Converts 'RefWorks' and 'RIS' exports, and saved 'Google Scholar' results pages, to 'BibTeX', and reads 'BibTeX' files into data frames and 'Excel' workbooks. Looks up missing abstracts in 'OpenAlex'. Runs text analytics on abstracts: topic modeling (latent Dirichlet allocation), cosine document similarity, and trends over time. The computationally heavy steps are implemented in 'C++' via 'Rcpp'.

Converts 'RefWorks' and 'RIS' exports, and saved 'Google Scholar' results pages, to 'BibTeX', and reads 'BibTeX' files into data frames and 'Excel' workbooks. Looks up missing abstracts in 'OpenAlex'. Runs text analytics on abstracts: topic modeling (latent Dirichlet allocation), cosine document similarity, and trends over time. The computationally heavy steps are implemented in 'C++' via 'Rcpp'.

A new release of prrd arrived at CRAN today, and has already been built for r2u and on r-universe. The prrd package facilitates the _parallel running [of] reverse dependency [checks]_ when preparing R packages. It is used extensively for releases I make of Rcpp, RcppArmadillo, RcppEigen, BH, and others. The key idea of prrd is simple, and described in some more detail on its webpage and its GitHub repo. Reverse dependency checks are an important part of package development that is easily done in a (serial) loop. But these checks are also generally _embarassingly parallel_ as there is no or little interdependency between them (besides maybe shared build depedencies). See the (somewhat dated) screenshot (running six parallel workers, arranged in a split byobu session). This release updates internals to allow for greater concurrency. SQLite is used as the backend, both for the job queue (managed via the liteq package) as well as for storing actual reverse-dependency test results. It is well-known that SQLite copes quite well with multiple _readers_. Multiple concurrent _writers_ are more challenging. We tended to get by via `BEGIN EXCLUSIVE` pragma use, but still get occassional issue even at a somewhat moderate concurrency levels. After some back and forth and trying a few approaches, more recently we established one first solution relying on very explicity (OS-level, filesystem-based) locking via package filelock. That worked. We mentioned this in an old liteq issue that had circled around the same question with a number of posts over the years, but no resolution. This comment seemingly awoke Gábor, and he nailed this years-open issue with a fine pull request deploying `BEGIN IMMEDIATE` and well as a loop around `tryCatch` to not immediately fail. I borrowed/ported that approach to prrd and we now have a second solution (and no longer need filelock). On a somewhat better server with enough cores and memory, I am now running eighteen concurrent workers—watched via three multi-pane byobu windows. Works like a charm without issues. At last! A big thanks to Gábor for finding another solution, and especially that only relies on SQLite. The release is summarised in the NEWS entry: > #### Changes in prrd version 0.1.0 (2026-11-07) > > * Concurrent operations are now supported via updated sqlite semantics borrowed with appreciation from liteq > > * This follows an interim solution relying on filelock use; however this later package is not needed so no increase in dependencies > > Courtesy of my CRANberries, there is also a diffstat report for this release. This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. If you like this or other open-source work I do, you can sponsor me at GitHub.

Shopee · R$69,90

Sparse Bayesian factor models for multivariate data, built around a flexible Generalized Lower Triangular (GLT) process prior on the loading matrix by Canale and Frühwirth-Schnatter (2026) &lt;<a href="https://doi.org/10.48550%2FarXiv.2610.09762" target="_top">doi:10.48550/arXiv.2610.09762</a>&gt;. The number of active factors, their sparsity pattern, and the loadings themselves are learned jointly via a Markov chain Monte Carlo sampler implemented in C++ with 'Rcpp' and 'RcppArmadillo'.

The project, “Accelerating Regenerative Agriculture Through Public-Private Partnership,” is part of an investment of over $325 million in 42 projects to help farmers, ranchers, and forest landowners boost their operations and conserve natural resources across the nation through the Regional Conservation Partnership Program (RCPP). Through RCPP, the U.S, Department of Agriculture (USDA) works with partners to fund solutions to natural resource challenges on agricultural land. For example, this Pennsylvania project aims to increase farmer participation in conservation and consequently accelerate implementation on the ground by making conservation affordable and accessible to all farmers. “The Regional Conservation Partnership Program (RCPP) pairs private investment with federal funds to deliver better results,” said U.S. Secretary Brooke Rollins in her recent announcement of the nationwide projects. “Recently, we’ve taken steps to improve RCPP to reduce red tape and increase flexibility to better empower local partners to conserve natural resources while helping American farmers prosper." In the past year, NRCS has improved RCPP through streamlining partnership agreement processes and increasing flexibilities to ensure the program works more effectively for conservation partners and America’s farmers and ranchers. Seventy-five percent of the RCPP’s $325 million in funding this year will go directly to the American farmer or...

The project, “Accelerating Regenerative Agriculture Through Public-Private Partnership,” is part of an investment of over $325 million in 42 projects to help farmers, ranchers, and forest landowners boost their operations and conserve natural resources across the nation through the Regional Conservation Partnership Program (RCPP). Through RCPP, the U.S, Department of Agriculture (USDA) works with partners to fund solutions to natural resource challenges on agricultural land. For example, this Pennsylvania project aims to increase farmer participation in conservation and consequently accelerate implementation on the ground by making conservation affordable and accessible to all farmers. “The Regional Conservation Partnership Program (RCPP) pairs private investment with federal funds to deliver better results,” said U.S. Secretary Brooke Rollins in her recent announcement of the nationwide projects. “Recently, we’ve taken steps to improve RCPP to reduce red tape and increase flexibility to better empower local partners to conserve natural resources while helping American farmers prosper." In the past year, NRCS has improved RCPP through streamlining partnership agreement processes and increasing flexibilities to ensure the program works more effectively for conservation partners and America’s farmers and ranchers. Seventy-five percent of the RCPP’s $325 million in funding this year will go directly to the American farmer or...

Sparse Bayesian factor models for multivariate data, built around a flexible Generalized Lower Triangular (GLT) process prior on the loading matrix by Canale and Frühwirth-Schnatter (2026) &lt;<a href="https://doi.org/10.48550%2FarXiv.2610.09762" target="_top">doi:10.48550/arXiv.2610.09762</a>&gt;. The number of active factors, their sparsity pattern, and the loadings themselves are learned jointly via a Markov chain Monte Carlo sampler implemented in C++ with 'Rcpp' and 'RcppArmadillo'.

Fault tree analysis with tidy data. Represent a fault tree as two tables, one of nodes (the top event, gates and basic events) and one of edges, so the whole workflow stays in ordinary data frames. Derive the Boolean equation of the top event, enumerate the truth table, and find minimal cut sets with the Method of Obtaining Cut Sets (MOCUS) algorithm of Fussell and Vesely (1972), implemented in 'R' and, by default, in C++ through 'Rcpp'. Evaluate thousands of binary or probabilistic scenarios in one vectorized call, put uncertainty intervals around the top-event probability, follow it over time, and rank which component fix lowers it most. Lay out and draw the tree with 'tidygraph', 'igraph' and 'ggplot2'. Methods follow the "Fault Tree Handbook" of Vesely, Goldberg, Roberts and Haasl (1981) &lt;<a href="https://www.nrc.gov/docs/ML1007/ML100780465.pdf" target="_top">https://www.nrc.gov/docs/ML1007/ML100780465.pdf</a>&gt;. A 'Python' port with the same functions ships in the same repository.

Provides an R interface to 'LadybugDB', an embedded columnar graph database using the 'Cypher' query language. 'LadybugDB' was formerly known as 'Kuzu'. This package uses native 'Rcpp' bindings to the 'LadybugDB' C library, requiring no 'Python' runtime.

Provides an R interface to 'LadybugDB', an embedded columnar graph database using the 'Cypher' query language. 'LadybugDB' was formerly known as 'Kuzu'. This package uses native 'Rcpp' bindings to the 'LadybugDB' C library, requiring no 'Python' runtime.

Provides Markov chain Monte Carlo (MCMC) sampling and genetic algorithms for searching combinations of nodes in hierarchical trees. Includes scores for binary outcomes, continuous outcomes, and recurrent events, with applications to pharmacovigilance and hospital data. Importance weighting estimates uniform combination score references from tempered MCMC samples and reports weight-based effective sample sizes. Computational routines are implemented in C++ via 'Rcpp'.

Provides Markov chain Monte Carlo (MCMC) sampling and genetic algorithms for searching combinations of nodes in hierarchical trees. Includes scores for binary outcomes, continuous outcomes, and recurrent events, with applications to pharmacovigilance and hospital data. Importance weighting estimates uniform combination score references from tempered MCMC samples and reports weight-based effective sample sizes. Computational routines are implemented in C++ via 'Rcpp'.

I’ve been away from Julia for several years now, mostly because my company and field doesn’t really use it so implementing it is very difficult when no one will be able to read my code or use my packa...

Tools to Machinate 'Akin' HTTP Request Fingerprints

An animal rescue organization thanked actor Joseph Marco for spending his 38th birthday with their rescues and making a donation to help support their needs. Red Cubs Pet Patrol (RCPP) on Sunday, October 4, reshared a post from the actor’s Facebook page showing him spending time with cats and dogs at their shelter. “Celebrated my […] The post Joseph Marco spends birthday with his ‘600 beautiful souls’ appeared first on Interaksyon.