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This dataset contains raw CO₂ exchange flux measurements collected in raised bogs of Southern Patagonia (Tierra del Fuego, Argentina), during the growing seasons of 2021–2022 and 2022–2023. Measurements were conducted across contrasting microforms (hummocks and lawns) under light and dark conditions in eight raised bogs and 42 permanent collars, measured repeatedly throughout the growing seasons. The dataset includes net ecosystem exchange (NEE) and associated environmental and vegetation variables measured during each flux assessment, including air temperature, chamber temperature, soil temperature at 10 cm depth, water table level, vascular plant cover, and photosynthetically active radiation (PAR).

Additional result PICs of results not described in the paper “Continuous beam damage localization method and system based on differential current density influence line and deep residual learning”.

data for testing

This repository contains the de-identified analytical dataset and reproducibility materials supporting the study “Heat-Related Mobility Capability Gaps despite Similar Transport Walking among Women and Men in Najaf, Iraq.” The study includes 800 adults surveyed across 20 urban neighborhoods in Najaf, Iraq, during June 2026. The deposited materials include the de-identified analytical dataset, codebook, variable definitions and coding rules, reproducibility documentation, analysis scripts, and verification outputs. Direct identifiers, free-text location information, exact survey dates and times, and other potentially identifying fields have been removed. The materials support reproduction of the principal descriptive statistics, gender comparisons, heat-related necessary-trip suppression models, walking analyses, scale diagnostics, sensitivity analyses, and well-being analysis reported in the associated manuscript.

This dataset contains 5,674 unique movie records and 32 attributes prepared for machine learning, data analysis, and entertainment-domain research. It includes information such as movie title, release year, runtime, rating, vote count, Metascore, gross revenue, genre, certification, director, cast, and textual descriptions. The purpose of this dataset is to support the investigation of relationships between movie characteristics and performance-related indicators. The dataset enables exploration of questions such as how factors including genre, runtime, release year, audience voting behaviour, critical scores, and financial performance are related. It can also be used to investigate whether combinations of movie metadata features can support predictive or classification-based machine learning tasks. The data was prepared from real-world movie metadata through systematic data cleaning, transformation, missing-value treatment, text preprocessing, feature engineering, and statistical standardization. Redundant index artifacts were removed and duplicate records were checked. Missing numerical values were handled using genre-wise median imputation, while missing certification values were treated using categorical imputation. Cleaned and structured versions of genre, director, cast, and description fields were created, along with a primary genre feature. Additional standardized features were generated for movie rating, vote count, Metascore, gross revenue, runtime, and release year using Z-score and T-score transformations. These transformations allow numerical variables with different scales to be more easily compared and analysed. The dataset can be interpreted through exploratory statistical analysis, visualization, correlation analysis, regression, classification, clustering, and feature-based machine learning models. Potential applications include movie rating prediction, genre analysis, popularity and audience engagement analysis, financial performance analysis, recommendation system research, and natural language processing of movie descriptions. The final dataset is intended as a structured research resource for analysing patterns and relationships within movie metadata and for evaluating machine learning approaches using real-world entertainment-domain data.

Trading with the Machines: Partner-Country AI Innovation and African Export Performance." The paper estimates whether growth in AI patenting among destination economies raised African merchandise exports between 2016 and 2023, using a shift-share instrument built from destinations' baseline composition of AI patenting across technology fields. UN Comtrade Database, UN Statistics Division, extracted 10 August 2026. Eight annual files, 2016–2023, split by year because a single query is capped at 100,000 records. Parameters: goods, annual, HS as reported, AG2 commodity codes, all 54 African economies as reporters, all partners, second partner World, exports only, total modes and customs codes, Plus breakdown. Appended: 629,649 records, 49 reporters, 238 partners, no duplicates. The WORLD_TOTALS file is a separate extract with partner set to World; it supplies export-share denominators and does not enter the estimation sample. Encoding is latin-1. Rows carry a trailing comma, creating one empty variable on import. Import all columns as strings so chapter codes 01–09 keep leading zeros. Country AI Activity Metrics, Emerging Technology Observatory, CSET, Georgetown University, extracted March 2026. ai_patents_subfield.csv reports AI patent applications by country, field and year and supplies the treatment; ai_patents_granted_subfield.csv reports granted patents and is retained but unused. Attribution follows the priority jurisdiction, the first office at which protection was sought, so the data describe where patents are filed rather than where inventors reside. CSET flags counts incomplete from 2022, reflecting the filing-to-publication lag; baseline shares are fixed at 2016–2018. Nine of eleven fields map onto merchandise trade. cset_patents_iso3.csv adds ISO3 codes and removes aggregates and patent offices, leaving 69 countries; the estimation code reads this file. cset_pubs_iso3.csv is the publications equivalent, unused, as its field taxonomy has no sectoral interpretation. afcfta_ratification.csv gives deposit dates for 49 AfCFTA signatories from the tralac Ratification Barometer (June 2026); unused, because by 2023 the never-treated pool was too thin to identify anything. code/ — Stata do-files for construction, estimation and figures. Run 00_master_v2.do. Bilateral geography variables from CEPII, not redistributed under CEPII's terms. Download from cepii.fr; the merge is documented in 02_merge_gravity_v2.do. These are absorbed by exporter-destination fixed effects in the headline specification.

This dataset provides a comprehensive geospatial inventory of 80 agromineral deposits identified in the Northeast Region of Brazil as potential sources of rock dust for soil remineralization. The inventory was compiled from official records of the Geological Survey of Brazil (SGB/CPRM) and the Centre for Mineral Technology (CETEM). For each deposit, the dataset includes: state, municipality, geographic coordinates (latitude/longitude, SIRGAS 2000/EPSG:4674, georeferenced at the municipal centroid level), lithology, lithochemical classification (ASiCaMg, ASiK, ASiMg, ASiCaMgK, ASiMgCaK, Phosphate), estimated oxide contents (K₂O, CaO, MgO) based on published literature, dominant mineral phases, relative dissolution rate category, potentially toxic element (PTE) concern level, and primary bibliographic reference. The data support a preliminary geological-lithological screening study and are not intended as direct agronomic recommendations. Users should note that coordinates represent municipal centroids rather than precise deposit locations, and oxide ranges are literature-derived estimates rather than site-specific analytical measurements.

96 participants (72 AD + 24 controls), 36/36 Phase II allocation, modality-specific missingness, H1/H2 repeated-measures data, tau/MENRI mediation variables, 12-week longitudinal outcomes

Molecular dynamics simulation data for the interactions between free aromatic amino acids and x-type HMW-GS. This dataset contains representative protein and small molecules structures, molecular dynamics input parameters, topology files, and trajectory files supporting the study of interactions between free aromatic amino acids (phenylalanine, tryptophan, and tyrosine) and x-type high-molecular-weight glutenin subunits (Ax1, Bx7, and Dx2).

Harmonized comparative bulk RNA-seq data from dorsal root ganglias in rat models of acute and persistent postsurgical pain