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     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
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/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.

API method:

GET /api/packages?search=hello&page=1&limit=20

where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned in response headers.

If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-bevimed 7.0
Propagated dependencies: r-rcpp@1.1.0 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BeviMed
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Evaluation of Variant Involvement in Mendelian Disease
Description:

This package provides a fast integrative genetic association test for rare diseases based on a model for disease status given allele counts at rare variant sites. Probability of association, mode of inheritance and probability of pathogenicity for individual variants are all inferred in a Bayesian framework - A Fast Association Test for Identifying Pathogenic Variants Involved in Rare Diseases', Greene et al 2017 <doi:10.1016/j.ajhg.2017.05.015>.

r-bayeslife 5.3-1
Propagated dependencies: r-wpp2019@1.1-1 r-hett@0.3-3 r-data-table@1.17.8 r-coda@0.19-4.1 r-car@3.1-3 r-bayestfr@7.4-4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://bayespop.csss.washington.edu
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Bayesian Projection of Life Expectancy
Description:

Making probabilistic projections of life expectancy for all countries of the world, using a Bayesian hierarchical model <doi:10.1007/s13524-012-0193-x>. Subnational projections are also supported.

r-bayesics 2.1.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-survival@3.8-3 r-rlang@1.1.6 r-patchwork@1.3.2 r-mvtnorm@1.3-3 r-matrix@1.7-4 r-janitor@2.2.1 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-future@1.68.0 r-extradistr@1.10.0 r-dplyr@1.1.4 r-dfba@0.1.0 r-cluster@2.1.8.1 r-bms@0.3.5
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/dksewell/bayesics
Licenses: GPL 3+
Build system: r
Synopsis: Bayesian Analyses for One- and Two-Sample Inference and Regression Methods
Description:

Perform fundamental analyses using Bayesian parametric and non-parametric inference (regression, anova, 1 and 2 sample inference, non-parametric tests, etc.). (Practically) no Markov chain Monte Carlo (MCMC) is used; all exact finite sample inference is completed via closed form solutions or else through posterior sampling automated to ensure precision in interval estimate bounds. Diagnostic plots for model assessment, and key inferential quantities (point and interval estimates, probability of direction, region of practical equivalence, and Bayes factors) and model visualizations are provided. Bayes factors are computed either by the Savage Dickey ratio given in Dickey (1971) <doi:10.1214/aoms/1177693507> or by Chib's method as given in xxx. Interpretations are from Kass and Raftery (1995) <doi:10.1080/01621459.1995.10476572>. ROPE bounds are based on discussions in Kruschke (2018) <doi:10.1177/2515245918771304>. Methods for determining the number of posterior samples required are described in Doss et al. (2014) <doi:10.1214/14-EJS957>. Bayesian model averaging is done in part by Feldkircher and Zeugner (2015) <doi:10.18637/jss.v068.i04>. Methods for contingency table analysis is described in Gunel et al. (1974) <doi:10.1093/biomet/61.3.545>. Variational Bayes (VB) methods are described in Salimans and Knowles (2013) <doi:10.1214/13-BA858>. Mediation analysis uses the framework described in Imai et al. (2010) <doi:10.1037/a0020761>. The loss-likelihood bootstrap used in the non-parametric regression modeling is described in Lyddon et al. (2019) <doi:10.1093/biomet/asz006>. Non-parametric survival methods are described in Qing et al. (2023) <doi:10.1002/pst.2256>. Methods used for the Bayesian Wilcoxon signed-rank analysis is given in Chechile (2018) <doi:10.1080/03610926.2017.1388402> and for the Bayesian Wilcoxon rank sum analysis in Chechile (2020) <doi:10.1080/03610926.2018.1549247>. Correlation analysis methods are carried out by Barch and Chechile (2023) <doi:10.32614/CRAN.package.DFBA>, and described in Lindley and Phillips (1976) <doi:10.1080/00031305.1976.10479154> and Chechile and Barch (2021) <doi:10.1016/j.jmp.2021.102638>. See also Chechile (2020, ISBN: 9780262044585).

r-bidistances 0.1.3
Dependencies: pandoc@2.19.2
Propagated dependencies: r-vegan@2.7-2 r-rcppparallel@5.1.11-1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-paralleldist@0.2.7 r-ggplot2@4.0.1 r-e1071@1.7-16 r-diptest@0.77-2 r-datavisualizations@1.4.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BIDistances
Licenses: GPL 3
Build system: r
Synopsis: Bioinformatic Distances
Description:

This package provides a selection of distances measures for bioinformatics data. Other important distance measures for bioinformatics data are selected from the R package parallelDist'. A special distance measure for the Gene Ontology is available.

r-bprinstrattte 0.0.7
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-furrr@0.3.1 r-dplyr@1.1.4 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/Boehringer-Ingelheim/BPrinStratTTE
Licenses: GPL 3+
Build system: r
Synopsis: Causal Effects in Principal Strata Defined by Antidrug Antibodies
Description:

Bayesian models to estimate causal effects of biological treatments on time-to-event endpoints in clinical trials with principal strata defined by the occurrence of antidrug antibodies. The methodology is based on Frangakis and Rubin (2002) <doi:10.1111/j.0006-341x.2002.00021.x> and Imbens and Rubin (1997) <doi:10.1214/aos/1034276631>, and here adapted to a specific time-to-event setting.

r-bergm 5.0.7
Propagated dependencies: r-statnet-common@4.12.0 r-rglpk@0.6-5.1 r-network@1.19.0 r-mvtnorm@1.3-3 r-mcmcpack@1.7-1 r-matrixcalc@1.0-6 r-matrix@1.7-4 r-ergm@4.12.0 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://acaimo.github.io/Bergm/
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Exponential Random Graph Models
Description:

Bayesian analysis for exponential random graph models using advanced computational algorithms. More information can be found at: <https://acaimo.github.io/Bergm/>.

r-bentcablear 0.3.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bentcableAR
Licenses: GPL 3+
Build system: r
Synopsis: Bent-Cable Regression for Independent Data or Autoregressive Time Series
Description:

Included are two main interfaces, bentcable.ar() and bentcable.dev.plot(), for fitting and diagnosing bent-cable regressions for autoregressive time-series data (Chiu and Lockhart 2010, <doi:10.1002/cjs.10070>) or independent data (time series or otherwise - Chiu, Lockhart and Routledge 2006, <doi:10.1198/016214505000001177>). Some components in the package can also be used as stand-alone functions. The bent cable (linear-quadratic-linear) generalizes the broken stick (linear-linear), which is also handled by this package. Version 0.2 corrected a glitch in the computation of confidence intervals for the CTP. References that were updated from Versions 0.2.1 and 0.2.2 appear in Version 0.2.3 and up. Version 0.3.0 improved robustness of the error-message producing mechanism. Version 0.3.1 improves the NAMESPACE file of the package. It is the author's intention to distribute any future updates via GitHub.

r-betategarch 3.4
Propagated dependencies: r-zoo@1.8-14
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://www.sucarrat.net/
Licenses: GPL 2
Build system: r
Synopsis: Simulation, Estimation and Forecasting of Beta-Skew-t-EGARCH Models
Description:

Simulation, estimation and forecasting of first-order Beta-Skew-t-EGARCH models with leverage (one-component, two-component, skewed versions).

r-bayespiecehazselect 1.1.0
Propagated dependencies: r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BayesPieceHazSelect
Licenses: GPL 2
Build system: r
Synopsis: Variable Selection in a Hierarchical Bayesian Model for a Hazard Function
Description:

Fits a piecewise exponential hazard to survival data using a Hierarchical Bayesian model with an Intrinsic Conditional Autoregressive formulation for the spatial dependency in the hazard rates for each piece. This function uses Metropolis- Hastings-Green MCMC to allow the number of split points to vary and also uses Stochastic Search Variable Selection to determine what covariates drive the risk of the event. This function outputs trace plots depicting the number of split points in the hazard and the number of variables included in the hazard. The function saves all posterior quantities to the desired path.

r-brinton 0.2.7
Dependencies: pandoc@2.19.2
Propagated dependencies: r-tibble@3.3.0 r-sm@2.2-6.0 r-scales@1.4.0 r-rmarkdown@2.30 r-rcolorbrewer@1.1-3 r-patchwork@1.3.2 r-pander@0.6.6 r-lubridate@1.9.4 r-gridextra@2.3 r-glue@1.8.0 r-ggplot2@4.0.1 r-ggally@2.4.0 r-forcats@1.0.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://sciencegraph.github.io/brinton/
Licenses: GPL 3
Build system: r
Synopsis: Graphical EDA Tool
Description:

An automated graphical exploratory data analysis (EDA) tool that introduces: a.) wideplot graphics for exploring the structure of a dataset through a grid of variables and graphic types. b.) longplot graphics, which present the entire catalog of available graphics for representing a particular variable using a grid of graphic types and variations on these types. c.) plotup function, which presents a particular graphic for a specific variable of a dataset. The plotup() function also makes it possible to obtain the code used to generate the graphic, meaning that the user can adjust its properties as needed. d.) matrixplot graphics that is a grid of a particular graphic showing bivariate relationships between all pairs of variables of a certain(s) type(s) in a multivariate data set.

r-bootur 1.0.4
Propagated dependencies: r-urca@1.3-4 r-rcppthread@2.2.0 r-rcppparallel@5.1.11-1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-parallelly@1.45.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/smeekes/bootUR
Licenses: GPL 2+
Build system: r
Synopsis: Bootstrap Unit Root Tests
Description:

Set of functions to perform various bootstrap unit root tests for both individual time series (including augmented Dickey-Fuller test and union tests), multiple time series and panel data; see Smeekes and Wilms (2023) <doi:10.18637/jss.v106.i12>, Palm, Smeekes and Urbain (2008) <doi:10.1111/j.1467-9892.2007.00565.x>, Palm, Smeekes and Urbain (2011) <doi:10.1016/j.jeconom.2010.11.010>, Moon and Perron (2012) <doi:10.1016/j.jeconom.2012.01.008>, Smeekes and Taylor (2012) <doi:10.1017/S0266466611000387> and Smeekes (2015) <doi:10.1111/jtsa.12110> for key references.

r-boussinesq 1.0.6
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/ecor/boussinesq
Licenses: GPL 3+
Build system: r
Synopsis: Analytic Solutions for (Ground-Water) Boussinesq Equation
Description:

This package provides a collection of R functions were implemented from published and available analytic solutions for the One-Dimensional Boussinesq Equation (ground-water). In particular, the function "beq.lin()" is the analytic solution of the linearized form of Boussinesq Equation between two different head-based boundary (Dirichlet) conditions; "beq.song" is the non-linear power-series analytic solution of the motion of a wetting front over a dry bedrock (Song at al, 2007, see complete reference on function documentation). Bugs/comments/questions/collaboration of any kind are warmly welcomed.

r-bild 1.2-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bild
Licenses: GPL 2+
Build system: r
Synopsis: Package for BInary Longitudinal Data
Description:

This package performs logistic regression for binary longitudinal data, allowing for serial dependence among observations from a given individual and a random intercept term. Estimation is via maximization of the exact likelihood of a suitably defined model. Missing values and unbalanced data are allowed, with some restrictions. M. Helena Goncalves et al.(2007) <DOI: 10.18637/jss.v046.i09>.

r-borrowr 0.2.0
Propagated dependencies: r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-bart@2.9.10
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=borrowr
Licenses: GPL 3+
Build system: r
Synopsis: Estimate Causal Effects with Borrowing Between Data Sources
Description:

Estimate population average treatment effects from a primary data source with borrowing from supplemental sources. Causal estimation is done with either a Bayesian linear model or with Bayesian additive regression trees (BART) to adjust for confounding. Borrowing is done with multisource exchangeability models (MEMs). For information on BART, see Chipman, George, & McCulloch (2010) <doi:10.1214/09-AOAS285>. For information on MEMs, see Kaizer, Koopmeiners, & Hobbs (2018) <doi:10.1093/biostatistics/kxx031>.

r-bupar 1.0.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-stringi@1.8.7 r-shiny@1.11.1 r-rlang@1.1.6 r-purrr@1.2.0 r-pillar@1.11.1 r-miniui@0.1.2 r-magrittr@2.0.4 r-lubridate@1.9.4 r-lifecycle@1.0.4 r-glue@1.8.0 r-ggplot2@4.0.1 r-forcats@1.0.1 r-eventdatar@0.3.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://bupar.net/
Licenses: Expat
Build system: r
Synopsis: Business Process Analysis in R
Description:

Comprehensive Business Process Analysis toolkit. Creates S3-class for event log objects, and related handler functions. Imports related packages for filtering event data, computation of descriptive statistics, handling of Petri Net objects and visualization of process maps. See also packages edeaR','processmapR', eventdataR and processmonitR'.

r-breathtestcore 0.8.10
Dependencies: pandoc@2.19.2
Propagated dependencies: r-xml2@1.5.0 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-signal@1.8-1 r-readxl@1.4.5 r-readr@2.1.6 r-purrr@1.2.0 r-nlme@3.1-168 r-multcomp@1.4-29 r-mass@7.3-65 r-ggplot2@4.0.1 r-ggfittext@0.10.2 r-dplyr@1.1.4 r-broom@1.0.10 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/dmenne/breathtestcore
Licenses: GPL 3
Build system: r
Synopsis: Core Functions to Read and Fit 13c Time Series from Breath Tests
Description:

Reads several formats of 13C data (IRIS/Wagner, BreathID) and CSV. Creates artificial sample data for testing. Fits Maes/Ghoos, Bluck-Coward self-correcting formula using nls', nlme'. Methods to fit breath test curves with Bayesian Stan methods are refactored to package breathteststan'. For a Shiny GUI, see package dmenne/breathtestshiny on github.

r-bdribs 1.0.4.1
Propagated dependencies: r-rjags@4-17
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bdribs
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data
Description:

This package implements Bayesian inference to detect signal from blinded clinical trial when total number of adverse events of special concerns and total risk exposures from all patients are available in the study. For more details see the article by Mukhopadhyay et. al. (2018) titled Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data', in Pharmaceutical Statistics (to appear).

r-bumblebee 0.1.0
Propagated dependencies: r-rmarkdown@2.30 r-magrittr@2.0.4 r-hmisc@5.2-4 r-gtools@3.9.5 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://magosil86.github.io/bumblebee/
Licenses: Expat
Build system: r
Synopsis: Quantify Disease Transmission Within and Between Population Groups
Description:

This package provides a simple tool to quantify the amount of transmission of an infectious disease of interest occurring within and between population groups. bumblebee uses counts of observed directed transmission pairs, identified phylogenetically from deep-sequence data or from epidemiological contacts, to quantify transmission flows within and between population groups accounting for sampling heterogeneity. Population groups might include: geographical areas (e.g. communities, regions), demographic groups (e.g. age, gender) or arms of a randomized clinical trial. See the bumblebee website for statistical theory, documentation and examples <https://magosil86.github.io/bumblebee/>.

r-bvls 1.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bvls
Licenses: GPL 2+
Build system: r
Synopsis: The Stark-Parker algorithm for bounded-variable least squares
Description:

An R interface to the Stark-Parker implementation of an algorithm for bounded-variable least squares.

r-bioregion 1.3.0
Propagated dependencies: r-tidyr@1.3.1 r-sf@1.0-23 r-segmented@2.1-4 r-rmarkdown@2.30 r-rlang@1.1.6 r-rdpack@2.6.4 r-rcpp@1.1.0 r-rcartocolor@2.1.2 r-phangorn@2.12.1 r-matrix@1.7-4 r-mathjaxr@1.8-0 r-igraph@2.2.1 r-httr@1.4.7 r-ggplot2@4.0.1 r-fastkmedoids@1.4 r-fastcluster@1.3.0 r-dynamictreecut@1.63-1 r-dbscan@1.2.3 r-data-table@1.17.8 r-cluster@2.1.8.1 r-bipartite@2.23 r-ape@5.8-1 r-apcluster@1.4.14
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/bioRgeo/bioregion
Licenses: GPL 3
Build system: r
Synopsis: Comparison of Bioregionalization Methods
Description:

The main purpose of this package is to propose a transparent methodological framework to compare bioregionalization methods based on hierarchical and non-hierarchical clustering algorithms (Kreft & Jetz (2010) <doi:10.1111/j.1365-2699.2010.02375.x>) and network algorithms (Lenormand et al. (2019) <doi:10.1002/ece3.4718> and Leroy et al. (2019) <doi:10.1111/jbi.13674>).

r-bertopic 0.1.0
Propagated dependencies: r-tibble@3.3.0 r-rlang@1.1.6 r-reticulate@1.44.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/Feng-Ji-Lab/BERTopic
Licenses: Expat
Build system: r
Synopsis: Topic Modeling with 'BERTopic'
Description:

Interface to the Python package BERTopic <https://maartengr.github.io/BERTopic/index.html> for transformer-based topic modeling. Provides R wrappers to fit BERTopic models, transform new documents, update and reduce topics, extract topic- and document-level information, and generate interactive visualizations. Python backends and dependencies are managed via the reticulate package.

r-biolink 0.1.8
Propagated dependencies: r-xml2@1.5.0 r-rmysql@0.11.1 r-rentrez@1.2.4 r-memoise@2.0.1 r-glue@1.8.0 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=biolink
Licenses: Expat
Build system: r
Synopsis: Create Hyperlinks to Biological Databases and Resources
Description:

Generate urls and hyperlinks to commonly used biological databases and resources based on standard identifiers. This is primarily useful when writing dynamic reports that reference things like gene symbols in text or tables, allowing you to, for example, convert gene identifiers to hyperlinks pointing to their entry in the NCBI Gene database. Currently supports NCBI Gene, PubMed', Gene Ontology, KEGG', CRAN and Bioconductor.

r-biglasso 1.6.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-ncvreg@3.16.0 r-matrix@1.7-4 r-bigmemory@4.6.4 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://pbreheny.github.io/biglasso/
Licenses: GPL 3
Build system: r
Synopsis: Extending Lasso Model Fitting to Big Data
Description:

Extend lasso and elastic-net model fitting for large data sets that cannot be loaded into memory. Designed to be more memory- and computation-efficient than existing lasso-fitting packages like glmnet and ncvreg', thus allowing the user to analyze big data with limited RAM <doi:10.32614/RJ-2021-001>.

r-biovenn 1.1.3
Propagated dependencies: r-svglite@2.2.2 r-plotrix@3.8-13 r-biomart@2.66.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BioVenn
Licenses: GPL 3
Build system: r
Synopsis: Create Area-Proportional Venn Diagrams from Biological Lists
Description:

This package creates an area-proportional Venn diagram of 2 or 3 circles. BioVenn is the only R package that can automatically generate an accurate area-proportional Venn diagram by having only lists of (biological) identifiers as input. Also offers the option to map Entrez and/or Affymetrix IDs to Ensembl IDs. In SVG mode, text and numbers can be dragged and dropped. Based on the BioVenn web interface available at <https://www.biovenn.nl>. Hulsen (2021) <doi:10.3233/DS-210032>.

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