From 9eaa2493fc633a8d2d307a941f027553b5c5dd16 Mon Sep 17 00:00:00 2001 From: rachaelvp Date: Tue, 31 Jan 2023 13:51:29 -0800 Subject: [PATCH 1/4] bump gh-actions versions --- .github/workflows/R-CMD-check.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/R-CMD-check.yml b/.github/workflows/R-CMD-check.yml index c78460b7..049f8d22 100644 --- a/.github/workflows/R-CMD-check.yml +++ b/.github/workflows/R-CMD-check.yml @@ -29,7 +29,7 @@ jobs: steps: - name: Checkout repo - uses: actions/checkout@v2 + uses: actions/checkout@v3 - name: Setup R uses: r-lib/actions/setup-r@v2 @@ -37,10 +37,10 @@ jobs: r-version: ${{ matrix.config.r }} - name: Install pandoc - uses: r-lib/actions/setup-pandoc@v1 + uses: r-lib/actions/setup-pandoc@v2 - name: Install tinyTeX - uses: r-lib/actions/setup-tinytex@v1 + uses: r-lib/actions/setup-tinytex@v2 - name: Install system dependencies if: runner.os == 'Linux' @@ -50,7 +50,7 @@ jobs: - name: Install package dependencies run: | - install.packages(c("remotes", "rcmdcheck", "covr", "sessioninfo")) + install.packages(c("remotes", "rcmdcheck", "covr", "sessioninfo", "devtools")) if(Sys.info()["sysname"] == "Windows") install.packages("igraph", type = "binary") remotes::install_deps(dependencies = TRUE) shell: Rscript {0} From 6bf168cc381a975118dad9307238ae60e3875728 Mon Sep 17 00:00:00 2001 From: rachaelvp Date: Tue, 31 Jan 2023 14:34:58 -0800 Subject: [PATCH 2/4] cv predict error handling --- R/Lrnr_cv.R | 46 ++++++++++++++++++++++++---------------------- 1 file changed, 24 insertions(+), 22 deletions(-) diff --git a/R/Lrnr_cv.R b/R/Lrnr_cv.R index 9aa85837..3373e3df 100644 --- a/R/Lrnr_cv.R +++ b/R/Lrnr_cv.R @@ -102,47 +102,45 @@ Lrnr_cv <- R6Class( predict_fold = function(task, fold_number = "validation", pred_unique_ts = FALSE) { fold_number <- interpret_fold_number(fold_number) if (fold_number == "validation") { - # return cross validation predicitons (what Lrnr_cv$predict does, so use that) + + # return cross validation predictions (what Lrnr_cv$predict does) preds <- self$predict(task) ### Time-series addition: # Each time point gets an unique final prediction if (pred_unique_ts) { folds <- task$folds - index_val <- unlist(lapply(folds, function(fold) { - fold$validation_set - })) + index_val <- unlist(lapply(folds, function(fold) fold$validation_set)) preds_unique <- unique(index_val) if (length(unique(index_val)) != length(index_val)) { # Average over the same predictions: preds <- data.table(index_val, preds) - preds <- preds %>% group_by(index_val) %>% summarise_all(mean) %>% select(-1) } } - return(preds) - } else if (fold_number == "full") { - # check if we did a fold fit, and use that fit if available - if (self$params$full_fit) { - fold_fit <- self$fit_object$full_fit - } else { - stop("full fit requested, but Lrnr_cv was constructed with full_fit=FALSE") - } } else { - # use the requested fold fit - fold_number <- as.numeric(fold_number) - if (is.na(fold_number) || !(fold_number > 0)) { - stop("fold_number must be 'full', 'validation', or a positive integer") + if (fold_number == "full") { + # check if we did a fold fit, and use that fit if available + if (self$params$full_fit) { + fold_fit <- self$fit_object$full_fit + } else { + stop("full fit requested, but Lrnr_cv was constructed with full_fit=FALSE") + } + } else { + # use the requested fold fit + fold_number <- as.numeric(fold_number) + if (is.na(fold_number) || !(fold_number > 0)) { + stop("fold_number must be 'full', 'validation', or a positive integer") + } + fold_fit <- self$fit_object$fold_fits[[as.numeric(fold_number)]] } - fold_fit <- self$fit_object$fold_fits[[as.numeric(fold_number)]] + revere_task <- task$revere_fold_task(fold_number) + preds <- fold_fit$predict(revere_task) } - - revere_task <- task$revere_fold_task(fold_number) - preds <- fold_fit$predict(revere_task) return(preds) }, chain_fold = function(task, fold_number = "validation") { @@ -334,6 +332,10 @@ Lrnr_cv <- R6Class( return(fit_object) }, .predict = function(task) { + if (length(self$training_task$folds) != length(task$folds)) { + stop("Training and prediction tasks have different numbers of folds") + } + folds <- task$folds fold_fits <- private$.fit_object$fold_fits @@ -376,7 +378,7 @@ Lrnr_cv <- R6Class( # don't convert to vector if learner is stack, as stack won't if ((ncol(predictions) == 1) && !inherits(self$params$learner, "Stack")) { - predictions <- unlist(predictions) + predictions <- as.numeric(unlist(predictions)) } return(predictions) }, From 59bc68b399e8a159d5b1bc166030294138c8844c Mon Sep 17 00:00:00 2001 From: rachaelvp Date: Tue, 31 Jan 2023 14:35:25 -0800 Subject: [PATCH 3/4] test cv prediction error --- tests/testthat/test-cv.R | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) diff --git a/tests/testthat/test-cv.R b/tests/testthat/test-cv.R index b67b5f35..e4db7bfe 100644 --- a/tests/testthat/test-cv.R +++ b/tests/testthat/test-cv.R @@ -155,3 +155,26 @@ if (Sys.info()["sysname"] == "Windows") { learners <- learners[!(learners == "Lrnr_grfcate")] lapply(learners, test_loocv_learner, loocv_task) test_loocv_learner("Lrnr_grfcate", loocv_task, A = "apgar1") + + +###################### test CV predictions with new tasks ###################### +data(mtcars) +mtcars_task <- make_sl3_Task( + data = mtcars[1:10,], outcome = "mpg", + covariates = c( "cyl", "disp", "hp", "drat", "wt"), folds = 3 +) +mtcars_task2 <- make_sl3_Task( + data = mtcars[11:30,], outcome = "mpg", + covariates = c( "cyl", "disp", "hp", "drat", "wt") +) +lrnr_cv_glm <- Lrnr_cv$new(Lrnr_glm$new(), full_fit = TRUE) +cv_glm_fit <- lrnr_cv_glm$train(mtcars_task) +expect_error(cv_glm_fit$predict(mtcars_task2)) +expect_error(cv_glm_fit$predict_fold(mtcars_task2, "validation")) + +mtcars_task3 <- make_sl3_Task( + data = mtcars[11:30,], outcome = "mpg", + covariates = c( "cyl", "disp", "hp", "drat", "wt"), folds = 3 +) +expect_equal(length(cv_glm_fit$predict(mtcars_task3)), 20) +expect_equal(length(cv_glm_fit$predict_fold(mtcars_task2, "validation")), 20) From b25211d1d52e7ade4efe6fd2b0ce0767e0511339 Mon Sep 17 00:00:00 2001 From: rachaelvp Date: Tue, 31 Jan 2023 14:35:40 -0800 Subject: [PATCH 4/4] make pr changes --- README.md | 62 +++++++++++++++++-- docs/articles/custom_lrnrs.html | 2 +- docs/articles/intro_sl3.html | 87 ++++++++++++++------------- docs/authors.html | 4 +- docs/index.html | 62 +++++++++++++++++-- docs/news/index.html | 1 + docs/pkgdown.yml | 2 +- docs/reference/Lrnr_HarmonicReg.html | 2 +- docs/reference/Lrnr_gbm.html | 2 +- docs/reference/importance.html | 18 +++--- docs/reference/importance_plot-1.png | Bin 37012 -> 36797 bytes 11 files changed, 172 insertions(+), 70 deletions(-) diff --git a/README.md b/README.md index a21d6a10..61c5a0fc 100644 --- a/README.md +++ b/README.md @@ -131,12 +131,12 @@ stack_fit <- learner_stack$train(task) preds <- stack_fit$predict() head(preds) #> Lrnr_pkg_SuperLearner_SL.glmnet Lrnr_glm_TRUE -#> 1: 0.35767321 0.36298498 -#> 2: 0.35767321 0.36298498 -#> 3: 0.25185377 0.25993072 -#> 4: 0.25185377 0.25993072 -#> 5: 0.25185377 0.25993072 -#> 6: 0.04220823 0.05680264 +#> 1: 0.3525946 0.36298498 +#> 2: 0.3525946 0.36298498 +#> 3: 0.2442593 0.25993072 +#> 4: 0.2442593 0.25993072 +#> 5: 0.2442593 0.25993072 +#> 6: 0.0269504 0.05680264 #> Pipeline(Lrnr_pkg_SuperLearner_screener_screen.glmnet->Lrnr_glm_TRUE) #> 1: 0.36228209 #> 2: 0.36228209 @@ -1462,6 +1462,56 @@ x +Lrnr_grfcate + + +√ + + +√ + + +√ + + +x + + +x + + +x + + +x + + +x + + +x + + +x + + +x + + +x + + +x + + +√ + + +x + + + + Lrnr_gru_keras diff --git a/docs/articles/custom_lrnrs.html b/docs/articles/custom_lrnrs.html index 8e08507d..9cada1b2 100644 --- a/docs/articles/custom_lrnrs.html +++ b/docs/articles/custom_lrnrs.html @@ -100,7 +100,7 @@

Defining New sl3 Learners

Jeremy Coyle, Nima Hejazi, Ivana Malenica, Oleg Sofrygin

-

2022-12-08

+

2023-01-31

Source: vignettes/custom_lrnrs.Rmd diff --git a/docs/articles/intro_sl3.html b/docs/articles/intro_sl3.html index 2299faa4..c7701ce5 100644 --- a/docs/articles/intro_sl3.html +++ b/docs/articles/intro_sl3.html @@ -94,14 +94,14 @@ -
+

Modern Machine Learning in R

Jeremy Coyle, Nima Hejazi, Ivana Malenica, Oleg Sofrygin

-

2022-12-08

+

2023-01-31

Source: vignettes/intro_sl3.Rmd @@ -421,8 +421,8 @@

Pipelines

- +
+

Stacks @@ -459,8 +459,8 @@

Stacks method now returns a matrix, with a column for each learner included in the stack.

We can visualize the stack:

-
-

We see one “branch” for each learner in the stack.

+
+

We see one “branch” for each learner in the stack.

Cross-validation @@ -487,8 +487,8 @@

Cross-validation## 1: Lrnr_glm_TRUE ## 2: Pipeline(Lrnr_pkg_SuperLearner_screener_screen.corP->Lrnr_glm_TRUE) ## coefficients MSE se fold_sd fold_min_MSE fold_max_MSE -## 1: NA 1.600368 0.1042245 0.3521137 1.062662 2.139263 -## 2: NA 1.601804 0.1032100 0.3419678 1.066897 2.108442 +## 1: NA 1.603528 0.1047656 0.3075915 1.199039 2.220739 +## 2: NA 1.604261 0.1032685 0.3024194 1.211052 2.235441

In this example, we don’t see much difference between the two learners, suggesting the addition of the screening step in the pipeline learner didn’t improve performance much.

@@ -522,7 +522,7 @@

The Super Learner Algorithmsl_pipeline <- make_learner(Pipeline, stack_fit, ml_fit) sl_preds <- sl_pipeline$predict() head(sl_preds)

-
## [1] 0.36977825 0.36977825 0.27474433 0.27474433 0.27474433 0.03143954
+
## [1] 0.3701791 0.3701791 0.2756184 0.2756184 0.2756184 0.0299430

A Super Learner may be fit in a more streamlined manner using the Lrnr_sl learner. For simplicity, we will use the same set of learners and meta-learning algorithm as we did before:

@@ -532,7 +532,7 @@

The Super Learner Algorithmsl_fit <- sl$train(task) lrnr_sl_preds <- sl_fit$predict() head(lrnr_sl_preds)

-
## [1] 0.36977825 0.36977825 0.27474433 0.27474433 0.27474433 0.03143954
+
## [1] 0.3701791 0.3701791 0.2756184 0.2756184 0.2756184 0.0299430

We can see that this generates the same predictions as the more hands-on definition above.

@@ -558,8 +558,8 @@

Computation with delayed
 delayed_sl_fit <- delayed_learner_train(sl, task)
 plot(delayed_sl_fit)
-
-

delayed then allows us to parallelize the procedure +

+

delayed then allows us to parallelize the procedure across these tasks using the future package. For more information on specifying future plans for parallelization, see the documentation of the future @@ -588,46 +588,47 @@

Session Information## [8] base ## ## other attached packages: -## [1] origami_1.0.6 SuperLearner_2.0-28 gam_1.22 +## [1] origami_1.0.7 SuperLearner_2.0-28 gam_1.22 ## [4] foreach_1.5.2 nnls_1.4 data.table_1.14.6 ## [7] sl3_1.4.5 ## ## loaded via a namespace (and not attached): -## [1] nlme_3.1-157 fs_1.5.2 lubridate_1.8.0 +## [1] nlme_3.1-157 fs_1.5.2 lubridate_1.9.0 ## [4] progress_1.2.2 rprojroot_2.0.3 tools_4.2.0 ## [7] backports_1.4.1 bslib_0.3.1 utf8_1.2.2 ## [10] R6_2.5.1 rpart_4.1.16 DBI_1.1.2 ## [13] colorspace_2.0-3 nnet_7.3-17 withr_2.5.0 -## [16] tidyselect_1.1.2 prettyunits_1.1.1 compiler_4.2.0 -## [19] glmnet_4.1-4 textshaping_0.3.6 cli_3.3.0 -## [22] desc_1.4.1 sass_0.4.1 scales_1.2.0 +## [16] tidyselect_1.2.0 prettyunits_1.1.1 compiler_4.2.0 +## [19] glmnet_4.1-6 textshaping_0.3.6 cli_3.6.0 +## [22] desc_1.4.1 sass_0.4.1 scales_1.2.1 ## [25] checkmate_2.1.0 randomForest_4.7-1.1 pkgdown_2.0.3 -## [28] systemfonts_1.0.4 stringr_1.4.0 digest_0.6.29 -## [31] rmarkdown_2.14 pkgconfig_2.0.3 htmltools_0.5.2 -## [34] parallelly_1.32.0 fastmap_1.1.0 htmlwidgets_1.5.4 -## [37] rlang_1.0.5 BBmisc_1.12 shape_1.4.6 -## [40] visNetwork_2.1.0 jquerylib_0.1.4 generics_0.1.2 -## [43] jsonlite_1.8.0 ModelMetrics_1.2.2.2 dplyr_1.0.9 -## [46] magrittr_2.0.3 delayed_0.3.0 Matrix_1.4-1 -## [49] Rcpp_1.0.9 munsell_0.5.0 fansi_1.0.3 -## [52] abind_1.4-5 lifecycle_1.0.1 pROC_1.18.0 -## [55] stringi_1.7.6 yaml_2.3.5 MASS_7.3-56 -## [58] plyr_1.8.7 recipes_1.0.1 grid_4.2.0 -## [61] parallel_4.2.0 listenv_0.8.0 crayon_1.5.1 -## [64] lattice_0.20-45 hms_1.1.1 knitr_1.39 -## [67] pillar_1.7.0 igraph_1.3.1 uuid_1.1-0 -## [70] stats4_4.2.0 reshape2_1.4.4 future.apply_1.9.0 -## [73] codetools_0.2-18 glue_1.6.2 evaluate_0.15 -## [76] vctrs_0.4.1 Rdpack_2.3.1 gtable_0.3.0 -## [79] purrr_0.3.4 rstackdeque_1.1.1 future_1.26.1 -## [82] assertthat_0.2.1 cachem_1.0.6 ggplot2_3.3.6 -## [85] xfun_0.31 gower_1.0.0 rbibutils_2.2.8 -## [88] prodlim_2019.11.13 ragg_1.2.2 class_7.3-20 -## [91] survival_3.3-1 timeDate_3043.102 tibble_3.1.7 -## [94] iterators_1.0.14 memoise_2.0.1 hardhat_1.2.0 -## [97] lava_1.6.10 globals_0.15.0 imputeMissings_0.0.3 -## [100] ellipsis_0.3.2 caret_6.0-92 ROCR_1.0-11 -## [103] ipred_0.9-13 +## [28] systemfonts_1.0.4 stringr_1.5.0 digest_0.6.31 +## [31] rmarkdown_2.14 R.utils_2.12.2 pkgconfig_2.0.3 +## [34] htmltools_0.5.4 parallelly_1.34.0 fastmap_1.1.0 +## [37] htmlwidgets_1.5.4 rlang_1.0.6 BBmisc_1.13 +## [40] shape_1.4.6 visNetwork_2.1.2 jquerylib_0.1.4 +## [43] generics_0.1.3 jsonlite_1.8.4 ModelMetrics_1.2.2.2 +## [46] dplyr_1.0.10 R.oo_1.25.0 magrittr_2.0.3 +## [49] delayed_0.4.0 Matrix_1.4-1 Rcpp_1.0.10 +## [52] munsell_0.5.0 fansi_1.0.3 abind_1.4-5 +## [55] lifecycle_1.0.3 R.methodsS3_1.8.2 pROC_1.18.0 +## [58] stringi_1.7.12 yaml_2.3.6 MASS_7.3-56 +## [61] plyr_1.8.8 recipes_1.0.3 grid_4.2.0 +## [64] parallel_4.2.0 listenv_0.9.0 crayon_1.5.2 +## [67] lattice_0.20-45 hms_1.1.2 knitr_1.39 +## [70] pillar_1.8.1 igraph_1.3.5 uuid_1.1-0 +## [73] stats4_4.2.0 reshape2_1.4.4 future.apply_1.10.0 +## [76] codetools_0.2-18 glue_1.6.2 evaluate_0.15 +## [79] vctrs_0.5.2 Rdpack_2.4 gtable_0.3.1 +## [82] purrr_0.3.5 rstackdeque_1.1.1 future_1.30.0 +## [85] assertthat_0.2.1 cachem_1.0.6 ggplot2_3.4.0 +## [88] xfun_0.31 gower_1.0.0 prodlim_2019.11.13 +## [91] rbibutils_2.2.11 ragg_1.2.2 class_7.3-20 +## [94] survival_3.3-1 timeDate_4021.107 tibble_3.1.8 +## [97] iterators_1.0.14 memoise_2.0.1 hardhat_1.2.0 +## [100] lava_1.7.0 timechange_0.1.1 globals_0.16.2 +## [103] imputeMissings_0.0.3 ellipsis_0.3.2 caret_6.0-93 +## [106] ROCR_1.0-11 ipred_0.9-13
diff --git a/docs/authors.html b/docs/authors.html index f85df727..e6a69fe4 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -117,14 +117,14 @@

Citation

-

Coyle J, Hejazi N, Malenica I, Phillips R, Sofrygin O (2022). +

Coyle J, Hejazi N, Malenica I, Phillips R, Sofrygin O (2023). sl3: Pipelines for Machine Learning and Super Learning. doi:10.5281/zenodo.1342293, R package version 1.4.5, https://github.com/tlverse/sl3. 

@Manual{,
   title = {{sl3}: Pipelines for Machine Learning and {Super Learning}},
   author = {Jeremy Coyle and Nima Hejazi and Ivana Malenica and Rachael Phillips and Oleg Sofrygin},
-  year = {2022},
+  year = {2023},
   note = {R package version 1.4.5},
   doi = {10.5281/zenodo.1342293},
   url = {https://github.com/tlverse/sl3},
diff --git a/docs/index.html b/docs/index.html
index ccf443f7..8b89ddc9 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -183,12 +183,12 @@ 
Examplespreds <- stack_fit$predict()
 head(preds)
 #>    Lrnr_pkg_SuperLearner_SL.glmnet Lrnr_glm_TRUE
-#> 1:                      0.35767321    0.36298498
-#> 2:                      0.35767321    0.36298498
-#> 3:                      0.25185377    0.25993072
-#> 4:                      0.25185377    0.25993072
-#> 5:                      0.25185377    0.25993072
-#> 6:                      0.04220823    0.05680264
+#> 1:                       0.3525946    0.36298498
+#> 2:                       0.3525946    0.36298498
+#> 3:                       0.2442593    0.25993072
+#> 4:                       0.2442593    0.25993072
+#> 5:                       0.2442593    0.25993072
+#> 6:                       0.0269504    0.05680264
 #>    Pipeline(Lrnr_pkg_SuperLearner_screener_screen.glmnet->Lrnr_glm_TRUE)
 #> 1:                                                            0.36228209
 #> 2:                                                            0.36228209
@@ -1493,6 +1493,56 @@ 
Learner Properties
+Lrnr_grfcate
+
+
+√
+
+
+√
+
+
+√
+
+
+x
+
+
+x
+
+
+x
+
+
+x
+
+
+x
+
+
+x
+
+
+x
+
+
+x
+
+
+x
+
+
+x
+
+
+√
+
+
+x
+
+
+
+
 Lrnr_gru_keras
 
 
diff --git a/docs/news/index.html b/docs/news/index.html
index 60d4f4a9..9c5eea55 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -98,6 +98,7 @@ 
sl3 1.4.5, "binary" or binomial() can be supplied for a binary outcome; "continuous","gaussian", or gaussian() for a continuous outcome; "categorical", "multinomial", or mutlinomial()" for a categorical outcome. As before, when outcome_type is not supplied, we will try to detect it from the outcome values. If the supplied outcome_type differs from the detected one, a warning is now thrown. If outcome_type is supplied but invalid, then an error is thrown upon sl3_Task instantiation, opposed to learner training.
 
     

 
sl3 1.4.4

diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 1437bb28..5eea63fa 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -4,7 +4,7 @@ pkgdown_sha: ~
 articles:
   custom_lrnrs: custom_lrnrs.html
   intro_sl3: intro_sl3.html
-last_built: 2022-12-09T06:05Z
+last_built: 2023-01-31T22:01Z
 urls:
   reference: https://tlverse.org/sl3/reference
   article: https://tlverse.org/sl3/articles
diff --git a/docs/reference/Lrnr_HarmonicReg.html b/docs/reference/Lrnr_HarmonicReg.html
index 50f7704c..6f92c3ce 100644
--- a/docs/reference/Lrnr_HarmonicReg.html
+++ b/docs/reference/Lrnr_HarmonicReg.html
@@ -201,7 +201,7 @@ 
See also

     

     
Examples

     
library(origami)
-#> origami v1.0.6: Generalized Framework for Cross-Validation
+#> origami v1.0.7: Generalized Framework for Cross-Validation
 library(data.table)
 data(bsds)
 
diff --git a/docs/reference/Lrnr_gbm.html b/docs/reference/Lrnr_gbm.html
index 1cd90ea6..71f11213 100644
--- a/docs/reference/Lrnr_gbm.html
+++ b/docs/reference/Lrnr_gbm.html
@@ -130,7 +130,7 @@ 
References

 “Greedy function approximation: a gradient boosting machine.”
 Annals of statistics, 1189--1232.

 Friedman JH (2002).
 “Stochastic gradient boosting.”
-Computational statistics \& data analysis, 38(4), 367--378.

+Computational statistics & data analysis, 38(4), 367--378.

     

     

     
See also

diff --git a/docs/reference/importance.html b/docs/reference/importance.html
index 3ef2a598..20934887 100644
--- a/docs/reference/importance.html
+++ b/docs/reference/importance.html
@@ -193,12 +193,12 @@ 
Examples

 importance_result <- importance(sl_fit)
 importance_result
 #>    covariate MSE_difference
-#> 1:  gagebrth    0.040187378
-#> 2:      mage    0.035690483
-#> 3:  meducyrs    0.031440057
-#> 4:    apgar1    0.016076870
-#> 5:    parity    0.007267036
-#> 6:    apgar5   -0.007811246
+#> 1:  gagebrth   0.0404065437
+#> 2:      mage   0.0317210881
+#> 3:  meducyrs   0.0211521927
+#> 4:    apgar1   0.0128016825
+#> 5:    parity   0.0003541107
+#> 6:    apgar5  -0.0095269432
 
 # importance with groups of covariates
 groups <- list(
@@ -208,9 +208,9 @@ 
Examples

 importance_result_groups <- importance(sl_fit, covariate_groups = groups)
 importance_result_groups
 #>    covariate_group MSE_difference
-#> 1:          scores     8.18253682
-#> 2:        maternal     0.13998895
-#> 3:        gagebrth     0.03466159
+#> 1:          scores     8.40154165
+#> 2:        maternal     0.13142329
+#> 3:        gagebrth     0.02949398
diff --git a/docs/reference/importance_plot-1.png b/docs/reference/importance_plot-1.png index f07f9a80e94aa65a63d48261a8890a09cc3d405f..b2505d4507f97baeae2a63aaa450dfd5d7212645 100644 GIT binary patch literal 36797 zcmeFaXH=DE*Di{hXpB*VT@XkRyMT&-bd8`Q0xBZXRYZhE3B7}fiJ}N7C`eZkQ0cvc z1wp#>CZJSd(R*iKlf2)Lea1Ow@AvF-#@OR?3&mq3pN40O|~}5)mc(s21K_0aOLcGrYtMA9gES5igHnVbTuL+dG99m z#Ph3^)$@Cdn4g2IMMEyWQogszRc+fn9j45M*D8r?lFl2RW0leUBzoZEhF{*#&wcfB zTz}}n(cj`b9E0z4)z9=M)oSVK1s*Tm#f*F`=gG5j@zM_MYN=Vh_@~QFKiDjxKOH*# zW)*#XaBis$^mEyi4kM14I3V5!0ak<3oLQEt{`@U(C7~t`Jzk zNct;m++%fLa-*?a<5(!aKn7f zqI~lEF4MtS`QpVBwzjs9e0+p2b%yyH-wTqk&r@`su6!bDX|P`_^T@?$jjajSOYYhC zr|r7EnthYMQL^fN4l%2&M)Mj~z0f|};euT{U*G**65aOf4(Dm+Zhn4`EAMYdS!dLo zl#!8X@Xq_q$NTJvZOUI^qaMj;m6abSM?8Q2Jj#D0?ZU;2-nVZC;)9r-hK~%ggKEc3 zItm{TH85g6JUOV-dUM$t7srVvVaeIS_jb&tPcaNfJk}d)zsodCbQ+7${;*XqAg;!& zqoZT!J=gq!==7e~W9iMGo*ifONlkvag)8!7M9Zd3d^Rup)|4?}m$XvoBJbRaWkLZy z+D;<0@RrltRT-arunUrRe$fpX?avs+^x7$Z zPbyiUULhnxycdwQ0P(9qwZN zE@&RyijN*WlIHVqt*EFt(i{7}wM4k(J{~=|RPvcLmZev6tjaT@VwR&TmF{uIC7>ZED#iCXn;nVTMS zjnm1`3-!_RK zt7Dv!YLfahM@n}F`tZoo3Fw}G@aysCaz1>Pg}kcqJb4~mTqikguNh{I)s#Oweg}`s zdYjYa*MrxKpG>xUDf%^ahRXTm?eNi9htJX3uz7Qg`O^wEBYQlB)-I_9+fimMzo=!; z2FICkH>{MHmVIB6rGbu4XIU^89;5BH-`^}LPc!fORvvP4n|bj;)2=}4yoyjc^;x?T zWi2hvwtNqdWoyL`(0gRrPq;taezGQQv#e+CqdiKkf2~(=;Z3gN7Pao*wt~ar>}Q9O zk~o9v*Vi@83p{t2_9fNkZO$J2`&-p3B}1%?Y2H@7Ty~Sp@<=;Rp1VF;c6&-CXL?8V z>NBhdwn#eI%uba#YlWw|sK0Kx$Z(riS5@7L^A>!SR(h(_|72HbU>j}yb0H@_U`zOE zDB@X&Pqlj;G;9AzE0cZ}F<`q+;iEn0l$ER7(;Muiqy{oa40sb$C0D&lI+26zb7TF= z#N+0j#j;k-wp~2jY_lq7&pr^J{uZ*j#EoM^V^_Z2a}j)nD6>naNrOQ|t`#kVj!QdX<3CzllU^5t$`Yyh*l zv07oZTGMPIt<>y+daFhwcEc8z+IXN{SMXv0;QS)$R!o@Vs#0Lgd(#6M|L&9!ll6xxVHs`{7nsexXYzm1g=ZYc+i~ zY}~lx`|rO`a#s#+OfhK@wM@CN5H%&Bo@rx>mj&}=^rtg!S#HEn@#oAAs|~cwPL0$~ zYo+0o@Zd2hgp3(}bJ9v^&Y2&JDG{9*e7{z)Ork5m+<=48!?bgpX-Xg6frwLc^*jE) zQX~epjDc+XVn4x%al5$p$!)+JAAaY7;8GF&pbKs>+&_*Qnf+`3yX?$K0Q5l&~EhGi6W$hyzcN|&U_AQ zjaw7Xc2s8$2#N8<2X*r99~u6*y>j^d?bVFKH`J6$V$S2SmNIx3 zJe+5@H_Z?GIIbHbE=Ju;X|~%}DmIX*RvRE;ZxvEI*KeJ}zVBkB%iCKk^6zgIxH{HT z{g6j?w7)5%pe!k=!3rlCu*R2p@2MAbME5BO)~>I&J+!}x$VY#w>nQ1X;=Ks z?ZcFtmxw+WZc&K0;MlgqW6!E_!-O}4ACnKDiKXdn&v=(=WkFs^gi}>e0=<9 zL^SG>(?-;CFtd6!uEHT2tNLszE_LAGHvDmV3tpPXY(1~1HZjn-kW&z*>|$Fha%BA~U@h-i%j$w(hEtcyL7<1XPa zId~%HdXuM7gow;>X&xUSYa8M056J%894-}7CJE>v!>Q%e1`%eb&d0^1nP3&@Tc zZ@UJ)f@gVnRn*k{9zA|sy+;6tKJiSjq+`$A)*Z5*D9m;qzx|VJQGfPKzhw}^e5Nm6 zx5!}3<96b;1C4E6W8M)WJLIK#f}N)I zquPwB%NWV8M3fGr!rX<@pgV1?_~6l~Hio@s%C#Ih&#;NbSa=Pw@N~&T)mtmpy0767 zty1UnDGCiavYlJYajbfiQ9d$Co3CEbUD}wm16?K!NBf=UYMql#&Aq>~RxxGYzI|;} zxv}q8H-DiKqm}hsJI5)>z1E?h;h+5FTZo53N<^^AaqQ978g&yl4ZhkNX?ckk8<+pI z<>$>BzaP70lrcM86kt@@yN(HfM^)l=1kwA-?sjgs?Q9lX$@%t2( z-?ph}S}GeRRbRxXd@SFi6jmjwh4KTBS|QzeVQzwwKQn4ya9RFeE7wEHwZQy5~{O zoE>=X%F2o$sJ_iKm$iF-UrgqCrp?7^+a#(ja26`&j@?==IQ6;ao3(u3VsI=7XKi@g z6T^N|S{x;;Td9uCnzl*Ny_gv!W}l#VYV+DH*LzJE!N*+-Qp;3IHc#ztG>x=m!i9ii^Rld z0m3y&L5qRB(L-w9CLuaS^2GfuhpRs5N; zZ+}13nlPh1vi1OOPcf=3CUf}ov|5X8SD+4RN#jww9Xoa;X|=h{iK{)v*C27@$ z2bi4>`D4^iEujU_GjYcf+T$P0H|@Xl^YJ@tqBaI3h5?U#dJ*Oz$ps+sa-(F*UsxmI zCMQ%dIyg#}g^?n|iJh}yC3w!PCYeJgqHGV>cJ9-jDiqa>NUI4ost);q-MsF~ozTWI z$r;0hhEYUb-lq9H;q3Ak=Gfa0j7>gHiLRBL{Ic95YHGz@qvZOqxAB6@Mv_YOH6>P< z=oq+1Iv^JsaMA;m0vAj#-vW1ddmf;bgx7*o~gh20-!j^sK|pFuspO#p=O`P7715 z)h}^c0pRKVW3ASALILu^O^1Ofz1=76QS;EzGyV4LPM&qnOw*BXPj6i%q#2{X%nv|m zZ**$wy~(i{XAbNw4@t-A#8X)aP5?R?}KDUE=ban{`)RdD)^8 zo{6>`&l@K1zllF<^!)5h%Yw1h41!*Huep$PBkf~AS`9`TL8+!7VH2$j z%F2Sa-;D#Dc^hk+e%L6l_A;uo_L~&4=1$G<9RyV5`5GV1)SR#FMRrY>&?^m4o5<-r zyhL!>`@AZLrs|(|)>c&@iOFRr3$-|mBzeC|d(i5KOYkE$SGu9%wh6G@?s$s?s=!rkeN+rFq^ zRx9Ynh6y*@gp{V03=QRT2}jIM@8;z-GOPEV_7xJ!I+`T-J_YM>QdU-0S{fNe!ZGvJ z63Y_Ss3ISJlLN6P-BR<3c?^c*t#Lo|Wie%30r6F3_G3L8DU93)@>sr_Z3BW^Npy(d z45eiC;XQv_h2yvk^(K_%ZTApg2V|!b*e2(_|1P_6>aSoemfVIau^m z?U@Jg6aeUL$;F9(z&V5H-#R}tU=qiu)=2HHR?&8w8tDq3p^_jf{tlEEt;lFBbsOxNJXQ&B$lk z(eXR-SUvglPCq>T`CY*dp2ot0PmNvAMkQ&fGiNl2ys)r$>|{6QpL6J`deyyQ-Re1i z?6BFdYn@$=uMxQx_^!#NcT^0JpmVt3Z>v2B{=zv^B~OHm)G`<5XNK-b&Hm~xKKxOX zE4i!Kcl}IXiuP<9*TRjY1|8q&abH z)ZT|rzkBJ{gqyoA6_eIf71PPDp1i+_kB_hUm$&NnPDaY=!K_7np}{eX%Ndfj`ek!# zz#ybKoPXBTXb=%ae1O1AvZ`ByV7KpDQ>1j+hhPD45fkk$unAwGBXD zVFG1N!zoW5WV7`^9A~(s`VuR9Bo^8{q}*4o-}z#uEzixhE6ARYxG1sS*yGcWCk;xr zen`(&i!eg9V{pFS?`^TSx^aEv&#yXXv&_3njfQR6Zvj;7l$SX>GC$E>fCr^ zc%wXr%rrJecq58pJ+D$#uD+=xW%Ibqv8{h+#Ep&YUwkN*zkb=F^y8{klpowdA5ei_ zk-sqH;hc*MT4Ogq+)>1c`jibqV5eqE=krs%5`QxB%&w%*4LC0>G7)NT&!YxymD8R+ zpVgI(I-`3W;4`7-seSo#8D@P$7$YhfH7%k28a3mZNY!quh50%E3)V?abJGaz5)&E; zrA=F^W?$PMr|QSTzGOZFU>j?Lb*l*$RsXb7?Ol+4|5l`< zQxhjWI5`$0>H@Y~>f7@01idna6l_hC=rJ{=ursP2-a?9u%i4=1d6)nbMLMP9YSnc;s8B`l60*a4X}uAoZ4|$Wuio0 z)c%xbz_;ayX>0D}WSa+jl*xE+eYeXTvOB>NbN|mzZ-@EcD2s{mn;5_W)Mn0Qw0p`` zNEvY0eEDPX9!>h3Y9GC#LQL(}O&=@WFK_n#e%f)I!p0i6wht1M zi7GpKW}z?GeOZtS&RhJt6?cf~nO4Wqc8ZwKM^TtwbOgKslYo9WJld%_R1 zEiVDNSt>qKoH(#%>!BB_wMBlQGxPdVTC@h@kj##J{cAmeS60^YaK&IX$6vXhTMslJ zv>E(jv4BABhVt8v83B+8%8;)~3TME7R?Xy8iT*{r*g!u2Y?MS!a&rB3|0C@Wj#tci zDTuy$EAyVyw*8?Es>bcD2_^@s0!~`#FuS742mC5P+_I?oW1&JjSM-dONl7^&FfPV8 zY--ja)!&ETuHee8i_>A0Fm0=qRRpKlPI6dY811Rv$1TaOPsC*&XoZbbh2HX2j=1OM?Ys_VAG1T*^-TJ`Prs({Z%iBDxFf14?^s>+6W7%9 za%yI#xR!0l<2sX^xeD8}uE0jmUHQ}olC8ge`gMA=+pFKXTTc6)2A|5lDkE%LTvEkF zs@2+Dw!6F3C+LOG{Z70W0e{<-)(V2Vs;i|EnJt;MPPEAE;B2tooU(o`pLZj+rqT^T}_JU|B*r=jW{=&|A zBBMpHZahr97PRk9&2$TWGp?=THou=&RZXjzsd+-Qg}x&d6Ir?j%@fYxnA~bq5*+ub zL>tC_X2#?+f3u7ja0VLJveWnK&sWt8tiI9cMDNNJtou~aXoT|PI zAtHf;SGm7UBwn>oQ)!?%t1ZyF`K}`>peSAEVXxp^)c6;f`x=8)2$^a)O?9|=r}f4c z)ri{JVYdz8ELU$;P7eb?m5*y<@Oma?D~Rz=Y=oi)z#Xfb zeKyVCf%B;Nim+ zyPDE1<%rkj$5|uZ+jqZ4YOGA7Hbks5fue#UL%Hj{kR^6ZIY@S+GB|`s(VoX{az=7~ zvTakAmi-0u?*?8gM_@;IB31_%;B0$EB{%HFb1Xoh@Ft*MfEwLjc><+`XA5}10@jn; z9$NG@2=3Xv`xKqQ0Egj%0x)R}ueW#kKSy}PyMX|Dbe~OdZ#^i3#ft~my_HUgtM)9n zuOQ>17qh-@+SY!+8Ua!sa_B{^)yr=d@8jcB=z6CGlnOpP#nctwy!nG`V;n(3{*8dqI>Ee6+8#?P=L+0|MNjv1c!AKZ2-Cu5rK=tD)Dfq6(>$`zTRgYo&-C5QOpP~kJBcmM zX}oyxqFv4ofzzi?<3pJV*G}MVr=6JQTiv=pJ$o-2%(zF=`~Nbn`rmyF|E6MYw_a)I ze|Q1@_X+U-i*M?G_l+pm)vW$SEXcOgcM^JP^_L+EB*xiOovZ7(=~nAfSK8>uBiEe( zzPpvrE|z@I9^tbMl8gsbiaZF>TL7$$nt14^C3k(7dAJ^tdOb0TZVqj+f>F5>qfZauEiIO7Aj(pD7I z9;n=TtdJmGTx@`nNo9K1lmswYD$*4&iGobKtM1+3tJ+j@rj^AJqD_f#o#<~8c34I+ zaPsrdgVA@O?(M^;Wvh9V1WAZpFAL%zqVTg>5pNvo($IVqV$b8_579S-TO7X$)5bcFEk-!WZ^_Y0egSVVN#@!YTRy95V)N6gH3HYSp~q& zyD9{Vet;^%MhUQeWa?6~p{h9Q#Dl;fsbe+jZTQeA^L{YY&z->l^t=i`Q5&sEfr*%X z8!F}gT*c>teINh;zMcE({Or^a3NcXxs5TU7_ZDW$7VZNB5VxdZ*Bv?p(2*e1NQBjg z=!||g6)js`lt9~8bNK*Qu(IN57|Au~l?B4d@&Qas(~Ec_CTWwb5ov#L(Rd?nfhAaF zX|v@hm@SA}F09+H;@K;34S?g{<~%z@*G}9=R@XS*m>!))TomjMTSUyRk?yrf;$;s0 z_S3c_2e`TWQN+8r9DzXBO1M`opD&|#9bHub^cmiU%@ccE?LM>2pcvm~ngET!#+II(fy zG4ldM%+(@|2YLd^!RBpVNqC$ir5v{3b%%HOm7>PmG(p8JaB+=j*>+ zTsW*h$GzR)3~Auy`oU<$M$|t_18sCjT*{VyfvYIAQrH2+)=<9G{K1`yLEAQKTAaJj zB_%1;WKnq{X2`bYb58D55qLuu7Upp*BT53D-nzJhIG<`B)-XdsAYcW9#2EaHm{>Do zGp23!di@M+IMUL&o&F}xmo)>$tc}Z)1vebww5&R33UamDHWRg>Dbzk0R0F`i0tan} z+b2t{vz1IZvfvfj7oGb2Eu#zk_^PrbVdw|lD$sH-of~Mi5)9A1aSt3$60@tg>o_=| z=Qw&$;v3TUeB!|;x#MWbdLCvpu-}mT`|rQY<8)3g#CUBL4A&)v0U}efsq0hyf69XJ zV4r7MRKkq};TzGlyX7TYYP!@@aFi@Sn0$C4>qVQ_6a}wLj?>(8us7vkM^1UZDE~Pr z`|<(q3hmdhM{u$(Y)%#$Z(RV}rj}^L?18fBN*uuT62I!pzVbr#JlW$(F@iP@Fm+Km zw8=zWjtm~ln!)SVvU~R-IL1NG&x58pu(Mj^+Q$c0a{&d}J!xl9{)`G93c>l(Z>csZ z@WTuIZ~2_ry?_6iWzAsm2U4z`Ff}!8HxqI6E`BNUAR0ALOXxAdE`~ARk^xb>FMq7y z=5D>sZv0Z%dogAe+{_(gXI0yHWmplaab3ktd`(K&P(FID#O)xD&Y- zspIRl3%2IDtS58ft!Vz%bLS3+)g=w!OZHf0+K&#LD{X3zNd|jBg4xNd3u_`@0HP*cmRey^&`K<`Jzf zwYixI4|fi+JX|LSd9aL|(xc290nKwh0O%DR0r}esofA0>R7>kR8vkd?##S+ez>6(_+<TFO=^BSa-h2KdV1N7Wt&t(nqoh)C5pR7 zK9t#{y4`hu{E3=N*W4oGKeDOnJQVaR3=uC_#bjR z|L0o#H|djq$2|W3>vCFe7ead6a_HJAqU?;CHqg~v=J>%z_$t_Cpi3Uv^UNWXdGsU1 zA-bt8f0Ir{C=4JxM61-u15aIEwg+s@Co8bNTb8X@6FG4SFNL$n_{*jxv3z7~A#I6# ztz_I{WhLwGfa8F@>ARJ?q!AL?Q+~$TCzmA4wK`(y$r~g!*R80Z%Fa3jnk^URke`Xq zCsuB?I%3LE#=61ehlFNs|Fm@-m&4#O(scedV$QG3WW&BY1>l%m=@C5v18z>09y}gRx2)N42&n zN#dF0L2F~KUP-QLdXD6T24AW+sIcU0FyKz=;Ja1+8$L@??Tb=+^{2hKWTC_6gUN9y zE@YrpwpA%9x}l^#ffD&M3i=@ke);r#;D^!^wQl{l@M<7JJul&SsxP3#b3QEUXaxoO zTB#ol_kFIpZzl-?)m`(FZ$%Qg?^5<>D{}v$Nen-BkEE*_TezYwNK0=6r@UISR>pPH z2RPpvzYKv7kwQUT<5byjs^m*LoCW7Ded{=G1=p_(aUj<}{Yje06Jk+|qz2zCGlfW< za@AE$p(MK@XhHj?-)m?7Z;(0JQ@-=t8N84aCyCOa*`(k;peD+S>HWUv1jGi@?&n1+ zwmdkS6bE537a-Q__8rtCWZ`~-CV?~lLcGM9Sp1qurfF_&0w&nF=4vNNDW;uzcm1xs zME%O1EQMpoj?Kb!YFKf{y=RT`h)*_9167yArD%bhKLU$Er4AUCgE+UigmSo+mopuS z{qdCJ(;u89XaFIcVWe&U37-FC z;;vr8@{(nLQaTqfL%pkxjDKUb+Ej|?0Y|n$=XS%M3NL3uchJjfOh>_V67^apmNCw- zK7N!xjO21@hfUnVVgJHyf;Qq%hauC~W&}osb|(IWK=f|ip4!nPt)f}g~629ARmWJ|rF{pt^-m`!Ieb^IUFgT9d`;>K6nuID}xR48qzadrT z6Cr;W2TAP#?zT^y;F3d?Or|wX=+x-#J-ft&o!OAY$nsF}NRAQ_&j5jh5?@{KSpXHk zM1df_tkw$OaiRu3t1XbJ&IE~zz(4N%0SBJ?5P;1&vGCJl%-U~Lpp0x04W7SkgK}wD zyCA!H!-g09LMDaRWGvsHCBuO0v!ovRxYzyCCxL*vy>(%eGP!WBq5=nDan#j) ziQ!S4n(oX_hW~wMSUw7imr^Nq*h4znt;AoLAFgrbuA!dqs}14-1|CLyvwzMyd;2uYY%qL6iwvELhN;XgUF!7NBIT4RQh~H28GiqZ zkq((q17n7E$gaaZSW8QjlZIPTeOtI_ZW9QUo+<$xrHjVhdPIa#Glq)`nYJn3;wcdQ zwc5;)#Xt-SwoYsA-8l5y)UXvaf(|&sj7(^a%ja~BN@-62S5`XoXNp@E5DO{!)B*Cy z+dB^dnI8ILB7;6z3#DDCVaR#+6FrAwQItdO=oz*)H-+}Dk$d{;Pf;LLV&m|s|~8VuWxDY&>? zP_0+r{k5{Y4JrmTT&3dNwLu!YOG^%VoS zq_lJPqjtG%@Bx?t zu;gRCR3i*qvK`yN6}V(gG>aiyEy61kN2WSK&~LRd+T?v&Y^VW92t1ckLdMg4fWP&N zN>7se<42EjDR{B6k}o-PQO|mF`>|Y20E_o(0&c_)=l=&tVs;*Ggp8z9_43>z3PT8N z;I`z`NIifAsrDke<`bUV?mc^84*uY}xprmtGl{|uvvTZ+OMs8d)$g;`)L!>D+JtpO zSJ3yXHYHk`Ka~}=`1UijY5IGWs`iqG5YTCLXn%p#;d_5%f`&ZaKf`cpLiPHnQ~w8>G5_-|{vCL- z5S(T2F`UjfC^bJ_`cv_N16r4R|KvU$rtjI&#Al%8`8Xj>$wuNjBkXaC($}Q@s|4gz zs&l_rF?ue|v-JBYnRALp`+xoLuvocp^4L9}1Lu~dtu8JeSX=7gqksM9pSMa5+61(T z45nr4%?<|+i01?k%)p<c8bC;s#3F>N<6D_&=-JuXNsM_(NeTUP-HnmXlA^({@6A6QTcP{r<`R)FHi3G^a)=M`61IVwx*_LKkO1zR8!c8?3I{t=Q|emsJOU;RFIEQLkU%0XqoXv z*XluZ%NDNO74U$(@cKqZef?KJJ{dlE-OqWnTmnGC7G?DaGK22aa7R7xj5(-wT_CP* zlq?xW1E?ZCgEiWUwiU`tRO(V%^7Ho}dFbK56CP-#MxBicWeI2wy3a1mM-`LUYDG|;da_dcLaoP$y9GS6A(2oP-ucIdq9O6c# zxf$mTaIzSx!Y-@LhXy~sTA$OQ@LNlrLVwIKv?SYA?muB!Du2i{c?)lu030q>MQAh) zhO1Z)X#?g-3(#-sTD27wwA?7bq(V-(8CZYciv%(PIU9bUl9b=`+oLd3Oa4@58$NL_4}bK1b?gz%dT6HPeoVDCg+th##5P zVMAUz@7n?0$TIcrGfM|{+QInb#e+>?)jZQY;q6mfUEKksSquOU4|0IQL{v;nnXZrK zMW=Jh>gxVwj{WAgFx(x&_r#&piNN{l#UnLUpyhe&KxS(r&kA4c=3M*EIb+K1cPVO3Zq5ZOl&_T%~Yi@2%J%Hz5J%ak5`redU zN2t6{aPPwzb*xNX#Uhhv)=`*ZiKln7|I3ffDK}7-_(Ck(#HaD(?^T;S$(V)Kme^)T zc=)TjhsmW_(6CR_D@lo$r@$WD-O6V)hB5f%Ev=nUW8FB!>9J_%eRPfysVvg6FYGm{ z&N(xIl51P1zn@?F{r1?TSFc_b;OUA5#;_-!sIIQY^Fuf(0p=2FG!?T~vT(#;e<>q2bv8ObaZrlW~|1_vy%7eHEL<_YG;ef#uxErSlC9EhW%)> zPiH27pQ~{A{M<|zc^7?{+UQlI($=JLs^vABR37C>K}9O_6J(^@N)LA87#J8B#A6jp z*b2Y&Rl!X?eBr47NY}galU#vNfmb`->Id>~dF{*>XZb2RS^*C?-mw0V`QZ56H`_?@z3I$5JqmtCK6uuN*ffry$lMUBSpHC8%_$@?5L()XNUFc_SW z@=HX8Sn9krvG1qQ7DatH7HK7LzI(wemlK*%M;T!cHtR|?HMPQLiEyWL)WEdim^IUa z*v}!EUfa;%M{!8j3|L`@s#xedV4x?^-E|>Oa=4Fxb?N~9-x#U0?52^byuAF*Gfy5s z1I&E?NLEl#Pz2Tu0&>IQ`Y14xt#H)Qq5ARWl4YJeQZw~sh5ra}l&XN%{O|}43kq6_ zu4n|)fS$(`pRPL1YzNy#VZj;J;*n_UtbJtt^-MC?3v!z7mi2^NMU+-SOejn7g0!$PbMsR7Tj-{TSo^*Q`TpN4whSmPx z;J7G6nDK_wMHkqxqXY3O4Y+ZHxIRkA6fY@9bVI4M^%p2TvK^vX8QBx9^1=VO9MqP z>IAHH{C50RWMnbi0iHAqWD3m=0W^sNxZar1bX8Rq0$F-f_8l%K8?rn*^y+ZQl?6#8 zAoO>=@KPxBa2gHCWNHo=q!0&qtJXn;evyAMy|YwLk=IJ>a8I(ZQU-zxmtYbtwc_*{C_CE*+CSZGerFZofsd z2W??ETb?{552JsgvSj<8!YX?oS3r70sZu4sY0rH~bYbWRi;9X;MW>7P+7&{lEG;eZ z1mbOmu2x%^fNMpJ)c z+&#_jQp~9{R}1DCQlkF$SX9E^wUsVkt7{f zhRGLU96~(mA3TosTU@i36~u>fd!Z&HMm9;Dp`!XJdujoj`f6d-TP0=kHM_ZmRYP1p zUvqnI>Lqxu5dXj?tg3T7t$>Yw_Knr4e+J&{-u=hoB%G&Dzx!uI&Y$c48GQ5O>Hquz zTB-kBhyTO&L(^|4NrDJ2L2vmNT)NEu>!9(kyu7^n#>NUrXx3{Nr$N=7xL`R!n}8+R z8sWVZgqat*{tjWTLm@h+d}%O7@N`x9dF34~ESe)fA-b}BlK1oTGeg|$fCb7pWfo;z zDFtnaXNSm$Pj0XNt-r)pH|`9(@kG+mj*X3t>M|Oeuzr_9G06u4W#R&EZf>fuS$bYW z*9Aog>h*6=2%a-!V`oo5UBTy(0m}$srOjG4R}|0_;4l`UU4npFl+P?iQX2^zaM(pd zD(JGQAF6~(t0pUIQMqyBBlR{Z)CObl1O9eONlEFBB{8cfJU9c(oW>JG(6C{SE|2T@ zaZGuTxAiaZ+7b_v055$p+5-16jEY7NAXMMbuo%(Rn-shb zN36#oxTrKN%4Mh^rOWvYtElZ*wMxcp5UnmpQgU)9=CbtvY+XA>elKz}kTS!263s{)c3G{g}?Cx7Uw$b zle7_%-@Lr}yng3W6MxXA64Y%*qGx6s$G}IBh60!`v6y#o_vUD^?xaRU8Zri=vg_Wy z=#PMX!C)^tVXttWI)XB)Bh?=BTRL^PW-d|5icJMbvy7I*91f#vu+&k%gJ(MqjU4V1 zl`YM`povYdUcW8`_VXt+h=C3D`?cFpk7>AP&`^stfGx0tU<+v#WM?eJ3Yf%wmj5#*bb%Y=g-6w|u*(C35GdtzEV1GUv%{Rj!K3-&&fwF!`LQC+> z=Pse5+B&Ns3MEtDPD-h1WdokHGqh*aBu9M9+Clr4La0>Q`}h!KXbKAyu<$QMjl#mh zdbo*KsD^=fv#q)y`xXn+xmZ)7ke-5DEeNKw{eZ*8Eoe*c#r6tx zpMx9NToQ$})l`x^8e(83ExPS2kY0`l{i*5rO}AE=Ut}(z41*xq&$-<25j@^$8F#=M zL759O*%M&YaZn6ndsa7Fp=nSx_VO`z(VmwnrqY>#vs!u67J?s`x9h^1g^tkrn5L9u zG>=8|6g)i1sp_6#)Wc+Y@j&ZtY2*!t_uA89>IHcbc^Kg`r)so(Me)8+wmTt1eTxMN z;Yf01oVLOW9O0?pg{fek0*L;VSLO&&5KtyJx2>xBcTR(ES2P-BpsY$vOnelscc~U? zPUElrI}5PI9$o9pxV>=1GMBo6@T#05AY)jWQY^YFfQ>KD#L8>F6+?x#rl_G+SN)r& zN~7*D)9Jo3?r*BGW!{@d1f%#wi`D&kkXdBU2N^%@TdqT8v5!x~T2ApJuu!xwcjgVW z#f&Vk$gD#z`hIK>PQcPX3crU=SmDBfO(jnbZZBwfGUJi%cXA@YytKe4XSRdLGGB}k zkVIQ~7c8Ac&<$1GJD8Q2x3djlNHd!M@oAIprh6&sP(P;@27pQ(WXyfb%XW_bu~57tcewdZUCOxPz_Dm;U7r`vzlPF z6Bs~S++5_IC&{%x$l}4-Wj!uUl>feYOr|V(Grvg~koRnt@XW~+bl~t5U^3dnYja$z z-5ANYJkVKlVUjzdPaGJcaXD8AKA60X6gX$$lrUL?X(Nfr$&_(W)YgNM5bGWBP#I08 zabL)K0*LqI+3-cugrhKshma9p>X$#qv|eT6ovuNy(TsLRS`pKb&l2ngPMA744v20j zz`wgL`SIycnjA+c9fU%<{gK#X#M}ktTQKI+SeUPY!GX2C_p7$bU;gnKgr3=zS;SB7 zeemvOM1-8KZimna+t(*L?)6{Z%wUL<7{&(HUC$oxlQA+f0)yj~3zDf;-S?f2|Bso0 znnoFMHE#YO)#{&;$wNRE(4&P-g zBDEU8?oze<&VUd?%+zd`RIque$Sz9JWMwB$!6Hf}GaLxVhLz z^ArHUB^Ts>2j-}6vF{D0ku3dG37iBoOjj{_c5aEx_QCmEV4om!OUe#|PD!sc>W8pL zB^gq!Y>n1$O;*)Cu(XRBE{EMFY7~dG9HpIRY%a9PR-pktUj<8C?`q7st2= z`WifWs4uW+2GOV;bEF)p8sq6WniZYw|4L9us1rH32n147|4t#3u;^$$40bF67cc?` zj*paN1sD`!=P>k0-g6r?0d@xhhQH9t1Q0&8MYuD^WUqFymMI1D9iu$li}LZ=tF1T3 z8p1liG-<$e;6tV1R!qdmp2!-oyriw9 zCrZt#Xl7y{c-fjGzbJ|iNz+8TWOZv8L%YyNU4}}nk$2(E3dslPd&MxMGu^R@o}~El zDR#t0lT)XlL7&GHQT8)r6IpMyo{))fzbhvXNly0G(RNU8_ z2LBga7N3sw@$Fnz_w!Pd%`_9^u#nJoklj=k;3#`ib39aOokQ>tp<^lHy=3rQuinVB zwT`=~)u*#G(4V-=T>-!UMu1u&Tx0j+)0EmDQ<@-$?EG|X&UJDv&`ds>pVl%}YAwpq zNOd|m6&_j&RKdQ)xIlL=3`fz6c9qylMnE}{Rc#b8fFOc>PR zj63C_#6N~N*dUEyDu$miCu?RJ_C0zLbiv!I!ZEPOfIvf6I(P0N_9SM#re@q(#tvRb z6uby=B$=6EKOpACW1iIxSq$)ajCKO65tqyFiB61ON%^lLBAA`$2p{3wA~q?e6r&*96go>mAIdO2 zOy7Ca$unr&W(E51(dp1$(3y*2&pL~#*(9;p$#z+Q6)#=AdNoR}Z~a&3H7q8}%>PqM zq=ooT$@ITpGF@ci{*Mu#)h`pVK=>QkGOMr4?;loS*uQ1A(@1KO-iy8RUGq|gzCMXR zh$_NGLlpJJqN?!_E z*az5gr!3HL%xqE4tXwnjf%VA8-Ru5g5tE;Wg@tKA8kxetqq?t^6;x;wTKf#ulGI*d zw+Gzy{YwWh(DRV-=Tw@DbPDx4g+6LLrC>@VOI}`HFXXbmakRkd4Z}^=iMqT9u0B#d zJ70#l7hAYDQC+5N+x)Gs6s%f31$F09&FL zEdcY27wKmj#S>swxTjf@c9hL}5Y8g7sR`&7KH^K+D&^!r7eqrfUmIi;SsT9S>tP*6 zuGYg`g^nD4_=#v_CTfU>m@921D)|2|M-b#$QO zed?}7g%(Ky?jmJVPZBf+iFA_ukTKXGvQUwApl?Yb-pb%MSn6Rb6iQv|xxFo2uwh|20FpN&SSSS5u6y_HkE2ln1G%vhPp zk4{Y_YG33L4a;g}vKO2O9;J(fof&B7+8swq$~4;v{XA4+Kt6l~DTb6Zs=yARACwH$ zX_%YTQeg|`sL*uc-75a#e97@RFyGfe)Yzhv%M9{W7yPaT(Bv!O8eTKA08CtX5|v*7 z9Gyh%llHdAdZDuPC*_9Bf3G7V8vD#azF)^^#{#UA4+JwL8%ROAb+K3K@zLgRs#{Jw z8iK+?r2%?AU(z`%h`pv#P=lL#YkV!yP?Ty zy$uc6;E|t~!EgZfx%-!juYJd6T80Q=qdi0M^K#2Uf# zhJ8R6vs2R`7MYLhh=7dA5Fe*8M8N%gn$azOy@{0yO%mVL?M4Mb>AnBTn-hQp9ARvKMroock(BLn zEV!7)&r8+CoQk$({f8GIhIRLI+$^y}=;Uts;s`1E0fIxgGf-gL$2vA}p>|#qed+B+ z$Eiw2p@bzRA2CPG+ARlufm_)AP6t{9N{KmBbZA}AQ8NcVOVM*pC7WTPEj=h6k)D?! zq8tl|6P`TeWC>>~O3jTbv=oqe!ixuW;ecqQ7*K$4w~U6~4A3D-IE$!1nI?_4tZek`YyGhqQz>|4$<$$CYuWSV?X3~W+m`9Z{|_p;YH0#I zuCsk6&T^g3d4x@v%O;cu#y{PX4`$w+-BdRBV%P=0CKZ(ck z%`DO=x$_gas&n%Tl>ioB`FvuNUPnfbJ_$VwkY426?B~q)CLP=y6gP2b#mV`G@#DYU zAIoyT6D8Z&R-@zn{L;i!a%kudGM?il!aah=9UZf3w?x)jvD%=aJBWulH|Y#PR&+nZ z*tit#=pZx}CaX8Yf*OEnF(67Ein{a-4E8Qel{g(u;#lAs>#aA>DpHA3tG?2do+EB@ zACJv4-NCU^G_f8Vy;kh*B-XA$H@BIMKoYnm*_yoBQsduNsQdq`KE>`1l-&HL<|XuC z5LBla4Cci-^CdOPnwo*wBAF0Go6m;)jEGWL>5ey`g0@MVyY2vOI?z}&yQk^+AFI!! zQVuGN@0*CHQ38ndbx-Fez>mUT@}Ak+ca-i6L;P>o@hvq`FV<+$*hD?0cXVNy`G_c~ zq@vK1k(SoRw_*}z7cpxw-9dNEKs8~ruqGF@-MUQ)|omX9`zf&?8wk& zn2t6_n_J5UK5W*W74o=k^w#R&iUBZV4|qrq4rk)>!~(xeQ~#tVO)%anYH@>NABR=l zuc7B(H9bx-=@17DeDzwbv0iwL<0GLm>`0&phWBvP?+_0?zbBu|*}=0N zL#8dm+j3y*B`zN^&NAHz;3?2)!|(Va>q&BCTcgP-P+uGYv3S+A(KSvB#-Ig)sOLX^i1_AT$DTJ23JJ=%QPZAKNV$?qtDg?*Bzpfcao54x*)rl zE|xR!VBpp?&ja>@AeNU@^rXm3k`7YI6R^4>pbP6Uji30O4tg26Lilo$;U+qQfu+SX z)d&Z6QIU8R9^{8z8RDS#d9@|90Ph$LEnw6Wi`Nh1U1&||PLrlJj$c=4e?;y2h(xC6 zt$oa9^&WAI82PUt?u)Rnodpf-tt-E5I0mW`DJI^c`@B-j*)3=%qrsdgY!g7T^>eN< ze1J;_a@B=+7TC5P-KSDFsShqAcg*DPJLde46fh1 zjcQ7W{$~##F5elF_(9NJzGZT%rm3rblkf8-LQ+bH&;FP8t~{LTwOy}DZAxl)Dw!Iz z2nkyB1EP|mZ7#XBpMJcm2pHvZs=eARYyE!j?|q-)e(vXfcBUMTKd;xM(R4lWRHCfb0<8lV7sJF{OUAGWN}-CKM*D$#wRv;f!uvu`cf@i*<3EX3dR&aw{S&rsmi=}gkZbt@bC4-SxAP_L%+B^$W5Ryr8gkV!C zO>`@co-Ie!3Ops%9r=YdYwgUv}aM3g6*J35HnF78%C z#i53v)ZgBjKCC719P}XxJg0<~*%H-R3wI<9k@x^Sc_U&r6{{Iib44m%N7S(i8P>wb z(_-DJ<4auV^gRF*NR^&=oM`pH0N-w~4~RSEUZMG_8{S6&aj9&`DNSAhL6UynpWH1=EzYhGKbZh}J8h2)p;B36W%| zAO%K5k=8LnXoqx#2a08mAhgGR2_^nMhzd9KUUoEl7#Cj;4auhWNCGWvjV+{46~=a< zT1Le5Jn&TC2z~I`y;|Cu45JtTGyFN?w;KfHB@qItWRj^^gyu^IWYphOQ6LSsb=CXt zAEXiXA(|Ht!KIV>6yomBC^eD%xDKW2*$)SSTl&Ko($|B?_errFka+}w#}ST@D@QNj zXFw6&YmSo8XO#4ae(k7Mi$vN>dYMVz8WAfYtU^948}fi0t#XW9L%eB0;2R|J^cMxF zEfN+wDS{XJ8e1sf7D=Q+6e((d$ty2cBY5eNBYI$l6GF$2nJ=Si4NsM4`lhCpJ&yM` zbcZk>ToH4+R=Rr2>R&FbO?1x{3rnQ7t$yY_amW9~dxjDPYd>#$;d<}{N{C5ZX+}ED4Y@cLX$9eRRcf0hUJfw@BD`q)H z4>%!wV}lcOabX#{5gAm>9@5+sE1zGmNmSGsO}2hW%kuyW+YbalJVWG}xoG7ua-=p8 z7Vd(j8lI-GeY+JlR}*r6Xm&4iIRQaP@PX6tGvXUJ?oc^CYRoF2`;S;G2gz3F50S*siBJ)ckPw^f_@=5bTiSN7Ex0R`90l?N)%4s%ESH1Ftn zq!_m!>$RKbJJT2eC{bIy&Ne-E>^?PODyZ&%QiIS!3$!T?;KB1|Dg*#u~tg>~x zj=ngd_CZ1Ihhu1orIbI`SNY`BJ)U)HnaHBwq39^qG>SBck%Tm7O32I{0F&hTEs~P0 z;8;q~boT7o@@3>&)Z~uq*RJ*DHZHM&vOoFdmhkz9*Kx&}ZBuVG9|;KSr?z}3uc>(y zD2Y2o(%yu+^F?}CXlNUDx*T92dloE)2n`_BIO~w6re;ncnpw>n>)7%YtcTKD%=2EL z^Y8m;V?zV;Q(v|2hEtL;1J8aZ@}P zlY*8wO)H+|SFT@QBO)q_1ox7|4cjGGuU=&`gz;ubg>1;?1FyC-+&qv4w(mS$#yg^f#QZYu`HOr!o9eRdX5r35YhSwP?p zEQ|{mYm`u&euk6b(ev_w%Kj5q6wIKE}G_oeAXNHCJ1Sn%{vAl^9r zW#mc0lgE$6WMvHz<0`xVu`}7MXqLoDp}cm&ov?w*+(z#qn|>fBWo^Ke-NVV#C5(F| zxuL$QYd1fh$nU9vbI?6=uP+3(KNaLThs`Wa z!@h~me_sjQfK1nOM!I!OQBXom>>l$p?iyPyl1kcvl#jhRuh$aJ8eu|3U>pD#Th-Lr zIfLp1iVz!~=dE|C$W056NuWFJ@DdSMuEb+sm=3zk5@RVEZ==G)lK{aS#+l*Y<{S=s zb2{?E!*F+<_Z=>QjqV=#^LKU0CR-2KhBj2^(!qXmK`y}bK3A0h0abL%>_qC+4zHMw zv^O2ndMFM?fhCrSdmMs>f&|kBE58a44qe#1tXud-3rX^L{Q(WVso40$>_t?)Ho#OOxsy|FnD}DEyuXY$I3LqUngIKHqFQ(dh|
    vh{fcUd)dsUn*;or9N4D+7Xdx2wxi>1G2thY|ZQ1`UEg!n6{IPiR^$ zr5IbIqcHC&3x_{JtZqE zo9EuQOGwd8BgF}C^mA^{zG-M^Xq@ldW?QCbyyDOMlc+_>5Tx$!v~o3kr9wNxw^e+6 zQvKj8r;n9(^TXLg5iU~73geLDn>o+9un-};0J~HRyP8D&4G2R^ zixyEhcPFepY9$p#VhG&%)cZymZb(&5Sw8AiZ; zd3zTid09B}GIzJQxHvzuk+T!L@A)a~1s8f`mUfiuwHUj)X7j97O@lU%6IzEDJO6Pd z7)t=D8Dj{9@XH=N4?^CZjt;Y%+fVER1FaQVqX^9p(JGuw{$k&Ccp_)3d{jL8^~jjq zcg@L{kPT+zXw=AXI~+RXQgM2r`NMz*jBD4nA=WH4Jd2~wE5g6$3?s;hneJnP<%(^d;8XKveG_Tpu=qjd{%`?h;-C^juVJ}+LD z3(H1l6{N?vjPRHkbNe_fCXyp6%_i`>*FUY{ zfi4b8Z{_PwZz%dQlETARqJ8y4j};>igS3L2$;0O98$o#-n?wTMH(c>)sr6k%5b)|6 z+u}cOe5I9)7#UV!6V3TW{HaEH(&R*SLQ1%*`JZ+R+mAhzN!2iGxwj~!@CO^AH3FMRsB*O4wNa0oCzGw$^^z;18T?BT z8j`<&cI$DT?CQ%xcdq=kz!mT6WI~!REuzF?T`g#Yv5@{f+blKpm0 zx;6~wTndqZ3yZj80Q0hqVVi&2>a$new>?38q@M@!VT>fmkeX-*R%DZ_lBrgHx`*;{ zi(ocgx9^irp4)59kW$x|ew=3L*`R zz(wEB&7HuLA402PGtpH(jL;t`=DukE+n@UiHyZ2w^2;xbBn-G?)B7ImaKHgSJN_Rh z<{wY{i{{IhFWIPk5W`XP+HDYEfDtNLnXxmJAfdB;KErR_6vJ=a$i)8JtfFEuG&IzC z&+hle*uvMfJ04xqc{aU?2e}Ud@Q=Q?&)Ecg)nXU}HD5d=-LZ|Lp}4r;th$JcQhpZC zH_9o-y!co$EXgJsI=M@+8=WV(DBi2}`{+&>l$;md_$kwWvG~azuSY?MPlU2-I)0O|7c@`nN-IjlF2#^Skd^o0YUFU5AAT?CcBL6c zNSM@S&NE#!-`dz5`Aj4gx1IS|4bve}x;4g%IfLQ*uTBM?U~Nr}0m5vk?WDlb+0^UK z3%a-Z-KPQ|{xE@9mK_&j@A#5^&1l7g2y)hVyBkY%2YTceLqb|Xd(5|gvKV6sYvuMh zI668*_lA)~IDqj_8l(#z+O{Lv61#pts85tKwVJ2BpvR3U`ef$Ape~;9iN!+zK(-I3 zI!2xzbL`kL95+}!ef`U5wN6Juc?asc&VVPLlyTh?sv7TUUY2&|%V_rU-*A?~@TlQNQ!iq;N!Mh@pwG>R6# z&CgrH_$y4oWSWrfQCsQ7luCoN+%q?B2!^iR-dQq_b=LmCfo*7KSTRr$aVa)4 z!4S2C=pLWGrCY2@jKPP9hLdoGKG?))w*@kdPkhUL+V6jw=&pV;e*BkeN>De4N0|dL zM4GWSHK~h9rUu4jS2lF!f@{w2*e*ffm`jo(HA&_VyC} zPpTrXS1h5-U*__dLRq$jw)0oxIY%x3q>}ch%eFQ8Q%DA~3;!E0i!z~_l?E$4oI{Lj z*cLG{1CT*-`Y< z^Bxx15*03!9Y}cczk{pG{DPwtSA9#-T@#F$By5)qU>0yeo8$el1e~EY286K{v{@JR zJ9yiyKxy+lZA5kRgi4)SL^14WVJlN^&jZNx`GH%j`+gc7W=NXVhk$XmK(1k1z&D>g z(XwP*s7R-u>Mi?;$aAcb^0dCw6*kX%MpB&EUF~^JMsPx1o&EkxlShy%X$;EzPQG=+ z1OmOpM6v> zhK02QY_M@=ft0Ha*+~B_Gij3pF!9T6_(ExgsTwsN8gbF-F-=U#o8}|+nimy<~gc3G%?iPqY zY`%2gfI zoA?IYah}k>5rC)#>+1;wYqOe~HHy2rDf%}vh;P~6j}3S6^5uP=o_WnJEmS!We71(2N^KXFa9kcG)h2da5! z%~3W1>1cct6BXTs6SB0{w;^yDJd;XvN;Jab*|X1i;oG;9Ch3M+2(+S%*|JNq z0&al#Bb8X~0)p5A?dGN4^yqvt#**2Y2cs@geTOp?xDMbHJ+z8v5Zyi`4I>>nJ3uKk z1fVqmrqT5F0;nBAd;Q6L?Xc14ohIn#GsICp=HW2` z*84C@<_4&Od|TA-(wntk_?0ej{xABGhCsw8+>_RwxMuqv3c^AT;AfU^>D_3GaK5Iq$$91T(Z z8)7tmRUd-xN*1!R5MaYFoPZN#W3r!Fwpw+lz@`?t35c#)u)16e^;%jHIDQ`;`|-XE zAZlxwuZKTS5xAqA0@rTmg%!PlGY`<)wgqk&DBLiJE*~u#OT30XQ9qgLUY9wBkqSo8 zUp+-U9d;c|#2~SAp_7*dl@bANmpyhzVwyve7&EgpR04)zrEuynFQ)~r7(y+{2&|nz z{9mYNAs^IW?-PlAW?9HsesRe!c;^n{dkS%qA%9DtQ`9+~t}o%dnv z-OJom@n@M9h1rdh%n|Qc5Ithso?zYc%r=N-=%u#ofBy~ff+M0HJ(?pzasP5&w5a5;)sc3*aE7(~c$SY)nmN;f(~(WW z$U~#rifL)fTN?}rSPn=z-+ROy=c%Ie2SU=r0E0`=AsPH*feMkEwe>APs1Ec%)NnEbk>Hh@(FZ04 zgoL)x2)*VbTBTQyY#|F$h_-qCKnrjw| znF&Z%ekFDSDkQOn(<+#ooWJkr{xE{}-C=6LLhfdegC|0zPSF+MqT=I9CCM7zf`rb? zqot^3)C_s*FpyNAEP%XJI6wLvUlTe`TyGx^Bz?Pjpi>xe+>F*D_XBNN7VQH$@SFTH zwn5Y(f*W7ygi-#}G#?{fJyaS})hA3Lga!AQ0S{VV+}{<-4~y9bTTPI4VnClbatyqA zlZH(VwEj%5TCIT0PuEx@1wFCNmA?*IPWcpPSrqCw7Yi`8cI{%*53LC{nL*{pzhI~{ zf7n5(5&bs;538ry`(snmk-F+IaN7DO&1mRE`61FGmk*B1;&dVKe=f}`y=~wH3G3MQywsc6DC;>xy#%80 z@w2!+kRyhtQ{7gMN*QiA*yIk$XQ@KIn#f8oKwsyD}63(dFI%C=B6*o zfpnI^jnvG^PnrXhe7wA-4Yks}Cvf(&CI9^J9`!nDF)>mTiinE~+*`M`K4x28%)P%*+y@!9MvbZGNcQ@Nh#r8XR@$C*Z6vN~N9w_t2aHG`TmZUA(7&Zqae8 zI%@3D>O&3=FEg+o4SZ+up!JfEpFTBLc;E*IBjx8CjK{e@cl|O!#pNH}m-5S9p|-(& zpFC?Ls-J3v>d7_ZZ%?5U0}B~-JINj`zN=}?xWLU%d{3ejv=`_UHG;1U@vm7^Qxm_^ zv84Ph;rR&K~O;Y?e=+aVt^?P$fQUWrX}ComM7O;@>4%?Un?>I8rN_T5Ht@n_182v|v` z6kQEQ(|(tmmobjfa-j4EI>lVJ$H_WeY?O!Wk%>0*=TT->ESTXEv}Vu{-xhWwq5&yP zB&_;2Y1}^2*cUcAhM_lU2&blwY=!NmF@Q$EE@X`)WMk(V>(4!60W2zb*@Y7yrlx%0 z3-5P*ufMh30?0nYQ%a7EM$bRmtLE}F*(nA|Xt+GRlPElqLJyRPV}z=oKWk|dbo!Jl<$4G+lN<+;F6$n}G9X#iD z02MGn0t+8bDlb`PIhBh?zqyxoGuh>*RN+u+txoK}<^N@W=sI<4#yGkHtx!L~kHSvr z&}e&60LsHji;q)Sj$+9Rmh%>YJSik0%~lfRd45yH6pU}Xz_o#- zvF#oDtFL-Wz1gF!jS>jPLbafMQ*@~7h|AGfw+!;2)c(R#C2FC!mv{2(vEkaw!tU6Fqoj?_H6u??Pi+^EVoP$| z#u0@Ufy2~y-m(TX*}?zHNG{(cF0d3o(N{IB@?>t{h}sRjFXk;F&K q_QG6M5!^oU+2cWe@c-J&^qGZ<+^()CM?M>o%cE)O@66V;J^k-d2)joB literal 37012 zcmeFa2UOMPwl7MGn#2}NthA^I3IeeJA}xt6h(MGkT}42t(u)+6Y!wR-7Xk_bD$<+O zMaKpR2#EBKz@qowxxa}y%& zH*9QdYvq1DdWMZ{g##Pg7Z<)-iGS1J`(zkjR$h=laTH(ipP3_>Zus)`m0vZi+1R*l z(*Hj5VvQKEvHid%cl2i!he!QQj`ufKWs3~!*;lMxyT9<;jht-!#B*2CtbgXtqU&Gj8U~URjN#%P+H* zf3bB}>k9hC+ufgu(AS@if9>!Y{bK*g7pv*(U#CCUrLWiSZW#WYesS^swaxVPhmils zM~qgBxQ^V}y=TuY27}=++Y@fGcdGmZPu@h09?wl4R|lJcdeM{e^7>Ov_FmpfG7^Ki zON(dItqhVXjmo5_PW6pV#JgpmE;yTEbJ^)GJ|b-}qt8Fo+(Xo=<889ANY3S{wD$S-Sb4K2^41aaSpi2}>Q9)wWm#R$7Bj7VUtd)yZ&Dp2cjU!7uEWW8wy7t5 zTFPt}v@-3?vPSYb_PNeaAHwIgKmK#wZMUVlmMU(0>)iO1U2JUU>YF3E)&NSA4 zZuJ*p!Roq>yX;zArjEPFRc}bfhdxgE+M!M$du}juBzI|QNwH?tI?gTeS)(UoG?MtN z(zRnWQv|r(=101#qSZA!U#%9oi^m#Y-qqineU;O7`eV;*mAYQj{SwcK`6c3!em2%eePUST3=k|g{ml3kHdqr6MgN2nL~;-LpgJUyZ6Q{#=g&SnVT-L zaP^K`DqEUY3Mtk2*r&JTD&DgF3hdY;@@`xB0r9Bb4bNc}}Vxn*>8)M32*g#PsK$MTR9UbTh+ zW^M0}toJa9&ld9)(bFAj@32aD=#31&(DC+Od8Yl)`0;x?Pk7#ac);kmuwV34Lh87k z>&q3JRnp5ZD4Rd4-Y~EZOInrp`3lXnE9Vm%%rkefpKi~6`t<3=+3_AxZvFA@^2>Fy zOEYCX?be;|!TheMIOJq=*Xi;ZZS6ZD%srPDrL zXHG9(->e%k`JhCV+1A#Utj*vpTr1xATVKMBwH&@NTFkh76HVp0+FJZ0BdJU#vozJA zScu7+t{s=(URh(tZ1Ux{&s~^|PCdoylflyNXjxjcPpnXstU8-3IheLnj=`&eva$ct z`^VdgZTqT)W`02j>?Px!8*}GbB5UiX(%L=cr=*9n z#-dE4hvqUO2jcdbeT_F1y5(i@rY_v`o$RS*$D#O4IId;gxNBj&LP^O_7GEAnU$qOIYs9kavC6a?XnX#8U3B6?VzKa@)goEXb-QwB zd!wT(pClI9KX#j8`ROk$OvT$)Hsc9@7?oqFXoaQss@1Xl^mGl@v3gJWAKbG}c7B-8 znT)akagoUei`=tVRvs)R>4{3Z zk~P~7?p~bllC3#Ah)#Cv$U2E<_3Xhu7Q7Q}cSQ0Z|NQ5Lh1m&F?mqF{83j%h(G*W^ z9W0IUo(lfONoH=<*|4X&U#wi?j;+kBADA#>rfUnMjXcfD%Bt^D)6u#dH>ouvI#(dO z$c}w;!bc)S9Q|q&3hG@YnVDz#`>8*w;u_p`zr# zePI!;)R>oZ;wLgqPHCa5U)uAzZt5YUU>Cb>rOTH;;^p=RrEI5PabA6jiGJxL3CsDB zf^gQ&bzGVz?~@aXWJ8;=6npnBP3100>ns+j=bRZDtL%93#rnI7frmr;Y)kqw&%eGQ zP;vB;W&YOkFogh{1zd#3(wN(#QihCiWdxPvkeHag)K0XR!p*L818J>)td4qQ{qm0$ zDM3?LTjq3Qbh8h8N{zmKaKK10MlV+e)dTgaW-dKdrRlgAHy1m5%XGf@1zg_c_lZ|N zzM6iy-t{lvt39E9ZS^McvGy+FcKKV4-e5^_u(Jmqw!J+!lq)MU*Pn#On}A2;FgL)A zZk)b6+EJ*g8(s2IvSmim8NJf--M)f1S&m~Lei#Y$)4eUMlktp2FWTYb_03PQ%m=f^ zO2-|YvHmU5uEJP!@ecT|#?oDj_$n*k75E|NLpp(3GkR3LTT7A7?NsyV4X zrnH23$sCrM>F}<_f^WyN^-M9TLE*czQBds-O37cov~IO5vQz5ysb8;?==kd_D#FpD z` zYQg%~$E#yByca7|fUpX&Afko*Q2D6e3eAPfE?oBBKd}&Lt}{`GE2?Ohnyl6LI9!^a ze|M`g%cv|xVb}1x17#{RUk^W$u#PfyL%H~1CX07vEIowB>+hRAklG+tr#s_+?C5^< z3{5vrY3J!-O*g})N4C*Y$BrE3_0zG_@UTTK8H>_x!F^WFYDb&!SY(YH&u|G3v^(i5 zq@||cB&ZbqK29g|BKB8`Oig{I(d`>WHPSm6%Xeq854Byv)sAYWv6se7*G!G>)d9W+ z@tno3psVH{WgqEIG~-<6CJX&VO~m#bFmFstJ{2tE66NB-;FT*XF7~D#EtCnYV==1D zQE#pur>zm{Qu$1xVJJVo4m;b}lz+31&1p?@FX_pM)OVsa+R6q3zoR9pYsHP;KgfR1 zd9uz(HI=C*8Lu6F<5c-?YHGg87A-PO_Vvk^Ra0vwa?DHZ{CFoUql2Y~fz9 zVnvE?w1Rwt~$#s7Ri-DYv05ktk=RH?3|dRsu&2c&@;L;U$&&Ob!}$C z>5$`jzpvun!p?3|6Q^+Ei1|7$NxQq~)~WR-mM=bArJ|9GjeVg;$3AxQ5PzV}nT&Zr z#!9DBth0OoMV#6Mvv|ZqefeJ zUly*8*W=l&=WLlFV^*JRY>}~rJpr#jul41h6%*=uE-6KmG09`!;9r?h&C%gGcMg0@PVX7>qOUfEwsqyRvjfUH$Bu2GZ}SPs%FYxj`8yAS#T-Igefs$E4~K1g zzdylgdGzp!&WO_?ZIR(Y#;LNcbK^bVQNhk|txynG)iN*f7qtZF4(;m-c3b3oSp`_| zK=-E0WL!A{vr(^G?2V2O8=7dcYY>`jaa+M_lAvVd_d zKgjW`I_d?x&i16N{J>#SXtxTF*8j^a)6)ViQeD(6iLHFCsCkCLd->8Cjq~Tv+YB{l zpPX*wECqqEaRgjTaGn`eC^D5AO&*;OTTAuTVXQ!WN}7hjVAE;;Yll+C_Nn8Z8U96|1d# z*XLi6abaC^y$ZL+3>B?9F_+nKn;A4)%fN!$)6UKH-=uhOHW5z$7!&X67M3kHcHTK&~(qhJn+aJa8~0b?BAmRC>QYBV>djv12~II z@AO|87{0543*6hpSlOPv);YtbX9EhY!ijn5`Qg{)v0BVSoe%Wes38*APC)+x?CFu~ zBF;~$_02&=J4*sKqaxk{GuUZZ;=fTOciw6q%*6Q0LI&tztBcr)CR)fKI<~$IM5$=G zoFIVxRX_bDot(DYg1xpOsYS9OOTd_Ywn3e^Q_0FqQ%b(Go1W2E*H=etFBMgM zsj_a3iSmq#y2OLVv)0UpZ%SsGdjanQ4Fp<#wbV~CEIH{X*s><(N$P#OpkkKT!y8Y< zQ03IYHo~iaMk!N{-9soPBum=htoaJW3$`^c+9MO z)okH5*MJS`#6Q7oah2pd_294OJlDM28!ge_3!Wak^Yq!XXN6sTA426ht>5kI8O!MO zH;MW(3phV^|L91U?2@BLK|NY`qfLdvKBw_+%@f-;Z`@clGdA)~iLFjRrg`Q-s#bPs zrsV?-z^`_dl^j>G5XI}5+hu0ELst4&+@2h0sL3?7&JIga5c%zV`>+}MQaSdKyF0f=o>Yrg~zrlk166xUXsQ<4vCY%1Gsa0c{_P#&IB~JkY}r6F0e?B2L!ndrE`> zK%g3~lNx?8U03F+X2wRgckHNl_=-rg z!S2q~^w(kFH%@`p?R|QV3+-OAihg|@zcG(TRG%4&4U_RB8KcKaxs#*$O#KWlHb8Ov z>55z|v4SD|)}h{rkZl_Wk6#R@_kQqxu6FH?jhi;*Gjk?lABdW$Wi2hvjm)(y$#}{x zPAe?d>H>mu0=kU=k7nof?mze9+Aut#vAM@{pKvko_3=kN5hmkH<0Chmp?qSS)j{CH<7uqj%yomjDp(+ zy(im4&IUw<_KE@aIQhhKzB6Su*{%KNo+*>1RW^ORgDN=qc4E!C|$G7A+qO-Jp6!uRO`01 zpx>Bgxetwb9GcO>5NSDwr}R>cRedCr<3Ve6yJDS{pLKG-oCx7r*sZgOioB5koX@#P z(Bl!7h+BHSiyjE1%?wyX%z8=zF1k=SG#d` zYA9G3ZDDL}y}ikAGvR}xj@SYfERTkv#X0C(7F5Z7aS>#n3pY$E~tzv7j;YarO{77_7+3W6td2XYxxw<}6J&g$3qoRdxV zEhL#_$N(IE(rtq0JNQLCWptjO`#EDi*1{#a)Vc(_<7-i~2fi^4EueIVi$P&__Kg0u z{YbA%zkAeY^9(VlUHr*{YB9h1^;su9 z`Qwj24xy7&O!QQQ*Q6^kct=Ps)B%~!)$Nj5OZpj!oF68jWU6f4uHm@Y;-MO(o;sQm zQ3@QfsXgDr#Q7LU#I8Ou&=gI#4Y}Y>eA$MXLpfJ%dOqyZaclj3Rc~V#Ua4)podwj1 zm4PBA!dOR|Ow_Q9BF+yStMq*=woK#AzB$3;qS80AY46#;JZnYv?!8L{`H5=WX@v>} z)54+Hq8bYj2V33Tefs&&^o${Zo$qPKinHjkQxA?LV66GaH9w&u6tAF_?BDU7ib&}P z*7Pk^&IDepnKK{t=}O9m1{T$LFXwQLo|{Y7{Ah8{EFRg}__2d;s3RKl3^gz?|vHY?*N;SIe?M|E1KYAjh!NmUJBd)iNxdhtep&G4r>`m7gzuU*v zdY68!3IWuM%bD%9AtfSSbdA5bh3+HZx62LEAOG>)Hk+InN5K8|xXi&QJ1y`tWkrcy zghSccfhi(CY}&EIX=;$`1h?bG4A;>@{sQO`QPQMJTtH#ynN9Bs(i)m_QV>u|g3c6m zs^GWt@~##GP){r?PoD_w1MkuF5MO(>d-)DU>cV7y-3X-21Foo*;d8n`9|=U=dL-1s0U4^AUvvT3$Jplnx$f}p zz?}1Si3a;1Lp_kRH+S-z+a>S&hReQ@outg%g#n8Mpv%y?Qh!lFp_&bvQRW*9q$Vnr z+lhtk)y+C2l<6?iwnfI-q0y>X=<*DQdD@fH6Fg}0{ZNP5M`pe%U0j$e0G+N#53)|z zUZ(9;s_J>*Mm{S|bEoq}qE4mXi$CtkxfLbRl^O=%04awME88MMJfrq+7-!}#n0^2K z_oj(%tl*q7NSnZh%R=|IHGa_1qvLb7t>SUMa(KP5rKROvZt09dTZ@KNGtz2wmS8S$ zf-$N7(j+vKy>Vpb*ZObP%g$d}!!31)R(I-aG7QYINd-c}A)Xfr?DXE5nq$}8I1neZ zEO_PZdVXC3z5&BMVk-CbdReJLmQ?_!5y_DcNsd%aEeVp&{JG2By@R7=`gkJ1?xw5F zR9(d-y1>QGbh)+{c*UzPK%Rdvk8ar9F|q`{r|6~HAR1i?C|WT}K8I$qd0t+g+)>_D zTsFU10WwzhrO_KOiMi?$)CVlY@Z^%L&h+2}(OeceYhuOFCA6Hfz%1kI_xr@p5xCX# zQcrgU#fwd7Y)rQ{k+#U2@N&P{Uz;$I!AP@rc=tOEFgHk6VPbnt42 zq@>R0BOZ@PK63Kd#4T#9LVGjCR|31WomexmPg3vss*<*2`EAy|^7H(Z+mgLU12BC% zEqtiTVi7qUeUPb91SBm{<*GF%X@Sl|Ad4CG9&om8cI?U{>CogMz*bCYc?Bua^t1x* z3N)Q%nm5s=Q8i~&sZg_SbRH{7fB;=}))0I7nDZhh2(5}yI#l+2Y6|ULHPzLn0hvuz z;X;IWBdQf2JmFh{n&?gDjRa5;1J})W{rYt|06GTgN9ogTcf2L6I}grq!n-OAhQf0Z zXrU0GCgA@4`@C>DQFvLRuaho2x-InSd1FoOYRa&czkT~Q1J8#) z9hH+oJ?~_?kDxjqR+$ya*(4pIAYI+B#UvHC5Y_Ynd3Jk*g%wGs+652EAQ8>LFxE}j zPd*4A)lsReqyQA)1N6y#sHMYM3G zZ&t7N&Yr9nT)wkocQ%Q3*PmV<$>$ z3Vi3APeT3%aIhLkso}fHY4s~zJV`8D4_!Go3jDj{p{$#0wpUV0%9v0#VarPOpBc%+ zP3PF&W`U#G2>0WPj>*Z%3D$gtUgLhnTNGc|uD$yo+Mf}Bz!0d8`((AQHTv?O>ZdMW z)4#W5>yzzPJbpFGDuxYE9d|rhKuE{~;Hj@V)?^^+{g>c!r_WB$Oc~*EHupBz`fl8~ z@fZN+S*3TBrKl$|KDZUKUr`&;W;{IOUP{(Di z2)-FC-OH5{;PCt4V?M813V#mjib8we$0x;3_0k_8K_>#lg59!=YwFYhG$6m+TFW7J z6kdvn`c1xw`JnNw0cQ9vkK^C*eEMee1^*;6(Ibdj+tA$}@D%UqKk7LD-#nrJh-v-L z`G|7+!RCL-0{o}Bseks3q+A~O<}a=?sj*Y@;BrxxbCBbCm~eXyW7z36nKpfyRoOta z9yUq-K#Ey|e>PD>Fo6@{ih)n{a$QfWs8rUgQikCNrLPul_iM~sWHmpKur|y>{Ux?T zX85uh3f<}W<;$0S65*98oeB^WGS8l-g0QVf#uEv< z#4kAQ8!eYj2+;F(VyBS4t-W11&M?WV7tWm@C71U?eD>sRId8r^G{Xz;9_)h+clGGe zHv}EJE5g05FxP=BLb=(DE;l4rmx}T{T@~-T@qpnwcPJ*u(VfKHR?yyh%kgIj5oXYpb$yMn*no(2UNcWZtk)Pg zAmG69ksL@?w${zhO0r@VrNM9PQ=LS=yaP`+ZTFBTfj}`y7T_yK58lh1B=90f*iN=6#+&aOB3C!uhOZn2HzicoUmh;Yz{W z)PHLLkcj+@)tom`pE>S?w$k&fLt=Pa%HHLEQ&W`kBtamTzajZ@`vI}`ai5tdknVM= z)eQr3_RFfcD)kB`Dd|1r!Ec1*xEQc%vYvdI<&j(_Gxr8U)|r7+{A%xxr}>-B-u|^+ zb+PuY`)-6Z2=&3wY9mLEz%mS(cH%u?x5nYeYb^`7^g)SkUthghOsk2ohQg~R_g}+J z)4-CWoFj-+P^##`euIFHhof5@TXw$_pkV zn~q|KxTjlp<)bWJz+Mg}>pRaE|79B}jF_tYbX;tSO^4`|ne&agPTgA>!NsDb> zDJ5bJ2Thuczu_c)Pyl)~pujzZRr1KO^C78Y4xJB;@Qs7qy%i5f*6WYMxr|F|yS=SU z=j_?DtbA(?6~~izXDLkM)76N*Nk*&PKz(Q2wt&-=K$!YayoScZvf8^9>Yb}x3>M!ne{n7U^iL7fcVnaDW72rk^}ll9xQsG2f_%)0 z0#7cI(a6@Kx@ps2yN|&eDSA{$L?nK4bYS;sx_+SP|ePj1Ng zLZ<72lUx7AvkczTnwr}nCd7{<1qkVZDQ0Nv>JENd`F}4De9`-Ru?WcM_w@=2x@{7_ ze~oz$;u$OxD7Ni{*t@t5gteg;ZJC-YJ8! zz+VbCs`=$Mz<$>|dUVZ}AAi^(vs4{x-BpTr5p_2CQaN7%s+QtjLt#_L~a`Y%CO6^)1*PN|V4p+2YXILrC3&Zqak%clpP)%vcYtFo_ zX8(Bg>J{zHojaEQ-r?(nPW5{$BQ23?IZBmVFE^)N;!J00AP2;pU%P5`vYl*~MQZUD z=L4xAOSGDf9;I4b$REtf&Q1{<+RaDOlMw0;MJLBjFYNcX?!GAWq$+sMM*z!=eywHhJ?aHD5ev3i?2*#j?WTg|?Z7 z+?qakV8A1j7uPAW>Z|`m#r~2L<51pP$j9p|w^f7Ie6ESBFVv zvnI7Rz@H0HVmddzdk#Uq8#v^svrNkZ_Muk#@q^bE-bMI z(~9nw*NzX1eL&uB>$0tY3JM_gy|mM~I~l-tZ+*vqd}(o^9nAa=x3m-4TTkIis7^{x zxBjU=KRq(y6Yso>j8W_w3Xv4(*f*)}YV??vx(}P!bROK+3#zI#NT2>qE<5+7+4!Z~ ztA*2k2=siS5Fl1^hUrg46YM{38myZW-m_8i`rI6myjAudcgG((9_N=D+s*0(*m$sJ`|TC;c9x>MUqHrzYQ7r`4HqwLU3*6>UU|S^HiGKR{A8@E8U+zU8iGNDGclomaJsthuPqzNqyyTygmj18D`TuJ8{D1y&dQ6gO zPVElW%4{Htjg9>@a(|S#g%g^Q5)Bk@%J;eMwooK%h#j$5tXQ3mY_+{5fs*2iNC0+| zu`tvkYloI`sQ>xvHgvE%6MZ#Iy9w;SjCTv7g{%C-djN zudmvkt0;|cP$t`|wJbac;e4@P>e~ZGrFSV%i6pr`Lh0qew8mwqDnoA&jBZP*(Y-U+ zlv#jgy}5wX`V{pvAl95T{0XwPZLfk{EQg2Xh0}SFf{lLwH4(IPC;Xb_WXsW`1O!Hq zFBWgF`hv}WIh;iP7_=qhy<A!uBqa75P{tnIGECX4yV?eURM~O%a>^z6pF+%XSZMH9-l8&kpoz%>M7pyaKU}{pg zmx3{vfGby*RQTmcpDzR{KfeOvc=SLZ)Botg$yPgxAUXxMVn3Q+C*PEU$Xlcwh7BXO zB62PPvUYi9l(o;G=sq6Tk-J=yVif&`_?iHg=YUqwj@*+w7@{=gQxqn_Hcj-=;SqT> zTJF1lXMFO&S2*b#!DN&^edf#tc6LN$Zv|N7NDvMN^!B9j2r}YO-0kQaQRL4swt);2 z3JnqND2HL0}BwDSk`3*GO2@P(?jtg(x*-6e0^|A->&Vezpyv`8jh_Y*;wFL3O zFXsh?^P#2ZlW&cb&EJX?Sl|14tP?$5;IX;8(7^}0w|M!}GZb-D901!7( z57EHFdHgf01pHoEuii zA;{F?bs%HG$BtG`dlynTY39bkwy_sB;HB*BBOl~NjvXZ>GYjq-y*$0y4}M}2rO0<~ zAw3|edVuW21Aq#edM;sxmrgpOA937mHG4`~O&~FS(82_)SPH|o2iiAB+6IF(sm(b6 z=>ahV7kRjsg=@OIch|)0d59mwwYXe>6i}kZMB1k^BYO`fR5S+M+rNPkMfiP_q}wJG z0E&Y`$6i)ofiOe$+EBjgl`ij(0i+^D078hzmA$V8mMU#t-&pH7ww26N@rZd+BsMR^ z{C7~;VWO9w^5I`|Fw=^#k$thCE+F9ga1V)xsXJyRCm%%2j2)_)k;j}J7E^tJ;PFzm zHHD~6w#c5Ml;!KIPI=!6t2ArBmsb*b!i#$!7SJ{(X%ko$6&Je7{=lUjcXXUlbK^>k z1GjMz0rsutk=&|=O@l??fyJ$M^@x1pleDz7BA!^R;092?+RNdA#`90@^;>4EnWJs# zeS%|u=InO^u04`7>7yn1X*qk{F00L$Eebmoy`$Ca8I1HdNTqO7RuLx1F@V^Rt5bvJ zP-A{&JgfdTC2X@b$SzU0`8hF_`Dxw~^%WLbK%r`j&8xiHd}NA{`$cYKH{ ztZ`EHTDG^I7OrCfmW8|g-iW}x+g3~y9)l2f_!c@al2vP!UZ}ZKC8*dC^t9>X9Jr2F z-y*(K!^Qgw3|@*99y|Kx+Gk(vXdBzJ5rl^`S}pcATof}abezsNi3Y{~DducHrIH;s z0w|pSaupBxm_6-OZt35`dB1BDgekTkmcX@1yPY!}PU-{jf^MdlKv zr$^wc7a)JiNjVX1tHNEPr3>rX*g96_R+&6QSVj=7D~p;CNvAGZxX!qY-l#O_zU>sJ z!P}J~N+;R>{D`I@R08TN4`f`NeDrOKvC zU>A`k*JNt@1zTb?VqxWw2dd*R^!I%0)|U;x5)Wy_v{C}T-HFquPh)}aTpW{KIsh`V zWnpg0i--wwW9;OaU|FlxP2pjCj@BVdO(JkrW-wZV0gJUy=cak{APRP!l zCayyHBGs)k0mpCyaDr;;t1hYPWY`dKK8pyriTZUuVuVyK|6vzsyKC33a*|2GbkHxE zcD9$E{R?M28l#gbrWU7NS0ws$&wtmw{++PFL`}W~>Jd_UZ{X+^L8fV4A`vc%|CTtX zVF4q~^+@H)YI`V|1<2pFBOZG)TpvOaW%}}<=pjf9>G5)j07<57v2PTrQ?G;^_qdIf zE=jit-qdh$4w4NQ4Ut{i**;pyrSD$#Z733Y&q`V{Or0omd_@thHl zX|JVeFKpOL1IC{|{ihe1TLZ0%_E;9}2|wtNORq$ZKk$2sDX*?16@%@qfc5{%zx!(UkIp$#++7ZyV~dTtEkj1rS*VBXn&%6c5F=9(SZfmspr>?DsZ7#uVs~=3XN`GXPp5-n0IosnT zQ8BSj^uBlh`1-q1beixdPqq&^)nty^yG_~8Gl(IiqgZQ0ILiM*G84s&{nHBgfAz>fON@DeHQiW=Nq#@UjepCi@{A zV+eHr5?Wk^VJ1*g=WW5bx1gAbfCDs~MSls}o==%`=K;rsi5jig7OAp9wC_jp&MZN? zE`U7mu&^+@u2yim%ciEL6Jx07%Q<~*VIze5%{u!P7)Y52;~MxMUHJt`_(ZN2yluN1 z&>1^hmKIu=Y0bb>_l6LUmCX48Z}|3}ZHMbH-}->sJ@g3HY2*RZVHgU4Kknz(;d27caGG{juFQ zI@iZUMMo>EvJR9#jfz{$%^gh3-xREy-VT4~d~{8qn3<+ptfmjRLr$!IkB`rh_?R_L z1_tGVg0DNX6YQS3i}mxR620pjh}_XUq^}EX3Bk>}4(I710ZArbeS|TU4jN0qGE2?#_jh|DwiGJp zb8@Sg=~?c8=9G3XC>=kch#S|{F{K!exP*T!ta!%%J<8_>Lg_&c=`>0 zeSa4g&aaGhvgPpjl~V;8T?A>_F*=|Q8;j;(qVOPU1T@tB(hw_t1`#m78MmJ8h3Ch0 z&5B~knA;VsKivJ8H(=1oB?)mUL!`1bVBl;L(S3v`wSDzwVdvuZtUjF~r-Brk7>bOG zD}@`F2&P7fD!EZOCcEms-;qnNE-WrC?lmj)%w^`%&0m0^Dk>|-J!Mj!jM)N0ver#Q zMVhO>{JW~EYADpHQvH{r!37s9bZ*8aUD1Lvc@Xb3a11&JAw%6@r2{bv3q* zV{}wqZDn?%m8n_0Gruy|*A9{zC-me@avJQ$R%80I6mtVXur*UOnczQL@w$8a`Xr@F zC)1KrqoM@DA6cCYQwk0u!wj%YPFYzQiuAoRk@t6c9%>U}%EEl6w3S`jJTd@f$j~-h z1|CbrE)LTc9-16FQckgB)~hV131jPB8_$lZe_w+-V3poj#~K!^s;o?&53vOYjZ0V& zj=R9G8hWqUV^*ck4cmRv5pVY2-o`;aeP*R#fW0c;(Nn#3&rMC#b76zUf0=T>1vBVukVF+(I zXT5@ntJ-U5VRN3`Uw+Q^VsdBez(tbZGuunnt2E4?Hzu2&K{>V}1S}6=5s(QQdS=hs zwQD7FYI&jHon*kq7vvB(f7f4^&AzZ@%s7YNOlvOdx-6~F3!dqh2D8Q zghzov^QEAG@{uY<_fBx9D|^x+9lPh{%u9*X%rZ3x%=iap4rU0_e&<(N$@bF;=kOfw z5=<~-Jm#v*LXT272)PFG5qSG!$T;r7tgKscRw|ZT4-7b3(rz<;ZiN~~fj<8J{xN40 zcF<=JBITfh6^Z7lprA0+EofcR5QpCbDYSUFKCNy~_#*}g*4~MU2}dCQF<3ZK=-C!a z3OKvMZ{L;H7i3X`os^(S1>hdLz*tI9bWat7X|3KcY?nx85WPX7#cJ)S2_?`Hw4{F? zg3wr|s;=V$PGtnANvIvyn*Q+y$7r$M;(jH>7D}bY-Zk1am`PxbHmfOARaMnNUrW4L z$RL_a&LyI$8NRF&T(&BV4kfo)Wro7~4w$Ej{dh}tP^Tm_*PzF|Ktnf$=0mxZ(F8A- zy|@SkWGb!E{yXszMTi--7&lF!x}_s+Fp4qcAHlK;AqjXBPo*@n)f@H`9SC332xxF+ zb#-cbpPiPDb%`iFUB*R_npoee>S{yCy>bjVY02-3m&sDU_F!w%ihlI0^wAUpMm4C0B#I6w5$ary5l%yu33azWu!U zUw}DEY@p8aZv1U~lw>CDuyY0VX_orjNMp?Riahy+rFqv!$8l8V1* z<@%OHjGtC$;iw7WjP9pWASAK*U4VMTT?p3EpoMp9Io+)`<0m12ItC8Zh3E1bI|;3B&=dar(-$)YR0b1?VYalprMD zW{4AYsMvvt`9oQgMkd_CJ^(hC!G~vZ4{1mQ$X!`US~PgJGQ3{L9>j>4QXEDn>}2<4 z_a_#QVl27SFL&O6ViU%72t6FY+?y0Kh#E|D9m4WnZu9MQamqT`J;{neQW8{pi2~gb z&WI>ktclg~Lo!eno#5e*=YJuj3o~EXZE4Ca7}2x+7^f&hm}C^VU3|HbA3S)lLvLw9 zZw!-MVx-W*016n0aHZaUD>@SVi#SK~>e*@SU!3-S*?W z4DufhOc&>8D8NqRte`>rpfg&elynq&E9>dCjE;dd(y0aWNCUkEgsnf{#8py^(IaJH zzlOWAcri3Yq3I!wC=iV%9e^G>Um?4oY;0_7MbpwbIWmZxm7)9h+&>wr)EnUHE&A$h{H`k`F8l`)L}dtP~?^Q=LeO&WmV4Gsv<8lIiDIli6G~Xo50- zu4@kY#wFj6=1Bx;XwrhL(!k#~vNb3l`!cJ9;&+_3m8a7&+MI}aLqp_MwqjyqlaS{9 zc-M(&2^;}K@N5rF1mmm+Us{p`$}q(2M+03#bC)k&y7aYu?x;_Ehd$5TSz{BEB&-n% z3m4%f(9jD_sz4@?V^Cl>GCp1jU}>Ye_C44-&oVL&g9jG@SB&8p9}B;lG{8gOD^pR? zaYayQgRvv&+@BdFE(+cOGa*6y7U<8KOe>?ZAPr356Q8DWnW`L6zLs5b0V`c0J{rD% z{Bt^;?}TWd?>UFIH@6&tl}96$Tm&fK3F71n%wq&*j8g<$8MGM5LAjYCe(>N$c#mAd z@sW|2ze^tSJQ>QEdeSPk^kZK7-qg-9byZc?_J=D{XM&H^)E2c$scq^?tQ{}XY3Qwr zwnjk7Vq%s?cyQXwK{sK+Yq}a5kBToeY|T!5`gt>)IV2rt6y>|?aam9pLh<6sWu$3z z+<2%#9T|6IPvR^Yi;csI!7|bS0;L#q34*L0Ymf!3D1pV1gfd0LjgB~tiB=Gw92ph7 z0l(Bx&_<|%!lg6iUat4SEiYzf<#)C_kKECF2ZR0n{u~4_I|5qf4GDa9!4IT?C1sE` z%n^|AfRT3kH(J#qe#HR1hG37QK~q`bRr??dFos-)u9|h~;iL{V#zokWLKT_-Rh{iT zOAeHGBmhpX0Yrrg^8pZvr9e97;B^h+y~#8it+iyR@?(XLiYHDqN=lMHC)wSdaeM^z zuVns@jlcX0skB$XMVc;8HuRPGi^|8x{NQB30wsCv>%>acj&F&1D)Tu_5^KI{G9DRu7Dcrf zYB+O(m3&&*Z)^y2TyhM!+UX^u5Ey7<5wg_G_dn7~^VwAy;FhQK_4SL#*91s{yw;m_ zmu$Wdl_d4y;WmGhxI!ey7xHlM)w#`-Ffh|}V-@*GMr>fSdv-hH&nXBHmk(5P>WZz( z4lr5VHqpsEVSz&dXj+WHOT%0Njwaru2FYoLaX3K#@aBcs-ani=^YYJCMhGNoEojz{ z(Wwe@AD9*`>v+~o8PW`Eu?jovrjr;X_U5IeF+<_}V1VsGuR$EeR_8omqF0O{!e8*- zI(G8R{7MEk4V?*{pV6wraWYo0nQYUtR0Og^lmrESwzah_)_(iFI(<#iw_ger&H(Mi zUNmh?E3Z*p9Wx`v7vPj;VwwQSV_67b#SK_2c3PxfUchi*pU=jhpo0WVovf+7&`_^C zqgZNrY(TF(uPTspOPI^gP9UfRqdOw7Gk z8w&X!@!+Q=Viq|e%sSX^q|)IGjV{#RBItw%koV^;{A?BHUu5Q4IEIhnH~i^zp4TiI zdJ4#lv==8Ysfd-RRJuA&DOg6Rg%3v`vNpx<>dzq23b|Gzyu8Ifw9lcx3bp)5wXP@p zd+$%|{)zfv{W_=+oL63arZw?b3NP`=@uF`YtE=58xypieH(vC)$>P*oUnhexg@+a= z@C*i;%raxe){BRqdYGs>*N?uzxQLp|6_*tI(f|xUU_ta|B}9g%Fqc4^4{{G-no(6V z00*MdPZ}506wBy8hYV@qcF9boJ5MGBmrzGWT$St>x7mtd(givZxM&Jv+XgPcMbA-P z+wxe>;zYcKWmA29y*6e@C7%eer7~~(|7m}agMaXBp zSLP;DiJb%PVOxi+G>O?fdrP!8A3*JU})8+M_)lPiv(DF=0fJMg< zGUn03EbIeuNZJorkB&%6FibP9XUxP^krt-01jn%i(4xgKYo@x7n!84IbHY`~YJaYm zIV3lVk5AE9v{;(7Ktr8*dqU=eaTdA`&qDVJZ_{sXhC{U=NySSlv8kpe2=RbtadE;3 zhM3#WV8LWm%>lig>)P#eG97u;G2jzsQ~c6895sgIOd%L$)7Mp>J(vE`i|B}Jk|)wxHLjY z+D*&S;?x)&8328wn2v^cbmi68fjT?bhJHF$@-j1b z0W?eW=70@Ei~?=d=-eO+mp-l7YFVT@aNtKl2c|?UL|xIrI~IoA+=6f_jhOY0Kzvt6 zoaD71vleRYLl8Hu!0`?7AO=c9#&N1ktbxGI5-wmBIWdKu_jn;!U5#cw_Q1QdaBk-y z&|;3ERvNb%s#{7a}R*+i`Ai_@#3-bbR zTjonzIy$_SmZx_S_z`Q+263LjvwlF>38!fmBbt7n@Uzh)%j22K!a!FJ!Evo%*<@%dhSP< zR|rFM7aAKize7_Nqz)mNM$v%|g2_n`b2^Y}d56|K_WOG0a{;u6pk29yLe2^+75*bo zABZ*`rd8GkNKj&q=ZmtEEAr2ZFM-Lt+f?c-^^my7Y_xpZj(H zr4#&fb%N#W!vAqra8yRp^1@(CH3e#ThzJq6LWnOKAWc{bQt%gIe+Mv)-q%0c&HKr< zuFaDMZ=Jzuvwz{>*z~GtBn174Ceeu{`!BxzOEJo`l()61kUom$CDJi`XN?najHr3R z7sH7g!8H0#hd|(9t04MzIH|@FvO0i{H(<;@BBUUU4NXI6;K6ic3;ixqjQ%v_LW0Ht za1uI-tjUb@73j@f5E}GxLZ;ux*EhRh9+#o2TG454U{VeP!3X6)Gs4Rp8QL-@A(qe3iNUa7YI!QD@ zwCf^z4r3PkRhQ~7ic?~flja)eHLS@*ihkVDM$tshPUpk9Vr-XvF*Ao%UD9fJb0B(a0V zdy=qDiV@B2Bb3I%Ni@dDOQt#Z$mkkUNY|c}o!=U$bSE0v(v#HaajW3&B)k`#3%50F0M+NZcu8 z!>$qfI7m?}=YD-2d9**A?HxcT@N5+~*QTL1LLUI!k}PSO>5s4>yF(ZDeXQnG-e$db zq!Uq8Kr(f=-JZ{z6+fU;P$Rzl^^rL&4C)ItHAWyoZ*gv)H>}d+y@;!gS>cp0BgiBs*!k6j*_c1-zkApI2&9_kOR=hx2XGgbrb^AVJJUJH;e5z zLjdDD9{+c&R+^pa_O=c==<3DvZBtErTUmD1%51R;f9xa5kA6&OD zZ#dN~Qr)~~-2n4U3QM(?9U?=rn0*HM>T(PmWs&-i%o5rgypA{>RnucV4n$E7S1jR| z8M!4^a7mY$kdR=2^R!9zAj<%U+tr)Wn&L!a%`BfEXoHtFU4x4>HikSy3Ku;fth8w1 zblY>0VjYiDut>}*X6bO^by5G&@sV_pEX2zFU>GA&X|~Qu9OgO0^c%Sb8pb8L=FVo3 zQmpbZSQZzNo;Ab4tQU?kI)I|>1Ja!X*5U%m_%1G^6-;wjyoETIrQ%F+r~i=-9N)>z zEaQcAREV^9?Z;8xOqcf!&Wd8|S$l#YO8Cn1XU+}Tl>3|vB_j+s_qtCcGpBRxfoX5Z zvNyZzz5=d*qVC1xt<6#&1gvUE9)MO7ojdr8-SPPEhwU!;dm>!;DGR`0&KAkrPE-f` zBCtZ+2jJI46hv@}G8pjEV)MyF<+YI5_zSqU)AFjHZ@NB=nIKY3F>p|IC+JE2dy{^U9IOD`wA%!x&-7EP*u!-gtb|0`7u> zGp3@TluQ+Mbt5=zGuQ&XpDpX>l5#K$UBOvd#L2Y6noX5(Nux=@3o)H-PIHNj ziaLoZTg+PuCQEIM(ZRF$k!KVvEHpB553({eO_+lj|J1870R8-OqwpD}NPa1Pv>imI zFdj#}(9!!nNMwNgtsi(_Lq_0p$-|gX8HM4>QqP@LrSR-BiziPNDNsX*XA+=ml9@*j z-`cb7o5BB(-%2tbH3GUeY7lC3lF;cZ@P?$oz+&?e$r*CSi7urix*}NoT!HIv-j>?) znI%0o(`>LRsI#VHf7V2p4z>!V{f7+JFr+o)#IEO}HkOj$jsZI~MgckkjtmfO1ha%H zWU?e;q)~uKwK-6FXeXVT2T_jBjAK2$BV0sd83Y0(7bd9kycmqBtekIhnO@2nzAn;1 zoFC%5eeavbzX^_g{fOPMPjZeGRFb;7(BXA-S`=2J+`R5)oxiu*UcHVv}6MOT2xbZ6updScJ-c()GRh{G7lvK0X};lqBeBcS#q zq|*UHa+HKA-Mf5bM(sC2?kODfBNfJQD1<0Y&(N_AV#Tr}x0E{YMy^m!0RJ&v{n?Ot zHx$D{%p(NClIg$z_*)EfC~Ij2taonxf&?ckI+ILAz}D^|{goG+zH+cv#=|T@3kyKZ zjF}|A?DsbF{T-(LKMuV9CrVTP7d!j^3Oiff|F2@AT&^*g=|c)kcxi-ZDdDx(vi)ny z^_c~=BBZI1a=o0{Zvjw*5JmAWKkW~O8p_HQcG8<@&kdKV+S`5BuZgf7{`+^nf;ts- z9!jI3ayYikHT#jpN&%$)4|ZEWk*srmiSR3yt1)fy{QP{iVghi~sqn4(p7q)ZW$L`h zL?Di)-r=$GkfB9K(^D*u8Wo9Cz$HBxe~dN@a$B64hbC77ku^xvq?&#%z&koJ41+eI zu#6i94nd$nFmo(`ngPL9I?WT%u@hWsX!uYGC0dDQfs@F?^uDoXEB!DGNgxN4lx7G$ z)=joGEHX)~ar~hn!aoo9=^t+fLSV@vp{g~hiVjSME~XB20`x^;rs0f#AmbCGl8hWld!dHMPxQrUYz^SeOK+21&8E^UEc=h1y7BlwJ6?rlx+i&xU~0AK}LWg|fPE zPHh(^JBwi!_|gHEO_5)dganF`TSa4xiC}3IY@!$qSj~i|*BHjy=v+1pWE+cXiHhJv zR{A3}R*$=H8SHa{sB8r)YzU|#q)&P$P6@hCFCq4in$C0^y?^DtLO(rVx_J55bZzsL zTto70hzsu3OpY)x1v8`*9Kd`mSfE@c%;R)}wcD7DR`NFy{Uw`^R8*Xa)~Xm`T$9r9 zWfmR(Ov)vYQkPcCtXeZ<*Kid9127fJ$>Mm12Ezcz(jAC8m0?cu9>h!|j5-3G6e06B ziV+V(xSQnQj(R`}<>Eq~`pK@w1^j3ThL=mfeq?OyGAE{^M{$3}WW6FqOrl}QBu&7` z%$9qRvRs0*1|DK~jYUTPa<1XE?EDc*7?Ai}-}&!Dx$r~YBHr`?yr>Z}^FWRlR^nF7 z@K8VFw0gU}4haboG4Y$?OXEsQ_i60DFLGHOM0m3qW2IV1R$<+P)bY`Q?sivHGgF)R zTC*WmGI()9ysalrt@9lLi0H)BX&J5!$0HnU2|bKBHT}pVp>{&JbcQ>)D6|NPq3J{9 zrIQ_tpE=S655Z*X5FT173`bHTy`)BeMKCau6O`60m4~uuz+Vt^dFAl)AjTe+IrCB0 z+8Z0}FrYq}npS zdEL@aKMg4$^NGDUflW9y0X>qteM^?sP(JfJ!HjH6C@pBTD5afNC(^!7TBZ_CWummIRJ_+e z=e+0n_CC-1>HYBfz)Yr@|NMWy-@RP-bzgS`LO4Q6x^@)!M?W?Rp*G)U=L>oYf&UcD zIQ&ra8OvUBreEe?%B1!vlg=MjRBChA4-@7jjn6rYumD6ji7%^^z0^|+q+Mx`38&C+ zxgZ_OB9tX?ZBV&W%FgFu^VQl1WZ`}}xEzV7n9-KKUtKk9xXD*Xl&)JDSH0}LydhWr zJc3q zC`S{x){_yG@lRm_5~vITZ{83!!RennFF&fC3CMc-GrdSI>_$rQPo*DGTdFTzVp|dK zka=~XfIi#4rR!F%6u8bFk+C$#K>L-swotHvmU!A~9o_4jIaC@m5=0}^wmQc@Tw|@H zZOtvb(ss+LC7Jb|?>5c$`M*3&qe@o(sTmvQ(#P|)D6W_5`E;p>NB17l)K`OOgH`($ zF}VkmR#sW$&5W*x+z-je+Ewp#9iLtS<#ipA}?KwC(DN1keL`OdX3xVD9KoZB>s-994UiqUU7Z=%| zJZqJxO z@+~yOm8FY>P}6OI(TL#;jHl*uE$Nn)czVl#9;~*>GI#HHR4ZTl+iynd6|e8l0puJR z2@&)7@M>u~Q-RJ47}4md|9tFBI-eqavT98ZI9RVvtSD>b2;1gX%~d(!Go_zW<{+_=}Sr9-bE83a#@$tyuYb^unRumRWBr+TNX zT996A(+q(!K`Qt-v>Th0#LC1WfRcTxeq+(>Xti2L+n_rP(P3J)L%U?wmp@Qn%0B*j z89gDP!YNNgN$K4Rqw3u^Tu0v9(WK6F%lm;NY@=}F%NK_^Oh*f7I*gA! zOit8Zx0GB*=40HVDBXuYEkl!DicrCuZ@^to26FL2+o);WO|y=y1;m#$}YHV+jqu% zOoym$dvxt%j2wc1?_zJ^7L(BYi$*Vas)~UGN6C9-f_%KU9e3EN^C+V5KtB-llMc$lYuHA#bd~<1xM=e z*JiZa)W}6b9j^NC%U5p6WLX zvgrf#hfdO;u6q|LtkqXOd^ki!RaJ1r&(RHCcfPO*FpD4OCQwzB(%Z#z1y6V>zbjpoHgo8&mfQX^gl=16+}b&Y@g zy2gVB;iox-=5F>h6neQ3`xwybHDX&r*FuNuiYfxaM<8Qrc0q>Hf9bzmYm&r*bTWWn zEogDI;?7?@{`ZwpOhc1j{;I8zNH2qaP3Xio6b=6Whr~kv|9$wi-T$}up~{9QXw@ew ziKY*gi%&vq_iJr#lg}BOm^wRWLUfHxg&LQxtE=nzQ+8xYpuk#r0*;fRr3N3-C zr}1HC2=RY7np}hjL>Nt`q7D^x{P^*O@>})U?CBHcFAU3HzqUmm{esw4!WVKRWeEB4 zj*@^9vXF#?4q(^i!y($Mic=$U>{@7D7R5g2RI6H+C9xsY3yfXZ^E(6*o4_|Fo6l~k zo0ML8R905Dj{;WHp{LY%zI@lT@F}0oD^EXv{v1EW$s>L$<2xm8FX(&V+C0#Odz7)` zS4RAAJxsc(tVJSSI0DHzB95Ta%HDGfJCLLt+O$zRqmc!DogKU8T#!LzK1t@?j)x_wdudmW@QZF7T^O0?+^F zhs&0ZvytLoR8&324y^@01J?n(~#6B66=x4to}BWF*@E`KN5JX=d1n0hjVGh zSqBhjwL*Pp$CWajSiOa!yBh3!ff(a<3nNH40xPMDBnR_w_Sk|5X4jN(O-XZAM!0f% z#PsyEhL%<u3rK4 z&2LWmFJO2g_`B82(g*fDflNjdADh|k5F8rXf*LCsZ-``DNKURm_n+I`{bMyZH)boV z!wbG%;Sm@mj5mkt3y+IS2mj6vS!RlPL9T;zv>oOFK-)(cI`Fh{3=}o&@FD4MZ?Q^4 zjr|ds1<*$u7kM&|St|_=8KDO0`hDECx3ABz3NPFfXdx2d2oW48)7}KN{&Riveu`S@ z^7wL7=pvJawrqJ&p?Ib20aBeqG*rt9G+5Pf9~ZqWeb>s?%A%};tQ2u(JBjT94g$?}YS@aZOVlmDD2XC3no|}}(zK`N72nrP#GHb(*;!xC4SN~( zq!nz@0~vVM776n*x zo1IWb=$R&ZjXC%hy{klIPsAVymql|pkGZwDr4>qbMkL@?60#q3{MN;ROhbQ&j{qCF zihbm@<1A;{hC-5^RGB!rGBNDNp-&(LFNd$W^YWJxd1azW1vm`ZjZ)yZc zhEUjy0$`L#ls!7uy}TSyNlI$OR~9r+)zjy%zfDC+WUf0>=?(jZz>@T(PbK0%EG#no zVPa$R7{;;07P9l1%t3Ed@}xY6kBvRhRL*!(XHV~PG9nHfjs>p44r|;|=#|yVuD0MM zxxt>^%wk~2q(nQtprUnT)b9faA0!&=r0NfvLTv>n=j+6KQ7{n#1gT(Tj{UQn^2^T$ z!xpiuc!IE5=^$DhqJc*5BuFOT^;<}}Z1A=U{eY+Od3~y@1COoylrxH&Sylb~P(D|p zVaPo-(O1LHE(NHm7!_mGA1R)>`M$N2WS8C0piSfkx+AZLfQ<-I?U=b~?`Hlsr!Of> z^vz%-S;zC`?B9wK2>=Xl3rag~Xd&PpdUzm(%f1(7XA1H}q-<-L>6rUTM&cT|m%Vf# zrOZUg+-#S*SnJ7MT9xe7K54d1aG#WJ93Md{1WZLT>shV?Kzy`4J@X0q%zsSfUu)hA zhaDap`xJV_LPA1RoFl+Ahzmnu`ZKjmb~#Jb&{*qz@Va_DQzlJk56*rE-n4;Bq!Rvc3btxDDY)wVoA z#>^dpf@-kSLLQdAj*HlK2Uy(hWz|O`1yQG=k3{&2WQ}eHiL{c9x__U3+555Qq?ZEP z_VnuBCbVP&TrvB~s*ahKUzT@719v>($NoF~~5%pOG+v@q8MG zgE$d4HYx}sNyc7IMsLgjGcO%SPo)3PKs(`vpHKJKzJ@LM_2-z*nx4NN{u^PGh6dV`ETtKW97xkF}at*?=jVQ~aE`t+18fVDTLNu8?WhYA%76fi@aU_=<$JZ?CD z_J|U`gTEon`q1?fwnFfmeV*w|dOe~Un<;s;;S0=!@yj0f?@H9#)b1c1_YIiY=Ci4D zd-U-Yj~c=?;evNjo1ks4Jum{CFoHQ~Xlp)ErMn|0Rw=G^`k=6H^L|#ROhGHm@L15?3VFrOeZ-3Kd4=j@83RMK7 zO?M?uFi>bwJ8&Qcw-=GNp}V{Lv#)eAuE-D_bK0nDtmWlR2K5ht-9B)whQF^Y2(H8E z)6(^SZ4e8K*oTiEwd9?#qzXpb=4Z>RLeKe75wn$>KLDQ2q{QDZ*@e~i?2&PFE;wZ; zWv-X1BlX0`kE1R`%rK~`s{@g*K+0`EpTHgC{Jt4Kb6mb`88X+i#v~SEBK8I^telJK zxtT(Ra4~p=J)LLavH23fDr4b*IPZ-yLG+0%;|UOb0_CIEIRc>ij)LW*@p0GQ{{G*W z9-fn^LxGZl_+VnF%M=VV!vhC`GPANKKm#(xppp;(fqD+diXjqDIo+U)p7|yMWh9VI z1YU54_t38zk1Jibex;H15H>=|yv)$~^TU@eLWMls^_kPtyi)D&C8I0AJk0pw?vw0s zP!Xa-HoSpTQ=Tv=hgmEZz5AB!VysjXus1Rl!>1T<3uO3BV5CG!hha>F(btQ^1<#IEJ&N44>V zR(?4VO2vGI>T69dl2}P#ihkY-=nh`%8Ci&8_Jvh^e0J)R0EoX%+=Udpg?ll`hf-cCTgIqy%|0k*CdDm77pRy z-X#kmoyE!6owv)fxO4U=q%tNmpPP4_fsrAzz_(5gCsx&SzUzE*k9=T4o+KyMCSp9G zm$ym)=rL|*E1HBJVDs&uPz><2KQq&(FEfsdD*QXL7G2) z{{1*AtF#0Z;vi<5()JPh#EK#)^c5 z_`}75!VDZy_NIv`W{8o=32h(Y*<^p>`}!z6MrFl7lHjNrJNTRlcpGGO8nH7i0c689 zOheiaG@fC@?=;R#(Cq_pyk{SwMt1)E^^gz-Iz|Pl5Z)5ci_DW(wIz~qV!#NhtadopaNU`~k3ReXXy%WCwJbx{4xt(cmlbbN#w?h99c+9&g^dwanf!w!lcl z=RU}!k})SVHE(!bndaQnsr@+jN9;fMB;_*V+N1O38jR%CNIB}Y#Insn8nOH5%mQ-c zPSd{0bF=T8n$~s?6kAk@hg8LCt|CykR(i|!Z~57|j+@Jc2K{Dp4$Y*3CC+=w!tE;v zX-US2+({(uot}z!;s7(i3W;EdhgmN#(q_l*#rKdv=|vMkCAJYQ0eLN^B^Z2cVt0-K z*gh4`ldk56$@fW zRIgZl15m;-u?m>asm>vU9(Tw@LC1kRT>yAIjthp;UMwhVhsiTI%#s9;;yT$DhjE|8 zjXm$*zXy~Ok)V6AmB2wnMGs?{cjqm3#$n#ZARYEVC>RmY)f6jb-pP=7H>ciY=$vL>dI@{w4od|(iBi# z5taJ>7+d;E=Cv0RZ9((d-4)f-&-Qkdjz+w2gS(Q|>~O4`S0B5FJQ(SVLdubSDt5)zG{C7_<^s643daN8@*`kw#`_X7~CnXy6*Kz{(GIm0&b~CfQ6cjXo7LhAtTf~xlO8$lZKc-J*-En~92BSp+dSr)a38?cWAscOR zzyCoB@dLqi5~QM6G#{Tp$6;5eIXgR#qp9`YiS66B6K1HR1`!O~_W1}#Ujz~odrHLY zy_R4^6NeufPx&Zz;bay>whR%a0710QYPZf~u0^#LWj%Ugq6nf+%#D`1SnvU1Nmg^6T&6#s#ulSFZh^nj=!kc)RxKgT`=KiND H$1eOA?@EN$