z4E^qxjp9;^byylnFZ?iIH@uH)t3#MljTmSlpg2c};!o8;^e3m=sPtfJ zq}&lHJ%!wwQf?MSl|(X(L_!Z=e@R&u!;LT%jri$mn^4B7@30AL@-~Cf^KrpvehDB4 z$y&cBNg%}DkZH%=xc;=?eGxlQcgx8z04g#_DDb5)9`{3EsXx$0*i6MNaopjNfFfcP z78HTXcVQ3he5ilK`#~gUC>)y<@x(H;24~c%hQ8$Mt9jyYG9lUupjg_FuGHkVXwoWYaUj%Zpejsppm~a-yT>uii1~XIT*e32Z87w*R?QgseIP?p`7NFbK z#{MDSe`Bgq7AgBMM?d@`f{NUk_>0i0B#EkH(jOtZTS?@b{CYx>IdJy3+-a;?5>cD24a@!w+*Dr zaQ(A)oLxGN5^{1j^>)*+1R3eFnqOa6D=OIQWFsGkr&+UY_*Xb+*PdQ4UHNqn9bJ>o zJEffZO4jiM#XS6vQUr|CGR}2YI76XQ*Wc^6q44<$SMV-=yYgpA0T#DFR6YWHw=S#9 zkGT|m_I?uLeDZFdy)%41auZA_ofP>+kHca{d-V%f#ET%a;>drOjd;di$jpf>wH)t< zFqOc#jzV4YlPRM!HIZK`i}NBe-eyN|Tiyrkk=bMgTJdss%2h0m`pYRRf0AJF=bfhH z&bpgDIw4-?yie52N&F@653~N*I{3BKlq1F2O|1IvkK|gZ>jugWn9CknqP76}k@&C;3 zCk(ygLMZYRIF=*yJ=6Ho;bq{bAbzliwO< zMQo}gg$Jb?)xy5Es-GID52XFY`~gr*3t3c3x=b&@8Xq_- zTiQjZE^7xxD^Pj=0qIzg>?$NItn6d^t~-07v#(49@K-4>}C8{%yY zsqMjmiS|@F5CDMlwAr#-DTw|H?6MUc^D|#ewOJXE-r(#X&icn*D~|7T52+jBR_9J% z2zcF#aDJm2`u>&xcz@oHw;-@Tr@h#nKIn3N-hX^@dcT@-eSUg1S4 z{|ep@v7bKFID0tUzX7XjkK=q*vT}bRFK+P0mzscScmX~-o@?-Yygd`-zT3Lq^|`$H zFKVu?rVv&xo{>&}5tt}NV~B&Ah*Q|_Zy;^o2&suI+#`D5Z{NQH+ie`^p$i~2=^)V& zrDJc%=rDCsKu1ap9UFQ)e=Ty;czSk^hXd+;VI)DiMp4Ula^Vy~W=C~SI7q0{8h);4 zQtra2G{8L~uBZtirlu9z$)%w|^9bsIIrQaxyys3uBK6=DWOiYIpIjr*h_&s=UtmLI ztZ80!iwLyQ*vNgqEwx{|NGB3}DHHp#;|?qu!_xEnv0h+GcABwHh-(vwR&*o0I2njT z6En9>68d2j_KTc}P-_ax;&}akP~BfH7emDgd||?2ar}ONVzm}oQxrIv#4eH zSDIW_zfEwXF+qQq3e&ND=sxX^IS?a>3WL+YbW-5P4P_T}x8YG8V3jvSGQp;mP~g){ z9j+mSpeEJtbz!An#gdKVs50)sCdsMfysq--`fJ5c!<#8Ehp+)lvmb0C%3o3cpcB5e z@BoMH1lPVoTDgLhB^=f-tA>09qbW)Vb&dG$3KVmngZp6N$yCWgm|*l&R}-boMFiEe zY`I)h{nXGwp5vW`3b@coJ9XjhDXR7-xj(`eGv@_|Miq%V$7nM+EluDc#rOhKq15~E zdo>fwQ1&$`MioqCaoxs0;m|d`CF)^UkN|?1fS{e$(&ApVMy)ZRbsUa|sQHlFr&S9cpQT34@lBHqk2w~tqBbRvL z`NcF*f9F(;2w5ZyPrz?da5MapK2C)RiqsP?!wKOWnqg|$YKh-)TJ&i8B~|M`*oYXO zhJtxa?a?;3$Czr6*d_6fB!qY?#s~o6MHEC&wJ76_9ia=Gb+l#l6Wv7)_yhSGce|3~ z1P%g&Ep>~5|BnI$!*e35EB{aHSSJJ@azu7ZUUq~#LOzs@WeogJV(nhh#+XZs@qloO?JM#V9E`!||45xk{lw_Hcnj5QJPv3rUN zQM(IC9+(Shin-b{WtfGxsQ{${R1#gN&!S@BK9tSZeTmi~7QrR)ehzFVT9*P+HxYRe zfVd14v~fPh;GRh5o)eMUnl`3N?#U~MM;fH}!gVtfT|rTamBnwKU;%}{!mY~G92qSr zk;BWwinNa`6rty(IL@#bc_Akmaf#KXR$nH-+Ia|!q<9GZ!^Dy*=m1o_=zvoM|Btti zuPeeu=eOs}47Xd3f`5GU%^_!o6mr{_zmj1=#(m!JzQDJI(hTf^M)b966AJzk8n)~_hy-I7iVIgX9uqt}KDm;zjV zXQo=EKH(+Z_X}>>9vOl!G}+Gac?qytf#=S7PcSNMn-(!jth4KdYh;VAX+eDa$M;Tr z*Eip#HNw3AE$wzu|04lNV01=LDUbS}hr6A!ILg+u`UEmse=elvhA1tTlxKgh8A-xa6gbx`xgssI@x?#BS~gSwr z6i?Gg9JoCa1(66pPP_6@B}eISr7soNoChd6E>I9C1tteiS0M^7k~AfwIWOXL!t(he z>sKvkJ{M5w!il>qjW{*1j~wJ*zXDGwK0GCCMxC)ZPw&{&u9w&yKw7&XOp4v^zC=Az zwa7;P-yxN7y?+v%Y`8mN^AbBrq2>LoqKWAAXK{#jcp-WRF~cm#&ZQYh-4ktM&X9u) zI7%Ry6BSFhvB5U#vAH~|YEhHpWJ;x&&?W;7OTa2jLMoC3&|x@qqFbDVFeD}r5A<<| zJ0jh`a!2RUtC~DZ02TB6>gV^9qlX#K&+0W6gVUf;jXy4URM32P;{#YbXC~tN`CCl9 zE5ZTF?!N`T{*^<@JW3tv;wF(KECyP*QfOd2z@nmH4_k1wuoL0Uz|)}%jNM{dX_0fV zI$LJ$c9H%XUM2#*xiJ_9)`djjD9$W;XuGnIkb<_RGT2Ht055y-hJoZga}uG978u`z zU8U@^xRq9U5=MkJHM~)*Dsy1taoZ|Y+GHj;3-qL(F4Xu`i82*WQ` zsV$;2nAtzYR;U zf2#hSp{w|O1{JHpW3PW9l!pEmlM~dmvzJ`SVjO?f@#)MGH*3QT?CZ2ZrBr-~pq(O> zdRrspUBI%Oz<`eR`^Yab=pHEb)grSQRwftz(=we|TL3kbA81Z;Bvo6h5A01?K78JS zzU()!2Pj#rpq{QJ;14qILw?*=xEmie3v(N>x7ANy_;7UW?sR0OZ$Tgbyu{6V4UiL7 zyX|>;pR2lKqh+|hjK4h6z1yPeY>1E@8!zGdym}JLTIYX+x%pAszkWWucBHIR-&iJ@ z3)%_`uRli}AhJ+caci%2&YMqtI#l@h@yv4G1E{!QJWVX#KA!Mh)~6`RjoZy;r&FpFwA}+uwI%iFq>0u9x)L8 z*5DR!m%E=uzNXx++dlv&QwBPN5W7oZx^sO0PSuvnoriM%22J4Knz)O8ZJbykt7R)e z02BrEPBF$_s4d*ny^j@bRDLX}m?*Dka7r9|-Kdxwy5dSTFknajMSJ?=pZUbdc_Jd5 zr#Ujur#fG9V{tdD-S6k>G9AYzZkDF({VIc&{jnc`93!hXs+>R4fG~mSs9v)raq4yS z(N|^@ozMeJ;)+T8zt~bKbcr}rDYvaK{~=4!0v4}vMdNy*z*oa*?5E~LUu%0o#UMH? z+}dEizp~HL{8%w=Y-^CksZ-Ol)2d6(yF7veA_~I-qzCWNb;vS^A!{f#(EKSq+lH}? zak*E$Kzx9gy>nlL!fj{c{uL4 z2dgKe*tGefex3V5qIY=)VPRg8L1PCE39mrxCp5-kl&MV2sSw%+@ic;L{s{RX^-M=l z=7-$^7*r~SBXWp^BC{rfIZUF*fn(|U0Qox`v+!9M{SD*>I^*Pcy3+ar6PdO%K~q5l ziyr_SWpa*3*RGIbGfxJkJ4iRundFvO9!BB`kCiYb1{ySvKkc)hIExs?O{f7pG!OEZ z->;a3>0fxOiHtWRMDHW%^+z-)6H@4SHWW^~eQ1d%$nij6E&+FmQS{T`V@pYO07&Q` z?3SODX}8QOSQ>)#q+BCDqowQW_x}5J*(&MlH*wcn7k5uu%bBxd*M*s~>4&vdbeTK% zJ4XS&Pp+9A8^87O1NDcHPmkg~I5|%?j)IfKq@rj0AjQOXgF4z#YE*q}BfBJU&4#;| zQ+;QbZJGPF?6>gbu+X(!NdxH%07b_0hib{6L09(r6UMwB!~f~@T+f@+(vt9#pIGO# zkiD%VceL=q!kd-lGVf%?=Q6)}n%{xHa(xtWm;tk43OB{D9CNwnyroNTe!rE$iVNIl z(hAe<9wUv&2;ZPzj7w(Yu=xD^tl?>q)8246v?qtB|E7sMjua76!NrjdnAqQe-{Yqn zV{OF=WTNqMb67L74MU#H7=096&(fy}W0lE^0~;B_rB;8YCqIU9v?02&;m63TrCF$n4IyrTma2~OK-Oik2{YyO6fOc>pqe}fAwU~n&M4=8eN}bS92;i5zVy5suHz2j z@=Py2bEp!-aC;M$#C?=w7oRs{uj(vzk zjT8S@z<*6grWzbYJE)sSi?j=0SZc0xEzn6FxU3kHd5yvnAW3^6{scZVR6#*W-J3m= zXA@ms99>(AK4$jMcT6iPJAqx~QOV)NN@hEsi)G{t+$XJ3V1cUtC@KNXZCs)a+H!$v zMJ2r6ChzWK#s#~Shq|RZr5ki{S#?8C+vu;D912FAz|%017l$3Dxh##D#KK5$EHlI3 zRogHrS6723K)qih-b_bfP^m(JDTi}-TE1X}?^r^T3J6pHp=~%tY575{zmS9f5+Ww_ zE&^vi@x^Ol()>DGhYE2!fuvA)W$BDopWx2iXugFw`)~H8l4@!pnqGnuk3m$$JV_)y zoFZyLZY;LRD%Dt`H`xVYNaxR`hPimHta`JmV2lp{fRpRuyQ^J;t_FRZb@F@dH)~ps zp7ZygMH?TwW4L$}W+pCX*njMf)K{HZG9_pAyj^MK^Q)@!Uk8l9;I8opvXoAjq|0b3Z|d3>IaG+wV+-``-W2|+;J+Li;1CiWNOhA3W?UMa^l@A zcWS`<0It_RB@g9Ha5D-QeCcYw*@RrtXWFQS333ax0Zf=p5MI9@X(Cax=+G+Kq|}qp5{N1*nqsgVl<>FEg!g#zVp zl;U-FRq6yUos;4Urp4m?f9Y{Wrm7~UlkPkJdE|BOE+(l^h*&ry|OEGl4*gs7JWS@cG>B zxaW@ekGRj=Zd~5NcL}^XBvw~$P_gt4$#y7gDk7*Kil zIG&)P-h?Bb_D`{xkxxrX!!S+!q-!t$k1Y1um}&_boEi$`W_sx^aznfeVQHD3DhiEz z#pt#3)G{l?PjJQ^cdNi}+)atPQ{1okCiRea`Yua>o`cypF{aSN=%#gA#8Myeu&XUd z@VDQkeW$XbM?|(!CT`zCu z{+L52pUZU5-yY2r{{MYXD`fqrRsJ7IeRLKM4q)AOT@2CtTK&TKF7{B*>xTk-m&JyHi)AQNNg)f*0o47ZQ$5>F9iK!5_>6-*moEtE1{A$K;Yz1#xk{W z5%RxnOz4;5h3i`#C#Ba$eDbI?5&-UxQml4~Uf;#pmsiIfL#8dZ>}yz;O@L}Zx_tR- z*XKt0a*gV}bw`($%_3O6GM~Q6JsJ!*-B#IAmldB-fKHR3CkNiwV!Ya{<*4YGr1=4i z?YA@kb@w){%Kfp&y(()?#D`gfB{#-9el1eceD$w{d&Lk9CUFQ7raM*7L?o~pS|cV* zm81fk(?sC0x@hktYZaK+N?i^B_Pj7CR1TKT7Dg7V6rVthpdZsy7_t-NSzsbR!b-<^ z^X1L3kaj(4DU;$-i6b0CO2w*f%L*IkG5Y=EhuJ1wOGC%vbIN&zfz=+=l++35mX))@ zxPdCQK+`y?=D#LQvI)uo@cM1@*dSnQU_8PZ9BQI5)`_46@?_WaT@o4)C45{a14&j( zG^;t9pbHSm3W+MDp9Ab)<0Mo3#}vZ>)K)l-m1#Q=JMCV zN>0C3z-I?($67b5_fq1VUq`fO*a?}yj|2e zTZFF_m&1>o_@4Yoz;+ug1(6;7oiLQh`^yNOL)=q~#x)v^W`4au>54~tm&y3fH|Rv` zvHmU--A*u$X2E6xFwq*vKW~r&B$QVZ&ZqP+%1lPq1HxaDoW4mEV&XF^UVP(|(SdMi zM}E^8jnZZ|^{LS1h(h|_EDt|_E;pzyZ(i!LO*;NiagX2XyZ$6Mn0hw6G+Vb1T{t#v z(dg?;wreu?SRPMa+K@9FuUFl8dpGD+w`X;4{ET=8gJGKiCNZ!kl?_SB@N$$jPBWQ- z(hSxR>Wmili>Vy>y={}DVUrwLGg)Imj$5OD@-tc*>1muwnV<;RI&PIrrB*w)Zx97s!uV*pAZ1)XJDMmza5NV;8AL8PGm_2% z9^cPFnJ+;c7Ik#ji!)l{#3oM;k_0||G;kp=KhGF-*hWr|mzDN!v&g&eik*os>0e1b zX6+}0$8RsYl!}5Mkd6Nx#(zLI2mprv#j#n`vbI|vLH*p)XT)#Nwb(+CtJCP6Dv)%` zD3q)3_=8Ae5f+~&Q7E9~^B@fHoW_lhCgu*KZ4*TkJQ!b|NaH^4HWLe)U>sE$;ZbIb zM@$`sg~D_q;|-q}1|pO~OClCzEMn=xWmV>yC)vfeo>v|RBt}T)=Lq}}VZpB=rDTYT zksM21BJ4s>YsP{zQDV9jB9LTc$&4#Zi_=RmNv)eoFiE@Z1sO%!a-J5xJB{eAoJ%f@ z)TEwoiQ82MnocxfV_pbRngFJf#0q#^2xpq$l-5Wzof;J?b0by1a+BF&H;kP}}fXvfBsB*6Mq|0>MttCj_OjvpVbFB}*@FX*^3h+j;69_}9mjb@b7`0E67@*td;sTJzyR(WKh>3ANIaA0|L7eAF4z{o z=$m)fbyM9$)#3ca{aus#V*S}}#{V@kXt+5M9^4g#In(1N!!sC!MW4-d8yQw$v^J}Y z+vd*)aGBYdNsT&WaWbF^k-K@Tm~?Qfqf32htK?(2X-m8mbMCx|@zhI9mDMZq&j!znDb_|cSF>c+To`E`;?x^P zD+lMBD=S>@iaDn$Mibg8*KCQ7tP^%0BO(v&)f}dZbxjw^y zmYxBT{!Iup5cPwPqGJXpYLI0U7p;D(uN7jD`GP~dY`#g{*UHEWgX@t8SEr49K@Gy` z)?HhCec``|?Uk$>3Db4q5F#|^7RVP{XL9Kk@)2g;mD3XE+&3HCct|^lzV5*sRw@Tr z9}GKTLFQYV(kr|uZec{@tztTCYj>dl3~Qp|1H8ZK?70V)edlI`W}+!6<7!?)10B?J zy-AcL7%AbAKIo)hJv;pxuoEOwQqedYScGmj{YO4RJ6$gZvOtfd3dTtFpIy5=+}!(< zCYuY_v$}Jan}kH>yGWb`qB{4G<&Zy;{n$*$s^_}wu8k=mA`LnBGN;UVsSHg(bz>WG zv3uJJOKPuI7EeC>`_5f>iOw7%G71th5M@oXpJ$;_i;!z-%TPl5S?b@98o<|M3HmlZ zO@yej&Owc1p{)3jQNsi_Pi65VtYS!*{`eV?4{8;fNUiJ>Hg{XpdOt|Y>;(4|0 zTe)aGF~LYkOKgnKplB${*Mc3O92pL+6hi0QC#EUn$(r+AZcVys<3qjxK6b*74BWEC zWg&W!!R`hFjWk8H|Bvzu7I{$?k-La2LEfR)XCnnVIWFk~1~{A_o*XQ%cl`u9Z3A!S zz`z@h0vVd-m54HGF-2d=^wy&tz0oj)&z>ZnA@Hr(`>sh<|aq81i_bkifdCcLKf zTQh}z{8X?>1MNkw^DKN(IT>z_Uh=K9hWf0BZM5g>aIq7PRmyDee>od(O#fQ&Pxc2M6|V z$j*C|{gj>4RfNq-f>R2B4uR1+>fvG9D~E}hz)!HufCM^I0F}NT1mz9JO%}WFvXQbr^A}EQ+;m-vi(ToL4s1&V|(q#Iw zI*}sIn4{?1xUtE|ILN5BpAT5^7rQM#Spjh%fFBaRmEif!AA!Cn(TUc^fu_v(J18|G zh+@dI4ux7VOsi6qSfMsFiUXCRi61$$_{z-RIP$bi{8dU|%e&v;vKjN^ROXN3)3xck z(N_FVgLWQvA?g;uynxyR7tp+=Z#smIvtQuIN1vXbj`oMBhJ$D>A`@!j+?tFoRfE~D zT8m{!WOOjmMtDJ{GPN{yg~2acJ}otXK_+(;T?U8wmTwjyDMn~k7=m|eI=w9MK5j>k zpx+rtwSZ=s)DCBvv_V7*UAZ2&WDZ{VINB7C-Ka?VEKvROrh}I&QbxTX_!U)SIcg!Kp zcN>K@3%eZ-`(%i8B9n{%(+e~QTdNn*wHx_nrjC+r1SyM%t&&3nLH4|RFXlK*nyjf< zi481j8~${~3R_McNXf9|=s1uHB6mJ!zsuv%BMt}He=bJ_N8#FU46XM1he`#ow!d8b z5~V7OjKTU)xN7#uM?A7r?`w_p40({WQem?PPq%LRHo9vsT^{$Zxw{H%xrZxfxXn4e zl{#=|wRWQ{RZM* zQ~d(S)>UV~*YzmcrkDb0?Ibjg7jRs*TWY=J!L@`wOq+cRH#(v>GCGQTs>?b2fGDt7 zNB1ticr>b#6ZYG`YR}VS>N7KAmvs6!qLg&Nw3vLkA>Z_tyv$_dYS!Ad8li}Ts?>OV zUiOBhyR#?V6v$C1b_Ix6`ILN0+}HAi$F2d)9oHN5?8Z&cuV_2sXTR9Kz6y9Fo8(ySd`-P`8-t+$L`Y6BH+ zvYuY>4lWf}xhpm$9E$4Rx)X1qyR&L0%_kU*s%IS53%u#mn-7aNtW1VsM%cvQREvm# zOcn2CJw#JIAOHbUfxMjDWbk9l*>iR&WJ1JM_G@2x{}`tv08ava$UJjTxbXNJ7j4t8m2~rvi6r{i zppI!kNB?MM+zW7@Vl1`&(I`|OGNYezosauCiw%*T*{tj))Pcrj_G;AAQd$AwCyJ8T zHVS4C^P*!YO1npb9yu7oL6V7A8ACj^0VB3XT$7+DETFMpcnb9DPI^gy#Lewo?T=Yl zs_2#BlQb7HZ@1>6pPbjBV+I*zeqYt1Lh$$Sd3-p&G#CequQK5tG(e_ONT&LIhhokl zj}Cn49qi8bIr%(5eQENdR&)Z^4#w435{fm@+_ggsBsE=RyUqzv!2SI7hkfSJ=@@W} zW-JF>wgp*Sm+lh0f+qsizqkB|gW=^AdU1?=%8Ra%ukn{M%8k>*a>g{Zk|IBi7;zU0 zdn^t}X^C8%eUx=Ky*(tS($n47@ec~cPjQY3QWa|pcEs}ZGd$f;d&L2ur(OmgaZ|wX zLTr$7wgq=f8=+^$>sMntZ&?ux7uCUrAauBV8&)asG(N74hB%UJ(6?`~bRBR5L=FmX z9`t9_C!a}Xbc?grOctD5H!VQ`WQv#lp``xe#X>PF6qR7|r8 zohgkC>k%`BJgDW2QCk2%DOvO&&JCP$f?U#7z;yJbE_v}g4P%3!!RgH{LFAhEIzB(% z)te$@0fSa5mbkMdT~+tsA8hd4TRMS9NR=3YM+sYA{{>=+|GTgdOEAB|GB@)u6ydjF zYO@=ko7rqeR&_}4&aFpozSLp!yY3I$esBQsyY3FteITv`;cGt`kNZ5Je}nO|@?p1x z*W&QP{@3!cGmZnFa?y!{1Q?IjX+hdNrfzknA0&%V^#TnBUd4uB?8G1!Ko*XOF8(9W zgkV?t^%mye7RbiwZRr>ku zn)e7IJbkr7l4vSR#5J9}PyRJJrCBRpU5NZNLu*{MQoxp_SSL=LP%F-?P5opcd#vV4 z87sMm48|)s85^ISizYGefjZZSXD=nGZV9Zk)TRNwavCWX8y;;vDrmW1E6(;|U@#Ue zIDogvV6ifgTLI@;3LrY`Q&xu6>cx{~v;g*G8OjB7!~upcJXo39_$90~&EjRs1Q7^Z zwz{#$5jR;CO}Z8d9_9iLKdLlgI_m(>MQjw4=`1#ghe;O@$XkA*Ljzed`v`6X(owMP^umJgjmvY2_Qkhn!p6fS>?}Le2?^$ zIt9^S!iAqnM0!$&{6x`=$2XX|g8XDr$qdxdXvI8ui1E$g1$UN=1#bf4$k zfcKosf8LKt>ptFYfVLhteju zK52Xbdf4yXOMZl&uGNl9H}#fp*B_VE$KBJ@mG9&fAnQ6KB4ztM0^RQF`YY)3WAk%* zeY|6NJ!A87ee-eP>1*io%cIA0#g1O@0>ImwI57G6Z7U)*1Y?n+;U#uM5+z`n-5YUi z*f$DC`Rd=BuheM5UauC zzt6k|sO{)%YyZ?>N4cwPY71{^2Vu|cbYJj0HtL^6u%PTb+7vlp9z#$?ghjn$)^c!p zpJkLC$y;{3o3ei(>c)+?82)LKFXYoHm%QW8l|9n3^12`^8XEj1Qygj`y^#minp1Rbo zHAt{7uNNad6-p4mSWR_fnu|u-(*wlC`IMzgY$ZN<)St!akr)}2mshldd+ErV+7CJa z6&V!+AOatI>p53f@B${+#-SNs9X2RK*KX|Z!@+A+@@}UnjcIg#0Yra_xp#ASCY?ob zQ0micBg_A?y4zT$s>nO#ENq$YT>oCn^v*WcD$>vBN>t^_H4^1Su)HFSIuAXXbVkQB zpvXA2;-NS*Yo|mAZ%(6|k`Cg$gzWbO2#os=jpX8*Rhc9ETSseZ$9BGP#P}sABcZwL z(i$F3s>&E^7>rfqo+)^eV8o{8Vo0J#^@uBQ1>LqRDH?w8_B#tTJjFj{a(CkIo3v!!AROD!N3n!jxW5Ma-{jyv51x^HuN$WMHPY zij(KjO-)`?uKFL7FQnP;>Z-$VDR9N;p4Sm;4Nv9QL@h9xHN|O~ko+NT7?D`}mzdkJ zPCbt^-x?~yV2d_fFQFeQLg(aijYOx57P|m(malP2t<}Oo*YQYGoQRg1tSaMD%9{r# zabxD8i2ZYTcq`zdTQb*w0`hGD#m6n2r9|W5aYwH73pOpI2rN^$78HKEf^i!iB7@4= zWzrf;HwbM`xC?6m=}Xkn@J%g4z+ug4*;pyi_d+<-iqILSxQ+^glMghnc*?vlIW=^T zG*9*A(4J(x(1#R*%1LkDZ8l6!cba+K5CTuB!{0)*v&Zm{e7ppi9mV#5nGlA8!E$Y6 z+Nq8$EmD{(4rCVDo0u?CO~gUQ1`-&54Q?rVSb^iv%Fn)TwcuuFGavZz;uLP@d!7!e zmkVW`sL4^SAL7Ny2`3~imIKAN`K(gYX#CufS< z2DF&5rq(aL-6Ofp9Jz#!`;6F1Jx&SzpQZ_vRc1kRmzP(4_-+#L-YAkHWY!Lorx-(C(Dt04@u#D$SHeLD7>nOvK+v4$DP4m&Y{0Dlzr5oDk~E}i@K|9t z@2Tre*yaaajl|2_#eUTpfT`#bC>Bb2(@=cp{GNV@7kBEJ8`4?+B9oJgmd})AJw_BR zZv%bm!3zIwQuwrk3rnBvT#Z7BZxi&3$HrN)VkVJrB!)m@mqK(A7LHzmg#n}QEzMgn zvw)SdEzDhogSN7@uRRF<;i28n;wU{pS^6C^D+L`YE1C56m=Rhc`!D{InKb`v?~0FS zV{7Pqi$Yc_k{*OJhpZ|by{F7{pfGDj7}6}#RJDrZ$HtnFT)^hs7^MR&U-$&BCdt^s zUf%0iY6bqcJ6g-&m8-m;34iF9!_&5^21cS$q+j5g0@8QVMsWBDfH0Mg2Go&iQYcsD zc{lHXj|W8?1_ogW*j+yUP{~n zz&+AdAUgl|?e3+z&k6F9(t{5don*$Rmku)f`(Z1J-P7?ta_slVET!kM?MPq1X=4Gd4D()W}oj8f=Rhny<&8n~qU1ebbr##Wh1Y54xd zAQqgqg7-|-)TCXJ=Teg9Ub+VZb(IkwCgxtafGP61IFeR!So0ZVh|xD?i|Az@|0?1j z7}FMadxs(Ps@+$4}fna+4S*4!YH5J-ExN)=$g(?SEyz z0M>ukL#<_75|_?Jd-gWPyybMryQt*Xq+EE8r7oZ`y}55USRPuS#v1w`#3|+-CwMnP zkcY!;GisiMd*Y^miuc=drhK@n*Uv88>d8+>x#e-t^Sa}-`Vp6+vnCQyAh}NXCZ_%W zP2;#~FZ>g$u)(g{Bh5tPLZjbpoSS`31)!Z$$UQeoh&!~;+siN>AKta_TNLi-%?>c$ zHQeQbI<35Tk(IB64a4HR(`-Iz4oRn?6?3vQBFbjfHd2Ie8CojByYwqz=4F6@!O`V3y`k*F}p?9937f0o0;K&27@HGO_= zH@S>{lIpjfOW29`=q$n*~RfS^-Ji@}r$y<)9x6&WAE90f5Xd46Sf!jiY7Nx`uPe}G~ zAu7^l%)~>kjlVO0d2p*}oRfNfh^rMN$28`an|mQFE{WO-u%!S?%5`s85))Erv>m$v#ImDzB{D}qKU@3=;)LGH)a^qBEp=XfC zRQ-MYkdAd4sSR}6OGZ%{_@j|&Mm*`#K?#kdVZ(khrOSTSCq|vA)L3ZRr1Zi^VX3gL zGP-hVG>(sn>Evaw>EG~(CF2+5{PmcF8VXB0Wd7N8lu?*&&i_+i1r+Ga*tI4oGhs#_ z%%#DnTaa-`5jRUE=Z)K1$%)#j^4X2b{_wC%N+WfmtefGG+(8vmu7kKG?`Z6n_;I_r zl~)@)x0P4AEOL>bb{ULpx(QFD?OT;IJFXKNlgXg`Ceyy;Ou*j~v?wQJwruETPe3!( zffcjo%j7@Y?{w

    o!*&Nl2JT0udLFt{|F@N= zt=h$C%6?nFtzcc*53=KeRFDi|{o&)%n*v5^4~n|_j+SQ10*&MT7cT#T$7(0NObTw8 zT1YarZZHsC6G31kJ09CFp_}4b6NMaTGY$EjalUr!N(tfDE`Xfw73s-g1ttE#EOyIR z#3%v^x=HOefVdf_dP^`~?u?t4)Qk`nTPB3n1AN$lk}Dd)439-7LUc+=eiNr1?}trEhMbt=KQ1*EpTNp5kd4?(icB zqF1Kj;oj~w&3-10XcOS^`Sy9|{POa;$?xm+@pSxbdA`c>MknKyw()j%(K|aFv{5@I zqFZEYZ#a10cE)htG%>od6Mb5HMliXsS!mzMCsjQ4MWFQ_$9lt`TTLZfYKU}5Xqakf znQN$L>QNJKTA|Q2U0%Is9&b5Ye{HH9-585GwO#i1{!?($g}SU>eV3_8cq>e#&)%hM zsu*-%_SN-f1g&96`zfN>HT$9Wb~ZHehT^yHatuApZ-B@0WM%aZd0PQMXC=$ZakwP3 z7AYA(ush*ev8ZKhTj5o5&`~k6Xhq=NqohY(EHU(O^&FiPZLvP@Cms5y-HmOK;xNle z*Xg9BkHS17308Rw!^Ceq=0H_#6!~#ueFY@QzpAt@JP?|;j6)T8nPas@QV9{axQJ^#&*(G0v6|q$D<3}bipDJ z?FgUdF&ieQRreGsvXG^l`_MaK|J&gi3P`fzjLo(tvu?J&KX5{RwlL0LRU9b{wLEw$ z<|Po5T`8z5h0@E)+75_tkhI7`x2S87z0GRUcC;eM$kf6gJLBDR`1c8M?vLKgQXu+ZphR|sMRaqNI076 z?qH-;(zEQvrR(S!b~vOoUQtn?aMx1NFtOF*4s&7dp!K}O zM{c4Ad>2Mda#^;gG%R6w#h{?SH|+$JrE@kd*qxVe{>sq%V<+ru;}BX|BXL=^rRi5u zNm}zJ{`Z6{v-;@miMyEjZl42OQ=c@!C$NhC73v&=Vmax(5Hl$<+szbS#&h}7&e6)+ z=Q|=F=R}?a-+-1a8sA|+3$j;yK#N4X3;vle^tdllTpf4coF5jVC67M37R3ZWF&v6v z;(q`)IzW5inBP3Xig+Z5us|0w6S?SHvSMW;8f`l$Oy6^U`3KFTQhs_A=?;bjq+{ET z6M1xAqA?#9m2ULCZn{H?xy80VpDvsg_Zl2WKHZ|1l_ZezMH||U{|JigE>drQ15cVS zpv(hme<*F|&uAQHKP(WiE2QZ5-FO_6O84S0W1PSI%s0}GVS?ZD48k5OLvCQpzG@2$ z{QIgo3hG4C_ibD0rYyb!aC0DfphXHE6pUsB*NMN<&m@vwAwa~l%z^NtFM5pJ+X^&-VvST7w{dy;g%T|YVCtza+lb@@4&x}~BsVImg zD8wxN7;AKD83`+^GK6d4aI1#cbEc~rZp-P4mg6bs+=tp@o*7?pVF&`n;17 zC6`_W*W-3`Yi}JdvXw|Ly9B*~rYv}SnDz03ay@fbr{9DLBzUt^bwj=AV%+dOLv)M7 zHK)ARBaA?=nKR{KU!SOtA|ZFjb#Tq3jjBa%iPiMpctGCEjkEeR2Xj5R=(#A}$4H%a zc!Q_7+SP&2c}v`?KQfBix$&hQe@D26&V}gSDi#pSp6Sv6;PJ7T2Iy>Ut5?1=&G9Xj zr$2#7y%=Va@?J0Fr8(y|7|pK_%2|-Il#sH`3bLJe+rF78e+bH9ek)%L3xE8hd$?8} zt-{z*2v}rn`_lV+GkZ~;p=~j@}7YHYRFbIp&1mRa%ED+d~6{`*Pt*ubh zexaL6chP^5nJ%6@#j*DOwn{Lq9ia+sPT#%}Iq^F|N0jhNMq4f4d73OaOrH;n&uQ*J zY7Uk0z1dcNB`AZ62cCQ2*2J8d=iL%uulf;3+PyW^PqQGDM}^3NjAW}T^GC>g=>ovA zWJ|h)Kozu}^zp!b_?3LT9wo5xsNb4c8xC4!+Ay3+!L_Qae@s(GPaLX|A~?WGxw%*A zQ4^(;yWKWa)=TW9npYisw zPiLz;M-9TfI%XBv`z~H~;qo+~239jtaoo;-yJKbJb0g2doty}rm}rly#>UGRCTgH0 z_g843q}woNQgJQogah&L1r7`Fg`hX8xREw=P@KogR=eL{&kj?kIDB5e)makBO~S?a zjMp9R3w#j>p0kx{T|7UF0BQg(G+G!``M|l}@PF9nO6_iO?MZx$_sPd{eL|MZ6!fbNyAMenwXCoit6MB3yab|R2a0cjcJ7Keqm^_F4m??-93pZx*@ z1fGLTI}g4WvByVEeuExecbaH~tb8ER)o`y_S|1Blf|b3f1Go&n$yGi$qO{Y6o0t@82hgKonIjE@ zE28F)uDq8S6i>2LB1T|XjOi9wpuJ|9j49HqE@Je}3Y8DevA7yXKUt00fV2uey%>xEMV}vNxcMgZOr#ov#RiFTO*TR z(0*Jti4IuErddAg8;48?JRp{0Xgw+KS_M3Dv&3^GI*}0HGCPsoD*a$hiCHNzW+96Dx_(wY758C4g`0_Re6qi6jg
    `1mIHAEN*^hgMtBJ-R-+h55?!|ibD*m=>5zS_Io-^90ZhSu@%2s+F}aGeh%WM z^(F2cAX2WB$5R&o3jz17x&r9;Ya7EoFO!&p>rH0y^OmYSTfd!&Zjr&t3l`n#sYwc| zx234Uzbb=JjZR))ua_4C4?O)gz{}P7rh8E*VW*Gp%i(Q_-F8245cyJ`#%`OW?dAS@ zwiRzOXVsNzbF#sfO>isu7(bx2Zs^u(@R& z{uN5-9^Y42FW~>ce+Z8x?P6RXRVWa1&GGWdOS!rPXI5LvsA5I;OIv%HLx1HU4HRm! zpHc26slG8#$w8$Hs_7m#Zi#BQBMd^2aW#%Luw>OLpug1{sjM&=bfjqQuwLs`Yf(;o z`b#S*nV}01Cn)(h`poTS9Ge=B7c|FqDSMyo=l9au+Q(g>uyw@jKLAf{o_5F<9|ymX zW1m9T;v#h~J>x6V9$~e-J1bJD4^f1~*itn1`tFh}S!F4#cEx`IU`KQW0~8alKiQX+37%FqoV!?o`Ri6W z@#-K>0BI`Ijw6?YW z&na!^)voNhL|PH+iuEJg#EFb@{Zw5Z&SpR4r<}(3DOPc$LnuuD?pa&jShNmpZaX+PjYSby-w0A;g{h+|^*4G?mW0Kg%1Nszk_wC(vh1tNDz8> zSZs&mqWl&+KS`Gx{=WdoPxAR>8YR?E%B7Q;K2~-aai33<)twiqgw~R0geZyo7a?f1 z_tNX#4?yb<%QP?vYE>5{odQZ z*>gi-R*Gk(+#-2<{{=g^wl;~I8^U4NlGXj-s8e6_m^MHb-_7Do;CGCGfB<~FF zSCF6^R7Q@{!#lt;W^bP_epT7f)Y5Bnne5U$#>wMhsF?jBP^h8?3!#3XGE*p`$%%0) zmE53kQ$p>bhwhoW6v8t+qV%^~znEHe=}ulxsTmQbI(re`de9`W^#f)d%*m3hr?F*F zHIs}!>=Ie~&`b~*!J>zB^t5~N3>@lhG(eIhKXg~>=+h{7=`7M zb7TN-h#GN>;et|;ITi7tLugeT*;ffFX&<`+7>S)bSzkZ$PU;3r&%yu){xd)cUPS>o zSlsNk$6QJr{KX(bc@%~4{2HJ?Ei-W>E*21mjIqHz5$FU7d$lDPkv3Qr<|WcCM&U~%p^v8Q z-$tDe?io45PD7|04(5q)e(We9afJ~xU0+2{*jwuJ$b5hQcxUbPxOxf5C-R9qxd6OB z-dlTJm+@5$s>Qq?(1vzU+|5rdl5VDxZI0#Gd!D?0_`xkpzy zS!PG3?I;LypH&+g@>iDnqwU?za#G{;f;paTUhgEwhIn08@(DXO0W~^yFvPCn?>F7w zMXJNyYCQYWpzF0%0J1LV`g@vftTsagqNw+4=2vSzn4YmaZiTS+M|iZzv{c7HB43l0 z%Ls;aA!A^-qwBOx&;lD1hlLza+IA}SMo4XQUZD!`5bJSu5AV_16yOF)%b8Vd8p#^@ zO>&8zVy^a&HfC#|z<(bBt`%;1kTs zbhFuXS^%9w>Kq!hTpYeLQ+82=Dt%yXmo^KT?Dctu_~+$Pk_JzGQ;NIiGiX5%gBuU5 zUaziWG-x8P)%*QPjm)iM94iCptk#vmVhcT_)`ocYIjIZ=G>R)R>E~V}@b<>|X~^`e z*kfio%L9KoR!=xW8kP%Ju~*G%>FHVEb-bgRY5|JByJek6)Vv)MZ)r5z?=DmZ*UeV3 zMXB)E5cwSh%q*gAJVj0oFsC}cXpwkLt|0!dEYA88^RHh7;g5H6(wH0$f${8PfG0{R#RB>5#b!GpzHImwAg>6fKHVE z7ar^vAAERgp3Wrx^+?9iTN>xrA0n}0~ zqH=+a+ezQro2Z1C0EPK=SX4n+GPF2m<&|3l9}6j=Hvux@3V^1u63Kh+ZY6En@y%&9 z_X5QPX{N8qPNaG8>12eDYgF-~+m<>;+%UumnS=T<7H*$VSn>wJk7KTP+NWfFLQlX)5FtUf%s1OPtL^{>ka{O*^^J74^T z46>}}fIS_k4-LgkiABDf?J`W8oxWclw3BxvUrLLEgI`Y;baXZ^ltFi?`hHJO`?H;d zg0Ogb8!HxR^Jhx~tMoR59Lr`=c(zr?@7`^{;SI6^OLUsF(Lb#gcXA(_?woM3*3BCD zCl*0kO~|(2vw(xfDjR0(0-!`&%m?FQF7il`9&!oaf)L*Bc9+eMSA?7PVq=bSP8~+_kVNI9q;5eI>tDfI- zKp(T}LK%Km%~?~(E#d7y)o6LwLYaczUfPnT*c>~D?S zZ1QaNr=xA##z$9}HTlMh2-U9vgrw?DOOGqpB7}p;e0+Y9Fb=1@@|umFpS&Q%rDA%V zsKJr=sornESqgQ-A4MoUa5Z@-Jn=HHMKOWdE|_#;3kguzP&TIE;@~=3Ah55Nlsc4+ z*kl>*`77lI&(HpjyzPyT{8EC_f%HCI2slm{B*Oy~vko`%=|PUNA_)Mh7-&9`R!|!l zsXnFg1z#<1;V^eOBpHs-J!#2GT^>K)g>m^9B4;ajl@OCMcok^z)A-5%h1C{F$z*v{ zXl3D^o>AP>hTTxUXd*YSx1Z!XIv&jbh3bW*KOFxH3k1Y%B5oa^r^k8wXO}8YdVnAg zdOqY_%FT^o>$oKp9QP^6=3&oLg{Vl5jo4>-v$BP8oBA8Z?X$~5D^SggIHDZ?- zzF>GJn6@gIl@eriE^X#E%pS1$9Xg>(CXvVLD@D%rs2!`OYmJA~B`fQ=Yt7^Cuk;x$ug|XG5A#l_l znurm|gV{CV@^7C3P^HeT0i>aZOvbGt?U8#S?RP`lyU-k&62{q0mStbT*t4HzVX2+& zx+^o-6VOeeYDq-}2_;<%(VepO|41YU|NR3+oj`635GSGF3m}gL3l^XECk-`fMdzl4 z6hp$()#By7{sosmv@JxhW1)!)E*4$*6_s0Y5A1P(L=)g(j~~uQrzrVgBdDM7y%=TWl#Dyz6RFk6E4= zSP8wkAmB)jJE5W|c%{*@DSo@xH1dkZZbcITwk75Rqt&QRm z)P*vsayx2QnyJPW)G$Qs-_9@5l^*#h7HH^30f@F->lb+7H|~U|w9i*@>&*^9&=okg zCd@??mf|qxX0F3yC!`9;;U_`meo~mS#%aI58`bIkL`j>sMKr1#FaK7PA~1xz`f_nw zMMh;7=?HGz`)z=8O5doqk~yM_j9C7hhQ0mdnCwV_=B9@4fG#?Rb(5`ss@UGo%wmpH z0B{?bDCeE(#vo@oojTx!yP7paI2wf2xd&x-E2n}`_gqL5BJRt|CX&~IlbWNnsSno2 zZab^hoq(H2e(K5W!!NcFR3=l}rMkKYk-Jiec{Rtu6jTV(!l7@dc>I^C#gNL*V{2Jl zsBumczY;~>?jw~;&>%;7ByOuVoNsIU0)S(Bn9qWvbMq>QXzsWxce6G>UzqsSxzO*i z`38SU%U%_@+To=^GJKJ?WM!3}iU@B~qR4<| z)pLMB_84{+kMdM%&w|^5dst>#LU5biK!0zX*+eLFpG;MiNGfByyA1EIJF`?z1ZWYs zJt%urD%Y1Y+GUxDk*RPQ3)-vg8{}1DlyMr%+poEm9+&kM=atPs(Q0_Vx~Lv0yh1ZYl1VX?!t3FM5U5M`Gr3H+Za&FfWc- zrnBc`;Bi(`=wIE(0pH-W(g<2K0XV9~3B}c~EM!aS+gdA<+d~T6&vEi)ka-oV@Uv#z zJkNF6KXUg}9()g~@lcEF)@&;s`a0CtdMjRI6Bm70$NI3Yu)##deLf*yRz+4J19Z+W z@idQbc!gn48c=0|0b2^3Z$NS!KG6_0}$%-%VihATp!&y(IiW8xpv zK4AE0waS6fS6}?`ZWFZs7R(?6Pp`h7M|MZ+Q6a29(rF&3pCArE2chr7XuD3Uty*AO z;;AV}&y-4u-##}W+7teKWJwicImAVHahT!HEj68@ICA$G0&%C%W+w#<4s5X!)vpRin+S7|F&maeE()DB18(Ek)VWv z6VFYG7td`p9BvYg3p4uCV*hRujbCq a$T3m<6XY?6`(Mib8+Ud<%Q-+rB~ z2Uect1ED2=*|(qojR*qQ5=Jam0?=fAs<4Y}nFnIkMHgoJ}Kq(#|6Tr{u| zhVgBzr@>NOp~Rra_3_xsBSZ3?F;SsPd{n88TW@2HNgdn6aykp3Y2DIBt}1E5idsxHxlwDfsP?1 z|KnJ_+9rnFzfw#&n6{>t&FEGzC5Zi6vyi-!kVV3wd*T;e;wkyU?z1g(hWxqTScJjIk^kMcs#((RX(S zXdo>45c6jWoNUF$wJ`z%q#eMcvSh_@A=@-xx|U*5cHe9s)A3jqM_nyOv4}*Ziqw8;5$3Qxh*3} zs}T)H=wM=4pikOgpXe2aKC2Gjm?EoFGC6FtBJGkVsd2lz&y+D<3BU52(;r$Il7=Je zwnY)kpg$$al%`_jtBBTs&L9MfSth1zm&}TxM!722C|uTe15?H1>7lE?QRA8mFW>UkL3K_%K7a*m%@gqs&PoiI}er{Ii zD4EbB3>isLi#a9TE2Ze^&Ff0ebs%LyNVEqf!km^Fg=)KVr(1 zqdmJBo`cQ5hz?r9B$x4Q@NSoM?VrBu+ke+-8(E5rk1PHRYgT;m`9kZ9M5(yO+B9?W z>7HD9D&Jps$N}ReXHM&#KUNLqP2i1k2;}FfehfK2oQ#GFbn1URzr7O({7XVSq@~HzUiQRn(SIVsVX4Jow#+Se8V*t-Grjcl=lhLGsz$O(UYlG$l zT0>=Y_Z1}Oi=54{pCc;zf1NfjR!5JrEPy=othz~=qyFZ)NfjMQ61ahzC$pX`Wp961pn+n?|(?&DUKJl&PO3ad{j?-BoU~m{!Q!SxmgS&h#L` z>q=~r$-`u==b1G~OG5{=L38(7^ki$J8SusEj`q z{>Hv5?xfszKgn0NS~ewF$I_}lPJl~p!U!aj4Zt-Hu8^z4>y0_D@Vty9D^#L>=6K=; zZ%UfDh^G-Jr6X4qH8622cMwBs`quLn7R!$u@}PBOY1&UHZTIIdl&qyF&}(_WX))$C@d>=SSto@VqJ9OCOpj&Ax+GeSh=2(4|Ui2>7Ar~yi2@RD^I$F+q zuO2s?st(63}?@62s6-3v)ZAl1k;2TU7=&jXi)yf zkZLnpIA7>d=*c9MQ}i8>;Ha`74;RNPkg1Snl~~}!PO8=pP$wmsL>Z1&#$$XrVQWi~ z_lg+*_4Xe?0R;7(1hve^Siot!Vj@yAvniya&t(vS18iBDeSF#pm*V8FOg7ZK*h zuwXnMnA-UXt5&N=CQAEE-B%KOjyDZHlAM@iT%suO4A2h+TW>Qc;@tFk)tlk##^Hc^ zec$Z-%p_dX$K;V*cF{99!#!HI>vdamU~$$O>vH|K++N;G_mDPm)xYtwGudu?zWiA? zIg`djw8`i9M(3Nw|9*O|Ktv?awh6}3#vm}tz?aWy@P2i1-W@8hiD|qrYm1^ecWaBH zJqKLf0&va>}KayrLy zJCKV@JFAUm(nhWlk`5Ufoiq|aCMf{d3u7N_1!P{_Az5zow2QP{mZ2=a?jTsohOHFZ z+{CkdDTdppOrDP@;61|g99B%o2)i(Uz~-B-Z#cnOE|Y|-X}D9rWNdU+JKV3NM{C{A zfVe+-4DK1In^H;aO+#uAWFA|h^yQ7%Ke;Ob=+Ra% z%F?RH#HX+Y3ms?{-aG1^I|~G{p`U`v-c}vb$r{8suA}!jLw*giZb4ebImh52!1%)_ zz@K6CS3;f2(#AB!+|I_mSG1KuD3a3o>6Bxou8EejxIR)AHb=9a)j8;2ySVIa56Kb| zQsZn51jSXw%`yCDW`H{7RGTSL&;ir}ch45g3gL*O0L>llJme1M*H*x6XfXM#IOm-U ze#WpCYtfy0LxGI)$GIbkNg))V9)4e>sL>Wut1ZX-X=SeXV(w>-Or5aW)Wvjiptxeo zUwq9``5+|M=s1~`O&&73A#B=CtXQFwH4;txr(mj`#aL@}UY#mTN6+#zk#Q4~df$ew zkzhp8yw-Rj*XuW>65r2LrE_Bu{+zjX{&$=KC~p;Ov^wVG0+RGnS3$e^Jz_Vu;dn-Yx9=)N4OW>rIE<{ zU{%cJ=ktDVXw0R6kIyUMB2)l?=dp_xR9+K;h-BMA+{9K9FETj|xheXmJ91^_U=(m< z@z*&`{q4jnoh2#LI#pzlEQ-+_tg1v&kejH>=WtsgRHDn{+>pEe8P~AAao@atwZ^fl z{f^ykds~q%)m*ganDc7|sX_*uE+yFW+|cb(`3r`Ph*a9${@bGn<43Mna=Wp#gN=(K zY)q8?hp5DWBf$@=!FqacgU7`kJ&zsp9cS&0lnd(D);czUjP(7m%WE28&v(xq^1e>U zNkuat*~fqG&;Q5#_rK*UV^9Prz}OFb1i+nO@kk<(ByB|b4K>rvl~JjU`S#u?+3^M; zq+BBpyV|TQk)Q*4^fyQXio|aO-ojT3a#3ghq-PGY*wv0U{8iH)$z>(a5T&Vi5am_p z@EGC{t3$|9@5B{!bL%KeHbP}kANU_+S{@B0+r5Ye_Q)!PN@QFPR3pTTlB|M{C;$sP zM++76d08v8-R2Dx+MJtGb%`psd~7`4`CF<<1Za$+?acBXkIXsh z#Rcke_TFtuOLy}BrqIuuW1i{`Nj!A~%d^c;vaED>R zo~3?i9x~Rtp|Cz_*H*@zYJJCwhd^wa?@)Q!Yg$J6TIsr%AF%~q-^L9y$ZmBQKNdd zHX)uBe9?D4cQUcFk~q2WjzB98Huc~C;;qIGh2ZVRL$sb=#y}2?HOTO+(D!QKJj`<0EuPwv$a-v&FdfZ0)_#Walvb^tREED4qS!Dl-blHxqd~QuW zKaAff;1u}yxPEUZ$x*etf$ke6G0=%+3@u#uFPcaB1+!Uj*%1+STn}JI9~#&PM)k@f z#G2iH`rk%2CY`e(H_6`WoE`F`#zgGqo1Yj^Ei^jI(DRZ$;G_0*6j1$Tuh|TQscD0G zb|Mc({7!YsQqytPVl-}Qf^q0jSC=VQdby*<){9+9J?dEPka4wqN(}P$3UOVk-5{(% zqB?CUqS8F9g$Z)4^alLYY(#H@THTkdCp*1M6p`o3f;wrA(a+&tNb$ssgQ^NPubT0} ztd_Z$jAP`?50&I4)nk;~Mt*VYB zTI0f&JRweZnEY9gM+H;lZ0=McJ;FWk2p0?#|mus zk%-A~xAF<%8+D{!QSUptQpn@O{;=dF2zND@a>79q)Ik*t6{1A|vY4Cg1`mi({Jah4 zz1=vacTLg?<@cD@1MLgr-TSGE=xh%anbH~oee7I`>EgeQojR!@hyC2M0PkiaA94khl)Q4 zCGBle`Py?)0a!9lUHh;ug@$j^Z&${9uH$4gM0UJd4WH?$ThF?C>wIA{hg(lws4)wg zw}T03r{PrUBGmA%#Y*TCZzbuN*l`}l-VmxlX|*H|+a+8BeXLzcS;Pv4$OAQsYeA0m z2@k*V;WGd;7cKS-TCVw~?Hp2ec?(0zrP}HQXoCOtJ9N!_WLG$Jr9)ouk7a)L?v9>u zlM*U`=0p=q-Fw(eRpB>t%7==|y-a-l`G)Fgh@}MG^G8jj>eaG3WtF z*wcSKoJ1J`m%uM%U`>`={4(sC+IKQ%974~_s;vRt40Imc8(D7HdeK-V1Ovd`D67zh z(QB&)4IhT0j#HZV4{|q-7vuiT?}w)sy*Z;1NX4*&itZ=nJdB4JmpyI(Mv-T=#Y5s& z0U7Te<0i8c6}$_tvndn6a;xd%6dB-j)o^H#D4Xn~f>e^UWuW|-TNFPHtDe&yG z*p3WY`pby@ZNj)EPj%>x&|M;eA+Oc_k5VOTF80?yCmsHBCs^;6-hM~k_svVFO6zRq zm^-BisA?9eQojNS;6<5zKn~$Qo&fEk2)=Ir8RGs=P6y!nf8-+*wMHwyeEj|+)N*H| zZNm2ihVUtfz|`hsWMN1JLElvyAo&5vqJ5Ag51madw_E22s_m6fd6v|KU>7?g$v)Km zp?|0gNjf)&52O7S7GTUw0%i6o91u}~frM&XBZ&f<&lRd=0OC6tqDfOL$$eFAR*Nts z*m$vp;L61mD*B>HlZa`C^uRGAN4e zP|y8CQ_4=rvt(Q%f8~~K4_{^gELCDk15OL>|$`#UUmpuh7~riuxzTCdQfxI z#_AfV-KH*AI5;@zTLttD$W%C(vfwocq0Y|aHZRt*acRddTU^!uwY01z0bMWrCTqQh z#w++Fut9HJ{hjy3y@g)PiigNSJJJ1PBZ(TsjxR)tgcue`UJVVqoxr;W5d23T`yCcs zY&sfB&8Rg{HPE6~WcMjo&md^;MevWwVyHlpjS}9rc8N)9jcjS^!8g2lSefeSE@<+l zYQf-dcn4sT>=vcbpzH*MU|I@x-vnZ{Sqb!nf5&7YS(CB30tB zWx-s_N{~um)Q-9Fl0}C(K%OMcOA_6Q^m%ZSWV@XC4f~7iRt4xKl7!$!Nd~;#zg})v zY)^6Q%-jTc5IJNxRPJ{bLbr{dmJnPmhXGz~J#OD$kuL>&5d=c*`9JPY2i-rP?>;64 zkho`r8u!uoH+ojD4nht1+q`T2y|`Z-yNA@hqE-xj^}g(BD$Ak)?TDMc<`Pzr6vec^ zAG5dnzF&t;!|{>j$rbG<%=A(Br#L41IN)3-DsivSMUIRVyXj}L&}QJ6%tYgK+-rCA z?k$YIBF*YlJ<%1qGv!zz*{Gx*i;8h~tzi9%*Y|{^aMeQc=(99S(?lk07ve491nr;N zSRcdo^%>H4odsZgNJ-3Kz3`ZfLEAU@-cBDfFD|KOBBqJZ0 zMVdbrVZDTGE06Pv(Z!clJ1RYuu(!ZTe^^D}Xfk;-y_8}M zM^ZTpu)e{B;V0*xvbL_`N~zc%xIW#*5B}q|rUQ^10?>7q=aB~t3pflq<*R8cG>NAW z9bK>(P`eiZe3{~z#^h5Q%LvbfhLW@!mH=ZD{3gwTOA0Oxu7DA)?OPXlc7^^dpkrbzp25kqN~ug$ z%WY9vpvr}5%Wz0ioh;|NQN~1D|E~Xe#9{w5aSRlL=|lxAYVWL?9+UgO#N=CL!{EP>wurVRPJuP=@+kY~Zea z9{l^m#kHFc>#1xtdg~&&rTfW6cGc)2nN82Axg4md3qJ7EKwLVLQwwKpPSEBMSru-K~Kuq zpJAOtjqd~{8}$&3LV6ZHm;T)8e1L8uI0W{SX8oMmf7KMM(HpF&B_~9FWd+lDh1#x~ zwTZ^Iro+yvsJ1PXV$EGr{MQ1ZKOhAZ{iMvq0^+YU;9)r|*(m4A2^IAVxR7%h?T;#1 z&r36riIU(v&sCL|zQsIENMcwxpSO*B1VG-!`ysJ?2m;{FYljx~$}>U@bix*1+x;&H z$g>~@KOaes!Z73yL%1`3rA!#Js&v%PysXY}X8CzP9)524c3qycU2)n3KsXNl#v3$QkW`YYv}8_xPfqN6Vzv!{-KC+E-NZ`0+F%}z5B*gt(v4k*1V+9e z4t?pDv@S#$yE&3JLA>HW*KS+@?dzA?qF_6DJ!r=mJW)sMN*>*v5jTrnZ+wOpqGYh z>$|YWUwdbqZa>hC@6PVEv*+G*kP{+&%U~%QFt@^}mseGQ`Ly8aLt5-Ld$HTS_^de;)3j?G@ly9M zHh)UVj!IjI8>!(^ibCf{BPmWxCwu%zYiCD0?8r;udL%Hma6%_2jxnTFZus~`YyF6c zoyWZ^t~qIu6qRoG8dnhnu(KF&;YLIcl!n~zG6`pc{Yhy{Atu$PFE$K>s$o_EDNDfS z(kLRDgc(o^)s8G+qSvWgr!kAOQ?iEajp!pA&z)@k6xXm1VD@^%WRN74;E|3tQt87= zW^OWp4~>+P9{#AvCfAQqvf`kNC$_;IIg-|`Nuia7?8mk`GwZU@85emZJu+x>gogIdFI$>sKc0__?S<#5J@d&J(|;)OUu ziYNZvcj3dIKY#iB?Q8fk{PF8=|NQ#tU*A6e`b+E))sD+2iFAaI;lp44@#WJ^gEH*s zhYgcsc+`$b%*XJpM;IN$%M5?}7{34Bm(&-^N>A&OVQ0&dTaA#_gkLBpjfwAZNFeqZ zuIuncW9Q$&C^l|qv_4_f8@O>lVrH=2A7ain^#2IcV>tdJtRCYKnAn!|zFOE`guPIw z*e1e--m4(cBhDe%aiob;;b}{Xcoj~u^v6|<^^_w|LRY@%oTBu{tbc#|>C>*53Hcm#qVozDtaOr}tN{%# zi8>oXEelTA5Loyvo@p1^;cg?<)9&Nj~-Z(HT?oLVR>-O!{cYZrO#xx2<=gx9p#?Pi`IYXo=X?IK2WdAT_32o z9U~*%fPRbw^$PfQ>3aSx{PbcRA}?F~_R5bP`@PM0oo&5DgbAzMR4{@Gv3(EQ8Qk+U|}(yp|!yJi=y$2198(wbZdAx9}QK5tHK z(evdzMX}YH$isgPC*p+1wPkSwyW_m~lhoWss7B@2B+G^5eowN8aNYGtF75h2k1p-1 zJK)l;yRncmnjqw$i~U1krPWt|td`iImW zTX}-pwS%AFlwy*5oV(fSYxb`6)qDB|f4fkN2YuUxT09uq?l{GRq3w=SJQ#XfiM^~0 z`BiF9R?Y=MH96}nU3YF|8qeCpT*?z>OHFn_ykxem%yPbG)+4hDBn;k4y^9&8_fpRv^`b-wy! zi>W`ku-Nr*+1HDgS0p1HY3Wqu@*;q2JW6}HEsKBTv)?&xwxu28x#~)0KgQ$L`h8p| zbE^CIbc~m+S=X263iiWvz87Dv7U(BE!AouH?R>_&*cqpne1v6A2Ad@`)Huqk<1G6X zY5D)|<}s@J3*JTw9pgc71IjVp_cnl!@!Yoo9u0Xt=`Qazq_Up#a?u~n;xT;A)=155 zGns$+&vj;vcF^1WU1%9+e(58)dbj6Foi6A1EbGcL-IMHLpC2gF<32x-q-#639dL2y zz5%{nv>tlP`i-2>XmZ9&4O21Vc!u>F1Z|R^;g>f%T<^yiwxXrd^OU$l@JvZIkSPYnw&%u|eBg_^{)AI<>u0pN0C=pxdKmUj1M6 zwEdReY@gq{Z~x!>$;}X1-a0(51clDisL=mbeX~>Z#fHXn9(w;T=vH{+mo*d}Zhx*^ zHxAtAE40kn$Pz{B0R;Jh3})d~GJzKZjDay=XMlWEUYRHBq( ziY~Ym6SOL2*;PjyL(8qKAu1_#HnsSzEEe$M1FzJ!5+ zb5(;~2^x~c6&sneE1A_Ot~4E)tAA_NK5se=jVb{as}tkKP&Ay7i!o?CNw8SQ5Z3vc z7c*zl0Fq&e2FG+Urbfq4d~aUF5c6ilC>AXvMq!q6An?M=sG3k;X0Lh@;LPLlIlt!mx^Y#gSOtf`1rdaWNqh zi;FH)Z1x2)s%Tq9j9N7=K%{0Fsff`mB^5E6rK@ts8rH2d{vbFR2HJ%T@ro`~6}5_? zQdHCwL~c4t!)HPoqroATNnO6!DjR-gTcu_;XB|Zy)mEtkR9j`kpBBxFp&EFTNNLgl z1T63=1W}7XF`Wj5;?a zXB`=xxhVS;2sV-u(!(uU8)7szm=L4s>?sx}L1#~~!m`-|b_o`Zf)k`rtq7~C7t|Bv zOsxbu>)8l7Csb?~$%Q{`&mc zeb5fb;-drjL(v1^!QUSK81XUI6r#sodh|gyzxBcX5+Psi?w@{g@BZ=W%crk@y5HT8 zU;q2@fB*mZ#mDGLuK9Pp+z0pWpa1^y@mbf@mFWHK$XC~<%~7r{R-2<0KufeS|xN^qU_9;K1pplt(3L54T_I4w)?BZd$5PBf1)Bfete{?EV*Qmov zm77s+hNRm!-zRLg$ey^HgxwfP@Ztza9*4jK+_8^|P4zjS{Z#TSMrmL@mWMs-DDgm$ zV|Ma9?{-X%k$+WovKm)q*BQ&D>^ftqlsa-dhk;vq>M?_S!}{}#Ar7@+SF3wG&+s8< z9|!JcUf`>7;(q2di&jp)rWep5k=Oh)9k8>WR!GiRpxtPiBR(C#qJ&1rX-F6HTr z%RJBmrGnCe{0EK@XjYn+La`q)TV%x6|ZRcUXKD3>O zy~J+2;Peu^?TXV&>^2{M%O#h=sx~3B5I0tArn4Uxd!OUzZ*$FtY>Terg83TQ zMSrpQjH~U|_Jn~(=JtewM&`DkcfGuByM`#<`rz_hmT%Ou2cT};E?@REbC%^@-}oWR z3#y7*t!LD6VbzM{;a{&wdaaLd_yhU+T9EZVG5tQ*dUo~Dcc=}_c=czg%|TaxrP>_n z>W@|G$%kMJHEtEX876>J-Pam+zLg$`UBnC zu3XpWy0yJt{qb&XZ&!cH8xSpZ5LwVgUq&&Oz^Zn%h2=Wb7T&~B*venN) ze5hwXVf+`bLG$(FeEaB^4}Gbept#*V^xbl8@BQ=EZY+&uYd4a{>0sN|6L6{wcz@hZ z+73C3Ugjb;;t1L8Xzg84o1q+&s#VQ^T9~s^akCk`ammS0Rv#hd2~#;jYQjii#lj$> zxHcO?L~C;&B(2T11&E)Eu0C9MiH+%Q+|-wD%JAWPG>pEzP)wtz`=IGQDBmSr-jH;f z3T^iF+1PZSdASdHJ8@E?^u1#je+Vz({|04ZUOSha8yz;6F=P@Lm*C4B50`-c91eet zSWT~OrwyI=S1|0J@W9vxq$qzNRR z;<8P^gb8dE{59Js=1_-ALTxr2zq)_8rD7FsX(1=Fg>gqqY-y6v>J~wA$eFC4P{`ET zTDEYqAi`*gjTJ$w+qw`vGkL!nvQ+PfIW&1c%%Q%1#T;5K0mU3O*}RH5DjOz>IXc-2 z6mxX36)5KD%_6G?O4%XXnDL^(DHwH6%}BQ zhXrAcwkj+fF+B?AsJ<4Uiyl4}b5tLTDXIC`hB><02!lE$8_|$zDmKD8r{T3S4=;x0 z;RQG)c|3F}P8eHw@ex)E_7NQ^u#d3fvDyfOT^%(mk5)t1QmD!D=m=GfN7V7Bs-e-F z(aJ~QXE)Mdy@3;8LMwx7saSuD&@xsc2ekCDNT%fdBya&$&{DK4>4G9NXSNm?%SOJE zjIvf4WF1(H#wBA8we*efT(hkpV~*vDh+8 zL=}Je-_JjX&(;UK=Dm*wEfIjdyJ4E$C{{#qCx3hQi=!Iz@8Q4uE`0jS*Kc2c`!)O& z{`}j&zx?OFU%o|(ddpEh&9hFqEXbNK#y zTePf;#+HpB!+TOn?|y&me#=OxM&+A6Ry|I!E`DBs18ri-Py7ErI`Gu z!ElCg-OVlr+;+2z0r%bPVjyWobkC)<9P7k0%CbViD->ly3WsXMnUtY+We&lsC%+5^V!#?`Uf()-(gye8>n6jGAfJ|ZpVrt7dvGg%H z>=NspAJ>mac63CUdI&9x$Qgp0pM!^VXhlyyMsIZV+uV+a?>%XU-PtMqusc099d_rZ z<^@;bb@SnjSd?$`=O)V;ari|d&!Fb|oYDJu)K1DvNb7$BDWzLTeedZ>J>PtKQqLKz zvfI5fs)yMbto0e9Tw|L7k@dDB2^^Z$PFJ-PoK*D0jT59j8%`R#yuy?6il^M+Nxn7p zpd2|s^`IO%b!$HCPThJa1vzzVc?Z;%{KMCO**eM_cK!kLXtYP8z8y_}K)^(ISFb4>N#Uj#R{ zxnOPc7u^5)OF(%+lx_j_E!oR~gwwY3VRznkIqXi{uDg8zU2kNzrH81tH@)p|dfVH* z%x-_W^+<2fztxT2xTG&=u5!Y-1<}b#{15!3fr#qFLZjM3b^q1XR5*YL~k>Rr_;yO6}r(U4MmS4 z+xdr2J$VJ&eEq7v%|FJiUgP;{L!w>dEo*->_iH?CE#~UtVy|4gIbGw;YZe90+f&d= zv)ykhTjk!L3I2O`t@9&7;q9pJbqfA5l-0Fx{&{ot8Xf&TZ^wbI@w&I$owT_ec4uwo z!|t@rvf{a=gpB9g{o$7$x!wD5H;g>qUyUcpQL|t z>gJPm&fVM(yOWpFZujC){#a=3jn`$>9&8_thvM2(>aEbOx>bMI**h@oGiCl+?$Ge> z8KwgbzxG3O4?DU2K*O*7T+&V2^hlc@PkMzPj}mA+IbXI!+T$VOh%S#<^)2Y*{3}A~ z4@d9g>WJX~2b@D!C}nPBb98cLVQrW5A{{FMHJ34>3>TL+BOOYAVKQN2H)3NoWI1Fv zH)druF=8+{G&C|fWjJ9nF*Y$WK0IY&H8VFkGBPq{Vq-QoWidE8WM(-rGh#S7WH4kn zG%!A0AU-|{b98cLVQmU{+U;0th*eb-KKsn|-h1BXPWFH-YYMF~9W^U86)8>gQOT&8 z8d*L{k-@ZwVrfZ#r6x>Mi_E~#9zWuGeuWcoNwz4K3wQS2$b|PI1`tQ(V=;uRk13gHjQ=LdVg#9Df zFG!>}9C`$MIdw-tzX+`~+QSiy-{~y!(v`U>kxdUF{^|H{Z+HMg)Br@a13F^!4?w>bx{jn3 zcDa{v7U}9GxKgQC(Ls%z(ePHwx<&o4@?q@$C3kd>!T+V~Nc=rk!b7+KdS7_Mf7KA! zJHU<{y^Fb{{{(bo=fc0bF_Fb%uzn6I15A3)!vZva7Wd%p5vrs*CK*NOlxhoa=Q0v+ zAbaHfLVSi5j4;s1hwh8W{YlXK5(Bz-uJ+RhYwlnL0*$LtuT#ECdY_Rjnu zdhrrjRL_WpQ*(^f@Q-reXoK*7kXVYQ5i{ZDBvYNE^Az*)bzWu2OZ3j0CgMLXIPgWd4$n*zh@1m^E%?$K<<6VD;P#ryL6s&FQ266^SX zHQSFQS9{a*Y-YunTsHVH-Rv*={;R0T7Qu40BF?=6^QG*adyZIhKkMUPLtgUl;~H;< zIBUZN53CXX7YJrvpZ`{Q&lF%x=i9s>uf3cCf3jZ!|3C8EpqSXmXETlfM>R^thNNFB1>JWug~5 z1-I{EJi!CvEYt~}7rhR53jQ1;a@@n1gQ3J{RLPozbHrZbSVMmv>mQdg$7qq@{4D(h zRpP8o;J#rGF_8y|x;3XBuM!+`z2L5y0%Pd10!wFV1YaE#=W)Nlb53y4EK#?Ag#r)t zd0jd=6jX)}6!rQjg-R3bL+; z_ml!A-S*gb5&IawE3h|7>^qFQmlkzsm&b#0w~F(-hO^tTdB=#KB)5BIr@#9J;%??% zNzQl51P%qSHr%&?H$Ml~60vWc z;GA0GGZ4M=DtNB5dXALgE}9kJz9wpZLU8qR!67Z_GwjbbK{YWGWylG^YB9@V5ralJ z^vp70Kg9J8_{S>1Rm0tX3DeWn+=wm|YimU+kDJIlbN2FZZ*>JpsChH7U$H z8?{Pp62FAtc4{Bt%f0A3STOYz&ZDha0&%u}1v=heCFr}A{3@bTm{hd4;J%Bk$llrVfpyQ|n9}8dbmQ zOdT3w*VdXk{Exc1%GAM3HzWU}o~|@?Fg-Q$U+BX7rVi%aZRFpoe7&hdW0JOcM;rN1 zo&6e92O|xZj5Js>(qPF*BMp{}G*~jyV97{>B_oYASTfR=?5IhXcv9Tk8%K70TG diff --git a/docs/genindex.html b/docs/genindex.html index 05a2e23..306efb1 100644 --- a/docs/genindex.html +++ b/docs/genindex.html @@ -242,13 +242,13 @@

    Index

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/index.html b/docs/index.html index 36fa858..111914b 100644 --- a/docs/index.html +++ b/docs/index.html @@ -10,8 +10,8 @@ - - + + @@ -28,6 +28,7 @@ + @@ -262,7 +263,7 @@

    Deep R ProgrammingMinimalist Data Wrangling with Python [20].

    -

    Any bug/typos reports/fixes +

    Also, check out my other book, +Minimalist Data Wrangling with Python [20].

    +

    Any bug/typos reports/fixes are appreciated. Although available online, this is a whole course, and should be read from the beginning to the end. Please refer to the Preface for general introductory remarks and design philosophy.

    - -

    Copyright (C) 2022 by Marek Gagolewski. Some rights reserved.

    +

    Consider citing this book as: +Gagolewski M. (2023), Deep R Programming, +Zenodo, Melbourne, +ISBN: 978-0-6455719-2-9, +URL: https://deepr.gagolewski.com/.

    + + +

    Copyright (C) 2022–2023 by Marek Gagolewski. Some rights reserved.

    This material is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

    +
    @@ -466,13 +496,13 @@

    Deep R Programming

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/search.html b/docs/search.html index 623ee54..c9aaf7b 100644 --- a/docs/search.html +++ b/docs/search.html @@ -250,13 +250,13 @@

    - Copyright © 2022 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. + Copyright © 2022–2023 by Marek Gagolewski. Some rights reserved. Licensed under CC BY-NC-ND 4.0. Built with Sphinx and a customised rtd theme. - Last updated on 2022-12-28T15:36:00+1100. + Last updated on 2022-12-29T11:00:10+1100. diff --git a/docs/searchindex.js b/docs/searchindex.js index b3c932d..7788970 100644 --- a/docs/searchindex.js +++ b/docs/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["chapter/000-preface", "chapter/110-basics", "chapter/120-numeric", "chapter/130-logical", "chapter/140-list", "chapter/150-indexing", "chapter/160-character", "chapter/170-function", "chapter/180-flow", "chapter/210-design", "chapter/220-s3", "chapter/230-matrix", "chapter/240-data-frame", "chapter/250-graphics", "chapter/310-compile", "chapter/320-language", "chapter/330-environment", "chapter/340-eval-expr", "chapter/350-eval-fun", "chapter/998-changelog", "chapter/999-bibliography", "chapter/chapter-header-motd", "index"], "filenames": ["chapter/000-preface.md", "chapter/110-basics.md", "chapter/120-numeric.md", "chapter/130-logical.md", "chapter/140-list.md", "chapter/150-indexing.md", "chapter/160-character.md", "chapter/170-function.md", "chapter/180-flow.md", "chapter/210-design.md", "chapter/220-s3.md", "chapter/230-matrix.md", "chapter/240-data-frame.md", "chapter/250-graphics.md", "chapter/310-compile.md", "chapter/320-language.md", "chapter/330-environment.md", "chapter/340-eval-expr.md", "chapter/350-eval-fun.md", "chapter/998-changelog.md", "chapter/999-bibliography.md", "chapter/chapter-header-motd.md", "index.md"], "titles": ["Preface", "1. Introduction", "2. Numeric Vectors", "3. Logical Vectors", "4. Lists and Attributes", "5. Vector Indexing", "6. Character Vectors", "7. Functions", "8. Flow of Execution", "9. Designing Functions", "10. S3 Classes", "11. Matrices and Other Arrays", "12. Data Frames", "13. \ud83d\udea7 Graphics", "14. \ud83d\udea7 Interfacing Compiled Code", "15. \ud83d\udea7 Expressions", "16. \ud83d\udea7 Environments", "17. \ud83d\udea7 Evaluating Expressions", "18. \ud83d\udea7 Evaluating Functions", "Changelog", "References", "<no title>", "Deep R Programming"], "terms": {"The": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22], "open": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "access": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 21, 22], "textbook": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "deep": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "program": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21], "marek": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "gagolewski": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], "i": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], "remain": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "freeli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "avail": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "everyon": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "enjoy": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "also": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "pdf": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "It": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "non": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "profit": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "project": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "thi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "still": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "work": [0, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "progress": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "beta": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "version": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "chapter": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], "12": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], "ar": [0, 1, 2, 3, 5, 6, 8, 10, 13, 14, 15, 16, 17, 18, 19, 21, 22], "alreadi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "complet": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "more": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "In": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "meantim": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "ani": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "bug": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "typo": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "report": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], "fix": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "appreci": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "although": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "onlin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "whole": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "cours": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "should": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "read": [0, 1, 3, 4, 5, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 21, 22], "from": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "begin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "end": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "refer": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 17, 18, 21, 22], "gener": [0, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 20, 21, 22], "introductori": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "remark": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "check": [0, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "out": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "my": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "other": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 21, 22], "minimalist": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "wrangl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "python": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "20": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "50": [0, 2, 4, 5, 7, 10, 11, 12, 20], "ha": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "been": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "name": [0, 1, 5, 6, 8, 9, 10, 11, 12, 22], "eleventh": 0, "most": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 19, 22], "dread": 0, "2022": [0, 6, 10, 12, 19, 20, 22], "stackoverflow": [0, 12], "develop": [0, 7, 10, 11, 12, 14, 20, 22], "survei": [0, 10, 20], "free": [0, 1, 2, 4, 7, 8, 9, 10, 13], "app": 0, "so": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "must": [0, 5, 7, 9, 10, 11, 12], "someth": [0, 1, 2, 3, 4, 7, 8, 9, 10, 11, 12], "wrong": [0, 3, 8, 9, 10], "right": [0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 22], "But": [0, 2, 5, 7, 8, 9, 10], "whatev": [0, 2, 4, 7, 8, 9, 10, 11, 12], "deprec": [0, 9], "anywai": [0, 2, 3, 6, 8, 9, 10, 11], "modern": 0, "wai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "us": [0, 1, 2, 3, 5, 8, 9, 11, 12, 13, 22], "tidyvers": 0, "Or": [0, 1, 5, 8, 9], "we": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16], "all": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "just": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "switch": [0, 1, 8], "well": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "realli": [0, 2, 5, 6, 7, 9, 10, 12], "let": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "u": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "get": [0, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22], "one": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "thing": [0, 2, 8, 9, 10, 12], "straight": [0, 2], "statist": [0, 1, 2, 3, 5, 6, 8, 13, 20, 22], "packag": [0, 1, 2, 3, 5, 6, 8, 10, 13, 20, 22], "purpos": [0, 2, 3, 5, 7, 9], "high": [0, 9, 11], "level": [0, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], "happen": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12], "veri": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], "power": [0, 2, 3, 5, 8, 9, 12, 20, 22], "kind": [0, 1, 4, 5, 6, 7, 9, 10, 11, 12], "numer": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 20, 22], "intens": [0, 1, 14], "comput": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 22], "offer": [0, 2], "extens": [0, 2, 5, 6, 7, 8, 9, 10, 11, 20], "support": [0, 1, 2, 6, 8, 9, 10, 12], "machin": [0, 1, 3, 6, 7, 8, 11, 12, 20, 22], "learn": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 20, 22], "analysi": [0, 1, 3, 8, 9, 11, 12, 14, 20], "visualis": [0, 1, 7, 12, 14], "applic": [0, 2, 3, 6, 9], "lot": [0, 4, 5, 7, 8, 9, 10, 12], "initi": [0, 2, 6, 11], "wa": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "written": [0, 1, 2, 3, 6, 7, 8, 10, 11, 12], "statistician": 0, "therefor": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 22], "mai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "thought": [0, 5, 7, 9, 10, 11, 12], "yet": [0, 2, 4, 7, 9, 10], "capabl": [0, 4, 10], "altern": [0, 1, 3, 5, 6, 7, 8, 9, 11, 12], "stata": 0, "sa": [0, 12], "spss": 0, "statistica": 0, "minitab": 0, "weka": 0, "etc": [0, 2, 3, 4, 5, 6, 9, 11, 12, 19], "unlik": [0, 4, 5, 9, 10, 12], "some": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "them": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "howev": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "spreadsheet": [0, 12], "like": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 22], "gui": 0, "main": [0, 1, 2, 3, 4, 9, 10, 11, 12], "gatewai": 0, "perform": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "user": [0, 1, 2, 4, 7, 8, 9, 10, 12, 13, 22], "write": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 20], "code": [0, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 22], "actual": [0, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "done": [0, 1, 2, 4, 7, 9, 10, 11, 12, 14], "despit": [0, 3, 4, 9, 10, 11, 12], "curv": [0, 2], "being": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "littl": [0, 2, 4, 7, 10], "steeper": 0, "programm": [0, 1, 2, 3, 5, 7, 9, 10, 11, 12], "long": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "run": [0, 1, 2, 7, 8, 9, 10], "empow": [0, 9], "becaus": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "thei": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "limit": [0, 2, 3, 7, 9, 10, 11, 12], "onli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13], "common": [0, 2, 3, 4, 5, 8, 9, 22], "scenario": [0, 1, 4, 5, 7, 8, 9, 10, 12], "If": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "function": [0, 1, 3, 4, 6, 8, 10, 12, 19, 20, 22], "miss": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "doe": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "suit": [0, 1], "need": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "can": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "easili": [0, 1, 2, 4, 5, 7, 9, 10, 11, 12], "implement": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14], "everyth": [0, 5, 7, 9], "themselv": [0, 2, 3, 4, 6, 10], "thu": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "conveni": [0, 1, 2, 4, 6, 7, 9, 10, 11, 12], "rapid": [0, 1, 5, 8, 12], "prototyp": [0, 1, 5, 8, 12, 14], "help": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 22], "turn": [0, 1, 2, 4, 6, 7, 8, 9, 11, 12], "our": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 16], "idea": [0, 1, 2, 7, 9, 10, 11, 12], "oper": [0, 1, 4, 5, 7, 8, 22], "test": [0, 1, 2, 4, 6, 8, 10, 11, 12], "extend": [0, 3, 5, 7, 9, 12, 20], "polish": [0, 7], "product": [0, 2, 7, 9, 11], "otherwis": [0, 2, 3, 6, 7, 8, 9, 10, 11, 12], "enjoi": [0, 2, 4, 7, 11], "overal": [0, 5, 9, 10, 11, 12], "As": [0, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12], "interpret": [0, 1, 2, 3, 8, 9, 10, 11, 12, 20], "interact": [0, 5, 6, 7, 8, 9, 12], "eval": [0, 1, 10, 11, 12], "print": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "loop": [0, 1, 3, 7, 8, 11], "command": [0, 1, 7, 8, 9, 12], "result": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "question": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12], "answer": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "batch": [0, 7, 8, 12], "mode": [0, 4, 7, 10], "standalon": [0, 1, 12], "script": [0, 2, 6, 9, 12], "would": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "rather": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12], "posit": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "amongst": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12], "tool": [0, 1, 7, 9, 10, 12], "scientif": [0, 2, 3, 6, 8, 9, 11, 20], "numpi": [0, 1, 2, 7, 20], "ecosystem": 0, "julia": [0, 2, 7, 10, 12], "gnu": [0, 1, 2, 3, 6, 7, 20], "octav": [0, 2], "scilab": [0, 2], "matlab": [0, 2], "specialis": [0, 6, 7, 9, 10, 12], "scienc": [0, 1, 2, 8, 9, 10, 11, 20, 22], "than": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "henc": [0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13], "provid": [0, 2, 4, 5, 7, 9, 10, 11, 12], "much": [0, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13], "smoother": [0, 2, 5], "experi": [0, 1, 2, 5, 9, 12], "why": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "over": [0, 1, 2, 3, 6, 7, 9, 11, 12, 13, 22], "year": [0, 2, 5, 9, 10, 12], "becom": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 22], "de": [0, 3, 6, 10], "facto": [0, 6, 10], "standard": [0, 2, 4, 6, 7, 10, 11, 12, 20], "mani": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 22], "relat": [0, 2, 3, 7, 8, 9, 10, 22], "field": [0, 7, 9, 10, 12], "consist": [0, 2, 6, 9, 10, 11, 12], "featur": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "advanc": [0, 1, 6, 7, 8, 9, 10, 20], "graphic": [0, 7, 20, 22], "see": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "13": [0, 2, 4, 5, 6, 7, 9, 10, 11, 12, 13, 20], "system": [0, 1, 2, 6, 7, 9, 10, 12, 13, 20], "section": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "4": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20, 22], "interfac": [0, 2, 9, 10, 11, 22], "compil": [0, 7, 9, 11, 22], "14": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 20], "centralis": 0, "repositori": [0, 4, 7, 9, 12], "cran": [0, 1, 2, 7, 9, 11, 20], "bioconductor": [0, 7], "7": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "3": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "live": [0, 1, 5, 7, 9, 12], "commun": [0, 7, 9, 10, 12], "curiou": 0, "passion": 0, "peopl": [0, 5, 9, 10, 20, 22], "you": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 22], "me": [0, 6], "predecessor": [0, 2], "popular": [0, 2, 3, 7, 9, 10, 11, 12, 22], "1980": 0, "john": [0, 5, 20], "m": [0, 1, 2, 4, 6, 7, 8, 10, 11, 20], "chamber": [0, 20], "hi": [0, 5, 6, 9], "colleagu": 0, "bell": 0, "lab": 0, "8": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "40": [0, 4, 5, 7, 11, 12, 20], "call": [0, 1, 2, 3, 4, 5, 6, 8, 11, 12], "sourc": [0, 1, 2, 6, 8, 9, 10, 11, 12], "its": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "commerci": 0, "counterpart": [0, 3, 6, 8, 10, 11, 13], "mid": 0, "1990": 0, "2": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "robert": 0, "gentleman": [0, 20], "ross": 0, "ihaka": [0, 20], "depart": 0, "univers": [0, 1, 4, 5, 6, 9, 12, 20], "auckland": 0, "larg": [0, 2, 3, 8, 11, 12], "number": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 20], "contributor": 0, "31": [0, 2, 6, 7, 9, 10, 11, 12, 20], "histor": [0, 7, 9, 12, 13], "note": [0, 1, 2, 3, 4, 5, 6, 10, 13, 22], "c": [0, 1, 3, 4, 6, 8, 9, 10, 11, 12, 20, 22], "syntax": [0, 1, 2, 3, 6, 7, 9, 10], "involv": [0, 1, 2, 3, 4, 5, 7, 8, 10, 11, 12], "curli": [0, 8], "brace": [0, 8], "principl": [0, 3, 5, 22], "beauti": [0, 11], "heavili": [0, 9, 12], "inspir": [0, 2, 3, 9, 10, 11], "scheme": [0, 2, 5, 7, 9, 10, 11], "17": [0, 2, 3, 5, 8, 9, 10, 11, 12, 20], "detail": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "somewhat": [0, 2, 4, 8, 9, 10, 11, 12], "object": [0, 1, 3, 5, 8, 9, 11, 12, 20, 22], "orient": [0, 1, 2, 6, 7, 10, 11], "10": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "have": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "introduc": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 20, 22], "mean": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "frame": [0, 2, 4, 5, 7, 8, 9, 10, 11, 22], "formula": [0, 2, 4, 9, 11, 12, 20, 22], "reli": [0, 2, 3, 4, 7, 8, 9, 10, 11, 12], "nonstandard": [0, 9, 12], "evalu": [0, 1, 2, 3, 4, 5, 7, 12, 22], "metaprogram": [0, 7], "lm": [0, 10, 11], "ozon": 0, "solar": 0, "temp": 0, "subset": [0, 4, 7, 9, 10, 11, 22], "airqual": 0, "60": [0, 5, 6, 12], "select": [0, 1, 2, 3, 5, 6, 9, 10, 12], "month": [0, 4, 5], "dai": [0, 1, 2, 7, 9, 10, 11, 12], "summari": [0, 1, 2, 5, 12], "horribl": 0, "anoth": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "group": [0, 1, 2, 5, 6, 8, 9, 10, 11, 22], "isol": [0, 7], "base": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 22], "through": [0, 2, 5, 7, 8, 10, 11, 12], "thick": 0, "layer": [0, 12], "third": [0, 2, 4, 5, 6, 8, 9, 10, 11, 12, 22], "parti": [0, 2, 4, 5, 6, 9, 10, 11, 12, 22], "overwhelm": [0, 9], "everi": [0, 1, 2, 3, 5, 6, 7, 9, 10, 11, 12, 20], "regardless": [0, 4, 5, 6, 8, 10, 12], "complex": [0, 2, 4, 7, 9, 10, 11, 12], "differ": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "often": [0, 2, 5, 7, 8, 9, 10, 12], "duplic": [0, 7, 10, 11], "core": [0, 1, 11, 20], "sometim": [0, 1, 3, 4, 7, 8, 9, 10, 11, 12], "quit": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 19], "incompat": [0, 10, 11, 12], "tradit": [0, 10, 13], "both": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "famili": [0, 2], "fine": [0, 4, 10], "solv": [0, 2, 3, 6, 7, 8, 9, 10, 12], "simplest": [0, 2], "process": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 12, 13, 20], "problem": [0, 3, 5, 7, 8, 9, 10, 11, 12], "yearn": [0, 3], "do": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12], "want": [0, 7, 8, 9, 10, 12], "hundr": [0, 11], "prefabr": [0, 9], "recip": 0, "dish": [0, 5], "mindlessli": 0, "appli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "without": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "understand": [0, 2, 6, 7, 9, 10, 12], "which": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "suppos": [0, 5, 7, 9], "lingua": 0, "franca": 0, "abl": [0, 1, 3, 4, 5, 7, 8, 9, 10, 11, 12], "everybodi": [0, 2], "modif": [0, 9], "ten": [0, 5, 6, 12], "now": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "slang": [0, 9], "tackl": [0, 11], "furthermor": [0, 1, 4, 5, 9, 10, 11, 12], "skill": [0, 5, 7, 9, 10, 12], "transfer": [0, 12], "new": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 20, 22], "panda": [0, 7, 12], "easier": [0, 1, 5, 7, 9, 10, 13], "later": [0, 1, 2, 4, 5, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18], "notabl": 0, "enough": [0, 5, 9, 10, 12], "preach": 0, "graduat": 0, "independ": [0, 1, 2, 5, 7, 9, 11, 12, 13, 22], "reader": [0, 1, 2, 6, 7, 9, 10, 11, 12, 13], "who": [0, 5, 7, 9, 10, 11, 12, 22], "mind": [0, 2, 3, 9, 10, 11, 12], "slightli": [0, 4, 7, 10, 11, 12], "cohes": 0, "comprehens": [0, 7, 12, 22], "organis": [0, 10, 11, 12, 22], "materi": [0, 2, 9, 10, 12, 22], "benefit": [0, 7, 8, 9, 10], "first": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 16, 19], "introduct": [0, 9, 20, 22], "pamper": 0, "For": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22], "5": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "good": [0, 1, 2, 3, 4, 6, 7, 9, 10, 11, 12], "intermedi": [0, 3, 7, 9], "skip": [0, 1, 5, 8, 9], "though": [0, 1, 2, 5, 6, 7, 9, 10, 11, 12], "either": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 12], "forget": [0, 10], "prescrib": [0, 10], "exercis": [0, 22], "luck": 0, "overview": [0, 11, 20], "preval": [0, 1, 4, 10], "figur": [0, 1, 2, 3, 5, 10, 11, 13], "16": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 20], "list": [0, 1, 2, 3, 6, 7, 8, 9, 10, 19, 22], "commonli": [0, 1, 2, 4, 12], "classifi": [0, 3, 4, 5, 7, 11, 12], "follow": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "basic": [0, 1, 2, 4, 6, 7, 8, 9, 10, 12, 19], "discuss": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "part": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12], "intern": [0, 6, 7, 8, 9, 10, 20, 22], "built": [0, 2, 5, 7, 12, 13, 22], "upon": [0, 2, 3, 4, 5, 7, 8, 9, 10, 12], "ones": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "hing": 0, "atom": [0, 2, 3, 4, 7, 8, 9, 10, 11, 12, 22], "vector": [0, 7, 8, 10, 12, 13, 22], "repres": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "sequenc": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "valu": [0, 1, 2, 3, 4, 5, 6, 7, 10, 11], "where": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "element": [0, 1, 2, 6, 7, 8, 9, 10, 12, 22], "same": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "logic": [0, 1, 2, 4, 6, 7, 8, 9, 10, 12, 22], "includ": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "item": [0, 1, 2, 5, 6, 10, 11, 12], "true": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "ye": [0, 3, 5, 7, 9, 10, 11, 12], "present": [0, 1, 4, 7, 9, 10, 11, 12, 16], "fals": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "absent": 0, "na": [0, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "real": [0, 1, 2, 3, 5, 6, 7, 9, 10, 11, 12], "0": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20, 22], "0000001": 0, "charact": [0, 1, 2, 4, 7, 8, 9, 10, 11, 12, 20, 22], "6": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "contain": [0, 1, 2, 4, 5, 6, 9, 11, 12], "string": [0, 1, 2, 4, 5, 9, 10, 11, 20, 22], "e": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "g": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "gro\u00df": [0, 6], "123": [0, 2, 10, 12], "\u0434\u043e\u0431\u0440\u0438\u0439": 0, "\u0434\u0435\u043d\u044c": 0, "seri": [0, 1, 2, 3, 7, 8, 10, 11, 12], "express": [0, 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 20, 22], "line": [0, 1, 2, 5, 6, 7, 8, 9, 11, 12], "input": [0, 1, 2, 3, 4, 5, 7, 8, 10, 11], "hopefulli": [0, 7, 10], "desir": [0, 8, 9, 10, 11, 12], "outcom": [0, 1, 2, 3, 10], "instanc": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "cat": [0, 1, 6, 7, 8, 9, 10, 11, 12], "plot": [0, 1, 2, 4, 5, 7, 9, 10, 11, 12, 22], "sampl": [0, 2, 3, 4, 5, 7, 9, 11, 12], "sum": [0, 2, 4, 7, 8, 9, 10, 12], "k": [0, 2, 4, 7, 8, 9, 10, 11, 20], "store": [0, 1, 2, 3, 4, 6, 7, 8, 9, 11, 12], "mix": [0, 1, 2, 4, 5, 6, 10, 12], "abov": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22], "complement": [0, 1], "index": [0, 2, 3, 4, 6, 7, 9, 10, 12, 22], "control": [0, 6, 7, 8, 9, 10, 12, 13], "flow": [0, 1, 7, 10, 22], "compound": [0, 1, 7, 9, 10, 19], "second": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13], "wrapper": [0, 2], "around": [0, 2, 6, 8, 9, 10, 22], "might": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "behav": [0, 4, 5, 6, 9, 10, 11, 12], "underli": [0, 2, 4, 7, 9, 10, 11, 12], "primit": [0, 2, 7, 8, 12], "thank": [0, 1, 2, 4, 7, 9, 10, 12, 22], "dedic": [0, 1, 12], "overload": [0, 2, 9, 11, 12, 22], "factor": [0, 4, 5, 9, 11, 13], "qualit": [0, 7, 10], "nomin": 0, "order": [0, 1, 2, 3, 4, 8, 9, 11], "scale": [0, 2, 3, 7, 11], "matrix": [0, 2, 4, 6, 7, 9, 10, 20, 22], "11": [0, 2, 4, 5, 6, 7, 9, 10, 11, 12, 20], "tabular": [0, 2, 8, 10, 11, 12], "arrang": [0, 5, 10, 12], "row": [0, 1, 2, 4, 5, 7, 8, 9, 10], "column": [0, 1, 2, 4, 6, 7, 8, 9, 10], "each": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "cell": [0, 11], "usual": [0, 1, 2, 6, 7, 9, 10, 11, 12], "deposit": [0, 7], "time": [0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 12], "defin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "arbitrarili": [0, 7, 10, 11, 12], "s3": [0, 5, 9, 11, 12, 22], "style": [0, 6, 7, 11, 13], "sustain": [0, 7, 10, 12, 22], "9": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "prepar": [0, 2, 7], "public": [0, 7, 19, 22], "qualiti": [0, 1, 7, 22], "case": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13], "essenti": [0, 1, 4, 7], "gain": [0, 4, 8], "full": [0, 1, 5, 8, 11, 12, 13], "externalptr": [0, 10], "sec": [0, 2, 7, 8, 9, 10], "symbol": [0, 2, 6, 7], "15": [0, 2, 3, 5, 6, 7, 9, 10, 11, 12, 20], "specifi": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12], "supervis": 0, "model": [0, 2, 3, 8, 9, 10, 11, 12, 20], "within": [0, 1, 2, 4, 5, 7, 8, 9, 10, 12], "subgroup": 0, "earli": [0, 9, 22], "draft": [0, 19, 22], "placehold": [0, 4, 6, 9, 22], "pleas": [0, 1, 2, 3, 9, 10, 12, 13, 14, 15, 16, 17, 18, 22], "come": [0, 2, 3, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18], "back": [0, 1, 2, 3, 8, 9, 12, 13, 14, 15, 16, 17, 18], "approxim": [0, 2, 6, 10, 16], "surpris": [0, 2, 3, 5, 6, 8, 9, 10, 11], "few": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "ourselv": [0, 1, 2, 5, 6, 7, 8, 9, 10], "pronounc": 0, "ma": 0, "rek": 0, "gong": 0, "oliv": 0, "ski": 0, "am": [0, 1, 12], "current": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "senior": 0, "lectur": 0, "ai": [0, 6], "deakin": 0, "melbourn": [0, 12, 20], "vic": 0, "australia": 0, "associ": [0, 2, 3], "professor": 0, "research": [0, 1, 2, 7, 22], "institut": 0, "academi": 0, "interest": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 12], "particular": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "phenomena": 0, "usabl": [0, 7], "algorithm": [0, 2, 3, 5, 7, 9, 10, 11, 12, 14, 20], "studi": [0, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12], "analyt": [0, 22], "properti": [0, 2, 3, 5, 7, 8], "find": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "how": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "misus": [0, 9], "misunderstand": 0, "method": [0, 1, 2, 5, 7, 9, 12, 20, 22], "decis": [0, 3], "make": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 22], "set": [0, 2, 4, 5, 6, 7, 9, 10, 11, 12, 22], "90": [0, 2, 5, 9, 12], "journal": [0, 20], "paper": [0, 2], "outlet": 0, "proceed": [0, 8, 12], "nation": 0, "pna": 0, "inform": [0, 1, 2, 4, 7, 8, 9, 10, 11, 12], "fusion": 0, "forecast": 0, "softwar": [0, 7, 9, 10, 13, 20], "knowledg": [0, 1, 6, 7, 22], "ieee": [0, 3], "transact": [0, 20], "fuzzi": 0, "informetr": 0, "spare": 0, "student": [0, 2, 9, 22], "libr": [0, 7], "stringi": [0, 6, 9, 20], "download": [0, 1, 2, 7, 8, 9, 12], "genieclust": 0, "fast": [0, 1, 2, 9, 13], "robust": [0, 3, 5, 7, 11], "cluster": [0, 1, 8, 10, 11], "success": [0, 2, 9], "programowani": [0, 20], "w": [0, 1, 3, 4, 5, 7, 9, 11, 12, 20], "j\u0119zyku": [0, 20], "19": [0, 2, 5, 10, 11, 12, 20], "publish": [0, 2, 7, 9, 12, 19, 22], "pwn": [0, 20], "1st": [0, 2, 5, 6, 9, 11], "ed": 0, "2014": [0, 20], "2nd": [0, 2, 5, 6, 7, 9, 11, 20], "2016": [0, 12, 20], "entir": 0, "serv": [0, 2, 4, 5, 6, 7, 9, 12], "excel": 0, "testb": 0, "convei": 0, "here": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "teach": [0, 2, 6, 7, 8, 9, 11, 12], "proven": [0, 3, 10, 12], "similar": [0, 2, 3, 5, 6, 9, 10, 11, 12], "your": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 22], "truli": [0, 2, 9, 10, 11], "respons": [0, 9, 10], "warsaw": 0, "technologi": 0, "retreat": 0, "berlin": 0, "feedback": 0, "given": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "last": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12], "describ": [0, 1, 2, 5, 9, 10], "patch": [0, 10], "r83330": 0, "expect": [0, 2, 3, 4, 6, 7, 8, 9, 10, 12], "99": [0, 2, 6, 9, 11], "cover": [0, 4, 8, 9, 10, 11, 12, 13], "valid": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12], "futur": [0, 9], "releas": [0, 19, 20], "consid": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12], "file": [0, 1, 2, 4, 7, 8, 9, 11, 12, 20], "discov": [0, 2, 9, 10], "markdown": [0, 1, 7], "superset": 0, "myst": 0, "sphinx": 0, "tex": 0, "xelatex": [0, 6, 7], "chunk": [0, 1, 6, 7, 8, 9, 12], "were": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13], "knitr": [0, 1, 20], "44": [0, 1, 12, 20], "low": [0, 1, 7, 9, 13], "own": [0, 1, 2, 4, 5, 6, 7, 8, 11, 12], "templat": [0, 1], "A": [0, 1, 2, 3, 4, 5, 6, 10, 20, 22], "makefil": [0, 9], "custom": [0, 7, 9, 12], "shell": [0, 1, 7], "plugin": [0, 1], "sphinxcontrib": 0, "bibtex": 0, "proof": [0, 2, 12], "dot": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11], "j": [0, 2, 4, 5, 7, 8, 11, 20], "cross": [0, 2, 3, 4, 12], "f": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "ubuntu": 0, "mono": 0, "font": [0, 4, 6, 7], "displai": [0, 2, 4, 5, 6, 7, 9, 10, 11, 12], "typeset": 0, "text": [0, 1, 2, 3, 4, 5, 7, 8, 9, 12], "alegreya": 0, "lato": 0, "typefac": 0, "receiv": 0, "fund": 0, "administr": [0, 20], "technic": [0, 1, 4, 7, 9, 11, 20], "editori": 0, "aussi": 0, "sai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "yeah": [0, 8], "nah": 0, "49": [0, 9, 10, 11, 20], "april": [0, 4], "1997": [0, 20], "rich": [0, 10], "1991": [0, 20], "taught": 0, "wonderfulli": 0, "ambiti": [0, 9, 22], "undergradu": 0, "math": [0, 20], "approach": [0, 1, 2, 3, 5, 7, 9, 10, 11, 12], "difficult": [0, 6, 10, 12], "requir": [0, 1, 6, 7, 11, 12], "motiv": 0, "mindset": 0, "And": [0, 1, 2, 5, 6, 8, 9, 10, 11, 12], "go": [0, 1, 2, 3, 5, 7, 8, 9, 12], "neither": [0, 2, 6, 7, 9, 12], "historian": 0, "stenograph": 0, "nor": [0, 5, 6, 7, 9, 12], "grammarian": 0, "allow": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "noninvas": 0, "idealis": [0, 3], "didact": 0, "evolv": 0, "shape": [0, 9], "slowli": [0, 2], "stabl": [0, 2, 5, 11, 12], "api": [0, 2, 6, 7, 9, 10, 12, 22], "even": [0, 2, 3, 4, 5, 6, 7, 9, 10, 12], "better": [0, 2, 7, 8, 9, 10, 11, 12], "stage": [0, 9], "career": 0, "drama": [0, 12], "ideal": [0, 3, 9, 10], "give": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "try": [0, 1, 2, 4, 6, 7, 8, 9, 10, 11, 12], "35": [0, 5, 7, 11, 20], "41": [0, 2, 5, 9, 12, 20], "42": [0, 2, 5, 7, 9, 10, 11, 12, 20], "43": [0, 5, 12, 20], "automat": [0, 2, 9, 10, 11, 12], "sugar": [0, 10, 22], "salt": [0, 11], "drug": [0, 9], "healthi": [0, 9], "book": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], "prefac": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "data": [1, 3, 4, 5, 7, 8, 10, 11, 13, 14, 15, 17, 18, 20, 21, 22], "tradition": 1, "journei": 1, "start": [1, 2, 4, 6, 7, 8, 9, 11, 12], "greet": 1, "asap": 1, "hovercraft": 1, "eel": 1, "By": [1, 2, 3, 5, 7, 9, 10, 11, 12], "enclos": [1, 9], "doubl": [1, 2, 3, 4, 5, 6, 8, 10], "quot": [1, 2, 6, 9, 10, 12], "document": [1, 2, 4, 5, 7, 8, 10, 20], "practic": [1, 2, 3, 4, 6, 7, 8, 9], "worth": [1, 2, 6, 7, 9, 10, 12], "know": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 20], "hash": [1, 6], "sign": [1, 2, 6, 8], "comment": [1, 2, 4, 6, 9, 10, 11, 12], "ignor": [1, 2, 4, 5, 6, 8, 10, 11], "cannot": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "wait": [1, 3, 7, 8], "till": 1, "lunchtim": 1, "two": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13], "argument": [1, 2, 3, 4, 5, 6, 8, 11, 12, 22], "bui": [1, 2], "record": [1, 8, 12], "n": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "scratch": [1, 7, 9, 12], "newlin": [1, 7], "convent": [1, 2, 5, 9], "textual": 1, "output": [1, 2, 3, 5, 6, 7, 8, 10, 11, 12], "itself": [1, 3, 6, 7, 8, 9, 11, 12], "alwai": [1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12], "preced": [1, 7, 8, 12], "copi": [1, 2, 4, 5, 9, 22], "past": [1, 2, 6, 7, 9, 10, 11], "themself": [1, 9, 10, 11], "highli": [1, 12], "encourag": [1, 7, 9, 11, 12], "whenev": [1, 5, 11], "made": [1, 6, 7, 9, 10, 12], "round": [1, 4, 5, 6, 7, 8, 9, 10, 11, 12], "bracket": [1, 2, 5, 7, 8], "obligatori": [1, 8], "parenthes": 1, "separ": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "comma": [1, 7, 12], "constitut": [1, 7, 8, 9, 11], "consum": [1, 10, 11], "some_function_to_be_cal": 1, "argument1": 1, "argument2": 1, "natur": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "pine": 1, "abil": [1, 5, 12], "execut": [1, 2, 7, 9, 10, 22], "hand": [1, 2, 3, 4, 6, 7, 8, 9, 12, 13], "dirti": 1, "offici": [1, 9], "precompil": 1, "binari": [1, 2, 3, 5, 10], "distribut": [1, 3, 6, 7, 9, 11, 20, 22], "http": [1, 2, 6, 7, 8, 9, 11, 12, 19, 20], "org": [1, 2, 7, 9, 12, 20], "seriou": [1, 7, 11], "recommend": [1, 2, 3, 6, 7, 9, 11, 12], "sooner": [1, 9, 11], "unix": [1, 2, 6, 7, 9, 10], "variant": [1, 2, 4, 6, 11], "linux": [1, 6, 7], "proprietari": [1, 9], "far": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "o": [1, 4, 5, 6, 7, 8, 9, 20], "thereof": [1, 2, 3, 4, 5, 7, 9, 10, 11, 12], "emploi": [1, 9], "favourit": [1, 5, 9, 12], "manag": [1, 2, 4, 8, 12, 22], "apt": 1, "dnf": 1, "pacman": 1, "homebrew": 1, "wi": 1, "anaconda": 1, "miniconda": 1, "interoper": [1, 10, 11], "below": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19], "review": [1, 2, 5, 6, 7, 12], "sever": [1, 9], "benign": 1, "setup": 1, "life": [1, 2, 8, 9, 12], "singl": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "best": [1, 5, 7, 9], "repl": 1, "instant": 1, "gratif": 1, "quickli": [1, 4, 9], "determin": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "aggreg": [1, 6, 7, 9, 10], "enter": [1, 2, 6], "mathemat": [1, 3, 6, 9, 20, 22], "vari": [1, 2, 4, 6, 12], "box": [1, 2, 5, 6, 7, 9, 10], "simpli": [1, 2, 3, 9, 10, 11, 12], "termin": [1, 6, 7, 8], "folk": 1, "fire": [1, 3], "rgui": 1, "menu": 1, "when": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "default": [1, 2, 5, 6, 8, 11, 12, 22], "prompt": 1, "await": 1, "moreov": [1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12], "denot": [1, 2, 3, 5, 6, 9, 11], "continu": [1, 2, 11], "unfinish": 1, "cancel": 1, "press": [1, 10, 20], "esc": 1, "ctrl": 1, "depend": [1, 2, 3, 6, 8, 9, 10, 13], "close": [1, 2, 3, 6, 8, 9, 12], "abort": 1, "readabl": [1, 2, 3, 4, 6, 7, 8, 9, 10, 19], "never": [1, 3, 10, 11, 12], "unsuit": 1, "complic": [1, 9, 13], "task": [1, 6, 7, 8, 9, 11, 12, 14], "extrem": [1, 4, 9, 10, 11], "intervent": 1, "To": [1, 2, 3, 4, 5, 6, 11, 12, 22], "invok": [1, 10, 22], "rscript": 1, "path": [1, 2, 7, 8, 9, 12], "editor": [1, 12], "notepad": 1, "kate": 1, "vi": 1, "emac": 1, "rstudio": [1, 9], "vscodium": 1, "creat": [1, 13, 22], "Then": [1, 5, 6, 9, 11, 12], "reproduc": [1, 2], "keep": [1, 2, 3, 7, 9], "tabl": [1, 2, 3, 4, 6, 7, 8, 10, 11, 20], "auxiliari": [1, 2, 3, 7, 9, 10], "synchronis": 1, "util": [1, 5, 7, 9, 11, 12], "sweav": 1, "exampl": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "processor": 1, "latex": [1, 6, 7, 9], "html": [1, 6, 7, 9, 20, 22], "markup": [1, 7], "languag": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 20, 22], "replac": [1, 2, 3, 4, 7, 8, 10, 12, 20, 22], "yield": [1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "showcas": [1, 11], "programmat": [1, 4, 5, 7, 9, 11, 12], "could": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12], "convert": [1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "websit": 1, "pandoc": [1, 7], "docutil": 1, "facilit": [1, 9], "session": [1, 2, 7, 8, 9], "rmd": 1, "content": [1, 2, 3, 4, 5, 7, 9, 11, 12], "stuff": [1, 8, 9], "attent": [1, 2, 4, 12], "assum": [1, 2, 3, 5, 6, 7, 9, 10, 11, 12], "locat": [1, 2, 5, 7, 12], "directori": [1, 2, 6, 7, 8, 9], "compar": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 22], "knit": 1, "inspect": [1, 2, 6, 7, 9, 10, 11], "md": [1, 6, 7, 8], "extern": [1, 3, 9, 10, 12, 22], "frequent": [1, 2, 3, 6, 7, 8, 9, 10, 11, 12], "workflow": 1, "trial": [1, 2], "error": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12], "short": [1, 3, 5, 9, 12], "fragment": [1, 7], "insid": [1, 2, 5, 7, 8, 9, 10, 12], "simpl": [1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13], "load": [1, 2, 6, 7, 8, 9, 11, 12], "cleans": [1, 8], "importantli": [1, 2, 9, 10, 12], "sent": 1, "therein": [1, 5, 6, 7, 9, 11, 12], "happi": [1, 12], "correct": [1, 2, 5, 6, 9, 10, 12], "necessari": [1, 2, 3, 5, 6, 7, 8, 9, 11, 12], "There": [1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12], "integr": [1, 8, 12], "id": [1, 3, 9, 12], "addit": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "enabl": [1, 3, 4, 5, 7, 8, 9, 10, 11], "jupyterlab": 1, "individu": [1, 5, 7, 9, 12], "configur": [1, 2, 8, 9, 11], "keyboard": [1, 8, 10], "shortcut": [1, 2, 10], "shift": [1, 3, 7], "web": [1, 6, 7, 9, 12, 20], "browser": [1, 6, 9], "irkernel": 1, "conda": 1, "save": [1, 2, 3, 6], "kernel": 1, "type": [1, 2, 3, 5, 7, 8, 9, 11, 12, 19, 22], "whilst": [1, 5, 9, 10, 22], "onto": [1, 7, 11], "illustr": [1, 2, 7, 9, 10, 12], "arbitrari": [1, 2, 4, 5, 6, 7, 9, 10], "whose": [1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "handl": [1, 2, 3, 4, 5, 6, 7, 10, 22], "edit": [1, 6, 7, 11, 20], "kept": 1, "togeth": [1, 11, 12], "ipynb": 1, "json": [1, 4, 7, 8], "quick": 1, "perspect": [1, 7, 10, 12, 13], "teacher": 1, "exploratori": 1, "analys": 1, "messi": 1, "luckili": [1, 2, 7, 8, 9, 10, 11, 12], "option": [1, 4, 5, 6, 8, 9, 10, 11, 12], "export": [1, 2, 7, 8, 9, 10, 12, 20], "plain": [1, 7, 9, 12], "after": [1, 2, 4, 5, 7, 8, 9, 10, 11], "messag": [1, 8, 9, 10], "typic": [1, 2, 7, 9, 11, 12], "normal": [1, 2, 3, 9, 11, 12, 20], "proce": 1, "next": [1, 2, 3, 4, 6, 7, 9, 10, 11, 12], "arithmet": [1, 3, 4, 5, 7, 9, 10, 11, 20, 22], "comparison": [1, 2, 6, 9, 10, 11], "scalar": [1, 2, 3, 6, 8, 9, 11], "definit": [1, 2, 4, 7, 8, 9, 10, 11, 20], "arrai": [1, 2, 3, 5, 7, 8, 10, 12, 20, 22], "collect": [1, 2, 4, 5, 9, 12], "iter": [1, 2, 8, 10], "instead": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "what": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "seem": [1, 2, 9, 10, 11, 12], "datum": 1, "length": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "71828": 1, "7183": [1, 2], "ombin": [1, 2], "three": [1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "respect": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "14159": [1, 6], "12345": [1, 2, 10], "four": [1, 2, 4, 5, 6, 7, 8, 11, 12], "0000": [1, 2, 6, 7, 10, 11], "1416": [1, 6], "6000": [1, 11], "spam": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "bacon": [1, 4, 5, 6, 7, 8, 9, 10, 11, 12], "Not": [1, 7, 8, 9], "greatli": 1, "simplifi": [1, 6, 7, 9, 10, 12], "area": [1, 2, 9], "simul": [1, 2, 8, 20], "client": [1, 9], "rate": [1, 2, 4, 7], "stock": 1, "market": [1, 2], "price": [1, 7, 10], "temperatur": 1, "sensor": 1, "fact": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "oppos": [1, 6], "special": [1, 5, 6, 8, 10, 11, 12, 20, 22], "add": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12], "ons": [1, 2, 7, 12], "29": [1, 5, 7, 10, 11, 12, 20], "assur": [1, 3, 4, 5, 7, 8, 10], "absolut": [1, 2, 3, 7, 8, 9, 10], "deviat": [1, 2, 7, 9, 11], "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "effortless": [1, 10], "ab": [1, 3, 5, 6, 7, 10, 11], "Such": [1, 5, 6, 7, 8, 9, 11, 12], "easi": [1, 7, 9, 10, 11, 12, 14], "maintain": [1, 12, 22], "aim": [1, 4, 5, 7, 9, 22], "omnisci": [1, 3], "authorit": [1, 7], "about": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20, 22], "specif": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "topic": [1, 5, 7, 9, 10, 12], "page": [1, 2, 3, 4, 6, 7, 9, 10], "equival": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "sight": 1, "manual": [1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 20], "structur": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20, 22], "header": [1, 12], "titl": [1, 12], "descript": [1, 6, 9, 12], "usag": [1, 2, 9], "formal": [1, 2, 7, 9, 10, 11, 12], "paramet": [1, 2, 5, 7, 9, 10, 11, 12], "explain": [1, 2, 7, 9, 10, 11, 12], "return": [1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "further": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "link": [1, 7], "yourself": [1, 9, 10], "search": [1, 4, 7, 8, 12, 22], "vagu": 1, "oftentim": [1, 5, 7, 8, 9, 10, 11], "reliabl": [1, 7, 10], "ask": [1, 2, 5, 7, 9], "duckduckgo": 1, "gle": 1, "irrelev": 1, "distract": 1, "lose": [1, 3, 7, 12, 22], "sacr": 1, "writer": [1, 7], "form": [1, 2, 4, 6, 7, 8, 9, 10, 11, 12, 20, 22], "On": [1, 2, 3, 6, 7, 8, 9, 11, 12, 13], "contrari": [1, 8], "reflect": [1, 5, 7, 9], "thorough": 1, "investig": 1, "look": [1, 2, 4, 5, 6, 8, 9, 10, 12], "plai": [1, 2, 4, 6, 7, 10, 12], "modifi": [1, 4, 7, 8, 9, 10, 11, 12], "benefici": [1, 9, 12], "habit": [1, 10, 12], "readi": 1, "import": [1, 2, 7, 9, 10, 11, 12, 20], "theme": 1, "accord": [1, 9], "classif": [1, 3, 11, 22], "previou": [1, 2, 3, 4, 5, 7, 8, 9, 10, 12], "think": [1, 2, 3, 5, 7, 8, 9, 10], "schedul": 1, "job": [1, 5, 7, 9, 10], "least": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "virtual": [1, 9, 10, 11], "vm": 1, "chang": [1, 2, 4, 7, 8, 10, 11, 12, 19], "date": [1, 6, 12, 20], "knuth": [1, 20], "liter": [1, 20], "concept": [1, 10, 11, 12], "32": [1, 2, 4, 5, 6, 7, 10, 11, 20], "r": [2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 17, 18, 20, 21], "uttermost": 2, "fundament": [2, 4, 12], "environ": [2, 3, 4, 7, 8, 9, 10, 12, 13, 20, 22], "tensorflow": 2, "At": [2, 6, 7, 8, 9, 12], "blush": 2, "explor": [2, 5, 7, 8, 9, 11], "kindli": 2, "place": [2, 4, 5, 7, 8, 9, 10, 12], "trust": 2, "rare": [2, 4, 5, 6, 7, 9], "compris": [2, 4, 5, 6, 7, 9, 12], "educ": [2, 7, 9, 22], "plethora": 2, "possibl": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "choic": [2, 4, 6, 9, 10, 12], "build": [2, 7, 12, 14], "block": [2, 7, 8, 9, 11, 14], "reduc": [2, 5, 7, 8, 9, 10, 11, 12], "creativ": [2, 9, 22], "combin": [2, 3, 4, 5, 7, 9, 10, 11, 12], "former": [2, 5, 6, 7, 8, 9, 10, 11, 12], "found": [2, 4, 7, 8, 9, 10, 12], "aris": [2, 7, 8], "librari": [2, 3, 5, 6, 7, 8, 11, 12, 20], "gsl": [2, 3, 7, 20], "23": [2, 3, 5, 6, 7, 9, 10, 11, 12, 20], "solid": 2, "effect": [2, 3, 4, 5, 9, 10, 11, 12], "deal": [2, 4, 5, 6, 8, 9, 10, 12], "dplyr": [2, 7], "caret": [2, 6], "todai": 2, "sequel": [2, 10, 12], "advoc": [2, 7, 9], "art": [2, 9, 12, 20], "pipelin": [2, 7, 9, 10, 14], "balanc": 2, "between": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "oneself": 2, "minimis": [2, 9, 10, 11], "lazi": [2, 7, 8, 10], "stand": [2, 3, 6, 7, 8, 11], "shoulder": [2, 7], "giant": 2, "suggest": [2, 3, 8, 9, 10, 11], "self": [2, 7, 9, 10], "unless": [2, 4, 5, 7, 9, 10, 11], "explicitli": [2, 4, 7, 8, 9, 10, 11, 12], "state": [2, 3, 5, 7, 9, 10, 11, 12], "construct": [2, 6, 7, 8, 10, 11, 13, 14, 15, 16, 17, 18], "while": [2, 4, 9, 11], "unnecessari": 2, "discourag": [2, 6, 9, 10], "against": [2, 3], "take": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "up": [2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 22], "partial": [2, 5, 10, 11, 12], "solut": [2, 3, 5, 8, 9, 11], "internet": [2, 7, 8], "seek": [2, 5, 22], "relev": [2, 7, 9, 11], "those": [2, 5, 6, 7, 9, 10, 11, 12, 22], "23e": [2, 3], "000123": 2, "latter": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "notat": [2, 5, 6, 7, 8, 9, 10, 11], "small": [2, 3, 5, 6, 7, 9, 10], "magnitud": [2, 3], "equal": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "word": [2, 3, 5, 6, 7, 9, 10, 11, 12, 14], "move": [2, 6, 7, 9, 12], "decim": [2, 3, 6, 8, 9], "digit": [2, 3, 4, 6, 8, 9, 11, 12, 20], "toward": [2, 6], "left": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "inher": [2, 9, 10, 11], "temporarili": [2, 9], "unknown": [2, 7, 11], "ot": 2, "vailabl": 2, "equip": [2, 4, 5, 7, 9, 10, 11, 12, 13], "indic": [2, 5, 7, 8, 9, 10, 11, 12], "na_real_": [2, 3, 4, 5, 7, 9, 10], "null": [2, 5, 7, 8, 9, 10, 11, 12, 22], "marker": [2, 6], "databas": [2, 5, 7, 8, 9, 11, 20], "queri": [2, 7, 9, 10], "sql": [2, 5, 7, 8], "chiefli": [2, 5], "inf": [2, 4, 5, 9], "infin": 2, "infti": [2, 5], "larger": [2, 8, 9, 10, 12, 14], "largest": [2, 5, 8, 9, 11], "represent": [2, 3, 4, 6, 20], "precis": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "64": [2, 3, 5, 6, 7, 9, 11, 12], "bit": [2, 3, 4, 5, 6, 7, 10], "float": [2, 4, 6, 20], "point": [2, 4, 5, 6, 7, 8, 9, 11, 12, 20], "nan": [2, 4, 6, 8], "illeg": 2, "possibli": [2, 6, 7, 8, 9, 10, 12], "context": [2, 3, 4, 5, 6, 7, 10, 11, 12], "an": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20, 22], "ellipsi": [2, 22], "licat": 2, "tile": 2, "interestingli": [2, 5, 6, 8, 11], "behaviour": [2, 4, 5, 9, 10, 11, 12], "correspond": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "across": [2, 9, 11, 13], "notion": [2, 9, 10], "unfortun": [2, 3, 4, 6, 7, 9, 10, 11, 12], "peculiar": [2, 4, 9, 10, 11, 12], "match": [2, 4, 7, 8, 9, 10, 11, 12], "keyword": [2, 3, 7], "pass": [2, 5, 6, 8, 10, 11, 12], "mention": [2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "whether": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "rang": [2, 3, 6, 7, 9, 11, 12], "matter": [2, 3, 4, 5, 6, 10, 12], "tast": [2, 9, 10, 11], "somehow": [2, 9, 12], "rememb": [2, 5, 7, 9, 10, 12], "nevertheless": [2, 6, 7, 12], "drastic": 2, "repetit": [2, 7, 9], "pattern": [2, 4, 5, 7, 8, 22], "prone": [2, 7], "warn": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12], "zero": [2, 3, 4, 8, 10, 11], "tricki": [2, 12], "empti": [2, 5, 7, 8, 9, 12], "space": [2, 6, 7, 11], "linear": [2, 5, 7, 8, 10], "increment": [2, 6], "decrement": 2, "via": [2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "00": [2, 3, 6, 7, 9, 10, 11, 12], "75": [2, 5, 7, 8, 9, 11], "25": [2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 20], "step": 2, "seq_along": [2, 8, 9, 12], "seq_len": [2, 8, 11, 12], "drawn": [2, 9], "univari": 2, "runif": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "uniform": [2, 7, 9, 20], "287578": [2, 12], "788305": [2, 12], "408977": [2, 12], "883017": [2, 12], "940467": [2, 11, 12], "045556": [2, 8, 11, 12], "528105": 2, "rnorm": [2, 3, 8, 11, 12], "23950": 2, "10897": 2, "11724": 2, "18308": 2, "28055": 2, "72727": 2, "69018": 2, "These": [2, 3, 5, 6, 7, 8, 11, 12], "seven": [2, 5], "unit": [2, 6, 7, 9, 11], "interv": [2, 3, 7, 9], "class": [2, 3, 4, 5, 7, 9, 12, 22], "occur": [2, 7, 8, 10], "variou": [2, 3, 7, 9, 11, 12], "world": [2, 3, 9, 10, 11, 22], "prob": [2, 3], "fed": [2, 4, 6, 7, 8, 10, 11, 12], "realis": [2, 3, 7, 12], "random": [2, 3, 5, 7, 8, 9, 11, 12, 20], "variabl": [2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 22], "pr": [2, 7], "obtain": [2, 3, 4, 5, 6, 7, 11, 12], "similarli": [2, 5, 7, 8, 9, 11, 12], "synonym": [2, 3, 5, 11, 12], "danger": [2, 3], "occasion": [2, 4, 7, 8], "backfir": 2, "lead": [2, 3, 4, 5, 7, 9, 10, 12], "nonetheless": 2, "extra": [2, 4, 5, 12], "care": [2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "stress": [2, 6, 9, 10, 11, 12], "mere": [2, 3, 4, 5, 7, 9, 10], "pseudo": [2, 20], "mersenn": 2, "twister": 2, "mt19937": 2, "36": [2, 4, 9, 10, 20], "rng": 2, "24": [2, 4, 5, 7, 10, 11, 12, 20], "33": [2, 3, 5, 7, 10, 11, 12, 20], "seed": [2, 8], "re": [2, 3, 5, 7, 8, 9, 10, 12], "integ": [2, 3, 4, 5, 7, 9, 10, 11, 12], "b": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "d": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "h": [2, 4, 5, 8, 9, 10, 11, 20], "previous": [2, 5, 6, 12], "did": [2, 6, 7, 9], "crucial": [2, 7, 9, 10], "condit": [2, 3, 7, 9, 11, 22], "exactli": [2, 3, 4, 5, 6, 11, 12], "claim": 2, "unsuspici": 2, "pick": 2, "1234": 2, "mont": 2, "carlo": 2, "th": [2, 3, 5, 7, 9, 11], "anyhow": 2, "sure": [2, 3, 5, 7, 8, 9, 10, 12, 22], "accus": 2, "tamper": 2, "evid": [2, 9], "ultim": [2, 6, 7, 9, 10], "lucki": [2, 10], "1679619": 2, "total": [2, 5, 6, 7, 10, 12], "alongsid": [2, 9], "transpar": [2, 9, 10], "fulli": [2, 6, 11, 12], "trustworthi": 2, "restor": [2, 4, 12], "initialis": [2, 11], "wall": 2, "identifi": [2, 6, 9, 12], "pid": 2, "impress": [2, 10], "said": [2, 3, 4, 5, 9, 10, 11, 12], "euraud": [2, 4, 5, 7], "20200101": [2, 5, 7, 11], "20200630": [2, 5, 7, 11], "csv": [2, 4, 5, 6, 7, 8, 10, 11, 12], "eur": [2, 4], "aud": [2, 4], "exchang": [2, 4, 6, 12], "australian": 2, "dollar": [2, 5, 22], "euro": 2, "januari": [2, 4], "30": [2, 3, 4, 5, 9, 10, 11, 12, 20], "june": [2, 4], "2020": [2, 4, 20], "covid": 2, "preview": [2, 5], "coupl": [2, 6, 7, 9, 10, 11], "warehous": 2, "european": 2, "central": 2, "bank": 2, "www": [2, 6, 20], "ecb": 2, "europa": 2, "eu": 2, "stat": [2, 4, 7, 10, 12], "policy_and_exchange_r": 2, "charg": 2, "6006": [2, 4], "6031": [2, 4], "human": [2, 3, 6, 10], "wednesdai": 2, "forex": [2, 7], "observ": [2, 4, 5, 8, 9, 12], "paste0": [2, 6, 8, 9, 11, 12], "github": [2, 6, 7, 9, 11, 12], "com": [2, 6, 7, 8, 9, 11, 12, 19, 20], "gagolew": [2, 6, 7, 8, 11, 12], "raw": [2, 7, 8, 11], "master": [2, 6, 7, 8, 11, 12, 13, 20], "char": [2, 4, 6, 11, 12], "6119": [2, 4], "6251": [2, 4], "6195": [2, 4], "6193": [2, 4], "6132": [2, 4], "6117": [2, 4], "6110": [2, 4], "6188": [2, 4], "6115": [2, 4], "6122": [2, 4], "6154": 2, "21": [2, 5, 6, 7, 9, 10, 11, 12, 20], "6177": 2, "6184": 2, "6149": 2, "6127": 2, "6291": 2, "6290": 2, "6299": 2, "6412": 2, "6494": 2, "6521": 2, "6439": 2, "6282": 2, "6417": 2, "6373": 2, "6260": 2, "6175": 2, "6138": 2, "6151": 2, "6129": 2, "6142": 2, "51": [2, 5, 9, 10, 12], "6294": 2, "6363": 2, "6384": 2, "6442": 2, "6565": 2, "6672": 2, "6875": 2, "61": [2, 12], "6998": 2, "6911": 2, "6794": 2, "6917": 2, "7103": 2, "7330": 2, "7377": 2, "71": [2, 10], "7389": 2, "7674": 2, "7684": 2, "8198": 2, "8287": 2, "8568": 2, "8635": 2, "8226": 2, "81": [2, 9, 12], "8586": 2, "8315": 2, "7993": 2, "8162": 2, "8209": 2, "8021": 2, "91": [2, 12], "7967": 2, "8053": 2, "7970": 2, "8004": 2, "7790": 2, "7578": 2, "7596": 2, "reach": [2, 3, 10], "getopt": [2, 7, 10, 11], "max": [2, 3, 4, 5, 7, 8, 10, 11, 12], "omit": [2, 4, 5, 10, 11, 12], "83": [2, 20], "too": [2, 3, 5, 7, 8, 10, 11, 12], "fit": [2, 6, 8, 10, 11, 12], "url": [2, 20, 22], "home": [2, 7, 10], "portabl": [2, 6, 7, 10, 12, 20], "reason": [2, 3, 5, 6, 7, 9, 11, 12], "slash": [2, 6], "platform": [2, 7, 9, 12], "recognis": [2, 4, 12], "rel": [2, 3, 7, 9, 10, 12], "getwd": [2, 7], "side": [2, 3, 4, 5, 7, 9, 10, 11], "parent": [2, 11], "iri": [2, 4, 6, 9, 10, 11, 12, 13], "dec": [2, 5, 12], "sep": [2, 5, 6, 7, 9, 11, 12], "show": [2, 3, 4, 7, 9, 11, 12], "graph": [2, 7, 11, 20], "aforement": [2, 9], "xlab": [2, 7, 11], "ylab": [2, 7, 11], "01": [2, 4, 6, 8, 9, 10, 11, 12, 20], "06": [2, 4, 12], "182": 2, "misleadingli": 2, "appar": 2, "col": [2, 3, 5, 7, 10, 11, 12, 13], "pch": [2, 13], "cex": 2, "lty": [2, 5, 7, 11], "lwd": 2, "routin": [2, 7, 9, 11], "bring": [2, 4, 7, 12], "forth": [2, 4, 5, 7, 9, 11, 12], "memoris": 2, "assign": [2, 3, 4, 6, 7, 8, 9, 11], "bind": [2, 3, 7, 9, 11, 12], "recal": [2, 4, 5, 7, 8, 9, 10, 11, 12, 16], "dealt": [2, 10, 13], "consol": [2, 3, 4, 5, 6, 8, 9, 11], "sensit": 2, "coexist": 2, "peacefulli": 2, "tri": [2, 4, 8, 9, 11], "syntact": [2, 5, 7, 10, 12, 22], "except": [2, 4, 5, 6, 7, 9, 10, 11, 12, 22], "letter": [2, 4, 5, 6, 9, 10, 11, 12], "underlin": 2, "2wai": 2, "reserv": [2, 3, 8, 22], "explanatori": [2, 10], "friendli": [2, 3, 7, 9, 10, 12], "patient": [2, 3], "average_scor": 2, "xyz123": 2, "crap": 2, "bad": [2, 9, 10, 12], "y": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20], "z": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "matric": [2, 4, 5, 8, 9, 10, 12, 22], "l": [2, 3, 4, 5, 6, 7, 9, 11, 12, 20], "size": [2, 4, 5, 6, 8, 9, 10, 11, 12], "p": [2, 3, 4, 5, 6, 7, 8, 11, 20], "nx": [2, 8], "ny": [2, 8], "especi": [2, 3, 4, 7, 8, 9, 10, 11, 12], "temporari": [2, 7, 9, 12], "adopt": 2, "snake_cas": 2, "lowercamelcas": 2, "uppercamelcas": 2, "flatcas": 2, "coher": 2, "adher": [2, 9], "agre": [2, 3], "contribut": [2, 7, 9], "asterisk": 2, "na_omit": 2, "naomit": 2, "java": [2, 12], "habitu": 2, "dynam": [2, 6, 7, 20], "exist": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "bound": [2, 5, 7, 8, 9, 11], "100": [2, 3, 4, 5, 9, 10, 11, 12], "suppress": [2, 7, 9], "verbatim": 2, "destroi": 2, "garbag": [2, 7], "collector": 2, "got": [2, 4, 5, 9], "rid": [2, 4, 5, 8, 11, 12], "begotten": 2, "memori": [2, 3, 6, 8, 9, 10, 11, 12], "boldsymbol": [2, 3, 4, 5, 11], "x_1": [2, 5, 7, 8, 9, 11], "x_2": [2, 5, 7, 8, 9, 11], "x_n": [2, 5, 7], "x_i": [2, 5, 7, 8], "ubiquit": [2, 10], "squar": [2, 3, 5, 7, 8, 9, 10, 11], "root": [2, 7, 9], "act": [2, 3, 4, 5, 7], "transform": [2, 3, 5, 7, 9, 11], "mark": [2, 6, 11], "don": [2, 3, 9, 10], "t": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20], "produc": [2, 3, 6, 7, 8, 9, 10, 12], "4142": [2, 7, 11], "attract": [2, 13], "neg": [2, 3, 8, 10], "reckon": 2, "irrat": 2, "crude": 2, "41421356237309504880168872420969807856967187537694": 2, "aesthet": [2, 6, 13], "roughli": [2, 8, 10, 11], "shall": 2, "devil": 2, "signific": 2, "000000000000000": 2, "414213562373095": 2, "portion": [2, 9], "fraction": [2, 3, 6], "floor": [2, 9], "down": [2, 4, 8, 10], "nearest": 2, "lfloor": 2, "rfloor": 2, "ceil": 2, "lceil": 2, "rceil": 2, "trunc": 2, "0001": 2, "9999": [2, 9], "3149": 2, "19999": 2, "4567": 2, "765": 2, "4321": 2, "766": 2, "124": 2, "800": [2, 11, 12], "exp": [2, 9, 11], "euler": 2, "simeq": [2, 7], "718": [2, 9], "log": [2, 3, 4, 8, 9, 10, 11, 12], "log_": 2, "invers": [2, 5, 11, 12], "3891": 2, "0855": 2, "grow": [2, 8, 9, 11], "ident": [2, 3, 5, 7, 9, 10, 11, 12], "inequ": 2, "cdot": [2, 11], "glanc": [2, 22], "handbook": [2, 20], "38": [2, 4, 10, 20], "1000": [2, 5, 8, 9, 10, 11], "1e10": 2, "neq": [2, 11], "rapidli": 2, "1001": 2, "par": 2, "mfrow": 2, "axi": [2, 9], "v": [2, 3, 4, 5, 6, 9, 11, 12, 22], "ax": [2, 6, 11], "strictli": [2, 5], "greater": [2, 3, 5, 6, 7, 9, 10, 11, 12], "unif": 2, "norm": 2, "gamma": 2, "mathrm": [2, 3, 11], "lnorm": 2, "cauchi": 2, "lorentz": 2, "chisq": 2, "chi": 2, "snedecor": 2, "fisher": 2, "weibul": 2, "prefix": [2, 6, 12], "densiti": 2, "cumul": [2, 7], "cdf": 2, "surviv": [2, 9, 11], "sf": 2, "q": [2, 3, 4, 7, 11], "quantil": [2, 4, 5, 12], "discret": [2, 11], "enumer": [2, 10], "binom": [2, 10], "binomi": 2, "geom": 2, "geometr": 2, "poi": 2, "poisson": 2, "hyper": 2, "hypergeometr": 2, "nbinom": 2, "mass": 2, "pmf": 2, "generalis": [2, 4, 7, 9, 11, 12], "characteris": 2, "mu": [2, 3], "sigma": [2, 3], "pinpoint": [2, 3, 5, 7, 11], "mathbb": [2, 11], "sd": [2, 4, 7, 12], "dnorm": 2, "parametris": 2, "subtli": 2, "parameteris": 2, "varianc": [2, 11], "reciproc": [2, 3, 11], "advis": [2, 3, 8], "carefulli": [2, 10, 12], "dunif": 2, "dexp": 2, "dbinom": 2, "event": [2, 4, 9], "per": [2, 7, 8, 9, 10], "hour": [2, 7, 10], "hist": [2, 3, 4, 9], "draw": [2, 11, 12, 13], "histogram": 2, "estim": [2, 5, 8], "10000": [2, 3, 11], "white": [2, 3], "101": [2, 3, 5, 7, 9, 12], "\u00b5": 2, "\u03c3": 2, "belong": [2, 3], "rbeta": 2, "\u03b1": 2, "\u03b2": 2, "alpha": [2, 19], "rexp": 2, "\u03bb": 2, "lambda": 2, "break": [2, 3, 5, 7, 9, 12], "xlim": 2, "ylim": [2, 5, 10], "roll": 2, "six": [2, 5, 11, 12], "dice": [2, 8], "face": [2, 7, 9, 12], "thrown": 2, "bin": [2, 12], "bernoulli": 2, "112157": 2, "269176": 2, "296094": 2, "197396": 2, "088828": 2, "throw": [2, 8], "le": [2, 3, 7, 8, 11], "pbinom": 2, "lower": [2, 3, 6, 7, 11], "tail": [2, 8, 9, 10, 22], "12518": 2, "smallest": [2, 5, 12], "ge": [2, 3, 7, 11], "95": [2, 7, 9], "qbinom": 2, "87482": 2, "96365": 2, "rbinom": 2, "assort": 2, "certain": [2, 4, 6, 7, 9, 10], "appear": [2, 6, 7, 9, 10, 12], "sake": [2, 3, 7, 9, 10, 11, 12, 22], "breviti": 2, "int_0": 2, "dt": [2, 10], "frac": [2, 3, 4, 5, 7, 11], "tailor": [2, 11], "faster": [2, 5, 7, 8, 10, 11, 12], "dii": 2, "250": [2, 5, 11], "okai": [2, 6, 7, 9, 11, 12], "91213": 2, "172": 2, "due": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "infinit": [2, 3, 8, 10], "plenti": [2, 5, 8], "28": [2, 7, 10, 11, 12, 19, 20], "famou": [2, 9, 10], "pochhamm": 2, "_x": 2, "poch": [2, 7], "instal": [2, 6, 7, 8, 9, 20], "gsl_sf_poch": [2, 7], "1320": [2, 7], "17160": [2, 7], "240240": [2, 7], "3603600": [2, 7], "sinc": [2, 6, 7, 8, 10], "hesit": 2, "permut": [2, 5, 11, 12], "lgamma": 2, "lbeta": 2, "dbeta": [2, 9], "Its": [2, 5, 6, 10, 11, 12, 13], "classic": [2, 7], "maximum": [2, 7, 10, 11], "likelihood": 2, "subtract": [2, 3, 7, 10, 11], "multipl": [2, 3, 6, 7, 8, 9, 12], "divis": [2, 3, 5, 8, 9], "modulo": [2, 8], "remaind": [2, 9], "200": [2, 5, 11], "3000": [2, 11], "elementwis": [2, 3, 4, 5, 6, 7, 9, 10, 11], "fashion": [2, 4, 12], "multipli": [2, 6, 7, 9, 10, 11], "manner": [2, 3, 5, 8, 9, 10, 11], "00000": [2, 3, 7, 11], "33333": 2, "66667": 2, "statement": [2, 3, 5, 7, 8, 9, 10, 11, 12], "concis": [2, 4, 7, 9], "operand": [2, 8, 10, 11], "shorter": [2, 5, 8, 11, 12], "128": 2, "256": [2, 6], "512": [2, 9], "1024": [2, 5], "entireti": [2, 3, 5, 7, 8], "longer": [2, 5, 6, 8, 9, 10, 11, 12], "300": [2, 5, 11, 12], "600": [2, 11], "80": [2, 5, 9, 12], "deepli": [2, 6, 11], "22": [2, 3, 5, 6, 7, 10, 11, 12, 20], "288": [2, 4], "577": 2, "227": 2, "uniformli": 2, "pmin": 2, "pmax": [2, 3], "parallel": [2, 10, 11], "minimum": [2, 7, 11], "clip": [2, 5], "perhap": [2, 4, 6, 7, 8, 10, 11, 12], "taylor": 2, "expans": 2, "fold": [2, 6], "tensor": [2, 4], "apart": [2, 6, 7, 12], "noteworthi": [2, 3, 7, 10, 19], "unari": [2, 3, 5, 7, 11, 12], "govern": [2, 3, 9, 10], "enforc": [2, 5, 9, 10], "prioriti": 2, "doubt": [2, 9], "subexpress": [2, 6], "intend": [2, 6, 10, 12], "increas": [2, 5, 8, 9, 10, 12], "taken": [2, 3, 7, 11], "x_3": 2, "vdot": 2, "y_1": [2, 5, 7, 9], "y_2": [2, 5, 9], "y_3": 2, "y_n": [2, 5, 7], "cumsum": [2, 4, 7], "cumprod": [2, 4], "cummin": [2, 4], "cummax": [2, 4], "min": [2, 3, 4, 5, 7, 10, 11, 12], "qquad": 2, "quad": 2, "ddot": 2, "120": [2, 5], "720": 2, "5040": 2, "40320": 2, "summaris": [2, 3, 11, 12], "dispos": [2, 12], "sum_": [2, 3, 4, 5, 7, 11], "prod": [2, 7], "prod_": 2, "greatest": [2, 5, 11], "propag": [2, 3, 7, 10], "diff": [2, 5, 8, 10], "3rd": [2, 5, 9, 11], "4th": [2, 5, 6], "y_i": [2, 3, 4, 5, 11], "x_": [2, 7, 8, 11], "recreat": 2, "daili": [2, 3, 7, 12], "aud_al": 2, "remov": [2, 5, 7, 8, 9, 10, 11, 12], "ablin": [2, 11], "horizont": 2, "basi": [2, 3, 5, 8, 10, 11, 12], "var": [2, 4, 7], "unbias": 2, "median": [2, 4, 7, 12], "middl": [2, 5], "sort": [2, 5, 6, 7, 10, 11, 12], "00046535": 2, "49727780": 2, "48995025": 2, "99940453": 2, "28748391": 2, "harmon": 2, "abstract": [2, 7, 10], "sens": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "anyth": [2, 3, 4, 5, 6, 7, 10, 12], "accur": [2, 3], "financi": [2, 3], "predict": [2, 8, 9, 10], "less": [2, 3, 5, 6, 7, 8, 9, 10, 12], "miser": 2, "super": [2, 6, 9], "phd": 2, "compani": [2, 9], "crunch": [2, 7], "hobbi": 2, "unavail": [2, 10], "rm": [2, 4, 7, 8, 9, 12], "behalf": 2, "request": [2, 9, 11], "6775": 2, "accept": [2, 3, 5, 8, 9, 10, 11, 12], "trim": [2, 5], "flexibl": [2, 9, 10, 11, 12], "ever": [2, 8], "hold": [2, 3, 7, 10, 11], "vice": 2, "versa": 2, "directli": [2, 5, 6, 7, 9, 11, 12], "compress": [2, 7, 11, 12], "archiv": [2, 7, 12], "gz": [2, 6, 7, 11], "arcsin": 2, "arccosin": 2, "straightforward": [2, 4, 9, 10], "asin": 2, "pi": [2, 3, 4, 6, 9, 11], "y_min": 2, "y_max": 2, "aco": 2, "label": [2, 5, 6, 9, 10, 11, 12], "red": [2, 5, 6, 7, 10], "dash": [2, 7], "legend": 2, "topright": 2, "black": [2, 9, 10], "bg": 2, "sin": [2, 3, 11], "view": [2, 7, 11], "shown": [2, 11], "2i": [2, 7], "converg": [2, 8, 9], "000": [2, 7, 9, 10, 11, 12], "pearson": [2, 20], "correl": [2, 5, 11], "coeffici": [2, 5, 11], "x_j": 2, "y_j": 2, "cor": [2, 5, 11], "averag": [2, 5, 10, 11, 12], "currenc": [2, 4], "smoothen": 2, "convolv": 2, "filter": [2, 6, 7, 12], "tempt": [2, 9, 12], "wrap": [2, 4, 5, 6, 7, 10, 12], "announc": 2, "twitter": 2, "noth": [2, 4, 7, 8, 9, 10, 11, 12], "els": [2, 3, 4, 7, 8, 9, 10, 11, 12], "entiti": [2, 4, 7, 9, 10, 11], "necess": [2, 9], "origin": [2, 8, 9, 11, 12], "everywher": 2, "almost": [2, 3, 5, 7], "redund": [2, 7, 12], "illusori": 2, "design": [2, 4, 5, 6, 7, 8, 10, 12, 20, 22], "compact": [2, 6, 10, 12], "altrep": [2, 6, 20], "incomplet": [2, 12], "inconsist": 2, "annoi": 2, "hope": [2, 5, 9, 22], "decad": 2, "fuss": 2, "constant": [3, 6, 7, 9], "meant": [3, 6, 7, 12], "instanti": [3, 9, 10, 11], "rep": [3, 4, 6, 8, 9, 10, 11, 12], "throughout": 3, "spell": 3, "na_logical_": 3, "mental": 3, "activ": [3, 5, 6, 7, 9, 12], "recycl": [3, 5, 6, 7, 9, 10, 11, 12], "rule": [3, 4, 5, 6, 7, 9, 10, 11, 12], "incorrect": 3, "na_reals_": 3, "finit": [3, 8, 9], "imposs": [3, 6], "1415926535897932384626433": 3, "preciou": 3, "wide": [3, 4, 10, 11, 12], "consensu": 3, "had": [3, 8, 9, 10, 11, 12, 20], "format": [3, 4, 7, 9, 10, 11, 12], "pm": [3, 5], "308": 3, "79": [3, 5, 9, 10, 11, 12], "00000000000000000000000000000000000000000000000000": 3, "000000000000000000000000000000000000000000000000000000000223": 3, "79e308": 3, "17900000000000000000000000000000000000000000000000000000000": 3, "distant": 3, "byte": [3, 6, 8], "12345678901234567890123456789012345678901234": 3, "1234567890123456773699": 3, "align": [3, 6, 11], "unexpect": [3, 8, 9, 10, 12], "suspici": 3, "mislead": 3, "1000000000000000055511": 3, "3000000000000000444089": 3, "2999999999999999888978": 3, "53": [3, 5, 6, 9], "beyond": [3, 8, 9], "violat": [3, 8, 9, 12], "1102e": 3, "1023": 3, "52": [3, 5, 10], "7977e": 3, "1022": 3, "9407e": 3, "324": [3, 4], "0000e": 3, "754": 3, "27": [3, 5, 7, 10, 11, 12, 20], "26": [3, 4, 5, 7, 10, 11, 12, 20], "audienc": [3, 9, 10], "issu": [3, 7, 9, 10, 12], "resourc": [3, 8, 9, 22], "dataset": [3, 5, 6, 7, 8, 9, 10, 11, 12], "rest": [3, 4, 9], "safe": [3, 4, 5, 8, 9], "sqrt": [3, 4, 6, 7, 8, 11], "sole": [3, 10, 11], "speak": [3, 7, 9], "treat": [3, 4, 5, 6, 7, 9, 10, 12], "neglig": 3, "account": [3, 6, 8, 9, 10, 11, 12], "obvious": [3, 5, 6], "margin": 3, "varepsilon": 3, "term": [3, 8, 9, 10, 12], "measur": [3, 4, 5, 10], "bah": 3, "sleep": 3, "exact": 3, "Their": [3, 4, 7, 10], "chain": [3, 7, 10], "forbidden": 3, "situat": [3, 6, 7, 8, 10, 12], "handi": [3, 5, 12], "negat": [3, 4], "conjunct": [3, 8], "xor": 3, "exclus": [3, 5, 9], "disjunct": 3, "again": [3, 4, 5, 6, 7, 9, 10, 11, 12], "confus": [3, 9, 10], "circuit": [3, 9], "reveal": [3, 6, 9, 10, 11], "\u0142ukasiewicz": 3, "substitut": [3, 5, 6], "moment": 3, "contempl": [3, 4, 5, 8, 9], "truth": [3, 7, 11], "appropri": [3, 6, 9, 11], "zone": [3, 10], "1e": [3, 9], "1998": [3, 11, 20], "proport": [3, 8], "aspir": 3, "fluent": 3, "tautologi": 3, "morgan": 3, "law": 3, "simplif": 3, "commut": 3, "symmetri": 3, "transit": [3, 9], "until": [3, 4, 5, 7, 8, 9, 10, 11], "ll": [3, 4], "t_i": [3, 11], "l_i": 3, "f_i": 3, "560476": 3, "230177": 3, "558708": 3, "070508": [3, 12], "129288": [3, 12], "715065": [3, 12], "46092": [3, 12], "26506": [3, 12], "68685": 3, "44566": 3, "22408": 3, "35981": 3, "40077": 3, "11068": 3, "55584": 3, "78691": 3, "49785": 3, "96662": 3, "21244": 3, "49838": 3, "12947": 3, "befor": [3, 5, 7, 8, 9, 10, 11, 12, 13], "decid": [3, 5, 9, 10, 12, 22], "44386": 3, "65202": 3, "04571": 3, "53945": 3, "logarithm": [3, 9], "nest": [3, 12], "55871": 3, "71506": 3, "xy": 3, "depict": [3, 12], "mixtur": 3, "sim": 3, "100000": [3, 6], "probabl": [3, 5, 7, 8, 9, 10, 11], "gaussian": 3, "variat": [3, 5, 20], "116": 3, "earth": 3, "flat": [3, 4, 11], "smallpox": 3, "vaccin": 3, "tendenc": [3, 10], "rewrit": [3, 5, 8, 9], "prevent": [3, 8, 9, 10], "verifi": [3, 4, 5, 7, 8, 11, 12], "log1p": 3, "expm1": 3, "belov": 3, "subject": [3, 6], "entropi": [3, 4], "loss": [3, 4, 7], "randomli": [3, 10, 12], "mathcal": [3, 4, 11], "ell_i": 3, "p_i": [3, 4, 7], "hospit": 3, "symptomat": 3, "confid": 3, "tree": [3, 6, 12], "person": 3, "unwel": 3, "quantifi": 3, "penalis": 3, "strong": [3, 12], "belief": [3, 10], "encount": [3, 4, 6, 9, 10], "higher": 3, "track": [3, 9], "brain": [4, 7, 10], "teas": 4, "cool": 4, "bare": [4, 12], "touch": [4, 10], "soon": [4, 8, 9, 12], "typeof": [4, 6, 7, 10, 11, 12], "gluten": 4, "demand": [4, 9, 22], "fly": [4, 7], "seen": [4, 7, 8, 10], "distinct": [4, 7, 10, 12], "na_character_": [4, 6, 7, 10], "23e4": 4, "12300": 4, "attempt": [4, 10, 11], "compos": 4, "wherea": [4, 11], "tend": [4, 5, 7, 9, 12], "wiser": 4, "unequivoc": 4, "1e9": 4, "pre": [4, 8], "alloc": [4, 6, 8, 10, 12], "vectoris": [4, 6, 8, 9, 12, 22], "ifels": [4, 8, 12, 22], "seamlessli": [4, 6], "translat": [4, 9, 10, 11, 12], "equat": 4, "recurs": [4, 5, 6, 7, 8], "wherev": [4, 8, 9], "multitud": 4, "notic": [4, 7, 11, 12], "overli": [4, 9], "talk": [4, 7], "18": [4, 5, 6, 7, 9, 10, 11, 12, 20], "28758": [4, 8, 12], "78831": [4, 12], "40898": [4, 12], "88302": [4, 12], "94047": [4, 12], "str": [4, 5, 10, 11, 12], "logi": [4, 12], "chr": [4, 10, 11, 12], "num": [4, 5, 10, 12], "788": 4, "409": 4, "883": 4, "94": [4, 5, 9, 11, 12], "retain": [4, 9, 12], "bytecod": [4, 7, 9, 10], "0x563242a38f18": 4, "namespac": [4, 7, 9, 10, 22], "concaten": [4, 7, 11, 12], "repeat": [4, 5, 6, 7, 9, 11, 12, 22], "flatten": [4, 6, 8], "unlist": [4, 7, 8, 9, 10, 11, 12], "simplify2arrai": [4, 9, 11, 12], "absenc": 4, "februari": 4, "march": [4, 12], "juli": 4, "august": 4, "septemb": [4, 6], "octob": [4, 12], "novemb": 4, "decemb": 4, "ness": 4, "alik": 4, "emplac": [4, 9], "semant": [4, 9], "invisibli": [4, 9], "inject": [4, 10], "unord": 4, "kei": [4, 5, 6, 9, 10, 12], "pair": [4, 5, 6, 8, 9, 11, 12], "x_simpl": 4, "attribute1": 4, "value1": 4, "attribute2": 4, "attr": [4, 5, 6, 9, 10, 11, 12], "concern": [4, 5, 6, 10, 12], "tini": [4, 5], "metadata": [4, 9], "ordinari": [4, 9, 10, 11, 12], "55": [4, 5, 7], "perk": 4, "pai": [4, 9, 12], "sneak": 4, "70": [4, 5, 10, 12], "y_na_fre": 4, "action": [4, 7, 9], "tell": [4, 9, 10], "gregexpr": [4, 6], "needl": [4, 6], "OR": 4, "haystack": [4, 6], "spammer": 4, "po": 4, "usebyt": [4, 6], "sought": [4, 7], "occurr": [4, 7, 8, 10], "gbp": 4, "usd": 4, "eurgbp": [4, 7], "eurusd": [4, 6, 7], "currency_from": 4, "currency_to": 4, "date_from": 4, "date_to": 4, "great": [4, 9, 12], "potenti": [4, 5, 9, 10, 12], "wast": [4, 7], "pessimist": 4, "realist": 4, "predestin": 4, "role": [4, 7, 12], "dimnam": [4, 5, 9, 11, 12], "dim": [4, 5, 7, 9, 10, 11, 12], "map": [4, 5, 6, 8, 9, 10, 11, 12], "spite": 4, "whatsoev": [4, 9, 11], "accessor": [4, 5, 11], "meaning": [4, 12], "sausag": [4, 10], "celeri": 4, "improv": [4, 7, 9, 10], "garner": [4, 12], "nice": [4, 5, 6, 8, 9, 12, 14], "additional_attribut": 4, "presenc": [4, 7, 9, 22], "smart": [4, 7], "scipen": 4, "width": [4, 6, 9, 10, 12, 13], "bore": [4, 7, 9], "df": [4, 10, 12], "head": [4, 6, 8, 9, 10, 12, 22], "sepal": [4, 9, 10, 11, 12, 13], "petal": [4, 9, 10, 12, 13], "speci": [4, 9, 10, 11, 12, 13], "setosa": [4, 9, 11, 12], "unclass": [4, 10, 11], "versicolor": [4, 9, 10, 11, 12], "virginica": [4, 9, 10, 11, 12], "value2": 4, "attribute3": 4, "value3": 4, "unset": [4, 10], "onc": [4, 8, 9, 10, 11, 12], "attribute4": 4, "ad": [4, 8, 10, 12], "un": [4, 7], "unnam": [4, 5, 11, 12], "some_attribut": 4, "new_valu": 4, "preserv": [4, 10, 11, 12, 22], "That": [4, 9, 10, 11, 12], "join": [4, 6, 11], "unwound": 4, "readrd": 4, "serialis": 4, "snapshot": 4, "disk": [4, 8, 9], "saverd": 4, "jsonlit": [4, 12], "fromjson": 4, "rejoic": 4, "devot": [4, 9, 12], "delici": [4, 5], "stimul": 4, "lightweight": [5, 9, 10], "fetch": [5, 6, 7, 10, 11, 12], "wish": [5, 7, 9, 10, 11], "big": [5, 8], "retriev": [5, 12], "seq": [5, 6, 7, 9, 10], "wonder": [5, 9], "110": [5, 11, 12], "130": [5, 10], "140": 5, "150": [5, 10, 12], "160": [5, 12], "170": 5, "180": 5, "190": [5, 12], "210": 5, "220": 5, "230": 5, "240": 5, "260": [5, 10, 12], "270": 5, "280": 5, "290": 5, "310": 5, "320": [5, 12], "330": 5, "340": 5, "350": [5, 12], "360": [5, 12], "370": 5, "380": 5, "390": 5, "400": [5, 11, 12], "410": 5, "420": 5, "430": 5, "440": [5, 12], "450": 5, "460": [5, 12], "470": 5, "480": 5, "490": 5, "500": [5, 11, 12], "510": 5, "visual": [5, 7], "hint": [5, 7], "boundari": [5, 9, 10], "stori": [5, 9, 10, 11, 12], "compon": [5, 6, 7, 9, 10, 11], "dig": [5, 7], "subscript": 5, "smaller": [5, 6], "exclud": 5, "consecut": [5, 7, 8, 9, 12], "ampl": 5, "perfect": [5, 14], "candid": [5, 12], "7777": 5, "log10": 5, "pseudorandom": [5, 8, 9, 11], "88": [5, 10, 11, 12], "05": [5, 9, 10, 12], "89": [5, 9], "46": [5, 12, 20], "birth": 5, "graham": 5, "terri": 5, "eric": 5, "michael": 5, "food": [5, 8, 9, 12], "egg": [5, 6, 7, 8, 9, 10, 11, 12], "bean": 5, "1941": 5, "1939": 5, "1942": 5, "1943": 5, "1940": 5, "born": 5, "lover": 5, "ag": [5, 9, 11, 12], "1969": [5, 10], "didn": 5, "utmostli": 5, "top": [5, 8, 9, 10, 12, 13], "unwrap": 5, "uniqu": [5, 6, 7, 8, 10, 11, 12], "direct": [5, 7, 9, 10, 11, 12], "workaround": [5, 10, 11, 12], "avoid": [5, 7, 8, 9, 11, 12], "repertoir": 5, "steve": 5, "pout": 5, "old": [5, 6, 9, 10, 12], "implicit": [5, 6, 10, 11, 12], "coercion": [5, 6, 8, 10, 12], "pour": 5, "wineskin": 5, "final": [5, 8, 10], "brought": [5, 11], "becam": [5, 11, 12], "forgotten": [5, 10], "alter": [5, 8, 9, 10, 11, 12], "safest": 5, "102": 5, "103": [5, 11, 20], "104": 5, "105": [5, 11], "106": [5, 12], "107": 5, "108": [5, 9, 12], "109": 5, "sub": [5, 6, 7, 11, 12], "idx": 5, "wrote": [5, 9], "drop": [5, 6, 8, 9, 10, 12], "push": [5, 9], "unlabel": 5, "blank": [5, 12], "five": [5, 9, 12], "slice": [5, 10], "intertwin": 5, "lefthand": [5, 10], "asid": 5, "ham": [5, 6, 7, 8, 12], "abb": 5, "jan": 5, "feb": 5, "mar": 5, "apr": 5, "jun": 5, "jul": 5, "aug": 5, "oct": 5, "nov": 5, "findinterv": [5, 8, 10], "inclus": [5, 6, 9], "knot": 5, "cccc": [5, 7, 11], "footnotes": 5, "66": 5, "member": [5, 11], "divid": [5, 6, 7, 10, 11], "pigeonhol": 5, "unsurprisingli": [5, 9], "z1": 5, "z2": 5, "toothgrowth": [5, 12], "experiment": 5, "guinea": 5, "pig": 5, "vitamin": 5, "supp": [5, 12], "lement": 5, "dose": [5, 12], "growth": [5, 8], "rodent": 5, "teeth": 5, "len": [5, 12], "gth": 5, "attrib": 5, "57": [5, 11, 12], "vc": [5, 12], "oj": [5, 12], "_": [5, 11], "oj_0": 5, "vc_0": 5, "oj_1": 5, "vc_1": 5, "oj_2": 5, "vc_2": 5, "medit": 5, "consciou": [5, 10], "avg": [5, 12], "BY": [5, 12, 22], "hurri": 5, "appetis": 5, "feed": [5, 9], "boxplot": [5, 10], "whisker": 5, "unsplit": [5, 7, 12], "revok": 5, "some_transform": 5, "standardis": [5, 7, 9, 11, 12], "666": [5, 10], "32787": 5, "bass": 5, "aaargh": 5, "aargh": 5, "aaaargh": 5, "lexicograph": [5, 6, 10], "dictionari": 5, "ow": [5, 7, 9, 10], "ti": [5, 6, 7, 9, 12], "guarante": [5, 9, 10, 12], "nonincreas": 5, "decreas": [5, 10, 12], "induc": 5, "speed": [5, 10, 11, 12], "bottleneck": [5, 9], "bother": 5, "pleasant": [5, 9], "expand": [5, 9, 12], "footprint": 5, "unsort": 5, "criteria": [5, 12], "resolv": 5, "rearrang": 5, "y1": [5, 7, 10], "y2": [5, 7, 10], "rank": [5, 6, 12], "7th": 5, "broken": 5, "proper": [5, 11], "theoret": [5, 12], "union": [5, 7, 12], "tabul": [5, 7, 10, 11], "conceiv": 5, "author": [5, 7, 9, 10, 11, 22], "put": [5, 7, 8], "spend": [5, 9], "strategi": [5, 7, 9], "48": [5, 6, 10, 11, 20], "attrib1": 5, "necessarili": [5, 6, 8, 9, 10, 11, 12], "adjust": [5, 11, 12], "accordingli": [5, 11], "prefer": [5, 7, 8, 9, 11, 12], "attrib2": 5, "4000": 5, "suffic": [5, 10, 11, 12], "significantli": [5, 10, 12], "mistak": [5, 10], "8th": 5, "9th": 5, "5th": 5, "propos": [5, 7, 10], "winsoris": 5, "q_p": 5, "q_": 5, "spearman": 5, "varrho": 5, "mathbf": [5, 11], "d_i": 5, "r_i": [5, 11], "s_i": 5, "approx": [5, 12], "interpol": [5, 7, 9, 12], "linearli": [5, 9, 12], "unobserv": 5, "somewher": [5, 9, 10], "spline": [5, 7], "cubic": 5, "x_new": 5, "y_new1": 5, "xout": 5, "y_new2": 5, "blue": 5, "piecewis": [5, 7], "imput": 5, "62": [5, 10, 11, 12], "58": [5, 9, 12], "fill": [5, 9, 11, 12], "63": [5, 9, 12], "rev": 5, "choos": [5, 8, 9, 10, 22], "fulfil": [5, 7, 9], "intersect": 5, "setdiff": 5, "setequ": 5, "cheapli": 5, "flag": [5, 12], "fantast": [5, 9], "econom": 6, "effici": [6, 8, 9, 10, 11, 12], "wow": 6, "innit": 6, "delimit": [6, 7], "apostroph": 6, "li": 6, "ol": 6, "love": [6, 7, 9, 12], "escap": [6, 8], "embrac": [6, 7], "backslash": 6, "implicitli": [6, 9], "nchar": 6, "disabl": 6, "devic": 6, "cursor": 6, "backspac": 6, "tab": [6, 7, 12], "stop": [6, 8, 9, 10], "carriag": 6, "abc": 6, "bd": [6, 11], "tef": 6, "rg": 6, "nhij": 6, "gbd": 6, "ef": 6, "hij": 6, "unbuff": 6, "stderr": [6, 7, 8], "statu": 6, "anim": 6, "bar": [6, 12], "eta": 6, "ecma": 6, "ansi": 6, "x3": [6, 7, 10, 12], "u001b": 6, "colour": [6, 9, 13], "31m": 6, "bold": [6, 7], "0m": 6, "reset": [6, 10, 12], "31mspam": 6, "36m": 6, "abacon": 6, "espam": 6, "unicod": [6, 20], "149": 6, "186": 6, "emoji": 6, "chart": 6, "invert": 6, "exclam": 6, "latin": 6, "supplement": 6, "hexadecim": 6, "0xa1": 6, "161": 6, "magic": [6, 10], "uxxxx": 6, "uxxxxxxxx": 6, "eight": 6, "u00a1": 6, "u000000a1": 6, "utf": 6, "encod": [6, 10, 11], "nativ": [6, 10], "latin1": 6, "cp1252": 6, "iconv": 6, "render": 6, "unabl": [6, 9], "ey": [6, 9], "joy": 6, "none": [6, 9], "glyph": 6, "properli": [6, 9, 11], "cordial": 6, "u0001f642": 6, "u2665": 6, "u0bb8": 6, "u0001f923": 6, "u0001f60d": 6, "u2307": 6, "\u0bb8": 6, "trivial": [6, 8, 9], "a1": [6, 7, 12], "b2": [6, 12], "c3": [6, 12], "collaps": [6, 9, 10, 11], "a1b2c1d2": 6, "customis": 6, "pretti": [6, 8, 10, 12], "123456": 6, "789": 6, "7890": 6, "drop0trail": 6, "1415927": 6, "sprintf": [6, 7, 8, 10, 11], "workhors": [6, 11], "justif": 6, "percent": 6, "2f": 6, "occupi": 6, "insert": [6, 11, 12], "5f": 6, "az": 6, "1f": 6, "142": 6, "readlin": [6, 8, 12], "readm": [6, 8], "train": [6, 12], "hard": [6, 9, 11, 12], "writelin": 6, "append": 6, "deriv": [6, 11], "bytewis": 6, "german": 6, "deem": [6, 12], "gross": 6, "unnormalis": 6, "nfc": 6, "canon": 6, "consider": [6, 10, 12], "startswith": 6, "spamtast": 6, "spontan": 6, "spoon": 6, "endswith": 6, "suffix": 6, "charmatch": 6, "sp": 6, "spoo": 6, "spoof": 6, "ambigu": 6, "arg": [6, 7, 9, 11], "grepl": [6, 7], "spammit": 6, "yummi": [6, 9, 12], "sram": 6, "regex": 6, "grep": [6, 9, 12], "familiar": [6, 7, 10, 11], "curios": [6, 12], "agrepl": 6, "levenshtein": [6, 11], "distanc": [6, 8, 11], "perl": [6, 7], "pcre2": 6, "man": [6, 9], "pcre2pattern": 6, "er": 6, "tre": 6, "poorer": 6, "air_quality_1973": 6, "anscomb": 6, "titan": [6, 9, 11, 12], "tooth_growth": 6, "world_phon": 6, "regexpr": 6, "3th": 6, "attribut": [6, 7, 10, 11, 12, 22], "worthwhil": 6, "global": [6, 9, 10], "insensit": 6, "clever": 6, "along": 6, "aid": 6, "meanwhil": 6, "regmatch": 6, "parenthesis": 6, "captur": 6, "basenam": 6, "unpack": 6, "something_els": 6, "txt": 6, "regexec": 6, "gregexec": 6, "gsub": 6, "hammit": 6, "thereto": [6, 11, 12], "aha": 6, "gag": 6, "palindrom": 6, "glob2rx": 6, "wildcard": 6, "strsplit": 6, "spammiti": 6, "10th": 6, "exce": 6, "chickpea": 6, "composit": 6, "tolow": 6, "toupper": 6, "upper": [6, 8, 11], "chartr": 6, "window": [6, 7], "cmd": [6, 9], "ex": [6, 9], "xtfrm": [6, 10, 12], "ch\u0142odni": 6, "hardi": 6, "chladn\u00fd": 6, "hladn\u00fd": 6, "local": [6, 7, 10, 12, 22], "sy": [6, 7, 10, 12], "getlocal": 6, "lc_collat": 6, "slovak": 6, "transmit": [6, 8], "1970": [6, 10], "gmt": [6, 10], "strptime": [6, 10], "strftime": [6, 10, 12], "stringx": [6, 7, 9, 10, 20], "icu": [6, 7], "suppresspackagestartupmessag": 6, "sk_sk": 6, "gro": 6, "u00df": 6, "detach": 6, "unload": 6, "pictur": 6, "briefli": [6, 11, 12], "1l": [6, 7, 11, 12], "2l": [6, 11], "na_integer_": 6, "truncat": [6, 12], "vast": 6, "major": [6, 9, 11, 22], "silent": 6, "coerc": [6, 8, 10, 12], "distinguish": 6, "maxim": [6, 7], "contigu": 6, "overflow": [6, 7], "ok": 6, "lost": [6, 9, 11], "fp": 6, "neat": 6, "unsign": 6, "255": [6, 11], "0xc0": 6, "254": 6, "02": [6, 10, 12], "c0": [6, 12], "fe": 6, "ff": 6, "0x": 6, "readbin": [6, 11], "chartoraw": 6, "rawtochar": 6, "1i": [6, 11], "imaginari": 6, "engin": [6, 7, 9, 12], "physic": 6, "electron": 6, "signal": [6, 11], "na_complex_": 6, "0000i": 6, "1416i": 6, "procedur": [6, 10, 12], "fft": [6, 11], "qr": 6, "svd": 6, "tinker": [6, 7, 9], "aubergin": [6, 12], "aaron": 6, "zorro": 6, "pastena": 6, "mib": 6, "paragraph": 6, "banal": 6, "prose": 6, "strwrap": 6, "dirnam": [6, 7], "trimw": 6, "hashtag": 6, "email": 6, "address": [6, 7], "hyperlink": 6, "42i": 6, "42l": 6, "0x42": 6, "stri_sort": 6, "a2": [6, 7, 12], "a10": 6, "a11": 6, "a100": 6, "formatt": [6, 10], "ascii": 6, "english": 6, "punctuat": 6, "a\u00dfc": 6, "\u0105\u00df": 6, "stri_pad": 6, "cach": [6, 7, 10], "clone": [6, 7], "ram": [6, 8, 12], "39": [6, 10, 20], "heavi": 6, "fiddl": 7, "dozen": 7, "vocabulari": [7, 9, 10, 12], "fluentli": 7, "achiev": [7, 9, 10, 11, 12], "goal": [7, 9], "under": [7, 9, 10, 13, 14, 15, 16, 17, 18, 22], "hood": [7, 9, 10], "nanosecond": 7, "malai": 7, "thereov": 7, "x1": [7, 10], "x2": [7, 10], "bunch": 7, "6545": 7, "borderlin": 7, "56203": 7, "tediou": [7, 9], "barbar": 7, "57206": 7, "concret": [7, 10], "50824": 7, "reinvent": [7, 9], "wheel": 7, "stack": [7, 12], "analyst": 7, "monoton": 7, "dreari": 7, "uninspir": 7, "plu": [7, 12], "quicker": 7, "dump": [7, 12], "pearl": 7, "minim": [7, 9], "bodi": [7, 8, 9], "disappear": 7, "immedi": [7, 8], "thereaft": [7, 9, 10], "arg1": 7, "argn": 7, "closur": [7, 10], "builtin": 7, "yesterdai": 7, "distil": 7, "concat": 7, "faithfulli": 7, "plead": 7, "guilti": [7, 9], "needlessli": 7, "anyon": [7, 11], "provis": 7, "spam1": 7, "spam2": 7, "spam3": 7, "spam4": 7, "spam5": 7, "contrast": 7, "dure": [7, 9, 10, 12], "caller": [7, 8, 9, 10], "se": [7, 9], "unambigu": 7, "manipul": [7, 9, 10, 12], "perfectli": [7, 10, 12], "position": 7, "particularli": [7, 8, 10, 11, 12], "saniti": [7, 8, 11, 12], "overus": 7, "forward": [7, 9, 22], "pipe": [7, 22], "sound": 7, "restrict": [7, 9], "experienc": 7, "sophist": 7, "grammat": 7, "indent": 7, "constitu": 7, "urban": 7, "semicolon": [7, 12], "a3": [7, 12], "1a": 7, "3c": 7, "4a": 7, "6c": 7, "brief": 7, "normalis": [7, 11, 12], "twice": [7, 9, 10, 12], "4826": 7, "0x55ec735ae130": 7, "0x55ec74c07a98": 7, "fortran": [7, 11, 14], "deeper": 7, "share": [7, 9, 12, 22], "emphasis": [7, 9, 10], "lisp": [7, 10, 11], "ocaml": 7, "haskel": 7, "clojur": 7, "fair": 7, "citizen": [7, 10], "invoc": 7, "nrow": [7, 9, 11, 12], "0x55ec7313ec30": 7, "0x55ec7422b320": 7, "euclidean_dist": 7, "helper": 7, "fill_na": [7, 12], "filler_fun": 7, "missing_on": 7, "replacement_valu": 7, "techniqu": [7, 9], "runtim": 7, "monopoli": 7, "hardcod": [7, 9, 10, 12], "buckwheat": [7, 12], "quinoa": 7, "barlei": 7, "cbind": [7, 9, 10, 11], "rbind": [7, 9, 10, 11], "plot_opt": 7, "log2": 7, "reus": 7, "scala": 7, "port": 7, "functool": 7, "recent": [7, 9, 11, 12], "framework": 7, "apach": [7, 8], "spark": [7, 8, 9], "obviou": [7, 8, 9], "accumul": 7, "cummmin": 7, "focu": 7, "off": [7, 9], "ish": 7, "centric": [7, 10], "One": [7, 8, 9], "eleg": 7, "7321": 7, "50000": [7, 11], "70711": [7, 11, 12], "86603": [7, 11], "3333": 7, "6667": 7, "111": [7, 12], "222": 7, "333": 7, "444": 7, "556": 7, "667": 7, "778": 7, "37": [7, 10, 11, 20], "889": 7, "toss": 7, "morearg": 7, "\u00e0": [7, 12], "la": [7, 12], "xi": 7, "file_nam": [7, 11], "scan": [7, 8, 11], "indulg": 7, "piec": [7, 9, 10], "fairli": 7, "successfulli": 7, "split": [7, 9, 10, 11, 12], "readili": 7, "nontrivi": [7, 9], "cry": 7, "reusabl": [7, 9], "vignett": [7, 11, 20], "45": [7, 9, 10, 11, 20], "moder": 7, "network": [7, 11], "bioinformat": 7, "pkg": [7, 9], "repo": [7, 9], "attach": [7, 8, 9, 12], "visit": 7, "entri": [7, 10, 12], "energi": [7, 10], "middleman": [7, 9], "acquir": [7, 11], "genet": 7, "optimis": [7, 8, 9, 10, 11], "expert": [7, 9], "whom": 7, "volunt": 7, "servant": 7, "enthusiast": [7, 8], "paid": [7, 10], "generos": 7, "spread": [7, 22], "cite": 7, "citat": 7, "lunch": 7, "social": 7, "media": 7, "clean": [7, 9], "somedai": 7, "defaultpackag": 7, "grdevic": 7, "primarili": [7, 10], "tarbal": 7, "untar": 7, "pkg_version": 7, "tar": 7, "pkgtype": 7, "47": [7, 11, 20], "rtool": 7, "xcode": 7, "courtesi": 7, "zip": 7, "tgz": 7, "gitlab": [7, 9], "host": [7, 9], "branch": [7, 20], "rpackagedemo": 7, "tempfil": [7, 12], "destin": 7, "destfil": 7, "extract": [7, 9, 11, 12, 22], "unzip": 7, "tempdir": 7, "exdir": 7, "git2r": 7, "git": [7, 9], "upgrad": [7, 8, 9], "updat": [7, 9, 10], "excit": 7, "welcom": [7, 9, 11], "flawlessli": 7, "wouldn": 7, "matur": 7, "conduct": 7, "libpath": 7, "x86_64": 7, "pc": [7, 10], "usr": 7, "lib": 7, "site": [7, 12], "folder": 7, "r_libs_us": 7, "setenv": 7, "honour": [7, 12], "target": [7, 8], "r_user_dir": 7, "r_user_data_dir": 7, "config": 7, "r_user_config_dir": 7, "r_user_cache_dir": 7, "accomplish": 7, "modular": 7, "restructuredtext": 7, "libreoffic": [7, 12], "epub": 7, "pdflatex": 7, "lualatex": 7, "imagemagick": 7, "bitmap": 7, "crop": 7, "convers": [7, 10, 12, 22], "graphviz": 7, "plantuml": 7, "diagram": 7, "jupyt": 7, "nbconvert": 7, "notebook": 7, "glue": [7, 8, 9, 14], "system2": [7, 12], "xml": [7, 8, 12], "stdin": [7, 8], "stdout": [7, 8], "redirect": [7, 9], "stream": [7, 8], "bash": [7, 10], "echo": 7, "python3": 7, "np": 7, "repr": 7, "arang": 7, "setwd": 7, "assumpt": [7, 9, 10, 12], "strongli": [7, 9], "freebsd": 7, "ethic": 7, "alon": [7, 8, 12], "industri": 7, "fftw": 7, "libsvm": 7, "mlpack": 7, "openbla": 7, "rjava": 7, "jvm": 7, "reticul": 7, "rpy2": 7, "feel": [7, 8, 9, 10], "oblig": [7, 9], "pars": [7, 8, 10], "steer": 7, "tutori": 7, "faq": 7, "googleit": 7, "optim": [7, 9, 11], "gini": 7, "correctli": 7, "strrep": [7, 9, 11], "dup": 7, "bbb": 7, "ccccc": 7, "aa": 7, "aaa": 7, "aaaa": 7, "bbbb": 7, "sublist": 7, "movstat": 7, "gram": 7, "bigram": 7, "abcd": 7, "bc": 7, "cd": 7, "recod": [7, 9], "count": [7, 8, 9, 10, 11, 12], "954": 7, "duplicatedn": 7, "my_split": 7, "my_unsplit": 7, "p_": 7, "x_m": 7, "increasingli": 7, "w_i": 7, "z_i": 7, "dpareto": 7, "ppareto": 7, "qpareto": 7, "rpareto": 7, "pareto": [7, 9], "awar": [7, 9], "mappli": [7, 9, 11], "fond": [7, 11, 12], "lappli": [7, 9, 10, 11, 12], "criterion": [8, 9, 12], "learnt": [8, 9], "adapt": 8, "circumst": 8, "other_express": 8, "spice": 8, "regard": [8, 9, 11, 12], "dangl": 8, "dandl": 8, "mint": 8, "requirenamespac": 8, "fail": [8, 9, 10], "process_data": 8, "some_extension_packag": 8, "quietli": [8, 9], "very_fast_method": 8, "normal_method": 8, "expression_a": 8, "expression_b": 8, "expression_c": 8, "expression_els": 8, "thenc": [8, 12], "immun": 8, "constraint": [8, 11], "trigger": [8, 9], "gracefulli": 8, "succe": 8, "bombast": 8, "formul": 8, "cherri": 8, "spamham": 8, "istru": 8, "isfals": 8, "connect": [8, 10, 11, 12, 14], "rt": 8, "No": [8, 9, 10, 11, 20], "critic": [8, 12], "diagnost": 8, "trycatch": 8, "suppresswarn": 8, "suppressmessag": 8, "emit": [8, 12], "silenc": 8, "reload": 8, "stopifnot": [8, 9, 10, 12], "exit": 8, "debug": [8, 12], "tip": [8, 11], "eleph": 8, "room": 8, "explicit": [8, 9, 10, 11], "congruenti": 8, "x_0": 8, "mod": 8, "74": 8, "remind": [8, 10, 11], "poor": 8, "cycl": [8, 9], "x_k": 8, "fridg": 8, "promis": [8, 9], "watch": 8, "tmp_vector": 8, "tmp_iter": 8, "influenc": 8, "ret": 8, "04206": 8, "024614": 8, "045831": 8, "094841": 8, "00062477": 8, "2529": 8, "many_stat": 8, "shorthand": 8, "cast": 8, "goe": 8, "my_unlist": 8, "34": [8, 10, 11, 20], "rough": 8, "consumpt": [8, 10], "oh": 8, "asymptot": 8, "cn": 8, "proportion": 8, "deadlin": 8, "hclust": [8, 11], "hierarch": [8, 11], "storag": [8, 12], "gb": 8, "opportun": [8, 9], "insight": 8, "intuit": [8, 9], "lengthi": 8, "innoc": 8, "buffer": 8, "generate_data": 8, "amortis": 8, "prospect": 8, "grant": [8, 9], "creation": [8, 9, 12], "hadoop": 8, "githubusercont": 8, "biggest": 8, "few_lin": 8, "93": 8, "establish": [8, 9, 11], "gzfile": 8, "textconnect": 8, "thousand": 8, "stai": [8, 19], "alert": 8, "microbenchmark": 8, "proc": 8, "impos": [8, 12], "shift_left": 8, "shift_right": 8, "longest": 8, "trend": 8, "subsequ": 8, "conclud": 8, "magnific": 8, "modul": 9, "highest": 9, "exposur": 9, "compromis": 9, "wors": [9, 10], "aspect": 9, "simpler": 9, "dry": 9, "tire": 9, "disciplin": 9, "trait": 9, "justifi": 9, "harm": 9, "backward": 9, "compat": [9, 11, 12], "smooth": 9, "mayb": [9, 12], "deparse1": 9, "depars": [9, 11], "expr": [9, 10, 11, 12], "cutoff": 9, "500l": 9, "0x55bfdca44690": 9, "cement": 9, "bloat": [9, 12], "joi": [9, 10], "team": [9, 10, 20], "profession": 9, "background": 9, "cohort": 9, "valuabl": 9, "attitud": 9, "novic": 9, "grasp": 9, "effort": 9, "nlargest": 9, "took": 9, "arriv": 9, "afraid": 9, "philosophi": [9, 13, 22], "awesom": 9, "serious": 9, "probabilist": 9, "stabil": [9, 20], "problemat": [9, 12], "huge": [9, 12], "anymor": [9, 10], "front": 9, "humbl": 9, "credit": 9, "clearli": 9, "hide": [9, 10], "gut": 9, "essenc": [9, 10, 11], "unhappi": 9, "Of": [9, 10, 12], "fewer": 9, "knn": 9, "coercibl": [9, 10], "utter": [9, 12], "nonsens": [9, 12], "atyp": 9, "believ": 9, "faith": 9, "compet": 9, "knew": 9, "round_rand": 9, "defend": [9, 10], "opt": 9, "divers": [9, 12], "diagnos": 9, "invalid": [9, 10, 12], "defens": 9, "mechan": [9, 10], "assert": 9, "cond1": 9, "cond2": 9, "round_rand2": 9, "strictest": 9, "tension": 9, "chao": 9, "foolproof": [9, 10], "duti": 9, "revisit": [9, 22], "domain": [9, 10], "vctr": 9, "vacuum": 9, "wider": 9, "utilis": 9, "deduc": [9, 11], "meet": 9, "sappli": [9, 11, 12], "proclaim": 9, "neaten": 9, "brute": 9, "forc": [9, 10], "gap": 9, "stri_list2matrix": 9, "pure": 9, "referenti": 9, "delet": [9, 11], "consequ": [9, 10, 11, 12], "invis": [9, 10], "anonym": 9, "instantli": 9, "path_to_fil": 9, "mylib": 9, "director": 9, "substanti": 9, "subdirectori": 9, "licens": [9, 22], "rd": 9, "src": 9, "pkg_directori": 9, "mypkg": 9, "submit": 9, "merci": 9, "busi": 9, "autom": [9, 10], "thoroughli": [9, 10, 12], "incud": 9, "stronger": 9, "asset": 9, "known": [9, 11, 12], "obscur": 9, "untrain": 9, "facil": 9, "roxygen2": 9, "extent": [9, 10], "heurist": 9, "mimick": 9, "invest": 9, "scm": 9, "doc": [9, 20], "tracker": 9, "wiki": 9, "board": 9, "guidelin": 9, "hygien": 9, "quadrat": 9, "16786054171151931769": 9, "testthat": 9, "tinytest": 9, "lighter": 9, "weight": 9, "runit": 9, "realtest": 9, "consult": [9, 10, 12], "ci": 9, "commit": 9, "servic": 9, "mostli": [9, 10], "suspect": [9, 10], "printf": 9, "shame": 9, "debugg": 9, "rprof": 9, "hight": 9, "underscor": 9, "whichev": 9, "grave": 9, "accent": 9, "lolloll": 9, "parser": 9, "condition": 9, "what_if_tru": 9, "what_if_fals": 9, "unevalu": [9, 12], "righthand": 9, "delai": 9, "postpon": 9, "wise": [9, 10], "myopnam": 9, "e1": [9, 10], "e2": [9, 10], "1013": 9, "tmp": [9, 12], "implic": [9, 12], "ceas": 9, "awai": 9, "shorten": 9, "new_length": 9, "behind": [9, 10, 11], "oval": 9, "smell": 9, "meati": 9, "umami": 9, "rose": 9, "tasteless": 9, "some_attrib": 9, "old_nam": 9, "new_nam": 9, "cauliflow": 9, "broccoli": 9, "crew": [9, 11], "male": [9, 11], "child": [9, 11], "adult": [9, 11], "670": [9, 11], "192": [9, 11], "subtask": 9, "ver": 9, "vir": 9, "test_chang": 9, "overshadow": 9, "refrain": [9, 10, 12], "carri": 9, "approxfun": 9, "f1": [9, 12], "f2": [9, 12], "565": 9, "4275": 9, "yleft": 9, "yright": 9, "0x55bfdbd80888": 9, "0x55bfdbd7ff20": 9, "0x55bfdbe82e30": 9, "04": [9, 10], "09": 9, "001": 9, "008": 9, "027": 9, "064": 9, "125": [9, 12], "216": 9, "343": 9, "729": 9, "sweet": 9, "spot": [9, 10], "oversimplist": 9, "tune": [9, 19], "78": [9, 10], "test_default": 9, "prior": [9, 10], "lazy_test1": 9, "amidst": 9, "lazy_test2": 9, "nose": 9, "uniroot": 9, "outer": [9, 11, 12], "variad": 9, "easiest": [9, 12], "test_dot": 9, "color": 9, "shape1": 9, "shape2": 9, "2e": 9, "fun": [9, 10, 12], "test_deparse_substitut": 9, "grill": 9, "shapiro": 9, "rlnorm": 9, "compactli": 9, "certainli": [9, 10], "theori": [9, 11, 12], "mm": 9, "118": [9, 12], "77": [9, 12], "132": [9, 12], "136": [9, 12], "outsid": [9, 10], "liberti": 9, "felt": 9, "realiti": 9, "prop": 9, "test_match_arg": 9, "predefin": 9, "heart": 9, "clue": 9, "sensibl": [9, 10, 11], "dislik": 9, "struggl": 9, "intellectu": 9, "mi": 9, "dialect": 9, "mother": 9, "tongu": 9, "blame": [9, 10], "elabor": 9, "Will": 9, "do_something_that_takes_a_million_year": 9, "envir": [9, 10, 11, 12], "baseenv": 9, "intention": 9, "predic": 9, "slide": 9, "package_depend": 9, "revers": [9, 12], "leav": 9, "feasibl": 9, "dealer": 9, "payabl": 9, "movement": 9, "autonom": 9, "contradict": 9, "polici": 9, "With": [9, 10], "caus": [9, 10, 12], "depth": [9, 22], "lexic": 9, "static": 9, "kwarg": 9, "latest": 10, "polit": 10, "spectra": 10, "hidden": [10, 11], "appeal": [10, 12], "oop": [10, 11], "beautifulli": 10, "admiss": 10, "endless": 10, "pretend": 10, "demystifi": 10, "xt": 10, "posixct": [10, 12], "posix": 10, "calendar": 10, "xd": 10, "decod": [10, 11], "03": 10, "aest": 10, "epoch": 10, "01t00": 10, "deciph": 10, "timestamp": 10, "ahead": 10, "bear": 10, "sic": [10, 11], "usemethod": [10, 11, 22], "0x5566182c8738": 10, "categor": [10, 11], "ctgrcl": 10, "spanishinquisit": 10, "categori": [10, 11, 12], "fallback": 10, "x_charact": [10, 11], "ensur": 10, "xu": [10, 11], "varieti": [10, 12], "forbid": 10, "instruct": 10, "internalmethod": 10, "groupgener": 10, "puzzl": 10, "xc": 10, "barebon": 10, "emul": 10, "partit": [10, 12], "kmean": 10, "center": 10, "nstart": 10, "0060": 10, "4280": 10, "4620": 10, "2460": 10, "9016": 10, "7484": 10, "3935": 10, "4339": 10, "8500": 10, "0737": 10, "7421": 10, "0711": 10, "151": 10, "821": 10, "879": 10, "between_ss": 10, "total_ss": 10, "totss": 10, "withinss": 10, "tot": 10, "betweenss": 10, "ifault": 10, "681": 10, "851": 10, "602": 10, "fanci": [10, 12], "enclo": [10, 11, 12], "gets3method": [10, 11], "tripl": 10, "colon": 10, "t1": 10, "aedt": 10, "t2": 10, "2021": [10, 20], "08": [10, 12], "15t12": 10, "59": [10, 12, 20], "posixt": 10, "posixlt": 10, "class1": 10, "class2": 10, "classk": 10, "inherit": [10, 12], "mimic": 10, "impli": [10, 12], "odditi": 10, "automag": 10, "ubiqu": 10, "2023": 10, "underneath": 10, "19353": 10, "midnight": 10, "utc": 10, "1672134577": 10, "timezon": 10, "tzone": 10, "isodatetim": 10, "2030": 10, "int": [10, 12, 20], "mdai": 10, "mon": 10, "wdai": 10, "ydai": 10, "364": 10, "isdst": 10, "gmtoff": 10, "datetimeclass": 10, "supposedli": 10, "closer": 10, "difftim": 10, "1e7": 10, "elaps": 10, "232": 10, "012": 10, "245": [10, 12], "proc_tim": 10, "micro": 10, "beginn": 10, "factor_cod": 10, "cut": 10, "unawar": 10, "en": [10, 20], "accident": [10, 12], "stringsasfactor": [10, 12], "sporad": 10, "fifth": 10, "Be": 10, "droplevel": [10, 12], "unus": 10, "someon": 10, "redefin": 10, "watertight": 10, "complain": 10, "opinion": [10, 11], "respond": 10, "numeris": 10, "digitis": 10, "numtabl": 10, "paradigm": 10, "hierarchi": [10, 22], "broad": 10, "privileg": 10, "stem": 10, "ingeni": 10, "simplic": 10, "encapsul": [10, 11], "versatil": [10, 12], "emphasi": 10, "verb": 10, "noun": 10, "sensibli": 10, "afterward": [10, 12], "group_bi": [10, 12], "list_df": [10, 12], "iris_subset": 10, "770": [10, 12], "974": [10, 12], "552": [10, 12], "priceless": 10, "seal": 10, "told": 10, "obj": 10, "method1": 10, "method2": 10, "nutshel": 10, "relationship": 10, "s3method": 10, "rle": 10, "package_vers": 10, "numeric_vers": 10, "chosen": [10, 12], "gl": 10, "poorli": 10, "messeng": 10, "undesir": 10, "elsewher": [10, 12, 22], "alien": 10, "implant": 10, "forcefulli": 10, "narrow": [10, 11], "s4": [10, 22], "sexptyp": 10, "pointer": [10, 22], "heap": 10, "struct": 10, "unoverload": 10, "fan": 10, "knowns3gener": 10, "s3_methods_t": 10, "challeng": 10, "overprotect": 10, "con": [10, 12], "debat": 10, "lookup": [10, 22], "trick": 10, "nextmethod": 10, "incomprehens": 10, "tm": 10, "op": 10, "nonlinear": 10, "calcul": 10, "fortun": 10, "compuls": 10, "stakehold": 10, "agil": 10, "harder": [10, 12], "seamless": 10, "kotlin": 10, "magrittr": 10, "uncool": 10, "school": 10, "primari": 11, "rowwis": [11, 12], "byrow": 11, "ncol": [11, 12], "columnwis": 11, "indistinguish": 11, "3d": 11, "2d": 11, "hypert": 11, "2x3": 11, "equis": 11, "tappli": 11, "replic": 11, "min_mean_max": 11, "900": [11, 12], "006": [11, 12], "936": [11, 12], "588": [11, 12], "referr": 11, "toi": [11, 12], "57825": 11, "12431": 11, "9666": 11, "7869": 11, "sapply2": 11, "ccc": 11, "eeeee": 11, "bb": 11, "dddd": 11, "ffffff": 11, "nonneg": 11, "1d": 11, "addition": [11, 12], "affect": 11, "placement": 11, "grid": [11, 12, 13], "newli": 11, "rownam": 11, "colnam": 11, "prettifi": 11, "conting": [11, 12], "fri": 11, "sat": 11, "sun": 11, "thur": 11, "87": 11, "76": [11, 12], "smoker": 11, "firstli": 11, "a_": 11, "multi": 11, "guess": 11, "colmean": 11, "coordin": 11, "arr": 11, "ind": 11, "arrayind": 11, "multidimension": 11, "diag": 11, "cartesian": 11, "sex": 11, "femal": 11, "accid": [11, 12], "121": 11, "NOT": 11, "b_": 11, "aperm": 11, "conjug": 11, "conj": 11, "co": [11, 20], "matplot": 11, "rowmean": 11, "625": 11, "65": 11, "156": 11, "221": 11, "2000": [11, 12, 20], "sweep": 11, "conform": 11, "lapack": 11, "bla": 11, "differenti": 11, "constrain": 11, "unconstrain": 11, "refresh": 11, "c_": 11, "ac": 11, "crossprod": 11, "tcrossprod": 11, "euclidean": 11, "orthogon": 11, "perpendicular": 11, "cov": 11, "covari": 11, "centr": 11, "lu": 11, "pivot": 11, "interchang": 11, "lcl": 11, "_1": 11, "max_": 11, "_2": 11, "sigma_1": 11, "sup_": 11, "_i": 11, "singular": 11, "frobeniu": 11, "_f": 11, "_m": 11, "atop": 11, "supremum": 11, "manhattan": 11, "taxicab": 11, "dist": 11, "pairwis": 11, "2361": 11, "ca": [11, 12, 20], "41421": 11, "canberra": 11, "adist": 11, "spa": 11, "leg": 11, "cutre": 11, "linkag": 11, "singleton": 11, "eigen": 11, "lambda_1": 11, "lambda_n": 11, "nondecreasingli": 11, "lambda_i": 11, "rotat": 11, "86603i": 11, "00000i": 11, "70711i": 11, "bivari": 11, "asp": 11, "princip": 11, "18609": 11, "98386": 11, "86715": 11, "49804": 11, "pca": 11, "triangular": 11, "theta": 11, "coef": 11, "regress": 11, "car": [11, 12], "qrx": 11, "9324": 11, "5791": 11, "scatter": [11, 12], "93241x": 11, "diagon": 11, "d_": 11, "zc": 11, "brilliantli": 11, "dispatch": [11, 12, 22], "class_of_x": 11, "mainstream": 11, "restless": 11, "lack": [11, 12], "polymorph": 11, "fourth": 11, "classes_detail": 11, "methods_detail": 11, "loos": 11, "defclass": 11, "defmethod": 11, "afterthought": 11, "appendag": 11, "patchwork": 11, "rebelli": 11, "pinch": 11, "regist": 11, "setclass": 11, "auto": 11, "novel": 11, "globalenv": 11, "cl": 11, "valueclass": 11, "setgener": 11, "degre": 11, "setmethod": 11, "signatur": 11, "setvalid": 11, "dens": 11, "spars": 11, "rectangular": 11, "symmetr": 11, "band": 11, "vertic": 11, "edg": 11, "ddimatrix": 11, "sparsematrix": 11, "dgcmatrix": 11, "crc": [11, 20], "hyperrectangl": 11, "thusli": 11, "min_i": 11, "max_i": 11, "hot": 11, "r_": 11, "multiclass": 11, "softmax": 11, "closest": 11, "min_j": 11, "combn": 11, "tsp": 11, "eurxxx": 11, "read_numeric_matrix": 11, "t10k": 11, "imag": [11, 12], "idx3": 11, "ubyt": 11, "mnist": 11, "homepag": [11, 13], "circular": 11, "convolut": 11, "affin": 11, "sharpen": 11, "shear": 11, "constroptim": 11, "bett": 11, "qp": 11, "quadprog": 11, "multivari": 11, "copula": [11, 20], "unitari": 11, "pseudoinvers": 11, "prcomp": 11, "class_nam": 11, "hypothet": 11, "imagin": 11, "class_name1": 11, "class_name2": 11, "heterogen": 12, "bias": 12, "nois": 12, "thriller": 12, "pop": 12, "driven": 12, "morn": 12, "77437": 12, "19722": 12, "97801": 12, "20133": 12, "36124": 12, "74261": 12, "ob": 12, "774": 12, "197": 12, "978": [12, 20], "201": 12, "361": 12, "sadli": 12, "unstack": 12, "mtcar": 12, "cyl": 12, "var1": 12, "var2": 12, "freq": 12, "eagerli": 12, "friend": 12, "97": 12, "428": 12, "tsv": 12, "hdf5": 12, "curl": 12, "287577520124614": 12, "788305135443807": 12, "4089769218117": 12, "tunabl": 12, "calc": 12, "dbi": 12, "driver": 12, "rsqlite": 12, "rmariadb": 12, "rpostgresql": 12, "rodbc": 12, "odbc": 12, "volatil": 12, "sqlite": 12, "dbconnect": 12, "dbwritet": 12, "dbexecut": 12, "send": 12, "INTO": 12, "dbgetqueri": 12, "mpg": 12, "AS": 12, "mpg_ave": 12, "hp": 12, "hp_ave": 12, "730": 12, "567": 12, "131": 12, "67": 12, "115": 12, "209": 12, "dbdisconnect": 12, "password": 12, "credenti": 12, "getenv": 12, "keyr": 12, "subsect": 12, "vigil": 12, "nasti": 12, "counterintuit": 12, "uninform": 12, "ri": 12, "besid": 12, "obliqu": 12, "iris2": 12, "croatica": 12, "advertis": [12, 13], "rag": 12, "dictat": 12, "sad": 12, "xtab": 12, "my_xtab": 12, "d1": 12, "d2": 12, "460916": 12, "265061": 12, "686853": 12, "fromlast": 12, "trickier": 12, "names_replac": 12, "new_c": 12, "new_a": 12, "12929": 12, "2651": 12, "set_row_nam": 12, "reset_row_nam": 12, "exhibit": 12, "402": 12, "metr": 12, "race": 12, "mtcars6": 12, "qsec": 12, "disp": 12, "drat": 12, "wt": 12, "gear": 12, "carb": 12, "351": 12, "264": 12, "ford": 12, "pantera": 12, "301": 12, "335": 12, "54": 12, "maserati": 12, "bora": 12, "73": 12, "84": 12, "camaro": 12, "z28": 12, "145": 12, "175": 12, "ferrari": 12, "dino": 12, "duster": 12, "mazda": 12, "rx4": 12, "minu": 12, "decreasingli": 12, "anydupl": 12, "143": 12, "developer_id": 12, "project_id": 12, "scope": [12, 22], "engag": 12, "b0": 12, "b1": 12, "b3": 12, "a0": 12, "a4": 12, "c1": 12, "c2": 12, "inner": 12, "iris_sampl": 12, "137": 12, "133": 12, "0667": 12, "1333": 12, "5500": 12, "7167": 12, "70405": 12, "03024": 12, "76004": 12, "65318": 12, "72094": 12, "49854": 12, "60591": 12, "78117": 12, "45878": 12, "46829": 12, "83674": 12, "85384": 12, "85202": 12, "18732": 12, "31738": 12, "30884": 12, "74927": 12, "74484": 12, "65540": 12, "93659": 12, "52684": 12, "dimension": [12, 20], "succeed": 12, "responsenam": 12, "val": 12, "superb": 12, "idvar": 12, "timevar": 12, "covert": 12, "worldphon": 12, "kat": 12, "ron": 12, "jo": 12, "mari": 12, "lollipop": 12, "opposit": 12, "straightforwardli": 12, "charm": 12, "var3": 12, "98": 12, "idempot": 12, "assist": 12, "462": [12, 20], "246": 12, "326": 12, "026": 12, "ave_len": 12, "rem": 12, "nappli": 12, "av": 12, "813": 12, "dramat": 12, "aaaggg": 12, "plate": 12, "cosmet": 12, "is_bi": 12, "res_mat": 12, "combined_aggreg": 12, "score": 12, "52811": 12, "89242": 12, "55144": 12, "45661": 12, "95683": 12, "45333": 12, "46357": 12, "17823": 12, "63478": 12, "65057": 12, "revert": 12, "overthink": 12, "2330": 12, "1450": 12, "230000": 12, "294000": 12, "245000": 12, "112": 12, "et": [12, 20], "voil\u00e0": 12, "weird": 12, "fall": 12, "119": 12, "gibberish": 12, "selector": 12, "chef": 12, "proudli": 12, "ultra": 12, "delivernoodl": 12, "log_hp": 12, "620": 12, "7005": 12, "wag": 12, "875": 12, "datsun": 12, "710": 12, "85": 12, "5326": 12, "hornet": 12, "drive": 12, "258": 12, "215": 12, "sportabout": 12, "1648": 12, "valiant": 12, "225": 12, "6540": 12, "fuel_economi": 12, "235": 12, "307": 12, "981": 12, "983": 12, "tild": 12, "4186": 12, "075": 12, "3709": 12, "7447": 12, "8552": 12, "050": 12, "2553": 12, "6950": 12, "060753": 12, "058754": 12, "053734": 12, "051440": 12, "193": 12, "049455": 12, "esoter": 12, "interdepend": 12, "invas": 12, "annoyingli": 12, "tibbl": 12, "tbl_df": 12, "haven": 12, "xpt": 12, "subclass": 12, "amount": 12, "ago": 12, "foo": 12, "x0": 12, "x9": 12, "y0": 12, "y9": 12, "coord": 12, "lat": 12, "xyz12345": 12, "id3": 12, "id5": 12, "y7": 12, "flight": 12, "70k": 12, "urban_forest": 12, "trunk": 12, "diamet": 12, "breast": 12, "height": 12, "hors": 12, "chestnut": 12, "plant": 12, "genera": 12, "genu": 12, "eucalyptu": 12, "platanu": 12, "ficu": 12, "acer": 12, "quercu": 12, "barplot": 12, "travel": 12, "stackexchang": 12, "travel_stackexchange_com_2017": 12, "displaynam": 12, "post": 12, "favoritecount": 12, "favoritetot": 12, "mostfavoritequest": 12, "mostfavoritequestionlik": 12, "ON": 12, "owneruserid": 12, "posttypeid": 12, "desc": 12, "posts2": 12, "positiveanswercount": 12, "parentid": 12, "AND": 12, "upvotesperyear": 12, "postid": 12, "vote": 12, "creationd": 12, "votetypeid": 12, "bestansw": 12, "maxscor": 12, "acceptedscor": 12, "acceptedanswerid": 12, "cmttotscr": 12, "commentstotalscor": 12, "userid": 12, "reput": 12, "badg": 12, "IN": 12, "valuablebadg": 12, "votesbyage2": 12, "oldvot": 12, "voted": 12, "THEN": 12, "newvot": 12, "2017": [12, 20], "votesbyag": 12, "colclass": 12, "unstructur": 12, "regular": [12, 20], "clear": 12, "corrupt": 12, "contamin": 12, "inde": 12, "datafram": 12, "set_index": 12, "reset_index": 12, "scientist": [12, 20], "focus": 12, "unanticip": 12, "overrid": 12, "billion": 12, "unread": 12, "newer": 13, "lattic": 13, "ggplot2": 13, "suffici": 13, "aren": 13, "v0": 19, "deepr": 19, "abelson": 20, "sussman": 20, "1996": 20, "mit": 20, "abramowitz": 20, "stegun": 20, "1972": 20, "dover": 20, "sfu": 20, "cbm": 20, "aand": 20, "becker": 20, "wilk": 20, "1988": 20, "chapman": 20, "hall": 20, "guid": 20, "springer": 20, "verlag": 20, "2008": 20, "rogram": 20, "476": 20, "doi": 20, "32614": 20, "rj": 20, "028": 20, "hasti": 20, "cormen": 20, "leiserson": 20, "rivest": 20, "stein": 20, "2009": 20, "mcgraw": 20, "hill": 20, "crawlei": 20, "2007": 20, "wilei": 20, "son": 20, "2003": 20, "davi": 20, "whistler": 20, "nicod": 20, "annex": 20, "tr15": 20, "scherer": 20, "collat": 20, "tr10": 20, "deisenroth": 20, "faisal": 20, "ong": 20, "cambridg": 20, "mml": 20, "demichiel": 20, "gabriel": 20, "1987": 20, "ommon": 20, "isp": 20, "bject": 20, "ystem": 20, "ecoop": 20, "dreamsong": 20, "devroy": 20, "1986": 20, "luc": 20, "rnbookindex": 20, "forb": 20, "evan": 20, "hast": 20, "peacock": 20, "2010": 20, "friedl": 20, "2006": 20, "reilli": 20, "naliza": 20, "danych": 20, "obliczenia": 20, "symulacj": 20, "wydawnictwo": 20, "naukow": 20, "isbn": 20, "18939": 20, "zenodo": 20, "6455719": 20, "datawranglingpi": 20, "5281": 20, "6451068": 20, "ast": 20, "18637": 20, "jss": 20, "v103": 20, "i02": 20, "rop": 20, "galassi": 20, "theiler": 20, "al": 20, "gentl": 20, "ont": 20, "arlo": 20, "algebra": [20, 22], "goldberg": 20, "acm": 20, "perso": 20, "lyon": 20, "fr": 20, "jean": 20, "michel": 20, "muller": 20, "hankin": 20, "gslpaper": 20, "harri": 20, "585": 20, "7825": 20, "357": 20, "362": 20, "1038": 20, "s41586": 20, "020": 20, "2649": 20, "higham": 20, "2002": 20, "accuraci": 20, "siam": 20, "philadelphia": 20, "pa": 20, "dx": 20, "1137": 20, "9780898718027": 20, "299": 20, "314": 20, "1080": 20, "10618600": 20, "10474713": 20, "1992": 20, "csli": 20, "ii": 20, "eminumer": 20, "addison": 20, "weslei": 20, "undament": 20, "matloff": 20, "2011": 20, "tour": 20, "starch": 20, "matsumoto": 20, "nishimura": 20, "ersenn": 20, "wister": 20, "623": 20, "equidistribut": 20, "nelsen": 20, "1999": 20, "olver": 20, "nist": 20, "dlmf": 20, "gov": 20, "tiernei": 20, "kalibera": 20, "2018": 20, "ltern": 20, "svn": 20, "venabl": 20, "riplei": 20, "smith": 20, "intro": 20, "wickham": 20, "grolemund": 20, "r4d": 20, "nz": 20, "xie": 20, "2015": 20, "ext": 20, "admin": 20, "lang": 20, "foundat": 20, "vienna": 20, "austria": 20, "practition": 22, "hardli": 22, "afford": 22, "tag": 22, "proxi": 22, "prove": 22, "mate": 22, "peer": 22, "copyright": 22, "noncommerci": 22, "noderiv": 22, "cc": 22, "nc": 22, "nd": 22, "acknowledg": 22, "hello": 22, "rcpp": 22, "changelog": 22}, "objects": {}, "objtypes": {}, "objnames": {}, "titleterms": {"prefac": 0, "To": [0, 7, 9], "r": [0, 1, 7, 9, 14, 16, 22], "languag": 0, "an": [0, 1], "environ": [0, 1, 16], "aim": 0, "scope": [0, 9], "design": [0, 9], "philosophi": 0, "classif": [0, 16], "data": [0, 2, 6, 9, 12, 16], "type": [0, 4, 6, 10, 16], "book": 0, "structur": 0, "about": 0, "author": 0, "acknowledg": 0, "introduct": 1, "hello": 1, "world": 1, "set": 1, "up": 1, "develop": [1, 4, 9], "instal": 1, "interact": 1, "mode": 1, "batch": 1, "work": [1, 9], "script": 1, "weav": 1, "automat": 1, "report": 1, "gener": [1, 2, 10, 18], "semi": 1, "jupyt": 1, "notebook": 1, "send": 1, "code": [1, 9, 14], "associ": 1, "consol": 1, "etc": [1, 7, 10], "atom": [1, 5, 6], "vector": [1, 2, 3, 4, 5, 6, 9, 11], "glanc": 1, "get": 1, "help": 1, "exercis": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "numer": [2, 11], "creat": [2, 3, 4, 6, 7, 9, 10, 11, 12], "constant": 2, "concaten": [2, 6], "c": [2, 5, 7, 14], "repeat": [2, 8], "entri": 2, "rep": 2, "arithmet": 2, "progress": 2, "seq": 2, "pseudorandom": 2, "number": [2, 5], "read": [2, 6, 12], "scan": 2, "name": [2, 4, 7], "object": [2, 4, 6, 7, 10], "vectoris": [2, 3, 5, 7, 11], "mathemat": [2, 11], "function": [2, 5, 7, 9, 11, 18], "ab": 2, "sqrt": 2, "round": [2, 3], "natur": 2, "exponenti": 2, "logarithm": 2, "probabl": 2, "distribut": 2, "special": [2, 4, 9], "oper": [2, 3, 6, 9, 10, 11, 12, 15], "recycl": 2, "rule": 2, "preced": [2, 3], "accumul": 2, "aggreg": [2, 3, 11, 12], "logic": [3, 5, 11], "compar": [3, 6], "element": [3, 4, 5, 11], "comparison": 3, "test": [3, 9], "na": 3, "nan": 3, "inf": 3, "deal": 3, "float": 3, "point": 3, "off": 3, "error": 3, "revisit": [3, 10, 16, 18], "missing": 3, "all": 3, "ani": 3, "sum": 3, "simplifi": [3, 11], "predic": 3, "choos": 3, "ifels": 3, "list": [4, 5, 11, 12], "attribut": [4, 5, 9], "hierarchi": 4, "convers": 4, "explicit": 4, "cast": 4, "implicit": 4, "coercion": 4, "coerc": 4, "from": [4, 5, 6], "null": 4, "perceptu": 4, "indiffer": 4, "most": 4, "But": 4, "There": 4, "ar": [4, 7, 9, 11, 12], "some": 4, "us": [4, 6, 7, 10], "case": 4, "label": 4, "alter": 4, "remov": 4, "index": [5, 11], "head": 5, "tail": 5, "subset": [5, 12], "extract": [5, 6], "nonneg": 5, "neg": 5, "charact": [5, 6], "replac": [5, 6, 9, 11], "modifi": 5, "insert": 5, "new": 5, "relat": [5, 12], "match": [5, 6], "anoth": 5, "assign": 5, "interv": 5, "split": [5, 6], "subgroup": 5, "order": [5, 6, 7, 10, 12], "identifi": 5, "duplic": [5, 12], "count": 5, "occurr": [5, 6], "preserv": 5, "lose": 5, "someth": 5, "input": [6, 9], "individu": [6, 11], "string": [6, 12], "mani": 6, "One": [6, 10], "format": 6, "text": 6, "file": 6, "pattern": 6, "search": 6, "whole": 6, "partial": 6, "anywher": 6, "within": 6, "regular": 6, "express": [6, 7, 15, 17], "locat": 6, "token": 6, "other": [6, 11], "substr": 6, "translat": 6, "integ": 6, "raw": 6, "complex": [6, 8], "invok": 7, "anonym": 7, "pass": [7, 9], "argument": [7, 9, 10, 18], "group": [7, 12, 18], "curli": [7, 9], "brace": [7, 9], "program": [7, 22], "call": [7, 9, 10], "precomput": 7, "do": 7, "common": [7, 10, 11, 12], "higher": [7, 11], "map": 7, "access": [7, 11], "third": 7, "parti": 7, "packag": [7, 9, 11, 12, 18], "default": [7, 9, 10, 18], "sourc": 7, "v": [7, 10], "binari": [7, 9, 11], "manag": [7, 9], "depend": 7, "extern": [7, 14], "A": [7, 8, 9, 11, 12, 16], "note": [7, 8, 9, 11, 12, 16], "interfac": [7, 12, 14], "python": 7, "java": 7, "flow": [8, 9], "execut": 8, "condit": 8, "evalu": [8, 9, 17, 18], "return": 8, "valu": [8, 9, 12], "nest": 8, "ifs": 8, "either": 8, "true": 8, "fals": 8, "short": 8, "circuit": 8, "except": 8, "handl": [8, 9, 12], "while": 8, "break": 8, "next": 8, "time": [8, 10], "space": 8, "algorithm": 8, "principl": 9, "sustain": 9, "write": 9, "abstain": 9, "pamper": 9, "challeng": 9, "build": 9, "reus": 9, "check": [9, 10], "integr": 9, "put": 9, "output": 9, "context": 9, "organis": 9, "maintain": 9, "librari": 9, "document": 9, "assur": 9, "qualiti": 9, "chang": 9, "collabor": 9, "driven": 9, "continu": 9, "debug": 9, "profil": 9, "syntact": 9, "sugar": 9, "backtick": 9, "too": 9, "built": [9, 10, 11], "own": [9, 10], "substitut": 9, "part": 9, "composit": 9, "local": 9, "variabl": 9, "closur": 9, "lazi": 9, "ellipsi": [9, 18], "metaprogram": [9, 12], "s3": [10, 18], "class": [10, 11, 16], "method": [10, 11, 18], "dispatch": 10, "custom": 10, "onli": 10, "directli": 10, "multi": 10, "ness": 10, "overload": [10, 18], "date": 10, "formula": [10, 15], "factor": [10, 12], "over": 10, "forward": 10, "pipe": 10, "matric": 11, "arrai": 11, "matrix": [11, 12], "promot": 11, "stack": 11, "beyond": 11, "intern": [11, 12], "represent": [11, 12], "upon": 11, "basic": 11, "select": 11, "row": [11, 12], "column": [11, 12], "drop": 11, "dimens": 11, "submatric": 11, "base": [11, 12], "two": 11, "dimension": 11, "transpos": 11, "algebra": 11, "multipl": 11, "solv": 11, "system": 11, "linear": 11, "equat": 11, "norm": 11, "metric": 11, "eigenvalu": 11, "eigenvector": 11, "qr": 11, "decomposit": 11, "svd": 11, "s4": 11, "defin": 11, "slot": 11, "constructor": 11, "inherit": 11, "frame": 12, "cbind": 12, "rbind": 12, "databas": 12, "queri": 12, "sql": 12, "like": 12, "join": 12, "merg": 12, "transform": 12, "miss": 12, "reshap": 12, "techniqu": 12, "dplyr": 12, "tidyvers": 12, "tabl": 12, "graphic": 13, "placehold": 13, "plot": 13, "refer": [13, 16, 20], "elsewher": 13, "compil": 14, "api": 14, "pointer": 14, "rcpp": 14, "The": 15, "dollar": 15, "copi": 16, "demand": 16, "lookup": 18, "usemethod": 18, "namespac": 18, "changelog": 19, "deep": 22, "start": 22, "here": 22, "deeper": 22, "deepest": 22, "appendix": 22}, "envversion": {"sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 6, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinxcontrib.bibtex": 9, "sphinx": 56}}) \ No newline at end of file +Search.setIndex({"docnames": ["chapter/000-preface", "chapter/110-basics", "chapter/120-numeric", "chapter/130-logical", "chapter/140-list", "chapter/150-indexing", "chapter/160-character", "chapter/170-function", "chapter/180-flow", "chapter/210-design", "chapter/220-s3", "chapter/230-matrix", "chapter/240-data-frame", "chapter/250-graphics", "chapter/310-compile", "chapter/320-language", "chapter/330-environment", "chapter/340-eval-expr", "chapter/350-eval-fun", "chapter/998-changelog", "chapter/999-bibliography", "chapter/chapter-header-motd", "index"], "filenames": ["chapter/000-preface.md", "chapter/110-basics.md", "chapter/120-numeric.md", "chapter/130-logical.md", "chapter/140-list.md", "chapter/150-indexing.md", "chapter/160-character.md", "chapter/170-function.md", "chapter/180-flow.md", "chapter/210-design.md", "chapter/220-s3.md", "chapter/230-matrix.md", "chapter/240-data-frame.md", "chapter/250-graphics.md", "chapter/310-compile.md", "chapter/320-language.md", "chapter/330-environment.md", "chapter/340-eval-expr.md", "chapter/350-eval-fun.md", "chapter/998-changelog.md", "chapter/999-bibliography.md", "chapter/chapter-header-motd.md", "index.md"], "titles": ["Preface", "1. Introduction", "2. Numeric Vectors", "3. Logical Vectors", "4. Lists and Attributes", "5. Vector Indexing", "6. Character Vectors", "7. Functions", "8. Flow of Execution", "9. Designing Functions", "10. S3 Classes", "11. Matrices and Other Arrays", "12. Data Frames", "13. \ud83d\udea7 Graphics", "14. \ud83d\udea7 Interfacing Compiled Code", "15. \ud83d\udea7 Expressions", "16. \ud83d\udea7 Environments", "17. \ud83d\udea7 Evaluating Expressions", "18. \ud83d\udea7 Evaluating Functions", "Changelog", "References", "<no title>", "Deep R Programming"], "terms": {"The": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22], "open": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "access": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 21, 22], "textbook": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "deep": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "program": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21], "marek": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "gagolewski": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], "i": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], "remain": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "freeli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "avail": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "everyon": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "enjoy": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "also": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "pdf": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "It": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "non": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "profit": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "project": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "thi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "still": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "work": [0, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "progress": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "beta": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "version": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "chapter": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], "12": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], "ar": [0, 1, 2, 3, 5, 6, 8, 10, 13, 14, 15, 16, 17, 18, 19, 21, 22], "alreadi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "complet": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "more": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "In": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "meantim": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21], "ani": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "bug": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "typo": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "report": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], "fix": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "appreci": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "although": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "onlin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "whole": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "cours": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "should": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "read": [0, 1, 3, 4, 5, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 21, 22], "from": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "begin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "end": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "refer": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 17, 18, 21, 22], "gener": [0, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 20, 21, 22], "introductori": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "remark": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "check": [0, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "out": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "my": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22], "other": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 21, 22], "minimalist": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "wrangl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "python": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "20": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22], "50": [0, 2, 4, 5, 7, 10, 11, 12, 20], "ha": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "been": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "name": [0, 1, 5, 6, 8, 9, 10, 11, 12, 22], "eleventh": 0, "most": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 19, 22], "dread": 0, "2022": [0, 6, 10, 12, 19, 20, 22], "stackoverflow": [0, 12], "develop": [0, 7, 10, 11, 12, 14, 20, 22], "survei": [0, 10, 20], "free": [0, 1, 2, 4, 7, 8, 9, 10, 13], "app": 0, "so": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "must": [0, 5, 7, 9, 10, 11, 12], "someth": [0, 1, 2, 3, 4, 7, 8, 9, 10, 11, 12], "wrong": [0, 3, 8, 9, 10], "right": [0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 22], "But": [0, 2, 5, 7, 8, 9, 10], "whatev": [0, 2, 4, 7, 8, 9, 10, 11, 12], "deprec": [0, 9], "anywai": [0, 2, 3, 6, 8, 9, 10, 11], "modern": 0, "wai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "us": [0, 1, 2, 3, 5, 8, 9, 11, 12, 13, 22], "tidyvers": 0, "Or": [0, 1, 5, 8, 9], "we": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16], "all": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "just": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "switch": [0, 1, 8], "well": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "realli": [0, 2, 5, 6, 7, 9, 10, 12], "let": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "u": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "get": [0, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22], "one": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "thing": [0, 2, 8, 9, 10, 12], "straight": [0, 2], "statist": [0, 1, 2, 3, 5, 6, 8, 13, 20, 22], "packag": [0, 1, 2, 3, 5, 6, 8, 10, 13, 20, 22], "purpos": [0, 2, 3, 5, 7, 9], "high": [0, 9, 11], "level": [0, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], "happen": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12], "veri": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], "power": [0, 2, 3, 5, 8, 9, 12, 20, 22], "kind": [0, 1, 4, 5, 6, 7, 9, 10, 11, 12], "numer": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 20, 22], "intens": [0, 1, 14], "comput": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 22], "offer": [0, 2], "extens": [0, 2, 5, 6, 7, 8, 9, 10, 11, 20], "support": [0, 1, 2, 6, 8, 9, 10, 12], "machin": [0, 1, 3, 6, 7, 8, 11, 12, 20, 22], "learn": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 20, 22], "analysi": [0, 1, 3, 8, 9, 11, 12, 14, 20], "visualis": [0, 1, 7, 12, 14], "applic": [0, 2, 3, 6, 9], "lot": [0, 4, 5, 7, 8, 9, 10, 12], "initi": [0, 2, 6, 11], "wa": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "written": [0, 1, 2, 3, 6, 7, 8, 10, 11, 12], "statistician": 0, "therefor": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 22], "mai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "thought": [0, 5, 7, 9, 10, 11, 12], "yet": [0, 2, 4, 7, 9, 10], "capabl": [0, 4, 10], "altern": [0, 1, 3, 5, 6, 7, 8, 9, 11, 12], "stata": 0, "sa": [0, 12], "spss": 0, "statistica": 0, "minitab": 0, "weka": 0, "etc": [0, 2, 3, 4, 5, 6, 9, 11, 12, 19], "unlik": [0, 4, 5, 9, 10, 12], "some": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "them": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "howev": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "spreadsheet": [0, 12], "like": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 22], "gui": 0, "main": [0, 1, 2, 3, 4, 9, 10, 11, 12], "gatewai": 0, "perform": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "user": [0, 1, 2, 4, 7, 8, 9, 10, 12, 13, 22], "write": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 20], "code": [0, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 22], "actual": [0, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "done": [0, 1, 2, 4, 7, 9, 10, 11, 12, 14], "despit": [0, 3, 4, 9, 10, 11, 12], "curv": [0, 2], "being": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "littl": [0, 2, 4, 7, 10], "steeper": 0, "programm": [0, 1, 2, 3, 5, 7, 9, 10, 11, 12], "long": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "run": [0, 1, 2, 7, 8, 9, 10], "empow": [0, 9], "becaus": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "thei": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "limit": [0, 2, 3, 7, 9, 10, 11, 12], "onli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13], "common": [0, 2, 3, 4, 5, 8, 9, 22], "scenario": [0, 1, 4, 5, 7, 8, 9, 10, 12], "If": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "function": [0, 1, 3, 4, 6, 8, 10, 12, 19, 20, 22], "miss": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "doe": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "suit": [0, 1], "need": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "can": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "easili": [0, 1, 2, 4, 5, 7, 9, 10, 11, 12], "implement": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14], "everyth": [0, 5, 7, 9], "themselv": [0, 2, 3, 4, 6, 10], "thu": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "conveni": [0, 1, 2, 4, 6, 7, 9, 10, 11, 12], "rapid": [0, 1, 5, 8, 12], "prototyp": [0, 1, 5, 8, 12, 14], "help": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 22], "turn": [0, 1, 2, 4, 6, 7, 8, 9, 11, 12], "our": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 16], "idea": [0, 1, 2, 7, 9, 10, 11, 12], "oper": [0, 1, 4, 5, 7, 8, 22], "test": [0, 1, 2, 4, 6, 8, 10, 11, 12], "extend": [0, 3, 5, 7, 9, 12, 20], "polish": [0, 7], "product": [0, 2, 7, 9, 11], "otherwis": [0, 2, 3, 6, 7, 8, 9, 10, 11, 12], "enjoi": [0, 2, 4, 7, 11], "overal": [0, 5, 9, 10, 11, 12], "As": [0, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12], "interpret": [0, 1, 2, 3, 8, 9, 10, 11, 12, 20], "interact": [0, 5, 6, 7, 8, 9, 12], "eval": [0, 1, 10, 11, 12], "print": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "loop": [0, 1, 3, 7, 8, 11], "command": [0, 1, 7, 8, 9, 12], "result": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "question": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12], "answer": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "batch": [0, 7, 8, 12], "mode": [0, 4, 7, 10], "standalon": [0, 1, 12], "script": [0, 2, 6, 9, 12], "would": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "rather": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12], "posit": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "amongst": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12], "tool": [0, 1, 7, 9, 10, 12], "scientif": [0, 2, 3, 6, 8, 9, 11, 20], "numpi": [0, 1, 2, 7, 20], "ecosystem": 0, "julia": [0, 2, 7, 10, 12], "gnu": [0, 1, 2, 3, 6, 7, 20], "octav": [0, 2], "scilab": [0, 2], "matlab": [0, 2], "specialis": [0, 6, 7, 9, 10, 12], "scienc": [0, 1, 2, 8, 9, 10, 11, 20, 22], "than": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "henc": [0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13], "provid": [0, 2, 4, 5, 7, 9, 10, 11, 12], "much": [0, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13], "smoother": [0, 2, 5], "experi": [0, 1, 2, 5, 9, 12], "why": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "over": [0, 1, 2, 3, 6, 7, 9, 11, 12, 13, 22], "year": [0, 2, 5, 9, 10, 12], "becom": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 22], "de": [0, 3, 6, 10], "facto": [0, 6, 10], "standard": [0, 2, 4, 6, 7, 10, 11, 12, 20], "mani": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 22], "relat": [0, 2, 3, 7, 8, 9, 10, 22], "field": [0, 7, 9, 10, 12], "consist": [0, 2, 6, 9, 10, 11, 12], "featur": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "advanc": [0, 1, 6, 7, 8, 9, 10, 20], "graphic": [0, 7, 20, 22], "see": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "13": [0, 2, 4, 5, 6, 7, 9, 10, 11, 12, 13, 20], "system": [0, 1, 2, 6, 7, 9, 10, 12, 13, 20], "section": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "4": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20, 22], "interfac": [0, 2, 9, 10, 11, 22], "compil": [0, 7, 9, 11, 22], "14": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 20], "centralis": 0, "repositori": [0, 4, 7, 9, 12], "cran": [0, 1, 2, 7, 9, 11, 20], "bioconductor": [0, 7], "7": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "3": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "live": [0, 1, 5, 7, 9, 12], "commun": [0, 7, 9, 10, 12], "curiou": 0, "passion": 0, "peopl": [0, 5, 9, 10, 20, 22], "you": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 22], "me": [0, 6], "predecessor": [0, 2], "popular": [0, 2, 3, 7, 9, 10, 11, 12, 22], "1980": 0, "john": [0, 5, 20], "m": [0, 1, 2, 4, 6, 7, 8, 10, 11, 20, 22], "chamber": [0, 20], "hi": [0, 5, 6, 9], "colleagu": 0, "bell": 0, "lab": 0, "8": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "40": [0, 4, 5, 7, 11, 12, 20], "call": [0, 1, 2, 3, 4, 5, 6, 8, 11, 12], "sourc": [0, 1, 2, 6, 8, 9, 10, 11, 12], "its": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "commerci": 0, "counterpart": [0, 3, 6, 8, 10, 11, 13], "mid": 0, "1990": 0, "2": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19, 20, 22], "robert": 0, "gentleman": [0, 20], "ross": 0, "ihaka": [0, 20], "depart": 0, "univers": [0, 1, 4, 5, 6, 9, 12, 20], "auckland": 0, "larg": [0, 2, 3, 8, 11, 12], "number": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 20], "contributor": 0, "31": [0, 2, 6, 7, 9, 10, 11, 12, 20], "histor": [0, 7, 9, 12, 13], "note": [0, 1, 2, 3, 4, 5, 6, 10, 13, 22], "c": [0, 1, 3, 4, 6, 8, 9, 10, 11, 12, 20, 22], "syntax": [0, 1, 2, 3, 6, 7, 9, 10], "involv": [0, 1, 2, 3, 4, 5, 7, 8, 10, 11, 12], "curli": [0, 8], "brace": [0, 8], "principl": [0, 3, 5, 22], "beauti": [0, 11], "heavili": [0, 9, 12], "inspir": [0, 2, 3, 9, 10, 11], "scheme": [0, 2, 5, 7, 9, 10, 11], "17": [0, 2, 3, 5, 8, 9, 10, 11, 12, 20], "detail": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "somewhat": [0, 2, 4, 8, 9, 10, 11, 12], "object": [0, 1, 3, 5, 8, 9, 11, 12, 20, 22], "orient": [0, 1, 2, 6, 7, 10, 11], "10": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "have": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "introduc": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 20, 22], "mean": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "frame": [0, 2, 4, 5, 7, 8, 9, 10, 11, 22], "formula": [0, 2, 4, 9, 11, 12, 20, 22], "reli": [0, 2, 3, 4, 7, 8, 9, 10, 11, 12], "nonstandard": [0, 9, 12], "evalu": [0, 1, 2, 3, 4, 5, 7, 12, 22], "metaprogram": [0, 7], "lm": [0, 10, 11], "ozon": 0, "solar": 0, "temp": 0, "subset": [0, 4, 7, 9, 10, 11, 22], "airqual": 0, "60": [0, 5, 6, 12], "select": [0, 1, 2, 3, 5, 6, 9, 10, 12], "month": [0, 4, 5], "dai": [0, 1, 2, 7, 9, 10, 11, 12], "summari": [0, 1, 2, 5, 12], "horribl": 0, "anoth": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "group": [0, 1, 2, 5, 6, 8, 9, 10, 11, 22], "isol": [0, 7], "base": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 22], "through": [0, 2, 5, 7, 8, 10, 11, 12], "thick": 0, "layer": [0, 12], "third": [0, 2, 4, 5, 6, 8, 9, 10, 11, 12, 22], "parti": [0, 2, 4, 5, 6, 9, 10, 11, 12, 22], "overwhelm": [0, 9], "everi": [0, 1, 2, 3, 5, 6, 7, 9, 10, 11, 12, 20], "regardless": [0, 4, 5, 6, 8, 10, 12], "complex": [0, 2, 4, 7, 9, 10, 11, 12], "differ": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "often": [0, 2, 5, 7, 8, 9, 10, 12], "duplic": [0, 7, 10, 11], "core": [0, 1, 11, 20], "sometim": [0, 1, 3, 4, 7, 8, 9, 10, 11, 12], "quit": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 19], "incompat": [0, 10, 11, 12], "tradit": [0, 10, 13], "both": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "famili": [0, 2], "fine": [0, 4, 10], "solv": [0, 2, 3, 6, 7, 8, 9, 10, 12], "simplest": [0, 2], "process": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 12, 13, 20], "problem": [0, 3, 5, 7, 8, 9, 10, 11, 12], "yearn": [0, 3], "do": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12], "want": [0, 7, 8, 9, 10, 12], "hundr": [0, 11], "prefabr": [0, 9], "recip": 0, "dish": [0, 5], "mindlessli": 0, "appli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "without": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "understand": [0, 2, 6, 7, 9, 10, 12], "which": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "suppos": [0, 5, 7, 9], "lingua": 0, "franca": 0, "abl": [0, 1, 3, 4, 5, 7, 8, 9, 10, 11, 12], "everybodi": [0, 2], "modif": [0, 9], "ten": [0, 5, 6, 12], "now": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "slang": [0, 9], "tackl": [0, 11], "furthermor": [0, 1, 4, 5, 9, 10, 11, 12], "skill": [0, 5, 7, 9, 10, 12], "transfer": [0, 12], "new": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 20, 22], "panda": [0, 7, 12], "easier": [0, 1, 5, 7, 9, 10, 13], "later": [0, 1, 2, 4, 5, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18], "notabl": 0, "enough": [0, 5, 9, 10, 12], "preach": 0, "graduat": 0, "independ": [0, 1, 2, 5, 7, 9, 11, 12, 13, 22], "reader": [0, 1, 2, 6, 7, 9, 10, 11, 12, 13], "who": [0, 5, 7, 9, 10, 11, 12, 22], "mind": [0, 2, 3, 9, 10, 11, 12], "slightli": [0, 4, 7, 10, 11, 12], "cohes": 0, "comprehens": [0, 7, 12, 22], "organis": [0, 10, 11, 12, 22], "materi": [0, 2, 9, 10, 12, 22], "benefit": [0, 7, 8, 9, 10], "first": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 16, 19], "introduct": [0, 9, 20, 22], "pamper": 0, "For": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22], "5": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "good": [0, 1, 2, 3, 4, 6, 7, 9, 10, 11, 12], "intermedi": [0, 3, 7, 9], "skip": [0, 1, 5, 8, 9], "though": [0, 1, 2, 5, 6, 7, 9, 10, 11, 12], "either": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 12], "forget": [0, 10], "prescrib": [0, 10], "exercis": [0, 22], "luck": 0, "overview": [0, 11, 20], "preval": [0, 1, 4, 10], "figur": [0, 1, 2, 3, 5, 10, 11, 13], "16": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 20], "list": [0, 1, 2, 3, 6, 7, 8, 9, 10, 19, 22], "commonli": [0, 1, 2, 4, 12], "classifi": [0, 3, 4, 5, 7, 11, 12], "follow": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "basic": [0, 1, 2, 4, 6, 7, 8, 9, 10, 12, 19], "discuss": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "part": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12], "intern": [0, 6, 7, 8, 9, 10, 20, 22], "built": [0, 2, 5, 7, 12, 13, 22], "upon": [0, 2, 3, 4, 5, 7, 8, 9, 10, 12], "ones": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "hing": 0, "atom": [0, 2, 3, 4, 7, 8, 9, 10, 11, 12, 22], "vector": [0, 7, 8, 10, 12, 13, 22], "repres": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "sequenc": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "valu": [0, 1, 2, 3, 4, 5, 6, 7, 10, 11], "where": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "element": [0, 1, 2, 6, 7, 8, 9, 10, 12, 22], "same": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "logic": [0, 1, 2, 4, 6, 7, 8, 9, 10, 12, 22], "includ": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "item": [0, 1, 2, 5, 6, 10, 11, 12], "true": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "ye": [0, 3, 5, 7, 9, 10, 11, 12], "present": [0, 1, 4, 7, 9, 10, 11, 12, 16], "fals": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "absent": 0, "na": [0, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "real": [0, 1, 2, 3, 5, 6, 7, 9, 10, 11, 12], "0": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19, 20, 22], "0000001": 0, "charact": [0, 1, 2, 4, 7, 8, 9, 10, 11, 12, 20, 22], "6": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "contain": [0, 1, 2, 4, 5, 6, 9, 11, 12], "string": [0, 1, 2, 4, 5, 9, 10, 11, 20, 22], "e": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "g": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "gro\u00df": [0, 6], "123": [0, 2, 10, 12], "\u0434\u043e\u0431\u0440\u0438\u0439": 0, "\u0434\u0435\u043d\u044c": 0, "seri": [0, 1, 2, 3, 7, 8, 10, 11, 12], "express": [0, 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 20, 22], "line": [0, 1, 2, 5, 6, 7, 8, 9, 11, 12], "input": [0, 1, 2, 3, 4, 5, 7, 8, 10, 11], "hopefulli": [0, 7, 10], "desir": [0, 8, 9, 10, 11, 12], "outcom": [0, 1, 2, 3, 10], "instanc": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "cat": [0, 1, 6, 7, 8, 9, 10, 11, 12], "plot": [0, 1, 2, 4, 5, 7, 9, 10, 11, 12, 22], "sampl": [0, 2, 3, 4, 5, 7, 9, 11, 12], "sum": [0, 2, 4, 7, 8, 9, 10, 12], "k": [0, 2, 4, 7, 8, 9, 10, 11, 20], "store": [0, 1, 2, 3, 4, 6, 7, 8, 9, 11, 12], "mix": [0, 1, 2, 4, 5, 6, 10, 12], "abov": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22], "complement": [0, 1], "index": [0, 2, 3, 4, 6, 7, 9, 10, 12, 22], "control": [0, 6, 7, 8, 9, 10, 12, 13], "flow": [0, 1, 7, 10, 22], "compound": [0, 1, 7, 9, 10, 19], "second": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13], "wrapper": [0, 2], "around": [0, 2, 6, 8, 9, 10, 22], "might": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22], "behav": [0, 4, 5, 6, 9, 10, 11, 12], "underli": [0, 2, 4, 7, 9, 10, 11, 12], "primit": [0, 2, 7, 8, 12], "thank": [0, 1, 2, 4, 7, 9, 10, 12, 22], "dedic": [0, 1, 12], "overload": [0, 2, 9, 11, 12, 22], "factor": [0, 4, 5, 9, 11, 13], "qualit": [0, 7, 10], "nomin": 0, "order": [0, 1, 2, 3, 4, 8, 9, 11], "scale": [0, 2, 3, 7, 11], "matrix": [0, 2, 4, 6, 7, 9, 10, 20, 22], "11": [0, 2, 4, 5, 6, 7, 9, 10, 11, 12, 20], "tabular": [0, 2, 8, 10, 11, 12], "arrang": [0, 5, 10, 12], "row": [0, 1, 2, 4, 5, 7, 8, 9, 10], "column": [0, 1, 2, 4, 6, 7, 8, 9, 10], "each": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "cell": [0, 11], "usual": [0, 1, 2, 6, 7, 9, 10, 11, 12], "deposit": [0, 7], "time": [0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 12], "defin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "arbitrarili": [0, 7, 10, 11, 12], "s3": [0, 5, 9, 11, 12, 22], "style": [0, 6, 7, 11, 13], "sustain": [0, 7, 10, 12, 22], "9": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19, 20, 22], "prepar": [0, 2, 7], "public": [0, 7, 19, 22], "qualiti": [0, 1, 7, 22], "case": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13], "essenti": [0, 1, 4, 7], "gain": [0, 4, 8], "full": [0, 1, 5, 8, 11, 12, 13], "externalptr": [0, 10], "sec": [0, 2, 7, 8, 9, 10], "symbol": [0, 2, 6, 7], "15": [0, 2, 3, 5, 6, 7, 9, 10, 11, 12, 20], "specifi": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12], "supervis": 0, "model": [0, 2, 3, 8, 9, 10, 11, 12, 20], "within": [0, 1, 2, 4, 5, 7, 8, 9, 10, 12], "subgroup": 0, "earli": [0, 9, 22], "draft": [0, 19, 22], "placehold": [0, 4, 6, 9, 22], "pleas": [0, 1, 2, 3, 9, 10, 12, 13, 14, 15, 16, 17, 18, 22], "come": [0, 2, 3, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18], "back": [0, 1, 2, 3, 8, 9, 12, 13, 14, 15, 16, 17, 18], "approxim": [0, 2, 6, 10, 16], "surpris": [0, 2, 3, 5, 6, 8, 9, 10, 11], "few": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "ourselv": [0, 1, 2, 5, 6, 7, 8, 9, 10], "pronounc": 0, "ma": 0, "rek": 0, "gong": 0, "oliv": 0, "ski": 0, "am": [0, 1, 12], "current": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "senior": 0, "lectur": 0, "ai": [0, 6], "deakin": 0, "melbourn": [0, 12, 20, 22], "vic": 0, "australia": 0, "associ": [0, 2, 3], "professor": 0, "research": [0, 1, 2, 7, 22], "institut": 0, "academi": 0, "interest": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 12], "particular": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "phenomena": 0, "usabl": [0, 7], "algorithm": [0, 2, 3, 5, 7, 9, 10, 11, 12, 14, 20], "studi": [0, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12], "analyt": [0, 22], "properti": [0, 2, 3, 5, 7, 8], "find": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "how": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "misus": [0, 9], "misunderstand": 0, "method": [0, 1, 2, 5, 7, 9, 12, 20, 22], "decis": [0, 3], "make": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14], "set": [0, 2, 4, 5, 6, 7, 9, 10, 11, 12, 22], "90": [0, 2, 5, 9, 12], "journal": [0, 20], "paper": [0, 2], "outlet": 0, "proceed": [0, 8, 12], "nation": 0, "pna": 0, "inform": [0, 1, 2, 4, 7, 8, 9, 10, 11, 12], "fusion": 0, "forecast": 0, "softwar": [0, 7, 9, 10, 13, 20], "knowledg": [0, 1, 6, 7, 22], "ieee": [0, 3], "transact": [0, 20], "fuzzi": 0, "informetr": 0, "spare": 0, "student": [0, 2, 9, 22], "libr": [0, 7], "stringi": [0, 6, 9, 20], "download": [0, 1, 2, 7, 8, 9, 12], "genieclust": 0, "fast": [0, 1, 2, 9, 13], "robust": [0, 3, 5, 7, 11], "cluster": [0, 1, 8, 10, 11], "success": [0, 2, 9], "programowani": [0, 20], "w": [0, 1, 3, 4, 5, 7, 9, 11, 12, 20], "j\u0119zyku": [0, 20], "19": [0, 2, 5, 10, 11, 12, 20], "publish": [0, 2, 7, 9, 12, 19, 22], "pwn": [0, 20], "1st": [0, 2, 5, 6, 9, 11], "ed": 0, "2014": [0, 20], "2nd": [0, 2, 5, 6, 7, 9, 11, 20], "2016": [0, 12, 20], "entir": 0, "serv": [0, 2, 4, 5, 6, 7, 9, 12], "excel": 0, "testb": 0, "convei": 0, "here": [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "teach": [0, 2, 6, 7, 8, 9, 11, 12], "proven": [0, 3, 10, 12], "similar": [0, 2, 3, 5, 6, 9, 10, 11, 12], "your": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 22], "truli": [0, 2, 9, 10, 11], "respons": [0, 9, 10], "warsaw": 0, "technologi": 0, "retreat": 0, "berlin": 0, "feedback": 0, "given": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "last": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12], "describ": [0, 1, 2, 5, 9, 10], "patch": [0, 10], "r83330": 0, "expect": [0, 2, 3, 4, 6, 7, 8, 9, 10, 12], "99": [0, 2, 6, 9, 11], "cover": [0, 4, 8, 9, 10, 11, 12, 13, 19], "valid": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12], "futur": [0, 9], "releas": [0, 19, 20], "consid": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 22], "file": [0, 1, 2, 4, 7, 8, 9, 11, 12, 20], "discov": [0, 2, 9, 10], "markdown": [0, 1, 7], "superset": 0, "myst": 0, "sphinx": 0, "tex": 0, "xelatex": [0, 6, 7], "chunk": [0, 1, 6, 7, 8, 9, 12], "were": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13], "knitr": [0, 1, 20], "44": [0, 1, 12, 20], "low": [0, 1, 7, 9, 13], "own": [0, 1, 2, 4, 5, 6, 7, 8, 11, 12], "templat": [0, 1], "A": [0, 1, 2, 3, 4, 5, 6, 10, 20, 22], "makefil": [0, 9], "custom": [0, 7, 9, 12], "shell": [0, 1, 7], "plugin": [0, 1], "sphinxcontrib": 0, "bibtex": 0, "proof": [0, 2, 12], "dot": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11], "j": [0, 2, 4, 5, 7, 8, 11, 20], "cross": [0, 2, 3, 4, 12], "f": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "ubuntu": 0, "mono": 0, "font": [0, 4, 6, 7], "displai": [0, 2, 4, 5, 6, 7, 9, 10, 11, 12], "typeset": 0, "text": [0, 1, 2, 3, 4, 5, 7, 8, 9, 12], "alegreya": 0, "lato": 0, "typefac": 0, "receiv": 0, "fund": 0, "administr": [0, 20], "technic": [0, 1, 4, 7, 9, 11, 20], "editori": 0, "aussi": 0, "sai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "yeah": [0, 8], "nah": 0, "49": [0, 9, 10, 11, 20], "april": [0, 4], "1997": [0, 20], "rich": [0, 10], "1991": [0, 20], "taught": 0, "wonderfulli": 0, "ambiti": [0, 9, 22], "undergradu": 0, "math": [0, 20], "approach": [0, 1, 2, 3, 5, 7, 9, 10, 11, 12], "difficult": [0, 6, 10, 12], "requir": [0, 1, 6, 7, 11, 12], "motiv": 0, "mindset": 0, "And": [0, 1, 2, 5, 6, 8, 9, 10, 11, 12], "go": [0, 1, 2, 3, 5, 7, 8, 9, 12], "neither": [0, 2, 6, 7, 9, 12], "historian": 0, "stenograph": 0, "nor": [0, 5, 6, 7, 9, 12], "grammarian": 0, "allow": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "noninvas": 0, "idealis": [0, 3], "didact": 0, "evolv": 0, "shape": [0, 9], "slowli": [0, 2], "stabl": [0, 2, 5, 11, 12], "api": [0, 2, 6, 7, 9, 10, 12, 22], "even": [0, 2, 3, 4, 5, 6, 7, 9, 10, 12], "better": [0, 2, 7, 8, 9, 10, 11, 12], "stage": [0, 9], "career": 0, "drama": [0, 12], "ideal": [0, 3, 9, 10], "give": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "try": [0, 1, 2, 4, 6, 7, 8, 9, 10, 11, 12], "35": [0, 5, 7, 11, 20], "41": [0, 2, 5, 9, 12, 20], "42": [0, 2, 5, 7, 9, 10, 11, 12, 20], "43": [0, 5, 12, 20], "automat": [0, 2, 9, 10, 11, 12], "sugar": [0, 10, 22], "salt": [0, 11], "drug": [0, 9], "healthi": [0, 9], "book": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], "prefac": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22], "data": [1, 3, 4, 5, 7, 8, 10, 11, 13, 14, 15, 17, 18, 20, 21, 22], "tradition": 1, "journei": 1, "start": [1, 2, 4, 6, 7, 8, 9, 11, 12], "greet": 1, "asap": 1, "hovercraft": 1, "eel": 1, "By": [1, 2, 3, 5, 7, 9, 10, 11, 12], "enclos": [1, 9], "doubl": [1, 2, 3, 4, 5, 6, 8, 10], "quot": [1, 2, 6, 9, 10, 12], "document": [1, 2, 4, 5, 7, 8, 10, 20], "practic": [1, 2, 3, 4, 6, 7, 8, 9], "worth": [1, 2, 6, 7, 9, 10, 12], "know": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 20], "hash": [1, 6], "sign": [1, 2, 6, 8], "comment": [1, 2, 4, 6, 9, 10, 11, 12], "ignor": [1, 2, 4, 5, 6, 8, 10, 11], "cannot": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "wait": [1, 3, 7, 8], "till": 1, "lunchtim": 1, "two": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13], "argument": [1, 2, 3, 4, 5, 6, 8, 11, 12, 22], "bui": [1, 2], "record": [1, 8, 12], "n": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "scratch": [1, 7, 9, 12], "newlin": [1, 7], "convent": [1, 2, 5, 9], "textual": 1, "output": [1, 2, 3, 5, 6, 7, 8, 10, 11, 12], "itself": [1, 3, 6, 7, 8, 9, 11, 12], "alwai": [1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12], "preced": [1, 7, 8, 12], "copi": [1, 2, 4, 5, 9, 22], "past": [1, 2, 6, 7, 9, 10, 11], "themself": [1, 9, 10, 11], "highli": [1, 12], "encourag": [1, 7, 9, 11, 12], "whenev": [1, 5, 11], "made": [1, 6, 7, 9, 10, 12], "round": [1, 4, 5, 6, 7, 8, 9, 10, 11, 12], "bracket": [1, 2, 5, 7, 8], "obligatori": [1, 8], "parenthes": 1, "separ": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "comma": [1, 7, 12], "constitut": [1, 7, 8, 9, 11], "consum": [1, 10, 11], "some_function_to_be_cal": 1, "argument1": 1, "argument2": 1, "natur": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "pine": 1, "abil": [1, 5, 12], "execut": [1, 2, 7, 9, 10, 22], "hand": [1, 2, 3, 4, 6, 7, 8, 9, 12, 13], "dirti": 1, "offici": [1, 9], "precompil": 1, "binari": [1, 2, 3, 5, 10], "distribut": [1, 3, 6, 7, 9, 11, 20, 22], "http": [1, 2, 6, 7, 8, 9, 11, 12, 19, 20, 22], "org": [1, 2, 7, 9, 12, 20], "seriou": [1, 7, 11], "recommend": [1, 2, 3, 6, 7, 9, 11, 12], "sooner": [1, 9, 11], "unix": [1, 2, 6, 7, 9, 10], "variant": [1, 2, 4, 6, 11], "linux": [1, 6, 7], "proprietari": [1, 9], "far": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "o": [1, 4, 5, 6, 7, 8, 9, 20], "thereof": [1, 2, 3, 4, 5, 7, 9, 10, 11, 12], "emploi": [1, 9], "favourit": [1, 5, 9, 12], "manag": [1, 2, 4, 8, 12, 22], "apt": 1, "dnf": 1, "pacman": 1, "homebrew": 1, "wi": 1, "anaconda": 1, "miniconda": 1, "interoper": [1, 10, 11], "below": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19], "review": [1, 2, 5, 6, 7, 12], "sever": [1, 9], "benign": 1, "setup": 1, "life": [1, 2, 8, 9, 12], "singl": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "best": [1, 5, 7, 9], "repl": 1, "instant": 1, "gratif": 1, "quickli": [1, 4, 9], "determin": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "aggreg": [1, 6, 7, 9, 10], "enter": [1, 2, 6], "mathemat": [1, 3, 6, 9, 20, 22], "vari": [1, 2, 4, 6, 12], "box": [1, 2, 5, 6, 7, 9, 10], "simpli": [1, 2, 3, 9, 10, 11, 12], "termin": [1, 6, 7, 8], "folk": 1, "fire": [1, 3], "rgui": 1, "menu": 1, "when": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "default": [1, 2, 5, 6, 8, 11, 12, 22], "prompt": 1, "await": 1, "moreov": [1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12], "denot": [1, 2, 3, 5, 6, 9, 11], "continu": [1, 2, 11], "unfinish": 1, "cancel": 1, "press": [1, 10, 20], "esc": 1, "ctrl": 1, "depend": [1, 2, 3, 6, 8, 9, 10, 13], "close": [1, 2, 3, 6, 8, 9, 12], "abort": 1, "readabl": [1, 2, 3, 4, 6, 7, 8, 9, 10, 19], "never": [1, 3, 10, 11, 12], "unsuit": 1, "complic": [1, 9, 13], "task": [1, 6, 7, 8, 9, 11, 12, 14], "extrem": [1, 4, 9, 10, 11], "intervent": 1, "To": [1, 2, 3, 4, 5, 6, 11, 12, 22], "invok": [1, 10, 22], "rscript": 1, "path": [1, 2, 7, 8, 9, 12], "editor": [1, 12], "notepad": 1, "kate": 1, "vi": 1, "emac": 1, "rstudio": [1, 9], "vscodium": 1, "creat": [1, 13, 22], "Then": [1, 5, 6, 9, 11, 12], "reproduc": [1, 2], "keep": [1, 2, 3, 7, 9], "tabl": [1, 2, 3, 4, 6, 7, 8, 10, 11, 20], "auxiliari": [1, 2, 3, 7, 9, 10], "synchronis": 1, "util": [1, 5, 7, 9, 11, 12], "sweav": 1, "exampl": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "processor": 1, "latex": [1, 6, 7, 9], "html": [1, 6, 7, 9, 20, 22], "markup": [1, 7], "languag": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 20, 22], "replac": [1, 2, 3, 4, 7, 8, 10, 12, 20, 22], "yield": [1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "showcas": [1, 11], "programmat": [1, 4, 5, 7, 9, 11, 12], "could": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12], "convert": [1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "websit": 1, "pandoc": [1, 7], "docutil": 1, "facilit": [1, 9], "session": [1, 2, 7, 8, 9], "rmd": 1, "content": [1, 2, 3, 4, 5, 7, 9, 11, 12], "stuff": [1, 8, 9], "attent": [1, 2, 4, 12], "assum": [1, 2, 3, 5, 6, 7, 9, 10, 11, 12], "locat": [1, 2, 5, 7, 12], "directori": [1, 2, 6, 7, 8, 9], "compar": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 22], "knit": 1, "inspect": [1, 2, 6, 7, 9, 10, 11], "md": [1, 6, 7, 8], "extern": [1, 3, 9, 10, 12, 22], "frequent": [1, 2, 3, 6, 7, 8, 9, 10, 11, 12], "workflow": 1, "trial": [1, 2], "error": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12], "short": [1, 3, 5, 9, 12], "fragment": [1, 7], "insid": [1, 2, 5, 7, 8, 9, 10, 12], "simpl": [1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13], "load": [1, 2, 6, 7, 8, 9, 11, 12], "cleans": [1, 8], "importantli": [1, 2, 9, 10, 12], "sent": 1, "therein": [1, 5, 6, 7, 9, 11, 12], "happi": [1, 12], "correct": [1, 2, 5, 6, 9, 10, 12], "necessari": [1, 2, 3, 5, 6, 7, 8, 9, 11, 12], "There": [1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12], "integr": [1, 8, 12], "id": [1, 3, 9, 12], "addit": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "enabl": [1, 3, 4, 5, 7, 8, 9, 10, 11], "jupyterlab": 1, "individu": [1, 5, 7, 9, 12], "configur": [1, 2, 8, 9, 11], "keyboard": [1, 8, 10], "shortcut": [1, 2, 10], "shift": [1, 3, 7], "web": [1, 6, 7, 9, 12, 20], "browser": [1, 6, 9], "irkernel": 1, "conda": 1, "save": [1, 2, 3, 6], "kernel": 1, "type": [1, 2, 3, 5, 7, 8, 9, 11, 12, 19, 22], "whilst": [1, 5, 9, 10, 22], "onto": [1, 7, 11], "illustr": [1, 2, 7, 9, 10, 12], "arbitrari": [1, 2, 4, 5, 6, 7, 9, 10], "whose": [1, 2, 4, 5, 6, 7, 9, 10, 11, 12], "handl": [1, 2, 3, 4, 5, 6, 7, 10, 22], "edit": [1, 6, 7, 11, 20], "kept": 1, "togeth": [1, 11, 12], "ipynb": 1, "json": [1, 4, 7, 8], "quick": 1, "perspect": [1, 7, 10, 12, 13], "teacher": 1, "exploratori": 1, "analys": 1, "messi": 1, "luckili": [1, 2, 7, 8, 9, 10, 11, 12], "option": [1, 4, 5, 6, 8, 9, 10, 11, 12], "export": [1, 2, 7, 8, 9, 10, 12, 20], "plain": [1, 7, 9, 12], "after": [1, 2, 4, 5, 7, 8, 9, 10, 11], "messag": [1, 8, 9, 10], "typic": [1, 2, 7, 9, 11, 12], "normal": [1, 2, 3, 9, 11, 12, 20], "proce": 1, "next": [1, 2, 3, 4, 6, 7, 9, 10, 11, 12], "arithmet": [1, 3, 4, 5, 7, 9, 10, 11, 20, 22], "comparison": [1, 2, 6, 9, 10, 11], "scalar": [1, 2, 3, 6, 8, 9, 11], "definit": [1, 2, 4, 7, 8, 9, 10, 11, 20], "arrai": [1, 2, 3, 5, 7, 8, 10, 12, 20, 22], "collect": [1, 2, 4, 5, 9, 12], "iter": [1, 2, 8, 10], "instead": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "what": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "seem": [1, 2, 9, 10, 11, 12], "datum": 1, "length": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "71828": 1, "7183": [1, 2], "ombin": [1, 2], "three": [1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "respect": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "14159": [1, 6], "12345": [1, 2, 10], "four": [1, 2, 4, 5, 6, 7, 8, 11, 12], "0000": [1, 2, 6, 7, 10, 11], "1416": [1, 6], "6000": [1, 11], "spam": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "bacon": [1, 4, 5, 6, 7, 8, 9, 10, 11, 12], "Not": [1, 7, 8, 9], "greatli": 1, "simplifi": [1, 6, 7, 9, 10, 12], "area": [1, 2, 9], "simul": [1, 2, 8, 20], "client": [1, 9], "rate": [1, 2, 4, 7], "stock": 1, "market": [1, 2], "price": [1, 7, 10], "temperatur": 1, "sensor": 1, "fact": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "oppos": [1, 6], "special": [1, 5, 6, 8, 10, 11, 12, 20, 22], "add": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12], "ons": [1, 2, 7, 12], "29": [1, 5, 7, 10, 11, 12, 19, 20], "assur": [1, 3, 4, 5, 7, 8, 10], "absolut": [1, 2, 3, 7, 8, 9, 10], "deviat": [1, 2, 7, 9, 11], "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "effortless": [1, 10], "ab": [1, 3, 5, 6, 7, 10, 11], "Such": [1, 5, 6, 7, 8, 9, 11, 12], "easi": [1, 7, 9, 10, 11, 12, 14], "maintain": [1, 12, 22], "aim": [1, 4, 5, 7, 9, 22], "omnisci": [1, 3], "authorit": [1, 7], "about": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20, 22], "specif": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12], "topic": [1, 5, 7, 9, 10, 12], "page": [1, 2, 3, 4, 6, 7, 9, 10], "equival": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "sight": 1, "manual": [1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 20], "structur": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20, 22], "header": [1, 12], "titl": [1, 12], "descript": [1, 6, 9, 12], "usag": [1, 2, 9], "formal": [1, 2, 7, 9, 10, 11, 12], "paramet": [1, 2, 5, 7, 9, 10, 11, 12], "explain": [1, 2, 7, 9, 10, 11, 12], "return": [1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "further": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "link": [1, 7], "yourself": [1, 9, 10], "search": [1, 4, 7, 8, 12, 22], "vagu": 1, "oftentim": [1, 5, 7, 8, 9, 10, 11], "reliabl": [1, 7, 10], "ask": [1, 2, 5, 7, 9], "duckduckgo": 1, "gle": 1, "irrelev": 1, "distract": 1, "lose": [1, 3, 7, 12, 22], "sacr": 1, "writer": [1, 7], "form": [1, 2, 4, 6, 7, 8, 9, 10, 11, 12, 20, 22], "On": [1, 2, 3, 6, 7, 8, 9, 11, 12, 13], "contrari": [1, 8], "reflect": [1, 5, 7, 9], "thorough": 1, "investig": 1, "look": [1, 2, 4, 5, 6, 8, 9, 10, 12], "plai": [1, 2, 4, 6, 7, 10, 12], "modifi": [1, 4, 7, 8, 9, 10, 11, 12], "benefici": [1, 9, 12], "habit": [1, 10, 12], "readi": 1, "import": [1, 2, 7, 9, 10, 11, 12, 20], "theme": 1, "accord": [1, 9], "classif": [1, 3, 11, 22], "previou": [1, 2, 3, 4, 5, 7, 8, 9, 10, 12], "think": [1, 2, 3, 5, 7, 8, 9, 10], "schedul": 1, "job": [1, 5, 7, 9, 10], "least": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "virtual": [1, 9, 10, 11], "vm": 1, "chang": [1, 2, 4, 7, 8, 10, 11, 12, 19], "date": [1, 6, 12, 20], "knuth": [1, 20], "liter": [1, 20], "concept": [1, 10, 11, 12], "32": [1, 2, 4, 5, 6, 7, 10, 11, 20], "r": [2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 17, 18, 20, 21], "uttermost": 2, "fundament": [2, 4, 12], "environ": [2, 3, 4, 7, 8, 9, 10, 12, 13, 20, 22], "tensorflow": 2, "At": [2, 6, 7, 8, 9, 12], "blush": 2, "explor": [2, 5, 7, 8, 9, 11], "kindli": 2, "place": [2, 4, 5, 7, 8, 9, 10, 12], "trust": 2, "rare": [2, 4, 5, 6, 7, 9], "compris": [2, 4, 5, 6, 7, 9, 12], "educ": [2, 7, 9, 22], "plethora": 2, "possibl": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "choic": [2, 4, 6, 9, 10, 12], "build": [2, 7, 12, 14], "block": [2, 7, 8, 9, 11, 14], "reduc": [2, 5, 7, 8, 9, 10, 11, 12], "creativ": [2, 9, 22], "combin": [2, 3, 4, 5, 7, 9, 10, 11, 12], "former": [2, 5, 6, 7, 8, 9, 10, 11, 12], "found": [2, 4, 7, 8, 9, 10, 12], "aris": [2, 7, 8], "librari": [2, 3, 5, 6, 7, 8, 11, 12, 20], "gsl": [2, 3, 7, 20], "23": [2, 3, 5, 6, 7, 9, 10, 11, 12, 20], "solid": 2, "effect": [2, 3, 4, 5, 9, 10, 11, 12], "deal": [2, 4, 5, 6, 8, 9, 10, 12], "dplyr": [2, 7], "caret": [2, 6], "todai": 2, "sequel": [2, 10, 12], "advoc": [2, 7, 9], "art": [2, 9, 12, 20], "pipelin": [2, 7, 9, 10, 14], "balanc": 2, "between": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "oneself": 2, "minimis": [2, 9, 10, 11], "lazi": [2, 7, 8, 10], "stand": [2, 3, 6, 7, 8, 11], "shoulder": [2, 7], "giant": 2, "suggest": [2, 3, 8, 9, 10, 11], "self": [2, 7, 9, 10], "unless": [2, 4, 5, 7, 9, 10, 11], "explicitli": [2, 4, 7, 8, 9, 10, 11, 12], "state": [2, 3, 5, 7, 9, 10, 11, 12], "construct": [2, 6, 7, 8, 10, 11, 13, 14, 15, 16, 17, 18], "while": [2, 4, 9, 11], "unnecessari": 2, "discourag": [2, 6, 9, 10], "against": [2, 3], "take": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "up": [2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 22], "partial": [2, 5, 10, 11, 12], "solut": [2, 3, 5, 8, 9, 11], "internet": [2, 7, 8], "seek": [2, 5, 22], "relev": [2, 7, 9, 11], "those": [2, 5, 6, 7, 9, 10, 11, 12, 22], "23e": [2, 3], "000123": 2, "latter": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "notat": [2, 5, 6, 7, 8, 9, 10, 11], "small": [2, 3, 5, 6, 7, 9, 10], "magnitud": [2, 3], "equal": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "word": [2, 3, 5, 6, 7, 9, 10, 11, 12, 14], "move": [2, 6, 7, 9, 12], "decim": [2, 3, 6, 8, 9], "digit": [2, 3, 4, 6, 8, 9, 11, 12, 20], "toward": [2, 6], "left": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "inher": [2, 9, 10, 11], "temporarili": [2, 9], "unknown": [2, 7, 11], "ot": 2, "vailabl": 2, "equip": [2, 4, 5, 7, 9, 10, 11, 12, 13], "indic": [2, 5, 7, 8, 9, 10, 11, 12], "na_real_": [2, 3, 4, 5, 7, 9, 10], "null": [2, 5, 7, 8, 9, 10, 11, 12, 22], "marker": [2, 6], "databas": [2, 5, 7, 8, 9, 11, 20], "queri": [2, 7, 9, 10], "sql": [2, 5, 7, 8], "chiefli": [2, 5], "inf": [2, 4, 5, 9], "infin": 2, "infti": [2, 5], "larger": [2, 8, 9, 10, 12, 14], "largest": [2, 5, 8, 9, 11], "represent": [2, 3, 4, 6, 20], "precis": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "64": [2, 3, 5, 6, 7, 9, 11, 12], "bit": [2, 3, 4, 5, 6, 7, 10], "float": [2, 4, 6, 20], "point": [2, 4, 5, 6, 7, 8, 9, 11, 12, 20], "nan": [2, 4, 6, 8], "illeg": 2, "possibli": [2, 6, 7, 8, 9, 10, 12], "context": [2, 3, 4, 5, 6, 7, 10, 11, 12], "an": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20, 22], "ellipsi": [2, 22], "licat": 2, "tile": 2, "interestingli": [2, 5, 6, 8, 11], "behaviour": [2, 4, 5, 9, 10, 11, 12], "correspond": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "across": [2, 9, 11, 13], "notion": [2, 9, 10], "unfortun": [2, 3, 4, 6, 7, 9, 10, 11, 12], "peculiar": [2, 4, 9, 10, 11, 12], "match": [2, 4, 7, 8, 9, 10, 11, 12], "keyword": [2, 3, 7], "pass": [2, 5, 6, 8, 10, 11, 12], "mention": [2, 4, 5, 6, 7, 8, 9, 10, 11, 12], "whether": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "rang": [2, 3, 6, 7, 9, 11, 12], "matter": [2, 3, 4, 5, 6, 10, 12], "tast": [2, 9, 10, 11], "somehow": [2, 9, 12], "rememb": [2, 5, 7, 9, 10, 12], "nevertheless": [2, 6, 7, 12], "drastic": 2, "repetit": [2, 7, 9], "pattern": [2, 4, 5, 7, 8, 22], "prone": [2, 7], "warn": [2, 3, 4, 5, 6, 8, 9, 10, 11, 12], "zero": [2, 3, 4, 8, 10, 11], "tricki": [2, 12], "empti": [2, 5, 7, 8, 9, 12], "space": [2, 6, 7, 11], "linear": [2, 5, 7, 8, 10], "increment": [2, 6], "decrement": 2, "via": [2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "00": [2, 3, 6, 7, 9, 10, 11, 12], "75": [2, 5, 7, 8, 9, 11], "25": [2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 20], "step": 2, "seq_along": [2, 8, 9, 12], "seq_len": [2, 8, 11, 12], "drawn": [2, 9], "univari": 2, "runif": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "uniform": [2, 7, 9, 20], "287578": [2, 12], "788305": [2, 12], "408977": [2, 12], "883017": [2, 12], "940467": [2, 11, 12], "045556": [2, 8, 11, 12], "528105": 2, "rnorm": [2, 3, 8, 11, 12], "23950": 2, "10897": 2, "11724": 2, "18308": 2, "28055": 2, "72727": 2, "69018": 2, "These": [2, 3, 5, 6, 7, 8, 11, 12], "seven": [2, 5], "unit": [2, 6, 7, 9, 11], "interv": [2, 3, 7, 9], "class": [2, 3, 4, 5, 7, 9, 12, 22], "occur": [2, 7, 8, 10], "variou": [2, 3, 7, 9, 11, 12], "world": [2, 3, 9, 10, 11, 22], "prob": [2, 3], "fed": [2, 4, 6, 7, 8, 10, 11, 12], "realis": [2, 3, 7, 12], "random": [2, 3, 5, 7, 8, 9, 11, 12, 20], "variabl": [2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 22], "pr": [2, 7], "obtain": [2, 3, 4, 5, 6, 7, 11, 12], "similarli": [2, 5, 7, 8, 9, 11, 12], "synonym": [2, 3, 5, 11, 12], "danger": [2, 3], "occasion": [2, 4, 7, 8], "backfir": 2, "lead": [2, 3, 4, 5, 7, 9, 10, 12], "nonetheless": 2, "extra": [2, 4, 5, 12], "care": [2, 3, 4, 5, 6, 7, 9, 10, 11, 12], "stress": [2, 6, 9, 10, 11, 12], "mere": [2, 3, 4, 5, 7, 9, 10], "pseudo": [2, 20], "mersenn": 2, "twister": 2, "mt19937": 2, "36": [2, 4, 9, 10, 20], "rng": 2, "24": [2, 4, 5, 7, 10, 11, 12, 20], "33": [2, 3, 5, 7, 10, 11, 12, 20], "seed": [2, 8], "re": [2, 3, 5, 7, 8, 9, 10, 12], "integ": [2, 3, 4, 5, 7, 9, 10, 11, 12], "b": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "d": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20], "h": [2, 4, 5, 8, 9, 10, 11, 20], "previous": [2, 5, 6, 12], "did": [2, 6, 7, 9], "crucial": [2, 7, 9, 10], "condit": [2, 3, 7, 9, 11, 22], "exactli": [2, 3, 4, 5, 6, 11, 12], "claim": 2, "unsuspici": 2, "pick": 2, "1234": 2, "mont": 2, "carlo": 2, "th": [2, 3, 5, 7, 9, 11], "anyhow": 2, "sure": [2, 3, 5, 7, 8, 9, 10, 12], "accus": 2, "tamper": 2, "evid": [2, 9], "ultim": [2, 6, 7, 9, 10], "lucki": [2, 10], "1679619": 2, "total": [2, 5, 6, 7, 10, 12], "alongsid": [2, 9], "transpar": [2, 9, 10], "fulli": [2, 6, 11, 12], "trustworthi": 2, "restor": [2, 4, 12], "initialis": [2, 11], "wall": 2, "identifi": [2, 6, 9, 12], "pid": 2, "impress": [2, 10], "said": [2, 3, 4, 5, 9, 10, 11, 12], "euraud": [2, 4, 5, 7], "20200101": [2, 5, 7, 11], "20200630": [2, 5, 7, 11], "csv": [2, 4, 5, 6, 7, 8, 10, 11, 12], "eur": [2, 4], "aud": [2, 4], "exchang": [2, 4, 6, 12], "australian": 2, "dollar": [2, 5, 22], "euro": 2, "januari": [2, 4], "30": [2, 3, 4, 5, 9, 10, 11, 12, 20], "june": [2, 4], "2020": [2, 4, 20], "covid": 2, "preview": [2, 5], "coupl": [2, 6, 7, 9, 10, 11], "warehous": 2, "european": 2, "central": 2, "bank": 2, "www": [2, 6, 20], "ecb": 2, "europa": 2, "eu": 2, "stat": [2, 4, 7, 10, 12], "policy_and_exchange_r": 2, "charg": 2, "6006": [2, 4], "6031": [2, 4], "human": [2, 3, 6, 10], "wednesdai": 2, "forex": [2, 7], "observ": [2, 4, 5, 8, 9, 12], "paste0": [2, 6, 8, 9, 11, 12], "github": [2, 6, 7, 9, 11, 12], "com": [2, 6, 7, 8, 9, 11, 12, 19, 20, 22], "gagolew": [2, 6, 7, 8, 11, 12], "raw": [2, 7, 8, 11], "master": [2, 6, 7, 8, 11, 12, 13, 20], "char": [2, 4, 6, 11, 12], "6119": [2, 4], "6251": [2, 4], "6195": [2, 4], "6193": [2, 4], "6132": [2, 4], "6117": [2, 4], "6110": [2, 4], "6188": [2, 4], "6115": [2, 4], "6122": [2, 4], "6154": 2, "21": [2, 5, 6, 7, 9, 10, 11, 12, 20], "6177": 2, "6184": 2, "6149": 2, "6127": 2, "6291": 2, "6290": 2, "6299": 2, "6412": 2, "6494": 2, "6521": 2, "6439": 2, "6282": 2, "6417": 2, "6373": 2, "6260": 2, "6175": 2, "6138": 2, "6151": 2, "6129": 2, "6142": 2, "51": [2, 5, 9, 10, 12], "6294": 2, "6363": 2, "6384": 2, "6442": 2, "6565": 2, "6672": 2, "6875": 2, "61": [2, 12], "6998": 2, "6911": 2, "6794": 2, "6917": 2, "7103": 2, "7330": 2, "7377": 2, "71": [2, 10], "7389": 2, "7674": 2, "7684": 2, "8198": 2, "8287": 2, "8568": 2, "8635": 2, "8226": 2, "81": [2, 9, 12], "8586": 2, "8315": 2, "7993": 2, "8162": 2, "8209": 2, "8021": 2, "91": [2, 12], "7967": 2, "8053": 2, "7970": 2, "8004": 2, "7790": 2, "7578": 2, "7596": 2, "reach": [2, 3, 10], "getopt": [2, 7, 10, 11], "max": [2, 3, 4, 5, 7, 8, 10, 11, 12], "omit": [2, 4, 5, 10, 11, 12], "83": [2, 20], "too": [2, 3, 5, 7, 8, 10, 11, 12], "fit": [2, 6, 8, 10, 11, 12], "url": [2, 20, 22], "home": [2, 7, 10], "portabl": [2, 6, 7, 10, 12, 20], "reason": [2, 3, 5, 6, 7, 9, 11, 12], "slash": [2, 6], "platform": [2, 7, 9, 12], "recognis": [2, 4, 12], "rel": [2, 3, 7, 9, 10, 12], "getwd": [2, 7], "side": [2, 3, 4, 5, 7, 9, 10, 11], "parent": [2, 11], "iri": [2, 4, 6, 9, 10, 11, 12, 13], "dec": [2, 5, 12], "sep": [2, 5, 6, 7, 9, 11, 12], "show": [2, 3, 4, 7, 9, 11, 12], "graph": [2, 7, 11, 20], "aforement": [2, 9], "xlab": [2, 7, 11], "ylab": [2, 7, 11], "01": [2, 4, 6, 8, 9, 10, 11, 12, 20], "06": [2, 4, 12], "182": 2, "misleadingli": 2, "appar": 2, "col": [2, 3, 5, 7, 10, 11, 12, 13], "pch": [2, 13], "cex": 2, "lty": [2, 5, 7, 11], "lwd": 2, "routin": [2, 7, 9, 11], "bring": [2, 4, 7, 12], "forth": [2, 4, 5, 7, 9, 11, 12], "memoris": 2, "assign": [2, 3, 4, 6, 7, 8, 9, 11], "bind": [2, 3, 7, 9, 11, 12], "recal": [2, 4, 5, 7, 8, 9, 10, 11, 12, 16], "dealt": [2, 10, 13], "consol": [2, 3, 4, 5, 6, 8, 9, 11], "sensit": 2, "coexist": 2, "peacefulli": 2, "tri": [2, 4, 8, 9, 11], "syntact": [2, 5, 7, 10, 12, 22], "except": [2, 4, 5, 6, 7, 9, 10, 11, 12, 22], "letter": [2, 4, 5, 6, 9, 10, 11, 12], "underlin": 2, "2wai": 2, "reserv": [2, 3, 8, 19, 22], "explanatori": [2, 10], "friendli": [2, 3, 7, 9, 10, 12], "patient": [2, 3], "average_scor": 2, "xyz123": 2, "crap": 2, "bad": [2, 9, 10, 12], "y": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20], "z": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "matric": [2, 4, 5, 8, 9, 10, 12, 22], "l": [2, 3, 4, 5, 6, 7, 9, 11, 12, 20], "size": [2, 4, 5, 6, 8, 9, 10, 11, 12], "p": [2, 3, 4, 5, 6, 7, 8, 11, 20], "nx": [2, 8], "ny": [2, 8], "especi": [2, 3, 4, 7, 8, 9, 10, 11, 12], "temporari": [2, 7, 9, 12], "adopt": 2, "snake_cas": 2, "lowercamelcas": 2, "uppercamelcas": 2, "flatcas": 2, "coher": 2, "adher": [2, 9], "agre": [2, 3], "contribut": [2, 7, 9], "asterisk": 2, "na_omit": 2, "naomit": 2, "java": [2, 12], "habitu": 2, "dynam": [2, 6, 7, 20], "exist": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "bound": [2, 5, 7, 8, 9, 11], "100": [2, 3, 4, 5, 9, 10, 11, 12], "suppress": [2, 7, 9], "verbatim": 2, "destroi": 2, "garbag": [2, 7], "collector": 2, "got": [2, 4, 5, 9], "rid": [2, 4, 5, 8, 11, 12], "begotten": 2, "memori": [2, 3, 6, 8, 9, 10, 11, 12], "boldsymbol": [2, 3, 4, 5, 11], "x_1": [2, 5, 7, 8, 9, 11], "x_2": [2, 5, 7, 8, 9, 11], "x_n": [2, 5, 7], "x_i": [2, 5, 7, 8], "ubiquit": [2, 10], "squar": [2, 3, 5, 7, 8, 9, 10, 11], "root": [2, 7, 9], "act": [2, 3, 4, 5, 7], "transform": [2, 3, 5, 7, 9, 11], "mark": [2, 6, 11], "don": [2, 3, 9, 10], "t": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20], "produc": [2, 3, 6, 7, 8, 9, 10, 12], "4142": [2, 7, 11], "attract": [2, 13], "neg": [2, 3, 8, 10], "reckon": 2, "irrat": 2, "crude": 2, "41421356237309504880168872420969807856967187537694": 2, "aesthet": [2, 6, 13], "roughli": [2, 8, 10, 11], "shall": 2, "devil": 2, "signific": 2, "000000000000000": 2, "414213562373095": 2, "portion": [2, 9], "fraction": [2, 3, 6], "floor": [2, 9], "down": [2, 4, 8, 10], "nearest": 2, "lfloor": 2, "rfloor": 2, "ceil": 2, "lceil": 2, "rceil": 2, "trunc": 2, "0001": 2, "9999": [2, 9], "3149": 2, "19999": 2, "4567": 2, "765": 2, "4321": 2, "766": 2, "124": 2, "800": [2, 11, 12], "exp": [2, 9, 11], "euler": 2, "simeq": [2, 7], "718": [2, 9], "log": [2, 3, 4, 8, 9, 10, 11, 12], "log_": 2, "invers": [2, 5, 11, 12], "3891": 2, "0855": 2, "grow": [2, 8, 9, 11], "ident": [2, 3, 5, 7, 9, 10, 11, 12], "inequ": 2, "cdot": [2, 11], "glanc": [2, 22], "handbook": [2, 20], "38": [2, 4, 10, 20], "1000": [2, 5, 8, 9, 10, 11], "1e10": 2, "neq": [2, 11], "rapidli": 2, "1001": 2, "par": 2, "mfrow": 2, "axi": [2, 9], "v": [2, 3, 4, 5, 6, 9, 11, 12, 22], "ax": [2, 6, 11], "strictli": [2, 5], "greater": [2, 3, 5, 6, 7, 9, 10, 11, 12], "unif": 2, "norm": 2, "gamma": 2, "mathrm": [2, 3, 11], "lnorm": 2, "cauchi": 2, "lorentz": 2, "chisq": 2, "chi": 2, "snedecor": 2, "fisher": 2, "weibul": 2, "prefix": [2, 6, 12], "densiti": 2, "cumul": [2, 7], "cdf": 2, "surviv": [2, 9, 11], "sf": 2, "q": [2, 3, 4, 7, 11], "quantil": [2, 4, 5, 12], "discret": [2, 11], "enumer": [2, 10], "binom": [2, 10], "binomi": 2, "geom": 2, "geometr": 2, "poi": 2, "poisson": 2, "hyper": 2, "hypergeometr": 2, "nbinom": 2, "mass": 2, "pmf": 2, "generalis": [2, 4, 7, 9, 11, 12], "characteris": 2, "mu": [2, 3], "sigma": [2, 3], "pinpoint": [2, 3, 5, 7, 11], "mathbb": [2, 11], "sd": [2, 4, 7, 12], "dnorm": 2, "parametris": 2, "subtli": 2, "parameteris": 2, "varianc": [2, 11], "reciproc": [2, 3, 11], "advis": [2, 3, 8], "carefulli": [2, 10, 12], "dunif": 2, "dexp": 2, "dbinom": 2, "event": [2, 4, 9], "per": [2, 7, 8, 9, 10], "hour": [2, 7, 10], "hist": [2, 3, 4, 9], "draw": [2, 11, 12, 13], "histogram": 2, "estim": [2, 5, 8], "10000": [2, 3, 11], "white": [2, 3], "101": [2, 3, 5, 7, 9, 12], "\u00b5": 2, "\u03c3": 2, "belong": [2, 3], "rbeta": 2, "\u03b1": 2, "\u03b2": 2, "alpha": [2, 19], "rexp": 2, "\u03bb": 2, "lambda": 2, "break": [2, 3, 5, 7, 9, 12], "xlim": 2, "ylim": [2, 5, 10], "roll": 2, "six": [2, 5, 11, 12], "dice": [2, 8], "face": [2, 7, 9, 12], "thrown": 2, "bin": [2, 12], "bernoulli": 2, "112157": 2, "269176": 2, "296094": 2, "197396": 2, "088828": 2, "throw": [2, 8], "le": [2, 3, 7, 8, 11], "pbinom": 2, "lower": [2, 3, 6, 7, 11], "tail": [2, 8, 9, 10, 22], "12518": 2, "smallest": [2, 5, 12], "ge": [2, 3, 7, 11], "95": [2, 7, 9], "qbinom": 2, "87482": 2, "96365": 2, "rbinom": 2, "assort": 2, "certain": [2, 4, 6, 7, 9, 10], "appear": [2, 6, 7, 9, 10, 12], "sake": [2, 3, 7, 9, 10, 11, 12, 22], "breviti": 2, "int_0": 2, "dt": [2, 10], "frac": [2, 3, 4, 5, 7, 11], "tailor": [2, 11], "faster": [2, 5, 7, 8, 10, 11, 12], "dii": 2, "250": [2, 5, 11], "okai": [2, 6, 7, 9, 11, 12], "91213": 2, "172": 2, "due": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12], "infinit": [2, 3, 8, 10], "plenti": [2, 5, 8], "28": [2, 7, 10, 11, 12, 20], "famou": [2, 9, 10], "pochhamm": 2, "_x": 2, "poch": [2, 7], "instal": [2, 6, 7, 8, 9, 20], "gsl_sf_poch": [2, 7], "1320": [2, 7], "17160": [2, 7], "240240": [2, 7], "3603600": [2, 7], "sinc": [2, 6, 7, 8, 10], "hesit": 2, "permut": [2, 5, 11, 12], "lgamma": 2, "lbeta": 2, "dbeta": [2, 9], "Its": [2, 5, 6, 10, 11, 12, 13], "classic": [2, 7], "maximum": [2, 7, 10, 11], "likelihood": 2, "subtract": [2, 3, 7, 10, 11], "multipl": [2, 3, 6, 7, 8, 9, 12], "divis": [2, 3, 5, 8, 9], "modulo": [2, 8], "remaind": [2, 9], "200": [2, 5, 11], "3000": [2, 11], "elementwis": [2, 3, 4, 5, 6, 7, 9, 10, 11], "fashion": [2, 4, 12], "multipli": [2, 6, 7, 9, 10, 11], "manner": [2, 3, 5, 8, 9, 10, 11], "00000": [2, 3, 7, 11], "33333": 2, "66667": 2, "statement": [2, 3, 5, 7, 8, 9, 10, 11, 12], "concis": [2, 4, 7, 9], "operand": [2, 8, 10, 11], "shorter": [2, 5, 8, 11, 12], "128": 2, "256": [2, 6], "512": [2, 9], "1024": [2, 5], "entireti": [2, 3, 5, 7, 8], "longer": [2, 5, 6, 8, 9, 10, 11, 12], "300": [2, 5, 11, 12], "600": [2, 11], "80": [2, 5, 9, 12], "deepli": [2, 6, 11], "22": [2, 3, 5, 6, 7, 10, 11, 12, 20], "288": [2, 4], "577": 2, "227": 2, "uniformli": 2, "pmin": 2, "pmax": [2, 3], "parallel": [2, 10, 11], "minimum": [2, 7, 11], "clip": [2, 5], "perhap": [2, 4, 6, 7, 8, 10, 11, 12], "taylor": 2, "expans": 2, "fold": [2, 6], "tensor": [2, 4], "apart": [2, 6, 7, 12], "noteworthi": [2, 3, 7, 10, 19], "unari": [2, 3, 5, 7, 11, 12], "govern": [2, 3, 9, 10], "enforc": [2, 5, 9, 10], "prioriti": 2, "doubt": [2, 9], "subexpress": [2, 6], "intend": [2, 6, 10, 12], "increas": [2, 5, 8, 9, 10, 12], "taken": [2, 3, 7, 11], "x_3": 2, "vdot": 2, "y_1": [2, 5, 7, 9], "y_2": [2, 5, 9], "y_3": 2, "y_n": [2, 5, 7], "cumsum": [2, 4, 7], "cumprod": [2, 4], "cummin": [2, 4], "cummax": [2, 4], "min": [2, 3, 4, 5, 7, 10, 11, 12], "qquad": 2, "quad": 2, "ddot": 2, "120": [2, 5], "720": 2, "5040": 2, "40320": 2, "summaris": [2, 3, 11, 12], "dispos": [2, 12], "sum_": [2, 3, 4, 5, 7, 11], "prod": [2, 7], "prod_": 2, "greatest": [2, 5, 11], "propag": [2, 3, 7, 10], "diff": [2, 5, 8, 10], "3rd": [2, 5, 9, 11], "4th": [2, 5, 6], "y_i": [2, 3, 4, 5, 11], "x_": [2, 7, 8, 11], "recreat": 2, "daili": [2, 3, 7, 12], "aud_al": 2, "remov": [2, 5, 7, 8, 9, 10, 11, 12], "ablin": [2, 11], "horizont": 2, "basi": [2, 3, 5, 8, 10, 11, 12], "var": [2, 4, 7], "unbias": 2, "median": [2, 4, 7, 12], "middl": [2, 5], "sort": [2, 5, 6, 7, 10, 11, 12], "00046535": 2, "49727780": 2, "48995025": 2, "99940453": 2, "28748391": 2, "harmon": 2, "abstract": [2, 7, 10], "sens": [2, 3, 4, 5, 7, 8, 9, 10, 11, 12], "anyth": [2, 3, 4, 5, 6, 7, 10, 12], "accur": [2, 3], "financi": [2, 3], "predict": [2, 8, 9, 10], "less": [2, 3, 5, 6, 7, 8, 9, 10, 12], "miser": 2, "super": [2, 6, 9], "phd": 2, "compani": [2, 9], "crunch": [2, 7], "hobbi": 2, "unavail": [2, 10], "rm": [2, 4, 7, 8, 9, 12], "behalf": 2, "request": [2, 9, 11], "6775": 2, "accept": [2, 3, 5, 8, 9, 10, 11, 12], "trim": [2, 5], "flexibl": [2, 9, 10, 11, 12], "ever": [2, 8], "hold": [2, 3, 7, 10, 11], "vice": 2, "versa": 2, "directli": [2, 5, 6, 7, 9, 11, 12], "compress": [2, 7, 11, 12], "archiv": [2, 7, 12], "gz": [2, 6, 7, 11], "arcsin": 2, "arccosin": 2, "straightforward": [2, 4, 9, 10], "asin": 2, "pi": [2, 3, 4, 6, 9, 11], "y_min": 2, "y_max": 2, "aco": 2, "label": [2, 5, 6, 9, 10, 11, 12], "red": [2, 5, 6, 7, 10], "dash": [2, 7], "legend": 2, "topright": 2, "black": [2, 9, 10], "bg": 2, "sin": [2, 3, 11], "view": [2, 7, 11], "shown": [2, 11], "2i": [2, 7], "converg": [2, 8, 9], "000": [2, 7, 9, 10, 11, 12], "pearson": [2, 20], "correl": [2, 5, 11], "coeffici": [2, 5, 11], "x_j": 2, "y_j": 2, "cor": [2, 5, 11], "averag": [2, 5, 10, 11, 12], "currenc": [2, 4], "smoothen": 2, "convolv": 2, "filter": [2, 6, 7, 12], "tempt": [2, 9, 12], "wrap": [2, 4, 5, 6, 7, 10, 12], "announc": 2, "twitter": 2, "noth": [2, 4, 7, 8, 9, 10, 11, 12], "els": [2, 3, 4, 7, 8, 9, 10, 11, 12], "entiti": [2, 4, 7, 9, 10, 11], "necess": [2, 9], "origin": [2, 8, 9, 11, 12], "everywher": 2, "almost": [2, 3, 5, 7], "redund": [2, 7, 12], "illusori": 2, "design": [2, 4, 5, 6, 7, 8, 10, 12, 20, 22], "compact": [2, 6, 10, 12], "altrep": [2, 6, 20], "incomplet": [2, 12], "inconsist": 2, "annoi": 2, "hope": [2, 5, 9, 22], "decad": 2, "fuss": 2, "constant": [3, 6, 7, 9], "meant": [3, 6, 7, 12], "instanti": [3, 9, 10, 11], "rep": [3, 4, 6, 8, 9, 10, 11, 12], "throughout": 3, "spell": 3, "na_logical_": 3, "mental": 3, "activ": [3, 5, 6, 7, 9, 12], "recycl": [3, 5, 6, 7, 9, 10, 11, 12], "rule": [3, 4, 5, 6, 7, 9, 10, 11, 12], "incorrect": 3, "na_reals_": 3, "finit": [3, 8, 9], "imposs": [3, 6], "1415926535897932384626433": 3, "preciou": 3, "wide": [3, 4, 10, 11, 12], "consensu": 3, "had": [3, 8, 9, 10, 11, 12, 20], "format": [3, 4, 7, 9, 10, 11, 12], "pm": [3, 5], "308": 3, "79": [3, 5, 9, 10, 11, 12], "00000000000000000000000000000000000000000000000000": 3, "000000000000000000000000000000000000000000000000000000000223": 3, "79e308": 3, "17900000000000000000000000000000000000000000000000000000000": 3, "distant": 3, "byte": [3, 6, 8], "12345678901234567890123456789012345678901234": 3, "1234567890123456773699": 3, "align": [3, 6, 11], "unexpect": [3, 8, 9, 10, 12], "suspici": 3, "mislead": 3, "1000000000000000055511": 3, "3000000000000000444089": 3, "2999999999999999888978": 3, "53": [3, 5, 6, 9], "beyond": [3, 8, 9], "violat": [3, 8, 9, 12], "1102e": 3, "1023": 3, "52": [3, 5, 10], "7977e": 3, "1022": 3, "9407e": 3, "324": [3, 4], "0000e": 3, "754": 3, "27": [3, 5, 7, 10, 11, 12, 20], "26": [3, 4, 5, 7, 10, 11, 12, 20], "audienc": [3, 9, 10], "issu": [3, 7, 9, 10, 12], "resourc": [3, 8, 9, 22], "dataset": [3, 5, 6, 7, 8, 9, 10, 11, 12], "rest": [3, 4, 9], "safe": [3, 4, 5, 8, 9], "sqrt": [3, 4, 6, 7, 8, 11], "sole": [3, 10, 11], "speak": [3, 7, 9], "treat": [3, 4, 5, 6, 7, 9, 10, 12], "neglig": 3, "account": [3, 6, 8, 9, 10, 11, 12], "obvious": [3, 5, 6], "margin": 3, "varepsilon": 3, "term": [3, 8, 9, 10, 12], "measur": [3, 4, 5, 10], "bah": 3, "sleep": 3, "exact": 3, "Their": [3, 4, 7, 10], "chain": [3, 7, 10], "forbidden": 3, "situat": [3, 6, 7, 8, 10, 12], "handi": [3, 5, 12], "negat": [3, 4], "conjunct": [3, 8], "xor": 3, "exclus": [3, 5, 9], "disjunct": 3, "again": [3, 4, 5, 6, 7, 9, 10, 11, 12], "confus": [3, 9, 10], "circuit": [3, 9], "reveal": [3, 6, 9, 10, 11], "\u0142ukasiewicz": 3, "substitut": [3, 5, 6], "moment": 3, "contempl": [3, 4, 5, 8, 9], "truth": [3, 7, 11], "appropri": [3, 6, 9, 11], "zone": [3, 10], "1e": [3, 9], "1998": [3, 11, 20], "proport": [3, 8], "aspir": 3, "fluent": 3, "tautologi": 3, "morgan": 3, "law": 3, "simplif": 3, "commut": 3, "symmetri": 3, "transit": [3, 9], "until": [3, 4, 5, 7, 8, 9, 10, 11], "ll": [3, 4], "t_i": [3, 11], "l_i": 3, "f_i": 3, "560476": 3, "230177": 3, "558708": 3, "070508": [3, 12], "129288": [3, 12], "715065": [3, 12], "46092": [3, 12], "26506": [3, 12], "68685": 3, "44566": 3, "22408": 3, "35981": 3, "40077": 3, "11068": 3, "55584": 3, "78691": 3, "49785": 3, "96662": 3, "21244": 3, "49838": 3, "12947": 3, "befor": [3, 5, 7, 8, 9, 10, 11, 12, 13], "decid": [3, 5, 9, 10, 12, 22], "44386": 3, "65202": 3, "04571": 3, "53945": 3, "logarithm": [3, 9], "nest": [3, 12], "55871": 3, "71506": 3, "xy": 3, "depict": [3, 12], "mixtur": 3, "sim": 3, "100000": [3, 6], "probabl": [3, 5, 7, 8, 9, 10, 11], "gaussian": 3, "variat": [3, 5, 20], "116": 3, "earth": 3, "flat": [3, 4, 11], "smallpox": 3, "vaccin": 3, "tendenc": [3, 10], "rewrit": [3, 5, 8, 9], "prevent": [3, 8, 9, 10], "verifi": [3, 4, 5, 7, 8, 11, 12], "log1p": 3, "expm1": 3, "belov": 3, "subject": [3, 6], "entropi": [3, 4], "loss": [3, 4, 7], "randomli": [3, 10, 12], "mathcal": [3, 4, 11], "ell_i": 3, "p_i": [3, 4, 7], "hospit": 3, "symptomat": 3, "confid": 3, "tree": [3, 6, 12], "person": 3, "unwel": 3, "quantifi": 3, "penalis": 3, "strong": [3, 12], "belief": [3, 10], "encount": [3, 4, 6, 9, 10], "higher": 3, "track": [3, 9], "brain": [4, 7, 10], "teas": 4, "cool": 4, "bare": [4, 12], "touch": [4, 10], "soon": [4, 8, 9, 12], "typeof": [4, 6, 7, 10, 11, 12], "gluten": 4, "demand": [4, 9, 22], "fly": [4, 7], "seen": [4, 7, 8, 10], "distinct": [4, 7, 10, 12], "na_character_": [4, 6, 7, 10], "23e4": 4, "12300": 4, "attempt": [4, 10, 11], "compos": 4, "wherea": [4, 11], "tend": [4, 5, 7, 9, 12], "wiser": 4, "unequivoc": 4, "1e9": 4, "pre": [4, 8], "alloc": [4, 6, 8, 10, 12], "vectoris": [4, 6, 8, 9, 12, 22], "ifels": [4, 8, 12, 22], "seamlessli": [4, 6], "translat": [4, 9, 10, 11, 12], "equat": 4, "recurs": [4, 5, 6, 7, 8], "wherev": [4, 8, 9], "multitud": 4, "notic": [4, 7, 11, 12], "overli": [4, 9], "talk": [4, 7], "18": [4, 5, 6, 7, 9, 10, 11, 12, 20], "28758": [4, 8, 12], "78831": [4, 12], "40898": [4, 12], "88302": [4, 12], "94047": [4, 12], "str": [4, 5, 10, 11, 12], "logi": [4, 12], "chr": [4, 10, 11, 12], "num": [4, 5, 10, 12], "788": 4, "409": 4, "883": 4, "94": [4, 5, 9, 11, 12], "retain": [4, 9, 12], "bytecod": [4, 7, 9, 10], "0x563242a38f18": 4, "namespac": [4, 7, 9, 10, 22], "concaten": [4, 7, 11, 12], "repeat": [4, 5, 6, 7, 9, 11, 12, 22], "flatten": [4, 6, 8], "unlist": [4, 7, 8, 9, 10, 11, 12], "simplify2arrai": [4, 9, 11, 12], "absenc": 4, "februari": 4, "march": [4, 12], "juli": 4, "august": 4, "septemb": [4, 6], "octob": [4, 12], "novemb": 4, "decemb": 4, "ness": 4, "alik": 4, "emplac": [4, 9], "semant": [4, 9], "invisibli": [4, 9], "inject": [4, 10], "unord": 4, "kei": [4, 5, 6, 9, 10, 12], "pair": [4, 5, 6, 8, 9, 11, 12], "x_simpl": 4, "attribute1": 4, "value1": 4, "attribute2": 4, "attr": [4, 5, 6, 9, 10, 11, 12], "concern": [4, 5, 6, 10, 12], "tini": [4, 5], "metadata": [4, 9], "ordinari": [4, 9, 10, 11, 12], "55": [4, 5, 7], "perk": 4, "pai": [4, 9, 12], "sneak": 4, "70": [4, 5, 10, 12], "y_na_fre": 4, "action": [4, 7, 9], "tell": [4, 9, 10], "gregexpr": [4, 6], "needl": [4, 6], "OR": 4, "haystack": [4, 6], "spammer": 4, "po": 4, "usebyt": [4, 6], "sought": [4, 7], "occurr": [4, 7, 8, 10], "gbp": 4, "usd": 4, "eurgbp": [4, 7], "eurusd": [4, 6, 7], "currency_from": 4, "currency_to": 4, "date_from": 4, "date_to": 4, "great": [4, 9, 12], "potenti": [4, 5, 9, 10, 12], "wast": [4, 7], "pessimist": 4, "realist": 4, "predestin": 4, "role": [4, 7, 12], "dimnam": [4, 5, 9, 11, 12], "dim": [4, 5, 7, 9, 10, 11, 12], "map": [4, 5, 6, 8, 9, 10, 11, 12], "spite": 4, "whatsoev": [4, 9, 11], "accessor": [4, 5, 11], "meaning": [4, 12], "sausag": [4, 10], "celeri": 4, "improv": [4, 7, 9, 10], "garner": [4, 12], "nice": [4, 5, 6, 8, 9, 12, 14], "additional_attribut": 4, "presenc": [4, 7, 9, 22], "smart": [4, 7], "scipen": 4, "width": [4, 6, 9, 10, 12, 13], "bore": [4, 7, 9], "df": [4, 10, 12], "head": [4, 6, 8, 9, 10, 12, 22], "sepal": [4, 9, 10, 11, 12, 13], "petal": [4, 9, 10, 12, 13], "speci": [4, 9, 10, 11, 12, 13], "setosa": [4, 9, 11, 12], "unclass": [4, 10, 11], "versicolor": [4, 9, 10, 11, 12], "virginica": [4, 9, 10, 11, 12], "value2": 4, "attribute3": 4, "value3": 4, "unset": [4, 10], "onc": [4, 8, 9, 10, 11, 12], "attribute4": 4, "ad": [4, 8, 10, 12], "un": [4, 7], "unnam": [4, 5, 11, 12], "some_attribut": 4, "new_valu": 4, "preserv": [4, 10, 11, 12, 22], "That": [4, 9, 10, 11, 12], "join": [4, 6, 11], "unwound": 4, "readrd": 4, "serialis": 4, "snapshot": 4, "disk": [4, 8, 9], "saverd": 4, "jsonlit": [4, 12], "fromjson": 4, "rejoic": 4, "devot": [4, 9, 12], "delici": [4, 5], "stimul": 4, "lightweight": [5, 9, 10], "fetch": [5, 6, 7, 10, 11, 12], "wish": [5, 7, 9, 10, 11], "big": [5, 8], "retriev": [5, 12], "seq": [5, 6, 7, 9, 10], "wonder": [5, 9], "110": [5, 11, 12], "130": [5, 10], "140": 5, "150": [5, 10, 12], "160": [5, 12], "170": 5, "180": 5, "190": [5, 12], "210": 5, "220": 5, "230": 5, "240": 5, "260": [5, 10, 12], "270": 5, "280": 5, "290": 5, "310": 5, "320": [5, 12], "330": 5, "340": 5, "350": [5, 12], "360": [5, 12], "370": 5, "380": 5, "390": 5, "400": [5, 11, 12], "410": 5, "420": 5, "430": 5, "440": [5, 12], "450": 5, "460": [5, 12], "470": 5, "480": 5, "490": 5, "500": [5, 11, 12], "510": 5, "visual": [5, 7], "hint": [5, 7], "boundari": [5, 9, 10], "stori": [5, 9, 10, 11, 12], "compon": [5, 6, 7, 9, 10, 11], "dig": [5, 7], "subscript": 5, "smaller": [5, 6], "exclud": 5, "consecut": [5, 7, 8, 9, 12], "ampl": 5, "perfect": [5, 14], "candid": [5, 12], "7777": 5, "log10": 5, "pseudorandom": [5, 8, 9, 11], "88": [5, 10, 11, 12], "05": [5, 9, 10, 12], "89": [5, 9], "46": [5, 12, 20], "birth": 5, "graham": 5, "terri": 5, "eric": 5, "michael": 5, "food": [5, 8, 9, 12], "egg": [5, 6, 7, 8, 9, 10, 11, 12], "bean": 5, "1941": 5, "1939": 5, "1942": 5, "1943": 5, "1940": 5, "born": 5, "lover": 5, "ag": [5, 9, 11, 12], "1969": [5, 10], "didn": 5, "utmostli": 5, "top": [5, 8, 9, 10, 12, 13], "unwrap": 5, "uniqu": [5, 6, 7, 8, 10, 11, 12], "direct": [5, 7, 9, 10, 11, 12], "workaround": [5, 10, 11, 12], "avoid": [5, 7, 8, 9, 11, 12], "repertoir": 5, "steve": 5, "pout": 5, "old": [5, 6, 9, 10, 12], "implicit": [5, 6, 10, 11, 12], "coercion": [5, 6, 8, 10, 12], "pour": 5, "wineskin": 5, "final": [5, 8, 10], "brought": [5, 11], "becam": [5, 11, 12], "forgotten": [5, 10], "alter": [5, 8, 9, 10, 11, 12], "safest": 5, "102": 5, "103": [5, 11, 20], "104": 5, "105": [5, 11], "106": [5, 12], "107": 5, "108": [5, 9, 12], "109": 5, "sub": [5, 6, 7, 11, 12], "idx": 5, "wrote": [5, 9], "drop": [5, 6, 8, 9, 10, 12], "push": [5, 9], "unlabel": 5, "blank": [5, 12], "five": [5, 9, 12], "slice": [5, 10], "intertwin": 5, "lefthand": [5, 10], "asid": 5, "ham": [5, 6, 7, 8, 12], "abb": 5, "jan": 5, "feb": 5, "mar": 5, "apr": 5, "jun": 5, "jul": 5, "aug": 5, "oct": 5, "nov": 5, "findinterv": [5, 8, 10], "inclus": [5, 6, 9], "knot": 5, "cccc": [5, 7, 11], "footnotes": 5, "66": 5, "member": [5, 11], "divid": [5, 6, 7, 10, 11], "pigeonhol": 5, "unsurprisingli": [5, 9], "z1": 5, "z2": 5, "toothgrowth": [5, 12], "experiment": 5, "guinea": 5, "pig": 5, "vitamin": 5, "supp": [5, 12], "lement": 5, "dose": [5, 12], "growth": [5, 8], "rodent": 5, "teeth": 5, "len": [5, 12], "gth": 5, "attrib": 5, "57": [5, 11, 12], "vc": [5, 12], "oj": [5, 12], "_": [5, 11], "oj_0": 5, "vc_0": 5, "oj_1": 5, "vc_1": 5, "oj_2": 5, "vc_2": 5, "medit": 5, "consciou": [5, 10], "avg": [5, 12], "BY": [5, 12, 22], "hurri": 5, "appetis": 5, "feed": [5, 9], "boxplot": [5, 10], "whisker": 5, "unsplit": [5, 7, 12], "revok": 5, "some_transform": 5, "standardis": [5, 7, 9, 11, 12], "666": [5, 10], "32787": 5, "bass": 5, "aaargh": 5, "aargh": 5, "aaaargh": 5, "lexicograph": [5, 6, 10], "dictionari": 5, "ow": [5, 7, 9, 10], "ti": [5, 6, 7, 9, 12], "guarante": [5, 9, 10, 12], "nonincreas": 5, "decreas": [5, 10, 12], "induc": 5, "speed": [5, 10, 11, 12], "bottleneck": [5, 9], "bother": 5, "pleasant": [5, 9], "expand": [5, 9, 12], "footprint": 5, "unsort": 5, "criteria": [5, 12], "resolv": 5, "rearrang": 5, "y1": [5, 7, 10], "y2": [5, 7, 10], "rank": [5, 6, 12], "7th": 5, "broken": 5, "proper": [5, 11], "theoret": [5, 12], "union": [5, 7, 12], "tabul": [5, 7, 10, 11], "conceiv": 5, "author": [5, 7, 9, 10, 11, 22], "put": [5, 7, 8], "spend": [5, 9], "strategi": [5, 7, 9], "48": [5, 6, 10, 11, 20], "attrib1": 5, "necessarili": [5, 6, 8, 9, 10, 11, 12], "adjust": [5, 11, 12], "accordingli": [5, 11], "prefer": [5, 7, 8, 9, 11, 12], "attrib2": 5, "4000": 5, "suffic": [5, 10, 11, 12], "significantli": [5, 10, 12], "mistak": [5, 10], "8th": 5, "9th": 5, "5th": 5, "propos": [5, 7, 10], "winsoris": 5, "q_p": 5, "q_": 5, "spearman": 5, "varrho": 5, "mathbf": [5, 11], "d_i": 5, "r_i": [5, 11], "s_i": 5, "approx": [5, 12], "interpol": [5, 7, 9, 12], "linearli": [5, 9, 12], "unobserv": 5, "somewher": [5, 9, 10], "spline": [5, 7], "cubic": 5, "x_new": 5, "y_new1": 5, "xout": 5, "y_new2": 5, "blue": 5, "piecewis": [5, 7], "imput": 5, "62": [5, 10, 11, 12], "58": [5, 9, 12], "fill": [5, 9, 11, 12], "63": [5, 9, 12], "rev": 5, "choos": [5, 8, 9, 10, 22], "fulfil": [5, 7, 9], "intersect": 5, "setdiff": 5, "setequ": 5, "cheapli": 5, "flag": [5, 12], "fantast": [5, 9], "econom": 6, "effici": [6, 8, 9, 10, 11, 12], "wow": 6, "innit": 6, "delimit": [6, 7], "apostroph": 6, "li": 6, "ol": 6, "love": [6, 7, 9, 12], "escap": [6, 8], "embrac": [6, 7], "backslash": 6, "implicitli": [6, 9], "nchar": 6, "disabl": 6, "devic": 6, "cursor": 6, "backspac": 6, "tab": [6, 7, 12], "stop": [6, 8, 9, 10], "carriag": 6, "abc": 6, "bd": [6, 11], "tef": 6, "rg": 6, "nhij": 6, "gbd": 6, "ef": 6, "hij": 6, "unbuff": 6, "stderr": [6, 7, 8], "statu": 6, "anim": 6, "bar": [6, 12], "eta": 6, "ecma": 6, "ansi": 6, "x3": [6, 7, 10, 12], "u001b": 6, "colour": [6, 9, 13], "31m": 6, "bold": [6, 7], "0m": 6, "reset": [6, 10, 12], "31mspam": 6, "36m": 6, "abacon": 6, "espam": 6, "unicod": [6, 20], "149": 6, "186": 6, "emoji": 6, "chart": 6, "invert": 6, "exclam": 6, "latin": 6, "supplement": 6, "hexadecim": 6, "0xa1": 6, "161": 6, "magic": [6, 10], "uxxxx": 6, "uxxxxxxxx": 6, "eight": 6, "u00a1": 6, "u000000a1": 6, "utf": 6, "encod": [6, 10, 11], "nativ": [6, 10], "latin1": 6, "cp1252": 6, "iconv": 6, "render": 6, "unabl": [6, 9], "ey": [6, 9], "joy": 6, "none": [6, 9], "glyph": 6, "properli": [6, 9, 11], "cordial": 6, "u0001f642": 6, "u2665": 6, "u0bb8": 6, "u0001f923": 6, "u0001f60d": 6, "u2307": 6, "\u0bb8": 6, "trivial": [6, 8, 9], "a1": [6, 7, 12], "b2": [6, 12], "c3": [6, 12], "collaps": [6, 9, 10, 11], "a1b2c1d2": 6, "customis": 6, "pretti": [6, 8, 10, 12], "123456": 6, "789": 6, "7890": 6, "drop0trail": 6, "1415927": 6, "sprintf": [6, 7, 8, 10, 11], "workhors": [6, 11], "justif": 6, "percent": 6, "2f": 6, "occupi": 6, "insert": [6, 11, 12], "5f": 6, "az": 6, "1f": 6, "142": 6, "readlin": [6, 8, 12], "readm": [6, 8], "train": [6, 12], "hard": [6, 9, 11, 12], "writelin": 6, "append": 6, "deriv": [6, 11], "bytewis": 6, "german": 6, "deem": [6, 12], "gross": 6, "unnormalis": 6, "nfc": 6, "canon": 6, "consider": [6, 10, 12], "startswith": 6, "spamtast": 6, "spontan": 6, "spoon": 6, "endswith": 6, "suffix": 6, "charmatch": 6, "sp": 6, "spoo": 6, "spoof": 6, "ambigu": 6, "arg": [6, 7, 9, 11], "grepl": [6, 7], "spammit": 6, "yummi": [6, 9, 12], "sram": 6, "regex": 6, "grep": [6, 9, 12], "familiar": [6, 7, 10, 11], "curios": [6, 12], "agrepl": 6, "levenshtein": [6, 11], "distanc": [6, 8, 11], "perl": [6, 7], "pcre2": 6, "man": [6, 9], "pcre2pattern": 6, "er": 6, "tre": 6, "poorer": 6, "air_quality_1973": 6, "anscomb": 6, "titan": [6, 9, 11, 12], "tooth_growth": 6, "world_phon": 6, "regexpr": 6, "3th": 6, "attribut": [6, 7, 10, 11, 12, 22], "worthwhil": 6, "global": [6, 9, 10], "insensit": 6, "clever": 6, "along": 6, "aid": 6, "meanwhil": 6, "regmatch": 6, "parenthesis": 6, "captur": 6, "basenam": 6, "unpack": 6, "something_els": 6, "txt": 6, "regexec": 6, "gregexec": 6, "gsub": 6, "hammit": 6, "thereto": [6, 11, 12], "aha": 6, "gag": 6, "palindrom": 6, "glob2rx": 6, "wildcard": 6, "strsplit": 6, "spammiti": 6, "10th": 6, "exce": 6, "chickpea": 6, "composit": 6, "tolow": 6, "toupper": 6, "upper": [6, 8, 11], "chartr": 6, "window": [6, 7], "cmd": [6, 9], "ex": [6, 9], "xtfrm": [6, 10, 12], "ch\u0142odni": 6, "hardi": 6, "chladn\u00fd": 6, "hladn\u00fd": 6, "local": [6, 7, 10, 12, 22], "sy": [6, 7, 10, 12], "getlocal": 6, "lc_collat": 6, "slovak": 6, "transmit": [6, 8], "1970": [6, 10], "gmt": [6, 10], "strptime": [6, 10], "strftime": [6, 10, 12], "stringx": [6, 7, 9, 10, 20], "icu": [6, 7], "suppresspackagestartupmessag": 6, "sk_sk": 6, "gro": 6, "u00df": 6, "detach": 6, "unload": 6, "pictur": 6, "briefli": [6, 11, 12], "1l": [6, 7, 11, 12], "2l": [6, 11], "na_integer_": 6, "truncat": [6, 12], "vast": 6, "major": [6, 9, 11, 22], "silent": 6, "coerc": [6, 8, 10, 12], "distinguish": 6, "maxim": [6, 7], "contigu": 6, "overflow": [6, 7], "ok": 6, "lost": [6, 9, 11], "fp": 6, "neat": 6, "unsign": 6, "255": [6, 11], "0xc0": 6, "254": 6, "02": [6, 10, 12], "c0": [6, 12], "fe": 6, "ff": 6, "0x": 6, "readbin": [6, 11], "chartoraw": 6, "rawtochar": 6, "1i": [6, 11], "imaginari": 6, "engin": [6, 7, 9, 12], "physic": 6, "electron": 6, "signal": [6, 11], "na_complex_": 6, "0000i": 6, "1416i": 6, "procedur": [6, 10, 12], "fft": [6, 11], "qr": 6, "svd": 6, "tinker": [6, 7, 9], "aubergin": [6, 12], "aaron": 6, "zorro": 6, "pastena": 6, "mib": 6, "paragraph": 6, "banal": 6, "prose": 6, "strwrap": 6, "dirnam": [6, 7], "trimw": 6, "hashtag": 6, "email": 6, "address": [6, 7], "hyperlink": 6, "42i": 6, "42l": 6, "0x42": 6, "stri_sort": 6, "a2": [6, 7, 12], "a10": 6, "a11": 6, "a100": 6, "formatt": [6, 10], "ascii": 6, "english": 6, "punctuat": 6, "a\u00dfc": 6, "\u0105\u00df": 6, "stri_pad": 6, "cach": [6, 7, 10], "clone": [6, 7], "ram": [6, 8, 12], "39": [6, 10, 20], "heavi": 6, "fiddl": 7, "dozen": 7, "vocabulari": [7, 9, 10, 12], "fluentli": 7, "achiev": [7, 9, 10, 11, 12], "goal": [7, 9], "under": [7, 9, 10, 13, 14, 15, 16, 17, 18, 22], "hood": [7, 9, 10], "nanosecond": 7, "malai": 7, "thereov": 7, "x1": [7, 10], "x2": [7, 10], "bunch": 7, "6545": 7, "borderlin": 7, "56203": 7, "tediou": [7, 9], "barbar": 7, "57206": 7, "concret": [7, 10], "50824": 7, "reinvent": [7, 9], "wheel": 7, "stack": [7, 12], "analyst": 7, "monoton": 7, "dreari": 7, "uninspir": 7, "plu": [7, 12], "quicker": 7, "dump": [7, 12], "pearl": 7, "minim": [7, 9], "bodi": [7, 8, 9], "disappear": 7, "immedi": [7, 8], "thereaft": [7, 9, 10], "arg1": 7, "argn": 7, "closur": [7, 10], "builtin": 7, "yesterdai": 7, "distil": 7, "concat": 7, "faithfulli": 7, "plead": 7, "guilti": [7, 9], "needlessli": 7, "anyon": [7, 11], "provis": 7, "spam1": 7, "spam2": 7, "spam3": 7, "spam4": 7, "spam5": 7, "contrast": 7, "dure": [7, 9, 10, 12], "caller": [7, 8, 9, 10], "se": [7, 9], "unambigu": 7, "manipul": [7, 9, 10, 12], "perfectli": [7, 10, 12], "position": 7, "particularli": [7, 8, 10, 11, 12], "saniti": [7, 8, 11, 12], "overus": 7, "forward": [7, 9, 22], "pipe": [7, 22], "sound": 7, "restrict": [7, 9], "experienc": 7, "sophist": 7, "grammat": 7, "indent": 7, "constitu": 7, "urban": 7, "semicolon": [7, 12], "a3": [7, 12], "1a": 7, "3c": 7, "4a": 7, "6c": 7, "brief": 7, "normalis": [7, 11, 12], "twice": [7, 9, 10, 12], "4826": 7, "0x55ec735ae130": 7, "0x55ec74c07a98": 7, "fortran": [7, 11, 14], "deeper": 7, "share": [7, 9, 12, 22], "emphasis": [7, 9, 10], "lisp": [7, 10, 11], "ocaml": 7, "haskel": 7, "clojur": 7, "fair": 7, "citizen": [7, 10], "invoc": 7, "nrow": [7, 9, 11, 12], "0x55ec7313ec30": 7, "0x55ec7422b320": 7, "euclidean_dist": 7, "helper": 7, "fill_na": [7, 12], "filler_fun": 7, "missing_on": 7, "replacement_valu": 7, "techniqu": [7, 9], "runtim": 7, "monopoli": 7, "hardcod": [7, 9, 10, 12], "buckwheat": [7, 12], "quinoa": 7, "barlei": 7, "cbind": [7, 9, 10, 11], "rbind": [7, 9, 10, 11], "plot_opt": 7, "log2": 7, "reus": 7, "scala": 7, "port": 7, "functool": 7, "recent": [7, 9, 11, 12], "framework": 7, "apach": [7, 8], "spark": [7, 8, 9], "obviou": [7, 8, 9], "accumul": 7, "cummmin": 7, "focu": 7, "off": [7, 9], "ish": 7, "centric": [7, 10], "One": [7, 8, 9], "eleg": 7, "7321": 7, "50000": [7, 11], "70711": [7, 11, 12], "86603": [7, 11], "3333": 7, "6667": 7, "111": [7, 12], "222": 7, "333": 7, "444": 7, "556": 7, "667": 7, "778": 7, "37": [7, 10, 11, 20], "889": 7, "toss": 7, "morearg": 7, "\u00e0": [7, 12], "la": [7, 12], "xi": 7, "file_nam": [7, 11], "scan": [7, 8, 11], "indulg": 7, "piec": [7, 9, 10], "fairli": 7, "successfulli": 7, "split": [7, 9, 10, 11, 12], "readili": 7, "nontrivi": [7, 9], "cry": 7, "reusabl": [7, 9], "vignett": [7, 11, 20], "45": [7, 9, 10, 11, 20], "moder": 7, "network": [7, 11], "bioinformat": 7, "pkg": [7, 9], "repo": [7, 9], "attach": [7, 8, 9, 12], "visit": 7, "entri": [7, 10, 12], "energi": [7, 10], "middleman": [7, 9], "acquir": [7, 11], "genet": 7, "optimis": [7, 8, 9, 10, 11], "expert": [7, 9], "whom": 7, "volunt": 7, "servant": 7, "enthusiast": [7, 8], "paid": [7, 10], "generos": 7, "spread": [7, 22], "cite": [7, 22], "citat": 7, "lunch": 7, "social": 7, "media": 7, "clean": [7, 9], "somedai": 7, "defaultpackag": 7, "grdevic": 7, "primarili": [7, 10], "tarbal": 7, "untar": 7, "pkg_version": 7, "tar": 7, "pkgtype": 7, "47": [7, 11, 20], "rtool": 7, "xcode": 7, "courtesi": 7, "zip": 7, "tgz": 7, "gitlab": [7, 9], "host": [7, 9], "branch": [7, 20], "rpackagedemo": 7, "tempfil": [7, 12], "destin": 7, "destfil": 7, "extract": [7, 9, 11, 12, 22], "unzip": 7, "tempdir": 7, "exdir": 7, "git2r": 7, "git": [7, 9], "upgrad": [7, 8, 9], "updat": [7, 9, 10], "excit": 7, "welcom": [7, 9, 11], "flawlessli": 7, "wouldn": 7, "matur": 7, "conduct": 7, "libpath": 7, "x86_64": 7, "pc": [7, 10], "usr": 7, "lib": 7, "site": [7, 12], "folder": 7, "r_libs_us": 7, "setenv": 7, "honour": [7, 12], "target": [7, 8], "r_user_dir": 7, "r_user_data_dir": 7, "config": 7, "r_user_config_dir": 7, "r_user_cache_dir": 7, "accomplish": 7, "modular": 7, "restructuredtext": 7, "libreoffic": [7, 12], "epub": 7, "pdflatex": 7, "lualatex": 7, "imagemagick": 7, "bitmap": 7, "crop": 7, "convers": [7, 10, 12, 22], "graphviz": 7, "plantuml": 7, "diagram": 7, "jupyt": 7, "nbconvert": 7, "notebook": 7, "glue": [7, 8, 9, 14], "system2": [7, 12], "xml": [7, 8, 12], "stdin": [7, 8], "stdout": [7, 8], "redirect": [7, 9], "stream": [7, 8], "bash": [7, 10], "echo": 7, "python3": 7, "np": 7, "repr": 7, "arang": 7, "setwd": 7, "assumpt": [7, 9, 10, 12], "strongli": [7, 9], "freebsd": 7, "ethic": 7, "alon": [7, 8, 12], "industri": 7, "fftw": 7, "libsvm": 7, "mlpack": 7, "openbla": 7, "rjava": 7, "jvm": 7, "reticul": 7, "rpy2": 7, "feel": [7, 8, 9, 10], "oblig": [7, 9], "pars": [7, 8, 10], "steer": 7, "tutori": 7, "faq": 7, "googleit": 7, "optim": [7, 9, 11], "gini": 7, "correctli": 7, "strrep": [7, 9, 11], "dup": 7, "bbb": 7, "ccccc": 7, "aa": 7, "aaa": 7, "aaaa": 7, "bbbb": 7, "sublist": 7, "movstat": 7, "gram": 7, "bigram": 7, "abcd": 7, "bc": 7, "cd": 7, "recod": [7, 9], "count": [7, 8, 9, 10, 11, 12], "954": 7, "duplicatedn": 7, "my_split": 7, "my_unsplit": 7, "p_": 7, "x_m": 7, "increasingli": 7, "w_i": 7, "z_i": 7, "dpareto": 7, "ppareto": 7, "qpareto": 7, "rpareto": 7, "pareto": [7, 9], "awar": [7, 9], "mappli": [7, 9, 11], "fond": [7, 11, 12], "lappli": [7, 9, 10, 11, 12], "criterion": [8, 9, 12], "learnt": [8, 9], "adapt": 8, "circumst": 8, "other_express": 8, "spice": 8, "regard": [8, 9, 11, 12], "dangl": 8, "dandl": 8, "mint": 8, "requirenamespac": 8, "fail": [8, 9, 10], "process_data": 8, "some_extension_packag": 8, "quietli": [8, 9], "very_fast_method": 8, "normal_method": 8, "expression_a": 8, "expression_b": 8, "expression_c": 8, "expression_els": 8, "thenc": [8, 12], "immun": 8, "constraint": [8, 11], "trigger": [8, 9], "gracefulli": 8, "succe": 8, "bombast": 8, "formul": 8, "cherri": 8, "spamham": 8, "istru": 8, "isfals": 8, "connect": [8, 10, 11, 12, 14], "rt": 8, "No": [8, 9, 10, 11, 20], "critic": [8, 12], "diagnost": 8, "trycatch": 8, "suppresswarn": 8, "suppressmessag": 8, "emit": [8, 12], "silenc": 8, "reload": 8, "stopifnot": [8, 9, 10, 12], "exit": 8, "debug": [8, 12], "tip": [8, 11], "eleph": 8, "room": 8, "explicit": [8, 9, 10, 11], "congruenti": 8, "x_0": 8, "mod": 8, "74": 8, "remind": [8, 10, 11], "poor": 8, "cycl": [8, 9], "x_k": 8, "fridg": 8, "promis": [8, 9], "watch": 8, "tmp_vector": 8, "tmp_iter": 8, "influenc": 8, "ret": 8, "04206": 8, "024614": 8, "045831": 8, "094841": 8, "00062477": 8, "2529": 8, "many_stat": 8, "shorthand": 8, "cast": 8, "goe": 8, "my_unlist": 8, "34": [8, 10, 11, 20], "rough": 8, "consumpt": [8, 10], "oh": 8, "asymptot": 8, "cn": 8, "proportion": 8, "deadlin": 8, "hclust": [8, 11], "hierarch": [8, 11], "storag": [8, 12], "gb": 8, "opportun": [8, 9], "insight": 8, "intuit": [8, 9], "lengthi": 8, "innoc": 8, "buffer": 8, "generate_data": 8, "amortis": 8, "prospect": 8, "grant": [8, 9], "creation": [8, 9, 12], "hadoop": 8, "githubusercont": 8, "biggest": 8, "few_lin": 8, "93": 8, "establish": [8, 9, 11], "gzfile": 8, "textconnect": 8, "thousand": 8, "stai": [8, 19], "alert": 8, "microbenchmark": 8, "proc": 8, "impos": [8, 12], "shift_left": 8, "shift_right": 8, "longest": 8, "trend": 8, "subsequ": 8, "conclud": 8, "magnific": 8, "modul": 9, "highest": 9, "exposur": 9, "compromis": 9, "wors": [9, 10], "aspect": 9, "simpler": 9, "dry": 9, "tire": 9, "disciplin": 9, "trait": 9, "justifi": 9, "harm": 9, "backward": 9, "compat": [9, 11, 12], "smooth": 9, "mayb": [9, 12], "deparse1": 9, "depars": [9, 11], "expr": [9, 10, 11, 12], "cutoff": 9, "500l": 9, "0x55bfdca44690": 9, "cement": 9, "bloat": [9, 12], "joi": [9, 10], "team": [9, 10, 20], "profession": 9, "background": 9, "cohort": 9, "valuabl": 9, "attitud": 9, "novic": 9, "grasp": 9, "effort": 9, "nlargest": 9, "took": 9, "arriv": 9, "afraid": 9, "philosophi": [9, 13, 22], "awesom": 9, "serious": 9, "probabilist": 9, "stabil": [9, 20], "problemat": [9, 12], "huge": [9, 12], "anymor": [9, 10], "front": 9, "humbl": 9, "credit": 9, "clearli": 9, "hide": [9, 10], "gut": 9, "essenc": [9, 10, 11], "unhappi": 9, "Of": [9, 10, 12], "fewer": 9, "knn": 9, "coercibl": [9, 10], "utter": [9, 12], "nonsens": [9, 12], "atyp": 9, "believ": 9, "faith": 9, "compet": 9, "knew": 9, "round_rand": 9, "defend": [9, 10], "opt": 9, "divers": [9, 12], "diagnos": 9, "invalid": [9, 10, 12], "defens": 9, "mechan": [9, 10], "assert": 9, "cond1": 9, "cond2": 9, "round_rand2": 9, "strictest": 9, "tension": 9, "chao": 9, "foolproof": [9, 10], "duti": 9, "revisit": [9, 22], "domain": [9, 10], "vctr": 9, "vacuum": 9, "wider": 9, "utilis": 9, "deduc": [9, 11], "meet": 9, "sappli": [9, 11, 12], "proclaim": 9, "neaten": 9, "brute": 9, "forc": [9, 10], "gap": 9, "stri_list2matrix": 9, "pure": 9, "referenti": 9, "delet": [9, 11], "consequ": [9, 10, 11, 12], "invis": [9, 10], "anonym": 9, "instantli": 9, "path_to_fil": 9, "mylib": 9, "director": 9, "substanti": 9, "subdirectori": 9, "licens": [9, 22], "rd": 9, "src": 9, "pkg_directori": 9, "mypkg": 9, "submit": 9, "merci": 9, "busi": 9, "autom": [9, 10], "thoroughli": [9, 10, 12], "incud": 9, "stronger": 9, "asset": 9, "known": [9, 11, 12], "obscur": 9, "untrain": 9, "facil": 9, "roxygen2": 9, "extent": [9, 10], "heurist": 9, "mimick": 9, "invest": 9, "scm": 9, "doc": [9, 20], "tracker": 9, "wiki": 9, "board": 9, "guidelin": 9, "hygien": 9, "quadrat": 9, "16786054171151931769": 9, "testthat": 9, "tinytest": 9, "lighter": 9, "weight": 9, "runit": 9, "realtest": 9, "consult": [9, 10, 12], "ci": 9, "commit": 9, "servic": 9, "mostli": [9, 10], "suspect": [9, 10], "printf": 9, "shame": 9, "debugg": 9, "rprof": 9, "hight": 9, "underscor": 9, "whichev": 9, "grave": 9, "accent": 9, "lolloll": 9, "parser": 9, "condition": 9, "what_if_tru": 9, "what_if_fals": 9, "unevalu": [9, 12], "righthand": 9, "delai": 9, "postpon": 9, "wise": [9, 10], "myopnam": 9, "e1": [9, 10], "e2": [9, 10], "1013": 9, "tmp": [9, 12], "implic": [9, 12], "ceas": 9, "awai": 9, "shorten": 9, "new_length": 9, "behind": [9, 10, 11], "oval": 9, "smell": 9, "meati": 9, "umami": 9, "rose": 9, "tasteless": 9, "some_attrib": 9, "old_nam": 9, "new_nam": 9, "cauliflow": 9, "broccoli": 9, "crew": [9, 11], "male": [9, 11], "child": [9, 11], "adult": [9, 11], "670": [9, 11], "192": [9, 11], "subtask": 9, "ver": 9, "vir": 9, "test_chang": 9, "overshadow": 9, "refrain": [9, 10, 12], "carri": 9, "approxfun": 9, "f1": [9, 12], "f2": [9, 12], "565": 9, "4275": 9, "yleft": 9, "yright": 9, "0x55bfdbd80888": 9, "0x55bfdbd7ff20": 9, "0x55bfdbe82e30": 9, "04": [9, 10], "09": 9, "001": 9, "008": 9, "027": 9, "064": 9, "125": [9, 12], "216": 9, "343": 9, "729": 9, "sweet": 9, "spot": [9, 10], "oversimplist": 9, "tune": [9, 19], "78": [9, 10], "test_default": 9, "prior": [9, 10], "lazy_test1": 9, "amidst": 9, "lazy_test2": 9, "nose": 9, "uniroot": 9, "outer": [9, 11, 12], "variad": 9, "easiest": [9, 12], "test_dot": 9, "color": 9, "shape1": 9, "shape2": 9, "2e": 9, "fun": [9, 10, 12], "test_deparse_substitut": 9, "grill": 9, "shapiro": 9, "rlnorm": 9, "compactli": 9, "certainli": [9, 10], "theori": [9, 11, 12], "mm": 9, "118": [9, 12], "77": [9, 12], "132": [9, 12], "136": [9, 12], "outsid": [9, 10], "liberti": 9, "felt": 9, "realiti": 9, "prop": 9, "test_match_arg": 9, "predefin": 9, "heart": 9, "clue": 9, "sensibl": [9, 10, 11], "dislik": 9, "struggl": 9, "intellectu": 9, "mi": 9, "dialect": 9, "mother": 9, "tongu": 9, "blame": [9, 10], "elabor": 9, "Will": 9, "do_something_that_takes_a_million_year": 9, "envir": [9, 10, 11, 12], "baseenv": 9, "intention": 9, "predic": 9, "slide": 9, "package_depend": 9, "revers": [9, 12], "leav": 9, "feasibl": 9, "dealer": 9, "payabl": 9, "movement": 9, "autonom": 9, "contradict": 9, "polici": 9, "With": [9, 10], "caus": [9, 10, 12], "depth": [9, 22], "lexic": 9, "static": 9, "kwarg": 9, "latest": 10, "polit": 10, "spectra": 10, "hidden": [10, 11], "appeal": [10, 12], "oop": [10, 11], "beautifulli": 10, "admiss": 10, "endless": 10, "pretend": 10, "demystifi": 10, "xt": 10, "posixct": [10, 12], "posix": 10, "calendar": 10, "xd": 10, "decod": [10, 11], "03": 10, "aest": 10, "epoch": 10, "01t00": 10, "deciph": 10, "timestamp": 10, "ahead": 10, "bear": 10, "sic": [10, 11], "usemethod": [10, 11, 22], "0x5566182c8738": 10, "categor": [10, 11], "ctgrcl": 10, "spanishinquisit": 10, "categori": [10, 11, 12], "fallback": 10, "x_charact": [10, 11], "ensur": 10, "xu": [10, 11], "varieti": [10, 12], "forbid": 10, "instruct": 10, "internalmethod": 10, "groupgener": 10, "puzzl": 10, "xc": 10, "barebon": 10, "emul": 10, "partit": [10, 12], "kmean": 10, "center": 10, "nstart": 10, "0060": 10, "4280": 10, "4620": 10, "2460": 10, "9016": 10, "7484": 10, "3935": 10, "4339": 10, "8500": 10, "0737": 10, "7421": 10, "0711": 10, "151": 10, "821": 10, "879": 10, "between_ss": 10, "total_ss": 10, "totss": 10, "withinss": 10, "tot": 10, "betweenss": 10, "ifault": 10, "681": 10, "851": 10, "602": 10, "fanci": [10, 12], "enclo": [10, 11, 12], "gets3method": [10, 11], "tripl": 10, "colon": 10, "t1": 10, "aedt": 10, "t2": 10, "2021": [10, 20], "08": [10, 12], "15t12": 10, "59": [10, 12, 20], "posixt": 10, "posixlt": 10, "class1": 10, "class2": 10, "classk": 10, "inherit": [10, 12], "mimic": 10, "impli": [10, 12], "odditi": 10, "automag": 10, "ubiqu": 10, "2023": [10, 20, 22], "underneath": 10, "19353": 10, "midnight": 10, "utc": 10, "1672134577": 10, "timezon": 10, "tzone": 10, "isodatetim": 10, "2030": 10, "int": [10, 12, 20], "mdai": 10, "mon": 10, "wdai": 10, "ydai": 10, "364": 10, "isdst": 10, "gmtoff": 10, "datetimeclass": 10, "supposedli": 10, "closer": 10, "difftim": 10, "1e7": 10, "elaps": 10, "232": 10, "012": 10, "245": [10, 12], "proc_tim": 10, "micro": 10, "beginn": 10, "factor_cod": 10, "cut": 10, "unawar": 10, "en": [10, 20], "accident": [10, 12], "stringsasfactor": [10, 12], "sporad": 10, "fifth": 10, "Be": 10, "droplevel": [10, 12], "unus": 10, "someon": 10, "redefin": 10, "watertight": 10, "complain": 10, "opinion": [10, 11], "respond": 10, "numeris": 10, "digitis": 10, "numtabl": 10, "paradigm": 10, "hierarchi": [10, 22], "broad": 10, "privileg": 10, "stem": 10, "ingeni": 10, "simplic": 10, "encapsul": [10, 11], "versatil": [10, 12], "emphasi": 10, "verb": 10, "noun": 10, "sensibli": 10, "afterward": [10, 12], "group_bi": [10, 12], "list_df": [10, 12], "iris_subset": 10, "770": [10, 12], "974": [10, 12], "552": [10, 12], "priceless": 10, "seal": 10, "told": 10, "obj": 10, "method1": 10, "method2": 10, "nutshel": 10, "relationship": 10, "s3method": 10, "rle": 10, "package_vers": 10, "numeric_vers": 10, "chosen": [10, 12], "gl": 10, "poorli": 10, "messeng": 10, "undesir": 10, "elsewher": [10, 12, 22], "alien": 10, "implant": 10, "forcefulli": 10, "narrow": [10, 11], "s4": [10, 22], "sexptyp": 10, "pointer": [10, 22], "heap": 10, "struct": 10, "unoverload": 10, "fan": 10, "knowns3gener": 10, "s3_methods_t": 10, "challeng": 10, "overprotect": 10, "con": [10, 12], "debat": 10, "lookup": [10, 22], "trick": 10, "nextmethod": 10, "incomprehens": 10, "tm": 10, "op": 10, "nonlinear": 10, "calcul": 10, "fortun": 10, "compuls": 10, "stakehold": 10, "agil": 10, "harder": [10, 12], "seamless": 10, "kotlin": 10, "magrittr": 10, "uncool": 10, "school": 10, "primari": 11, "rowwis": [11, 12], "byrow": 11, "ncol": [11, 12], "columnwis": 11, "indistinguish": 11, "3d": 11, "2d": 11, "hypert": 11, "2x3": 11, "equis": 11, "tappli": 11, "replic": 11, "min_mean_max": 11, "900": [11, 12], "006": [11, 12], "936": [11, 12], "588": [11, 12], "referr": 11, "toi": [11, 12], "57825": 11, "12431": 11, "9666": 11, "7869": 11, "sapply2": 11, "ccc": 11, "eeeee": 11, "bb": 11, "dddd": 11, "ffffff": 11, "nonneg": 11, "1d": 11, "addition": [11, 12], "affect": 11, "placement": 11, "grid": [11, 12, 13], "newli": 11, "rownam": 11, "colnam": 11, "prettifi": 11, "conting": [11, 12], "fri": 11, "sat": 11, "sun": 11, "thur": 11, "87": 11, "76": [11, 12], "smoker": 11, "firstli": 11, "a_": 11, "multi": 11, "guess": 11, "colmean": 11, "coordin": 11, "arr": 11, "ind": 11, "arrayind": 11, "multidimension": 11, "diag": 11, "cartesian": 11, "sex": 11, "femal": 11, "accid": [11, 12], "121": 11, "NOT": 11, "b_": 11, "aperm": 11, "conjug": 11, "conj": 11, "co": [11, 20], "matplot": 11, "rowmean": 11, "625": 11, "65": 11, "156": 11, "221": 11, "2000": [11, 12, 20], "sweep": 11, "conform": 11, "lapack": 11, "bla": 11, "differenti": 11, "constrain": 11, "unconstrain": 11, "refresh": 11, "c_": 11, "ac": 11, "crossprod": 11, "tcrossprod": 11, "euclidean": 11, "orthogon": 11, "perpendicular": 11, "cov": 11, "covari": 11, "centr": 11, "lu": 11, "pivot": 11, "interchang": 11, "lcl": 11, "_1": 11, "max_": 11, "_2": 11, "sigma_1": 11, "sup_": 11, "_i": 11, "singular": 11, "frobeniu": 11, "_f": 11, "_m": 11, "atop": 11, "supremum": 11, "manhattan": 11, "taxicab": 11, "dist": 11, "pairwis": 11, "2361": 11, "ca": [11, 12, 20], "41421": 11, "canberra": 11, "adist": 11, "spa": 11, "leg": 11, "cutre": 11, "linkag": 11, "singleton": 11, "eigen": 11, "lambda_1": 11, "lambda_n": 11, "nondecreasingli": 11, "lambda_i": 11, "rotat": 11, "86603i": 11, "00000i": 11, "70711i": 11, "bivari": 11, "asp": 11, "princip": 11, "18609": 11, "98386": 11, "86715": 11, "49804": 11, "pca": 11, "triangular": 11, "theta": 11, "coef": 11, "regress": 11, "car": [11, 12], "qrx": 11, "9324": 11, "5791": 11, "scatter": [11, 12], "93241x": 11, "diagon": 11, "d_": 11, "zc": 11, "brilliantli": 11, "dispatch": [11, 12, 22], "class_of_x": 11, "mainstream": 11, "restless": 11, "lack": [11, 12], "polymorph": 11, "fourth": 11, "classes_detail": 11, "methods_detail": 11, "loos": 11, "defclass": 11, "defmethod": 11, "afterthought": 11, "appendag": 11, "patchwork": 11, "rebelli": 11, "pinch": 11, "regist": 11, "setclass": 11, "auto": 11, "novel": 11, "globalenv": 11, "cl": 11, "valueclass": 11, "setgener": 11, "degre": 11, "setmethod": 11, "signatur": 11, "setvalid": 11, "dens": 11, "spars": 11, "rectangular": 11, "symmetr": 11, "band": 11, "vertic": 11, "edg": 11, "ddimatrix": 11, "sparsematrix": 11, "dgcmatrix": 11, "crc": [11, 20], "hyperrectangl": 11, "thusli": 11, "min_i": 11, "max_i": 11, "hot": 11, "r_": 11, "multiclass": 11, "softmax": 11, "closest": 11, "min_j": 11, "combn": 11, "tsp": 11, "eurxxx": 11, "read_numeric_matrix": 11, "t10k": 11, "imag": [11, 12], "idx3": 11, "ubyt": 11, "mnist": 11, "homepag": [11, 13], "circular": 11, "convolut": 11, "affin": 11, "sharpen": 11, "shear": 11, "constroptim": 11, "bett": 11, "qp": 11, "quadprog": 11, "multivari": 11, "copula": [11, 20], "unitari": 11, "pseudoinvers": 11, "prcomp": 11, "class_nam": 11, "hypothet": 11, "imagin": 11, "class_name1": 11, "class_name2": 11, "heterogen": 12, "bias": 12, "nois": 12, "thriller": 12, "pop": 12, "driven": 12, "morn": 12, "77437": 12, "19722": 12, "97801": 12, "20133": 12, "36124": 12, "74261": 12, "ob": 12, "774": 12, "197": 12, "978": [12, 19, 20, 22], "201": 12, "361": 12, "sadli": 12, "unstack": 12, "mtcar": 12, "cyl": 12, "var1": 12, "var2": 12, "freq": 12, "eagerli": 12, "friend": 12, "97": 12, "428": 12, "tsv": 12, "hdf5": 12, "curl": 12, "287577520124614": 12, "788305135443807": 12, "4089769218117": 12, "tunabl": 12, "calc": 12, "dbi": 12, "driver": 12, "rsqlite": 12, "rmariadb": 12, "rpostgresql": 12, "rodbc": 12, "odbc": 12, "volatil": 12, "sqlite": 12, "dbconnect": 12, "dbwritet": 12, "dbexecut": 12, "send": 12, "INTO": 12, "dbgetqueri": 12, "mpg": 12, "AS": 12, "mpg_ave": 12, "hp": 12, "hp_ave": 12, "730": 12, "567": 12, "131": 12, "67": 12, "115": 12, "209": 12, "dbdisconnect": 12, "password": 12, "credenti": 12, "getenv": 12, "keyr": 12, "subsect": 12, "vigil": 12, "nasti": 12, "counterintuit": 12, "uninform": 12, "ri": 12, "besid": 12, "obliqu": 12, "iris2": 12, "croatica": 12, "advertis": [12, 13], "rag": 12, "dictat": 12, "sad": 12, "xtab": 12, "my_xtab": 12, "d1": 12, "d2": 12, "460916": 12, "265061": 12, "686853": 12, "fromlast": 12, "trickier": 12, "names_replac": 12, "new_c": 12, "new_a": 12, "12929": 12, "2651": 12, "set_row_nam": 12, "reset_row_nam": 12, "exhibit": 12, "402": 12, "metr": 12, "race": 12, "mtcars6": 12, "qsec": 12, "disp": 12, "drat": 12, "wt": 12, "gear": 12, "carb": 12, "351": 12, "264": 12, "ford": 12, "pantera": 12, "301": 12, "335": 12, "54": 12, "maserati": 12, "bora": 12, "73": 12, "84": 12, "camaro": 12, "z28": 12, "145": 12, "175": 12, "ferrari": 12, "dino": 12, "duster": 12, "mazda": 12, "rx4": 12, "minu": 12, "decreasingli": 12, "anydupl": 12, "143": 12, "developer_id": 12, "project_id": 12, "scope": [12, 22], "engag": 12, "b0": 12, "b1": 12, "b3": 12, "a0": 12, "a4": 12, "c1": 12, "c2": 12, "inner": 12, "iris_sampl": 12, "137": 12, "133": 12, "0667": 12, "1333": 12, "5500": 12, "7167": 12, "70405": 12, "03024": 12, "76004": 12, "65318": 12, "72094": 12, "49854": 12, "60591": 12, "78117": 12, "45878": 12, "46829": 12, "83674": 12, "85384": 12, "85202": 12, "18732": 12, "31738": 12, "30884": 12, "74927": 12, "74484": 12, "65540": 12, "93659": 12, "52684": 12, "dimension": [12, 20], "succeed": 12, "responsenam": 12, "val": 12, "superb": 12, "idvar": 12, "timevar": 12, "covert": 12, "worldphon": 12, "kat": 12, "ron": 12, "jo": 12, "mari": 12, "lollipop": 12, "opposit": 12, "straightforwardli": 12, "charm": 12, "var3": 12, "98": 12, "idempot": 12, "assist": 12, "462": [12, 20], "246": 12, "326": 12, "026": 12, "ave_len": 12, "rem": 12, "nappli": 12, "av": 12, "813": 12, "dramat": 12, "aaaggg": 12, "plate": 12, "cosmet": 12, "is_bi": 12, "res_mat": 12, "combined_aggreg": 12, "score": 12, "52811": 12, "89242": 12, "55144": 12, "45661": 12, "95683": 12, "45333": 12, "46357": 12, "17823": 12, "63478": 12, "65057": 12, "revert": 12, "overthink": 12, "2330": 12, "1450": 12, "230000": 12, "294000": 12, "245000": 12, "112": 12, "et": [12, 20], "voil\u00e0": 12, "weird": 12, "fall": 12, "119": 12, "gibberish": 12, "selector": 12, "chef": 12, "proudli": 12, "ultra": 12, "delivernoodl": 12, "log_hp": 12, "620": 12, "7005": 12, "wag": 12, "875": 12, "datsun": 12, "710": 12, "85": 12, "5326": 12, "hornet": 12, "drive": 12, "258": 12, "215": 12, "sportabout": 12, "1648": 12, "valiant": 12, "225": 12, "6540": 12, "fuel_economi": 12, "235": 12, "307": 12, "981": 12, "983": 12, "tild": 12, "4186": 12, "075": 12, "3709": 12, "7447": 12, "8552": 12, "050": 12, "2553": 12, "6950": 12, "060753": 12, "058754": 12, "053734": 12, "051440": 12, "193": 12, "049455": 12, "esoter": 12, "interdepend": 12, "invas": 12, "annoyingli": 12, "tibbl": 12, "tbl_df": 12, "haven": 12, "xpt": 12, "subclass": 12, "amount": 12, "ago": 12, "foo": 12, "x0": 12, "x9": 12, "y0": 12, "y9": 12, "coord": 12, "lat": 12, "xyz12345": 12, "id3": 12, "id5": 12, "y7": 12, "flight": 12, "70k": 12, "urban_forest": 12, "trunk": 12, "diamet": 12, "breast": 12, "height": 12, "hors": 12, "chestnut": 12, "plant": 12, "genera": 12, "genu": 12, "eucalyptu": 12, "platanu": 12, "ficu": 12, "acer": 12, "quercu": 12, "barplot": 12, "travel": 12, "stackexchang": 12, "travel_stackexchange_com_2017": 12, "displaynam": 12, "post": 12, "favoritecount": 12, "favoritetot": 12, "mostfavoritequest": 12, "mostfavoritequestionlik": 12, "ON": 12, "owneruserid": 12, "posttypeid": 12, "desc": 12, "posts2": 12, "positiveanswercount": 12, "parentid": 12, "AND": 12, "upvotesperyear": 12, "postid": 12, "vote": 12, "creationd": 12, "votetypeid": 12, "bestansw": 12, "maxscor": 12, "acceptedscor": 12, "acceptedanswerid": 12, "cmttotscr": 12, "commentstotalscor": 12, "userid": 12, "reput": 12, "badg": 12, "IN": 12, "valuablebadg": 12, "votesbyage2": 12, "oldvot": 12, "voted": 12, "THEN": 12, "newvot": 12, "2017": [12, 20], "votesbyag": 12, "colclass": 12, "unstructur": 12, "regular": [12, 20], "clear": 12, "corrupt": 12, "contamin": 12, "inde": 12, "datafram": 12, "set_index": 12, "reset_index": 12, "scientist": [12, 20], "focus": 12, "unanticip": 12, "overrid": 12, "billion": 12, "unread": 12, "newer": 13, "lattic": 13, "ggplot2": 13, "suffici": 13, "aren": 13, "v0": 19, "deepr": [19, 22], "isbn": [19, 20, 22], "6455719": [19, 20, 22], "abelson": 20, "sussman": 20, "1996": 20, "mit": 20, "abramowitz": 20, "stegun": 20, "1972": 20, "dover": 20, "sfu": 20, "cbm": 20, "aand": 20, "becker": 20, "wilk": 20, "1988": 20, "chapman": 20, "hall": 20, "guid": 20, "springer": 20, "verlag": 20, "2008": 20, "rogram": 20, "476": 20, "doi": 20, "32614": 20, "rj": 20, "028": 20, "hasti": 20, "cormen": 20, "leiserson": 20, "rivest": 20, "stein": 20, "2009": 20, "mcgraw": 20, "hill": 20, "crawlei": 20, "2007": 20, "wilei": 20, "son": 20, "2003": 20, "davi": 20, "whistler": 20, "nicod": 20, "annex": 20, "tr15": 20, "scherer": 20, "collat": 20, "tr10": 20, "deisenroth": 20, "faisal": 20, "ong": 20, "cambridg": 20, "mml": 20, "demichiel": 20, "gabriel": 20, "1987": 20, "ommon": 20, "isp": 20, "bject": 20, "ystem": 20, "ecoop": 20, "dreamsong": 20, "devroy": 20, "1986": 20, "luc": 20, "rnbookindex": 20, "forb": 20, "evan": 20, "hast": 20, "peacock": 20, "2010": 20, "friedl": 20, "2006": 20, "reilli": 20, "naliza": 20, "danych": 20, "obliczenia": 20, "symulacj": 20, "wydawnictwo": 20, "naukow": 20, "18939": 20, "zenodo": [20, 22], "datawranglingpi": 20, "5281": 20, "6451068": 20, "ast": 20, "18637": 20, "jss": 20, "v103": 20, "i02": 20, "rop": 20, "galassi": 20, "theiler": 20, "al": 20, "gentl": 20, "ont": 20, "arlo": 20, "algebra": [20, 22], "goldberg": 20, "acm": 20, "perso": 20, "lyon": 20, "fr": 20, "jean": 20, "michel": 20, "muller": 20, "hankin": 20, "gslpaper": 20, "harri": 20, "585": 20, "7825": 20, "357": 20, "362": 20, "1038": 20, "s41586": 20, "020": 20, "2649": 20, "higham": 20, "2002": 20, "accuraci": 20, "siam": 20, "philadelphia": 20, "pa": 20, "dx": 20, "1137": 20, "9780898718027": 20, "299": 20, "314": 20, "1080": 20, "10618600": 20, "10474713": 20, "1992": 20, "csli": 20, "ii": 20, "eminumer": 20, "addison": 20, "weslei": 20, "undament": 20, "matloff": 20, "2011": 20, "tour": 20, "starch": 20, "matsumoto": 20, "nishimura": 20, "ersenn": 20, "wister": 20, "623": 20, "equidistribut": 20, "nelsen": 20, "1999": 20, "olver": 20, "nist": 20, "dlmf": 20, "gov": 20, "tiernei": 20, "kalibera": 20, "2018": 20, "ltern": 20, "svn": 20, "venabl": 20, "riplei": 20, "smith": 20, "intro": 20, "wickham": 20, "grolemund": 20, "r4d": 20, "nz": 20, "xie": 20, "2015": 20, "ext": 20, "admin": 20, "lang": 20, "foundat": 20, "vienna": 20, "austria": 20, "practition": 22, "hardli": 22, "afford": 22, "tag": 22, "proxi": 22, "prove": 22, "mate": 22, "peer": 22, "copyright": 22, "noncommerci": 22, "noderiv": 22, "cc": 22, "nc": 22, "nd": 22, "acknowledg": 22, "hello": 22, "rcpp": 22, "changelog": 22}, "objects": {}, "objtypes": {}, "objnames": {}, "titleterms": {"prefac": 0, "To": [0, 7, 9], "r": [0, 1, 7, 9, 14, 16, 22], "languag": 0, "an": [0, 1], "environ": [0, 1, 16], "aim": 0, "scope": [0, 9], "design": [0, 9], "philosophi": 0, "classif": [0, 16], "data": [0, 2, 6, 9, 12, 16], "type": [0, 4, 6, 10, 16], "book": 0, "structur": 0, "about": 0, "author": 0, "acknowledg": 0, "introduct": 1, "hello": 1, "world": 1, "set": 1, "up": 1, "develop": [1, 4, 9], "instal": 1, "interact": 1, "mode": 1, "batch": 1, "work": [1, 9], "script": 1, "weav": 1, "automat": 1, "report": 1, "gener": [1, 2, 10, 18], "semi": 1, "jupyt": 1, "notebook": 1, "send": 1, "code": [1, 9, 14], "associ": 1, "consol": 1, "etc": [1, 7, 10], "atom": [1, 5, 6], "vector": [1, 2, 3, 4, 5, 6, 9, 11], "glanc": 1, "get": 1, "help": 1, "exercis": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "numer": [2, 11], "creat": [2, 3, 4, 6, 7, 9, 10, 11, 12], "constant": 2, "concaten": [2, 6], "c": [2, 5, 7, 14], "repeat": [2, 8], "entri": 2, "rep": 2, "arithmet": 2, "progress": 2, "seq": 2, "pseudorandom": 2, "number": [2, 5], "read": [2, 6, 12], "scan": 2, "name": [2, 4, 7], "object": [2, 4, 6, 7, 10], "vectoris": [2, 3, 5, 7, 11], "mathemat": [2, 11], "function": [2, 5, 7, 9, 11, 18], "ab": 2, "sqrt": 2, "round": [2, 3], "natur": 2, "exponenti": 2, "logarithm": 2, "probabl": 2, "distribut": 2, "special": [2, 4, 9], "oper": [2, 3, 6, 9, 10, 11, 12, 15], "recycl": 2, "rule": 2, "preced": [2, 3], "accumul": 2, "aggreg": [2, 3, 11, 12], "logic": [3, 5, 11], "compar": [3, 6], "element": [3, 4, 5, 11], "comparison": 3, "test": [3, 9], "na": 3, "nan": 3, "inf": 3, "deal": 3, "float": 3, "point": 3, "off": 3, "error": 3, "revisit": [3, 10, 16, 18], "missing": 3, "all": 3, "ani": 3, "sum": 3, "simplifi": [3, 11], "predic": 3, "choos": 3, "ifels": 3, "list": [4, 5, 11, 12], "attribut": [4, 5, 9], "hierarchi": 4, "convers": 4, "explicit": 4, "cast": 4, "implicit": 4, "coercion": 4, "coerc": 4, "from": [4, 5, 6], "null": 4, "perceptu": 4, "indiffer": 4, "most": 4, "But": 4, "There": 4, "ar": [4, 7, 9, 11, 12], "some": 4, "us": [4, 6, 7, 10], "case": 4, "label": 4, "alter": 4, "remov": 4, "index": [5, 11], "head": 5, "tail": 5, "subset": [5, 12], "extract": [5, 6], "nonneg": 5, "neg": 5, "charact": [5, 6], "replac": [5, 6, 9, 11], "modifi": 5, "insert": 5, "new": 5, "relat": [5, 12], "match": [5, 6], "anoth": 5, "assign": 5, "interv": 5, "split": [5, 6], "subgroup": 5, "order": [5, 6, 7, 10, 12], "identifi": 5, "duplic": [5, 12], "count": 5, "occurr": [5, 6], "preserv": 5, "lose": 5, "someth": 5, "input": [6, 9], "individu": [6, 11], "string": [6, 12], "mani": 6, "One": [6, 10], "format": 6, "text": 6, "file": 6, "pattern": 6, "search": 6, "whole": 6, "partial": 6, "anywher": 6, "within": 6, "regular": 6, "express": [6, 7, 15, 17], "locat": 6, "token": 6, "other": [6, 11], "substr": 6, "translat": 6, "integ": 6, "raw": 6, "complex": [6, 8], "invok": 7, "anonym": 7, "pass": [7, 9], "argument": [7, 9, 10, 18], "group": [7, 12, 18], "curli": [7, 9], "brace": [7, 9], "program": [7, 22], "call": [7, 9, 10], "precomput": 7, "do": 7, "common": [7, 10, 11, 12], "higher": [7, 11], "map": 7, "access": [7, 11], "third": 7, "parti": 7, "packag": [7, 9, 11, 12, 18], "default": [7, 9, 10, 18], "sourc": 7, "v": [7, 10], "binari": [7, 9, 11], "manag": [7, 9], "depend": 7, "extern": [7, 14], "A": [7, 8, 9, 11, 12, 16], "note": [7, 8, 9, 11, 12, 16], "interfac": [7, 12, 14], "python": 7, "java": 7, "flow": [8, 9], "execut": 8, "condit": 8, "evalu": [8, 9, 17, 18], "return": 8, "valu": [8, 9, 12], "nest": 8, "ifs": 8, "either": 8, "true": 8, "fals": 8, "short": 8, "circuit": 8, "except": 8, "handl": [8, 9, 12], "while": 8, "break": 8, "next": 8, "time": [8, 10], "space": 8, "algorithm": 8, "principl": 9, "sustain": 9, "write": 9, "abstain": 9, "pamper": 9, "challeng": 9, "build": 9, "reus": 9, "check": [9, 10], "integr": 9, "put": 9, "output": 9, "context": 9, "organis": 9, "maintain": 9, "librari": 9, "document": 9, "assur": 9, "qualiti": 9, "chang": 9, "collabor": 9, "driven": 9, "continu": 9, "debug": 9, "profil": 9, "syntact": 9, "sugar": 9, "backtick": 9, "too": 9, "built": [9, 10, 11], "own": [9, 10], "substitut": 9, "part": 9, "composit": 9, "local": 9, "variabl": 9, "closur": 9, "lazi": 9, "ellipsi": [9, 18], "metaprogram": [9, 12], "s3": [10, 18], "class": [10, 11, 16], "method": [10, 11, 18], "dispatch": 10, "custom": 10, "onli": 10, "directli": 10, "multi": 10, "ness": 10, "overload": [10, 18], "date": 10, "formula": [10, 15], "factor": [10, 12], "over": 10, "forward": 10, "pipe": 10, "matric": 11, "arrai": 11, "matrix": [11, 12], "promot": 11, "stack": 11, "beyond": 11, "intern": [11, 12], "represent": [11, 12], "upon": 11, "basic": 11, "select": 11, "row": [11, 12], "column": [11, 12], "drop": 11, "dimens": 11, "submatric": 11, "base": [11, 12], "two": 11, "dimension": 11, "transpos": 11, "algebra": 11, "multipl": 11, "solv": 11, "system": 11, "linear": 11, "equat": 11, "norm": 11, "metric": 11, "eigenvalu": 11, "eigenvector": 11, "qr": 11, "decomposit": 11, "svd": 11, "s4": 11, "defin": 11, "slot": 11, "constructor": 11, "inherit": 11, "frame": 12, "cbind": 12, "rbind": 12, "databas": 12, "queri": 12, "sql": 12, "like": 12, "join": 12, "merg": 12, "transform": 12, "miss": 12, "reshap": 12, "techniqu": 12, "dplyr": 12, "tidyvers": 12, "tabl": 12, "graphic": 13, "placehold": 13, "plot": 13, "refer": [13, 16, 20], "elsewher": 13, "compil": 14, "api": 14, "pointer": 14, "rcpp": 14, "The": 15, "dollar": 15, "copi": 16, "demand": 16, "lookup": 18, "usemethod": 18, "namespac": 18, "changelog": 19, "deep": 22, "start": 22, "here": 22, "deeper": 22, "deepest": 22, "appendix": 22}, "envversion": {"sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 6, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinxcontrib.bibtex": 9, "sphinx": 56}}) \ No newline at end of file