793016,793022d
727604c
Package: libskarnet2.15
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726315a

Package: libsimint-dev
Description-md5: bc4491b36ad3f09aae4aa9459b1338d0
Description-en: Two-electron integral library (development)
 Simint is a vectorized implementation of the Obara-Saika (OS) method of
 calculating electron repulsion integrals. Speedup is gained by vectorizing the
 primitive loop of the OS algorithm, with additional vectorization and
 optimizations left to the compiler.
 .
 Simint is capable of calculating ERI with the angular momentum in any order.
 That is, it is possible to calculate (ds|ds) and (sd|ds) directly, without
 permutation of the resulting integrals.
 .
 This packages contains the static library and header files.
.
714079c
Package: libs6-2.15
.
709320c
 This package contains the source for the Rust crates
 ast_nodes from_variant string_enum
 swc_allocator swc_atoms swc_common swc_core swc_eq_ignore_macros
 swc_html_ast swc_html_codegen swc_html_codegen_macros
 swc_html_parser swc_html_utils swc_html_visit
 swc_macros_common swc_malloc swc_sourcemap swc_transform_common
 swc_visit,
.
709307c
Description-md5: 6ac24e90dd9b721da56c3c5aa88efb28
.
700055a

Package: librust-libcramjam-dev
Description-md5: 4271005d01ad40790f56fa3094341a52
Description-en: Compression library combining a plethora of algorithms in a similar as possible API - Rust source code
 Source code for Debianized Rust crate "libcramjam"
.
665458,665463d
655653a
Description-md5: 4773ff9f60de7f9516adebbc90922689
Description-en: Split, Combine and Compress PDF Files
 Content-preserving transformations transformations of PDF files such as split,
 combine, and compress. This package interfaces directly to the 'qpdf'
 C++ library <https://qpdf.sourceforge.io/> and does not require any command
 line utilities. Note that 'qpdf' does not read actual content from PDF files:
 to extract text and data you need the 'pdftools' package.

Package: r-cran-qpdf
.
654639,654647c
Description-md5: fc84048f8067feb1dbbb8d6c9556fdfc
Description-en: Processing of Model Parameters
 Utilities for processing the parameters of various statistical models. Beyond
 computing p values, CIs, and other indices for a wide variety of models (see
 list of supported models using the function 'insight::supported_models()'),
 this package implements features like bootstrapping or simulating of
 parameters and models, feature reduction (feature extraction and variable
 selection) as well as functions to describe data and variable characteristics
 (e.g. skewness, kurtosis, smoothness or distribution).
.
654614,654625c
Description-md5: e800be00a6f6bdcdf712225c97c70366
Description-en: Enhancing the 'parallel' Package
 Utility functions that enhance the 'parallel' package and support the built-in
 parallel backends of the 'future' package. For example, availableCores() gives
 the number of CPU cores available to your R process as given by the operating
 system, 'cgroups' and Linux containers, R options, and environment variables,
 including those set by job schedulers on high-performance compute clusters.
 If none is set, it will fall back to parallel::detectCores().
 Another example is makeClusterPSOCK(), which is backward compatible
 with parallel::makePSOCKcluster() while doing a better job in setting up
 remote cluster workers without the need for configuring the firewall to do
 port-forwarding to your local computer.
.
653348a

Package: r-cran-lwgeom
Description-md5: 8be02afe46a757626b61da89d41e9678
Description-en: Bindings to Selected 'liblwgeom' Functions for Simple Features
 Access to selected functions found in 'liblwgeom'
 <https://github.com/postgis/postgis/tree/master/liblwgeom>, the light-weight
 geometry library used by 'PostGIS' <http://postgis.net/>.
.
652921,652927c
Description-md5: 84f78baf5ce9029d777b6bbd63b73260
Description-en: Kernel Smoothing
 Kernel smoothers for univariate and multivariate data, with comprehensive
 visualisation and bandwidth selection capabilities, including for densities,
 density derivatives, cumulative distributions, clustering, classification,
 density ridges, significant modal regions, and two-sample hypothesis tests.
 Chacon & Duong (2018) <doi:10.1201/9780429485572>.
.
649502,649512c
 <DOI:10.1080/07350015.2016.1247004>. The package includes functions
 for estimating the variance- covariance matrix and for testing single- and
 multiple-contrast hypotheses based on Wald test statistics. Tests of single
 regression coefficients use Satterthwaite or saddle-point corrections.
 Tests of multiple-contrast hypotheses use an approximation to Hotelling's
 T-squared distribution. Methods are provided for a variety of fitted models,
 including lm() and mlm objects; glm(); geeglm() (from package 'geepack');
 lm_robust(), lm_lin(), and iv_robust() (from package 'estimatr'); ivreg()
 (from package 'AER'); ivreg() (from package 'ivreg' when estimated by ordinary
 least squares); plm() (from package 'plm'); gls() and lme() (from 'nlme');
 lmer() (from `lme4`); robu() (from 'robumeta'); rma.uni() and rma.mv()
 (from 'metafor'); and mmrm() (from 'mmrm').
.
649500c
 <https://www150.statcan.gc.ca/n1/pub/12-001-x/2002002/article/9058-eng.pdf>
.
649494,649496c
Description-md5: 6d2697d0aeff1cf6a511f3e17a81e42b
Description-en: Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections
 Provides several cluster-robust variance estimators
.
648514,648536d
501088a
Package: node-alertify.js
Description-md5: dfbc5812cb227ffc0c7f809c31975baf
Description-en: lightweight, unobtrusive customizable notification system
 Alertify.js is a small library which provides light-weight, high
 performance browser dialogs. Since it uses only 1 HTTP request and a
 payload of less than 3kB, it's a great option for adding basic style to
 alert, dialog, prompt and log messages even on low bandwidth connections.
 .
 Alertify is designed from the ground-up for great performance and a small
 footprint. That means it's not as feature-rich as some other options.
 That's on purpose. The plan is to not add a lot more features so it stays
 a great option for every kind of website and user.
 .
 It's also worth noting that the CSS is bundled by default, so there's no
 need to include any stylesheets to use the default theme. It's dyamically
 inserted before any other elements (like) stylesheets so it's super easy
 to override with your own styles.
 .
 An AngularJS module is also included; it's in the "ngAlertify.js" file.
 .
 Node.js is an event-based server-side JavaScript engine.

.
477921,477930d
432875,432884d
418029,418084d
412358a
Package: libraw25
Description-md5: 436cf471e5e66b160c9d836328eeba54
Description-en: raw image decoder library
 LibRaw is a library for reading RAW files obtained from digital photo cameras
 (CRW/CR2, NEF, RAF, DNG, and others).
 .
 This package contains the shared library.

.
345728,345734d
319672,319677d
250394,250426d
250111,250125d
250049a
Package: libgwyddion-dev
Description-md5: 69637105ae001a13874f9850366f92e8
Description-en: header files for Gwyddion SPM analysis tool
 Gwyddion is a modular program for Scanning Probe Microscopy (SPM) data
 visualization and analysis. It is primarily intended for analysis of height
 field data obtained by microscopy techniques like
  * Atomic Force Microscopy (AFM),
  * Magnetic Force Microscopy (MFM),
  * Scanning Tunneling Microscopy (STM),
  * Near-field Scanning Optical Microscopy (SNOM or NSOM)
 and others. However, it can be used for arbitrary height field and
 image analysis.
 .
 This package contains the header files for libgwyddion3-0.

Package: libgwyddion-doc
Description-md5: 0d30282608bd6a8b92ce64f2aec3a145
Description-en: HTML library API documentation for Gwyddion SPM analysis tool
 Gwyddion is a modular program for Scanning Probe Microscopy (SPM) data
 visualization and analysis. It is primarily intended for analysis of height
 field data obtained by microscopy techniques like
  * Atomic Force Microscopy (AFM),
  * Magnetic Force Microscopy (MFM),
  * Scanning Tunneling Microscopy (STM),
  * Near-field Scanning Optical Microscopy (SNOM or NSOM)
 and others. However, it can be used for arbitrary height field and
 image analysis.
 .
 This package contains the HTML API documentation of all the Gwyddion libraries.
 There is also a tutorial on writing Gwyddion modules included.

.
248579,248586d
247701,247740d
234964a
Package: golang-github-wcharczuk-go-chart-dev
Description-md5: 0de3ab6db6c0f7569911229a13c84cbd
Description-en: basic charting library (Golang)
 go-chart is a very simple golang native charting library that supports
 timeseries and continuous line charts.

.
221616a
Package: golang-github-hashicorp-cli-dev
Description-md5: 0febde3b1b9b0a3a09d5fe8373b4dec1
Description-en: Go library for implementing command-line interfaces
 cli is a library for implementing command-line interfaces in Go.

.
219944a
Package: golang-github-gofiber-fiber-v2-dev
Description-md5: 1706641159b4d642b9adc4525a5887e2
Description-en: Express inspired web framework (Go library)
 Fiber is a web framework, created with the idea of minimalism and follows the
 UNIX way. It is inspired by Express, the popular web framework for Node.js.

.
147956,147968d
124923,124935d
8123a
Package: libamgcl-dev
Description-md5: ec65c5ece2e2ac48e9fba2a354789071
Description-en: Solves large sparse linear systems with algebraic multigrid method
 AMG is one of the most effective iterative methods for solution of equation
 systems arising, for example, from discretizing PDEs on unstructured grids. The
 method can be used as a black-box solver for various computational problems,
 since it does not require any information about the underlying geometry. AMG is
 often used not as a standalone solver but as a preconditioner within an
 iterative solver (e.g. Conjugate Gradients, BiCGStab, or GMRES).
 .
 AMGCL builds the AMG hierarchy on a CPU and then transfers it to one of the
 provided backends. This allows for transparent acceleration of the solution
 phase with help of OpenCL, CUDA, or OpenMP technologies. Users may provide
 their own backends which enables tight integration between AMGCL and the user
 code.
 .
 AMG is a header-only C++ library, with the headers provided by this package.

Package: python3-amgcl
Description-md5: ecbb9c7c4315244c6b65581f6b220a1f
Description-en: Solves large sparse linear systems with algebraic multigrid method
 AMG is one of the most effective iterative methods for solution of equation
 systems arising, for example, from discretizing PDEs on unstructured grids. The
 method can be used as a black-box solver for various computational problems,
 since it does not require any information about the underlying geometry. AMG is
 often used not as a standalone solver but as a preconditioner within an
 iterative solver (e.g. Conjugate Gradients, BiCGStab, or GMRES).
 .
 AMGCL builds the AMG hierarchy on a CPU and then transfers it to one of the
 provided backends. This allows for transparent acceleration of the solution
 phase with help of OpenCL, CUDA, or OpenMP technologies. Users may provide
 their own backends which enables tight integration between AMGCL and the user
 code.
 .
 This package provides the Python interface

.
