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Agents v4.5.1 Diff since v4.5.0

What's Changed Pkg.instantiate before initial resolve when opening a notebook by @fonsp in https://github.com/fonsp/Pluto.jl/pull/2420 🫧 Fix #2421 by @fonsp in https://github.com/fonsp/Pluto.jl/pull/2422 Full Changelog: https://github.com/fonsp/Pluto.jl/compare/v0.19.18...v0.19.19

MMDCopula is a software package for the R Statistical Environment that provides functions for the robust estimation of parametric families of copulas using minimization of the Maximum Mean Discrepancy, following the article Alquier, Chérief-Abdellatif, Derumigny and Fermanian (2020) <arXiv:2010.00408>.

The R codes were developed and applied by the EFSA Working Group on Listeria monocytogenes contamination of ready-to-eat foods during the preparatory work on the Scientific Opinion ‘Listeria monocytogenes contamination of ready-to-eat foods and the risk for human health in the EU’ (see 10.2903/j.efsa.2018.5134). The codes were used to perform time-series analyses of the number of confirmed invasive listeriosis cases in the EU/EEA for the period 2008–2015. Data from The European Surveillance System – TESSy, provided by Austria, Belgium, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Luxembourg, Malta, Netherlands, Norway, Poland, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom, and released by ECDC. Two R codes are provided, one has been used for an analysis using the entire dataset of 14,002 confirmed cases (aggregated analysis) and another one has been used for the analysis using each time a subset of the population (14 subgroups defined by gender and age – disaggregated analysis). The following 14 gender–age group combinations were used: 1–4, 5–14, 15–24, 25–44, 45–64, 65–74, ≥ 75 years old, for both males and females. The analyses are implemented in R. Two codes are provided, one for the aggregated data analysis and one for the disaggregated data analysis. The working directory needs to be defined in the code (currently there is a placeholder named 'WORKING DIRECTORY'). The data are provided as .csv files ('totals.csv' for the aggregated analysis; 'merged_eu_wide.csv' and 'merged_eu.csv' for the disaggregated analysis) and can be read by the R code if placed in the same working directory. R packages that are required to be installed for the aggregated analysis are 'dlm' and 'strucchange' together with its dependencies, and for the disaggregated analysis the package 'epitools'. Also the script 'pests.R' needs to be downloaded from http://www.utdallas.edu/~pbrandt/code/pests.r and saved in the respective working directory, for both analyses. The analyses are explained step by step in the R script, which is intended to be run line by line and not entirely in one run. Indeed, the R code currently does not allow for opening new graph windows for new plots, which each time overwrite the previously created ones. It is recommended that the user ignores the specific warning messages that are produced during the disaggregated PAR analysis for the subgroups Female1524, male2544, male6574 and male75, since these have to do with the starting values used for the models but the results are still correct. {"references": ["Brandt P and Williams JT, 2001. A linear Poisson autoregressive model: the Poisson AR(p) model. Political Analysis, 9, 164-184.", "Petris G, 2010. An R Package for Dynamic Linear Models. Journal of Statistical Software, 36, 1-16.", "Petris G, Petrone S and Campagnoli P, 2009. Dynamic linear models. In: Eds Gentleman R, Hornik K and Parmigiani G. Dynamic Linear Models with R. Springer, Milano, Italy, pp.31-84."]} EU; CSV: biohaz@efsa.europa.eu

Reproduction Package Eurodeer paper n. 016 (RP016) Datasets and analysis scripts of Salvatori, De Groeve et al. (2022). Reference Salvatori M, De Groeve J, van Loon E, De Baets B, Morellet N, Focardi S, Bonnot NC, Gehr B, Griggio M, Heurich M, Kroeschel M, Licoppe A, Moorcroft PRM, Pedrotti L, Signer J, Van de Weghe N, & Cagnacci F (2022) Day versus night use of forest by red and roe deer as determined by Corine Land Cover and Copernicus Tree Cover Density: assessing use of geographic layers in movement ecology. Landscape Ecology, 37: 1453-1468 {"references": ["Salvatori M, De Groeve J, van Loon E, De Baets B, Morellet N, Focardi S, Bonnot NC, Gehr B, Griggio M, Heurich M, Kroeschel M, Licoppe A, Moorcroft PRM, Pedrotti L, Signer J, Van de Weghe N, & Cagnacci F (2022) Day versus night use of forest by red and roe deer as determined by Corine Land Cover and Copernicus Tree Cover Density: assessing use of geographic layers in movement ecology. Landscape Ecology, 37: 1453-1468"]} If you use this software, please cite it as below.

@netwerk-digitaal-erfgoed/network-of-terms-catalog 9.17.2 (2024-11-20) Bug Fixes Iconclass related resources (#1462) (1d7f0b2)

Experiment-independent toolkit for (charged) particle track reconstruction in (high energy) physics experiments implemented in modern C++

This repository contains the scripts and own generated data developed for the article: Miranda Xicotencatl, B., Kleijn, R., van Nielen, S., Donati, F., Sprecher, B., & Tukker, A. (2023). Data implementation matters: Effect of software choice and LCI database evolution on a comparative LCA study of permanent magnets. Journal of Industrial Ecology, 27(5), 1252–1265. https://doi.org/10.1111/jiec.13410 The data folder contains the characterized results of three alternatives for the production of rare earth magnets (REMs), calculated with several versions of the ecoinvent database (v2.2 and cut-off v3.1 to v3.6), their life cycle inventories, the foreground data to reproduce their product system models and the data plotted in Figures 3, 4 and 5 of the related article. The file with the Data Underlying the Figures in the Main Article is: `dataPlottedInFig_3_4_and_5.xlsx`. The document BWimport in the repository guides the user through the interaction with the custom scripts necessary to reproduce the results of this research. It is available as a PDF and as an interactive Jupyter notebook (IPYNB). Please refer to the article and the first part of the supplementary information (SI1) for further details about the context and purpose of this repository.Note on foreground dataSprecher et al. (2014) made their foreground data partially available in a human-readable format under a CC BY-NC 4.0 license. The file `processDataCMLCA.xlsx` is based on their complete product system model and consists of an annotated human- and machine-readable version. This modified version also includes the allocation factors used by Sprecher et al. (2014) that were not reported in their original publication.Note on licensesThe data in the repository is based on the work by Sprecher et al. (2014) and licensed under a Creative Commons Attribution-NonCommercial 4.0 International License by Brenda Miranda Xicotencatl. The underlying source code is available in this repository under the MIT license. If you use the scripts, please refer to the Zenodo repository. For other use cases, please cite the research article.