Mendeley Data Showcase

The replication package is organized to facilitate transparent reproduction of all tables and figures in the paper, "Firm and Labor Adjustments to FDI Liberalization." It contains a `code/` folder with all Stata and R scripts (coordinated by a master script), a `data/` folder with cleaned and intermediate datasets, and `output/table/` and `output/graph/` folders with the LaTeX tables and PDF figures reported in the paper. Due to confidentiality restrictions imposed by the Ministry of Finance of Taiwan, raw worker-level administrative data are not included; scripts that must be run inside the MOF Financial Information Agency secure data center are clearly marked. All file paths are relative, and once the root directory is set, the replication can be executed without further modification.

Introdução: O diabetes mellitus é uma das principais Doenças Crônicas Não Transmissíveis, com elevada prevalência global e impactos significativos na morbimortalidade e na qualidade de vida. No âmbito da Atenção Primária à Saúde, o fortalecimento do autocuidado apoiado é essencial para o manejo eficaz da doença, sendo as tecnologias educacionais estratégias promissoras para qualificar esse processo. Objetivo: Analisar as evidências científicas acerca das tecnologias educacionais aplicadas ao autocuidado apoiado de pessoas com diabetes mellitus no contexto da Atenção Primária à Saúde. Materiais e Métodos: Trata-se de uma revisão integrativa da literatura, com estudos publicados entre 2021 a 2025. A seleção seguiu critérios pré-estabelecidos, com extração e análise dos dados, bem como classificação dos níveis de evidência dos estudos incluídos. Resultados: Foram incluídos 20 estudos, que evidenciaram o uso de tecnologias educacionais, com melhores desfechos clínicos e de autocuidado em intervenções fundamentadas em modelos teóricos. Discussão: Os achados indicam que as tecnologias educacionais, quando associadas a estratégias pedagógicas estruturadas e modelos teóricos consolidados, potencializam o autocuidado apoiado na APS. Entretanto, desafios como a inclusão digital, a sustentabilidade das intervenções e a heterogeneidade dos instrumentos de avaliação ainda limitam a ampliação dessas estratégias. Conclusão: As tecnologias educacionais configuram-se como ferramentas eficazes e inovadoras para o fortalecimento do autocuidado apoiado em pessoas com diabetes mellitus na Atenção Primária à Saúde, contribuindo para melhores desfechos clínicos e psicossociais, desde que integradas ao acompanhamento contínuo e a abordagens educativas consistentes.

This dataset contains a comprehensive, ASV-level microbiota profile from a cohort study of 1016 community-dwelling older adults in China, stratified by multidimensional healthy aging (HA) status. Data are provided as an R phyloseq object (.rds` format), integrating: ASV Abundance Table (otu_table): A high-resolution Amplicon Sequence Variant (ASV) count matrix (samples × ASVs). Taxonomic Assignment (tax_table): A 7-rank taxonomic classification (Domain to Species) for each ASV. De-identified Sample Metadata (sam_data): A curated dataframe containing all variables essential for replication of the published analyses. This includes: Primary exposure: HA_Status (Healthy Aging / Usual Aging). Key covariates: Age, Sex, BMI, and other relevant sociodemographic, lifestyle, and health-related factors (as adjusted for in the original study). Sample identifiers and sequencing run information. Phylogenetic Tree (phy_tree): A phylogenetic tree of ASV sequences for phylogenetic diversity calculations (e.g., UniFrac). This curated phyloseq object enables full re-analysis of the study's core findings, including community structure (alpha/beta diversity), differential abundance testing, ecological network inference, and functional prediction. The data are sufficient to regenerate all microbiome-centric results and figures in the associated publication, providing a transparent and reproducible foundation for the conclusions on gut microbial signatures in healthy aging.

The transformation from the Roman-canonical tradition, or civil law, to the Anglo-Saxon tradition, or common law, is a complex process that has developed over centuries, shaped by various historical, political and social factors. Roman-canonical law, with roots in the ancient Roman Empire and enriched by the legal tradition of the Catholic Church, is characterized by its emphasis on written and codified law as the primary source of law. By contrast, Anglo-Saxon law, which originated in England, is distinguished by its focus on jurisprudence, that is, on court decisions and judicial precedents as the basis for resolving future cases. The thesis of this essay is that the transformation of civil law into common law in territories under Anglo-Saxon influence was not a spontaneous process; rather, it was driven by a series of interrelated factors such as colonial expansion, the prestige of the common law and the need to adapt the law to new social and economic realities.

This dataset contains the experimental adsorption isotherms and kinetic data for Cu2+ removal using hierarchically porous chitosan–alginate–CaCO₃ biocomposites. Data include equilibrium adsorption capacities and adsorption kinetics obtained using different copper counter-ions under controlled experimental conditions.

This repository reproduces the paper’s main empirical results from: “Difference-in-differences with endogenous externalities: Model and application to climate econometrics” Papers in Regional Science, 104 (2025) 100125. The code implements the paper’s strategy by combining (i) a PPML first stage to predict bilateral flows and construct a country–year exposure instrument, and (ii) an IV second stage to estimate causal effects on country–year outcomes. First stage (PPML). We estimate a Poisson model with high-dimensional fixed effects (exporter–importer and year) using fixest::fepois. From the estimated coefficients, we compute predicted bilateral flows and build WD_row_hat, an instrument that measures country i’s exposure in year t to shocks occurring in node j (e.g., drought). Exposure is weighted by shares derived from predicted bilateral flows, using either row-standardization (by exporter-year) or a year-global normalization, depending on the option selected. Second stage (IV). We estimate country–year panel models for outcomes such as ln_production (and optionally ln_area, ln_yield) as functions of observed exposure WD_row_obs, treated as endogenous and instrumented by WD_row_hat. Specifications include fixed effects and climate/structural controls (temperature, precipitation, irrigation, and drought indicators), estimated with fixest::feols using its IV formula syntax. Inference. Standard errors are obtained via a two-level bootstrap: (1) draw PPML coefficient vectors from a multivariate normal approximation based on the first-stage variance–covariance matrix; (2) resample country clusters (or a user-defined cluster key) with replacement and re-estimate the second-stage and IV models for each replication. This yields bootstrap standard errors that incorporate both first-stage uncertainty and within-cluster dependence. Parallelization uses foreach/doParallel, and reproducibility is ensured via doRNG with a fixed seed. Inputs are: (a) a bilateral panel (isoi, isoj, year) for the PPML stage and (b) a country–year panel (iso, year) for the IV stage. Running the replication script produces point estimates and a coefficient table with bootstrap standard errors and key diagnostics (e.g., first-stage F-statistics when available).

The dataset includes metagenomic sequencing data related to soil sulfur cycling under different long-term green manure treatments in paddy soil. The data were generated from field experiments and comprise functional gene abundance and taxonomic annotations associated with sulfur metabolism. These data support the analyses of microbial community composition and sulfur cycling functional pathways presented in this study and can be used for further comparative and meta-analyses of soil biogeochemical processes.

Supplemental material for "Food Restriction Patterns and Their Impact on Growth and Nutrition in Chinese Pediatric Atopic Dermatitis"

MONOBHAV is a Bengali dataset for fine-grained sentiment analysis. It contains 10,000 Bengali texts collected from social media platforms and newspaper websites. Each text is manually annotated by native Bengali speakers into five sentiment classes - Strongly Negative, Negative, Neutral, Positive, and Strongly Positive. This dataset enhances the resources available for Bengali sentiment analysis and supports the development and evaluation of more accurate sentiment models for the language.