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1. Comparing R Bytecode Compilers Written in R, Java, and Rust (Extended Abstract)

   https://doi.org/10.4230/oasics.programming.2025.1  

   Donat-Bouillud, Pierre; Křikava, Filip; Hain, Jakob; Plodek, Adam; Vitek, Jan (January 2025, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Edwards, Jonathan; Perera, Roly; Petricek, Tomas (Ed.)

   This paper presents a comparative analysis of three implementations of the R bytecode compiler: the official R implementation, a Java-based compiler, and a Rust-based compiler. The R compiler, written in R itself, poses challenges in terms of performance and maintainability. We evaluate designs of the compilers, their trade-offs, and performance characteristics. The Rust version outperforms the Java version, which itself outperforms the R version. 

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2. The R -Process Alliance: Analysis of limited- r stars

   https://doi.org/10.1051/0004-6361/202449376  

   Xylakis-Dornbusch, T; Hansen, T T; Beers, T C; Christlieb, N; Ezzeddine, R; Frebel, A; Holmbeck, E; Placco, V M; Roederer, I U; Sakari, C M; et al (August 2024, Astronomy & Astrophysics)

   Context.In recent years, theR-Process Alliance (RPA) has conducted a successful search for stars that are enhanced in elements produced by the rapid neutron-capture (r-)process. In particular, the RPA has uncovered a number of stars that are strongly enriched in lightr-process elements, such as Sr, Y, and Zr. These so-called limited-rstars were investigated to explore the astrophysical production site(s) of these elements. Aims.We investigate the possible formation sites for light neutron-capture elements by deriving detailed abundances for neutron-capture elements from high-resolution spectra with a high signal-to-noise ratio of three limited-rstars. Methods.We conducted a kinematic analysis and a 1D local thermodynamic equilibrium spectroscopic abundance analysis of three stars. Furthermore, we calculated the lanthanide mass fraction (X_La) of our stars and of limited-rstars from the literature. Results.We found that the abundance pattern of neutron-capture elements of limited-rstars behaves differently depending on their [Ba/Eu] ratios, and we suggest that this should be taken into account in future investigations of their abundances. Furthermore, we found that theX_Laof limited-rstars is lower than that of the kilonova AT2017gfo. The latter seems to be in the transition zone between limited-rX_Laand that ofr-I andr-II stars. Finally, we found that unliker-I andr-II stars, the current sample of limited-rstars is largely born in the Galaxy and is not accreted. 

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3. $$K_{r,s}$$ Graph Bootstrap Percolation

   https://doi.org/10.37236/8997  

   Bayraktar, Erhan; Chakraborty, Suman (January 2022, The Electronic Journal of Combinatorics)

   A graph $$G$$ percolates in the $$K_{r,s}$$-bootstrap process if we can add all missing edges of $$G$$ in some order such that each edge creates a new copy of $$K_{r,s}$$, where $$K_{r,s}$$ is the complete bipartite graph. We study $$K_{r,s}$$-bootstrap percolation on the Erdős-Rényi random graph, and determine the percolation threshold for balanced $$K_{r,s}$$ up to a logarithmic factor. This partially answers a question raised by Balogh, Bollobás, and Morris. We also establish a general lower bound of the percolation threshold for all $$K_{r,s}$$, with $$r\geq s \geq 3$$. 

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4. The R-process Alliance: A Nearly Complete R-process Abundance Template Derived from Ultraviolet Spectroscopy of the R-process-enhanced Metal-poor Star HD 222925*

   https://doi.org/10.3847/1538-4365/ac5cbc  

   Roederer, Ian U.; Lawler, James E.; Den Hartog, Elizabeth A.; Placco, Vinicius M.; Surman, Rebecca; Beers, Timothy C.; Ezzeddine, Rana; Frebel, Anna; Hansen, Terese T.; Hattori, Kohei; et al (June 2022, The Astrophysical Journal Supplement Series)

   Abstract We present a nearly complete rapid neutron-capture process ( r -process) chemical inventory of the metal-poor ([Fe/H] = −1.46 ± 0.10) r -process-enhanced ([Eu/Fe] = +1.32 ± 0.08) halo star HD 222925. This abundance set is the most complete for any object beyond the solar system, with a total of 63 metals detected and seven with upper limits. It comprises 42 elements from 31 ≤ Z ≤ 90, including elements rarely detected in r -process-enhanced stars, such as Ga, Ge, As, Se, Cd, In, Sn, Sb, Te, W, Re, Os, Ir, Pt, and Au. We derive these abundances from an analysis of 404 absorption lines in ultraviolet spectra collected using the Space Telescope Imaging Spectrograph on the Hubble Space Telescope and previously analyzed optical spectra. A series of appendices discusses the atomic data and quality of fits for these lines. The r -process elements from Ba to Pb, including all elements at the third r -process peak, exhibit remarkable agreement with the solar r -process residuals, with a standard deviation of the differences of only 0.08 dex (17%). In contrast, deviations among the lighter elements from Ga to Te span nearly 1.4 dex, and they show distinct trends from Ga to Se, Nb through Cd, and In through Te. The r -process contribution to Ga, Ge, and As is small, and Se is the lightest element whose production is dominated by the r -process. The lanthanide fraction, log X La = −1.39 ± 0.09, is typical for r -process-enhanced stars and higher than that of the kilonova from the GW170817 neutron-star merger event. We advocate adopting this pattern as an alternative to the solar r -process-element residuals when confronting future theoretical models of heavy-element nucleosynthesis with observations. 

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5. Efficiently Merging r-indexes

   https://doi.org/10.1109/DCC50243.2021.00028  

   Oliva, Marco; Rossi, Massimiliano; Siren, Jouni; Manzini, Giovanni; Kahveci, Tamer; Gagie, Travis; Boucher, Christina (March 2021, 2021 Data Compression Conference (DCC))

   null (Ed.)

   Large sequencing projects, such as GenomeTrakr and MetaSub, are updated frequently (sometimes daily, in the case of GenomeTrakr) with new data. Therefore, it is imperative that any data structure indexing such data supports efficient updates. Toward this goal, Bannai et al. (TCS, 2020) proposed a data structure named dynamic r-index which is suitable for large genome collections and supports incremental construction; however, it is still not powerful enough to support substantial updates. Here, we develop a novel algorithm for updating the r-index, which we refer to as RIMERGE. Fundamental to our algorithm is the combination of the basics of the dynamic r-index with a known algorithm for merging Burrows-Wheeler Transforms (BWTs). As a result, RIMERGE is capable of performing batch updates in a manner that exploits parallelism while keeping the memory overhead small. We compare our method to the dynamic r-index of Bannai et al. using two different datasets, and show that RIMERGE is between 1.88 to 5.34 times faster on reasonably large inputs. 

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