cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/kpwj92hhxr.1
title: Matemática Básica e Estatística: Fundamentos, Representações e Aplicações

description: A presente obra foi concebida com o objetivo de oferecer uma base sólida e acessível para estudantes que iniciam sua trajetória nas ciências exatas, especialmente na matemática e na estatística. Ao longo das últimas décadas, essas áreas tornaram-se essenciais não apenas para o desenvolvimento científico e tecnológico, mas também para a formação de um pensamento crítico e estruturado.
A matemática é, por excelência, uma linguagem universal. Seu rigor lógico e sua capacidade de representar fenômenos reais com precisão a tornam indispensável para a compreensão do mundo contemporâneo. Com isso em mente, esta apostila busca apresentar conteúdos fundamentais de forma gradual, clara e contextualizada.
O texto foi elaborado para atender tanto estudantes do ensino médio quanto universitários de cursos introdutórios em exatas, ciências sociais aplicadas e ciências biológicas. Também é indicado para professores que desejam ampliar suas estratégias didáticas ou revisar conteúdos essenciais de maneira sistemática.
Este material está organizado em módulos temáticos que percorrem desde os fundamentos do pensamento científico até conceitos avançados de estatística e modelagem. Cada capítulo oferece explicações conceituais, exemplos práticos e exercícios de fixação, visando à consolidação do aprendizado de forma ativa e reflexiva.
Destaca-se nesta obra o compromisso com uma abordagem interdisciplinar. A matemática aqui não é tratada como um fim em si mesma, mas como ferramenta de compreensão, análise e transformação da realidade. São frequentes os diálogos com a física, a biologia, a economia e outras áreas do conhecimento.
Outro diferencial deste trabalho está na valorização da visualização e da representação gráfica como estratégias de ensino. Figuras, gráficos e esquemas foram criteriosamente inseridos para facilitar o entendimento dos temas abordados, respeitando diferentes estilos de aprendizagem.
A elaboração deste material exigiu ampla pesquisa, revisão técnica e pedagógica. Agradeço aos colegas, alunos e instituições que colaboraram direta ou indiretamente para a construção deste conteúdo, contribuindo com sugestões, críticas e inspirações fundamentais para o aprimoramento da obra.
Que este livro seja mais do que um conjunto de informações: que ele desperte o interesse, a curiosidade e a vontade de aprender. Afinal, compreender a matemática é, também, compreender novas possibilidades de leitura do mundo.
DOI: 10.17632/vpbkb5f4j7
title: Research data

description: This is the original data of the paper "Pullout behavior and influencing mechanisms of Alhagi sparsifolia roots in clayey sand during thawing".
DOI: 10.17632/vpbkb5f4j7.1
title: Research data

description: This is the original data of the paper "Pullout behavior and influencing mechanisms of Alhagi sparsifolia roots in clayey sand during thawing".
DOI: 10.3886/icpsr00002.v2
title: Candidate Name and Constituency Totals, 1788-1990
title: Version 2

description: This data collection provides the names of candidates, political party name and ICPSR party ID code, and the number of votes received by each candidate in the constituency for elections between 1788 and 1990. The data include county-level returns for over 90 percent of all elections to the offices of president, governor, United States representative (1824-1990), and United States senator (1912-1990). The dataset also includes returns for approximately two-thirds of all elections to the offices of president, governor, and United States representative for the period 1788-1823. Returns for one additional statewide office are included beginning with the 1968 elections. Also presented are 1990 data from the District of Columbia election for United States senator and United States representative. The offices of two senators and one representative were created by the "District of Columbia Statehood Constitutional Convention Initiative," which was approved by District voters in 1980. Elections for these offices were postponed until the 1990 general election. The three offices are currently local District positions, which will turn into federal offices if the District becomes a state.
description: ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Checked for undocumented or out-of-range codes..
description: Datasets: 
 
 DS0: Study-Level Files 
 DS1: Data File 
 DS2: SAS Data Definition Statements 
 DS10: ICPSR State and County Codes Based on 1960 FIPS Codes (Text File)
description: United States Historical Election Returns Series
description: Candidates who ran for the offices of president, governor, and United States representative (1824-1990), United States senator (1912-1990), and one additional statewide office, usually attorney general or secretary of state (1968-1990).
DOI: 10.5281/zenodo.15267438
title: Public Data for "A Long Leg and a Short Leg Make for a Wobbly Equilibrium"

description: Data should be downloaded and saved under `data/public` in order to work with provided code. The makefile in the replication package includes a recipe to download these files using `src/download_zenodo.py`.
DOI: 10.17632/4kjz78m7x5.1
title: BDRubberLeaf: A Comprehensive Dataset of Rubber Tree Leaf Diseases from Bangladesh for Agricultural Research

description: The Rubber Leaf Disease Dataset is a comprehensive collection of high-quality images of rubber tree leaves, systematically gathered from a Rubber Garden in Sreemangal Upazila, Moulvibazar District, Bangladesh, between December 23 and December 27, 2024. The dataset consists of four distinct classes: Anthracnose, Dry Leaf, Healthy Leaf, and Leaf Spot, which represent various stages of both diseased and healthy conditions in rubber tree leaves. The total dataset contains 1,740 images, with class-wise distribution as follows: Anthracnose (300 images), Healthy Leaf (506 images), Dry Leaf (450 images), and Leaf Spot (484 images). The images were captured using the Realme 6i smartphone in natural lighting conditions, ensuring high resolution and clarity. The original images were captured in jpg format at a resolution of 4000 × 3000 pixels, later resized to 640 × 480 pixels with a resolution of 72 dpi to standardize the dataset. Although the dataset does not include annotations, it serves as a valuable resource for researchers and machine learning practitioners focused on plant disease classification and early disease detection in rubber trees. This dataset is particularly relevant for applications in precision agriculture and automated plant pathology analysis, where understanding leaf conditions can play a critical role in improving crop health management strategies.
DOI: 10.17632/tgmgzw3bsn.1
title: Lithium concentration and isotopic data from hydrothermal experiments on basaltic glass and gabbro with synthetic seawater (150–300 °C)

description: This dataset provides lithium (Li) concentrations and isotopic compositions (δ⁷Li) in both solid and fluid phases from 23 controlled hydrothermal experiments conducted at 150–300 °C and water-to-rock ratios of 10 and 100. The experiments involved fresh basaltic glass from the East Pacific Rise (EPR) and gabbro from the Southwest Indian Ridge (SWIR), reacted with synthetic seawater. The dataset includes time-series results for basaltic glass at 250 °C and 300 °C over durations of 3–30 days, as well as final-state measurements at multiple temperatures. It also contains BET surface area data, SEM and XRD mineralogical characterization results, and major and trace elemental compositions of starting materials and reacted solids. This dataset supports the GCA manuscript “L. Li et al., 2025, Li partitioning and isotope fractionation in basaltic glass, gabbroic rocks and synthetic seawater: new experimental constraints on Li behavior in oceanic crust” and underpins interpretations regarding temperature-dependent Li uptake, mineral-fluid partitioning, and isotopic fractionation during seafloor alteration.
DOI: 10.17632/ckkxx8mdcg.5
title: Kurdish Dataset for Stance Detection

description: This dataset comprises 2,174 Sorani Kurdish news articles scraped from the Rudaw website between March 2024 and February 2025. The articles span two primary domains—economy and politics—and include metadata such as title, content, publication date, link, accessed date, and category label.

To support stance detection research in a low-resource language, we implemented a multi-stage annotation pipeline:

Target Identification: Articles were first processed using a Python-based system that leveraged a curated lexicon of 2,456 domain-specific terms to detect the main topic (e.g., "currency", "election").

We used a stance lexicon of 4,243 verbs and adjectives to automatically assign a stance label—support, oppose, or neutral—to each article. For ambiguous cases, we applied semantic similarity (via Sentence Transformers) and zero-shot classification as fallback strategies.

Manual Validation: All articles were manually reviewed and refined by four native Sorani Kurdish experts—two specializing in economics and two in political journalism. The whole dataset was checked through group discussions, and the agreement between the annotators (Cohen’s kappa) was 0.90 for economy articles and 0.93 for politics, which shows that the final annotations are reliable.

The final dataset includes fields for article title, content, publication metadata, identified target topic, and stance label. We provide all related code in a separate folder to ensure reproducibility.
DOI: 10.17632/mt4mj23j73.10
title: Planetary Health: A Comprehensive View of Food in Brazil - PHFood Brazil

description: This dataset is a result of the "Integrating national open databases for a comprehensive view on food, environment and health in Brazil", an initiative that integrates diverse national open databases to provide insights into food production, consumption, environmental impact, and public health in Brazil from 1974 to 2022. The primary hypothesis behind the dataset is that analyzing food systems, nutrition, and agricultural practices over time will reveal patterns that can inform sustainable food policies and health interventions.
We hypothesize that by aggregating and harmonizing data from various national sources, it will be possible to identify critical relationships between food production, nutrient availability, and environmental sustainability. This integrated dataset allows us to evaluate how agricultural practices and food consumption patterns have evolved in response to changing environmental, economic, and societal conditions in Brazil.
Food Production and Nutrient Data: The dataset includes detailed information on harvested areas, food production (in tons), and nutrient availability (e.g., energy, protein, fiber, vitamins, and minerals) for various food groups across different Brazilian regions and states.
Water and Environmental Data: Water usage, deficit, and environmental impact data are linked to agricultural activities, allowing the assessment of water efficiency in food production.
Pesticides and Residue Monitoring: Information on pesticide usage, maximum residue levels (MRL), and residue percentage in food items is provided, with additional details on authorized pesticide types, toxicity classifications, and environmental risks. Food Consumption: Data on food acquisition and consumption patterns, broken down by food groups (e.g., beans, vegetables, fruits), are presented, highlighting dietary trends across various population groups.
Data Collection and Methodology: The dataset was constructed by linking several government datasets, including agricultural statistics, water use reports, and residue monitoring programs. Each dataset was meticulously harmonized to ensure compatibility and completeness, following Extract, Transform, Load (ETL) processes. The data was collected over several decades, representing longitudinal trends in food systems and health. The harmonization process ensures that all data fields are consistent and comparable across time and regions.
Interpretation and Use: This dataset can be used to explore the connections between food systems, health, and the environment. It supports studies in agrifood systems, sustainability, public health, and climate change. Researchers can investigate the impacts of food production on nutrient availability, water consumption, and pesticide use over time. It can also be used to model future food system sustainability under different climate scenarios and dietary patterns, contributing to the development of food policies that balance human and planetary health.
DOI: 10.17632/mt4mj23j73.7
title: Planetary Health: A Comprehensive View of Food in Brazil - PHFood Brazil

description: This dataset is a result of the "Integrating national open databases for a comprehensive view on food, environment and health in Brazil", an initiative that integrates diverse national open databases to provide insights into food production, consumption, environmental impact, and public health in Brazil from 1974 to 2022. The primary hypothesis behind the dataset is that analyzing food systems, nutrition, and agricultural practices over time will reveal patterns that can inform sustainable food policies and health interventions.
We hypothesize that by aggregating and harmonizing data from various national sources, it will be possible to identify critical relationships between food production, nutrient availability, and environmental sustainability. This integrated dataset allows us to evaluate how agricultural practices and food consumption patterns have evolved in response to changing environmental, economic, and societal conditions in Brazil.
Food Production and Nutrient Data: The dataset includes detailed information on harvested areas, food production (in tons), and nutrient availability (e.g., energy, protein, fiber, vitamins, and minerals) for various food groups across different Brazilian regions and states.
Water and Environmental Data: Water usage, deficit, and environmental impact data are linked to agricultural activities, allowing the assessment of water efficiency in food production.
Pesticides and Residue Monitoring: Information on pesticide usage, maximum residue levels (MRL), and residue percentage in food items is provided, with additional details on authorized pesticide types, toxicity classifications, and environmental risks. Food Consumption: Data on food acquisition and consumption patterns, broken down by food groups (e.g., beans, vegetables, fruits), are presented, highlighting dietary trends across various population groups.
Data Collection and Methodology: The dataset was constructed by linking several government datasets, including agricultural statistics, water use reports, and residue monitoring programs. Each dataset was meticulously harmonized to ensure compatibility and completeness, following Extract, Transform, Load (ETL) processes. The data was collected over several decades, representing longitudinal trends in food systems and health. The harmonization process ensures that all data fields are consistent and comparable across time and regions.
Interpretation and Use: This dataset can be used to explore the connections between food systems, health, and the environment. It supports studies in agrifood systems, sustainability, public health, and climate change. Researchers can investigate the impacts of food production on nutrient availability, water consumption, and pesticide use over time. It can also be used to model future food system sustainability under different climate scenarios and dietary patterns, contributing to the development of food policies that balance human and planetary health.
DOI: 10.17632/tpjvfbbzkk
title: bitfinex_api_BTCUSD_5m

description: bitfinex_api_BTCUSD_5m
DOI: 10.17632/tpjvfbbzkk.1
title: bitfinex_api_BTCUSD_5m

description: bitfinex_api_BTCUSD_5m
DOI: 10.6084/m9.figshare.29161676
title: Zipped folder containing Excel files for Ogren et al, 2025

description: Effect of estradiol on microtubule growth
DOI: 10.15468/dl.gsfyd3
title: Occurrence Download

description: A dataset containing 90836 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Oreochromis niloticus (Linnaeus, 1758))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 90836 records from 171 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004032-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/mhnt8k8nyc.1
title: Data: Energy conversion efficiency peaks at intermediate flight speed in a migratory songbird

description: Albeit costly, flight allows birds to travel great distances in short time, making it a highly effective mode of locomotion, especially during migration. Understanding how birds use energy during flight is essential for studying their flight ecology. To fly, birds flap their wings accelerating surrounding air and generating the flight forces, where the rate of energy added to the wake represents flight mechanical power (Pmech). For flapping, birds utilize chemical energy in their flight muscles, which along with the metabolism of other body functions, constitutes the flight metabolic power (Pmet). The ratio between Pmech and Pmet is the energy conversion efficiency (ɳ), which depends on the muscle’s ability to convert fuel into work (the rest being dissipated as heat), and on the energy losses during aerodynamic force production. Due to lack of direct measurements, ɳ has been assumed constant across speeds (23%) or relied upon modelling. Here we estimated, in vivo, ɳ from direct measurements of Pmet and Pmech using the 13C-labelled sodium bicarbonate method and particle image velocimetry, respectively, in thrush nightingales flown in a wind tunnel. We found that ɳ varied as a concave function with flight speed, with a maximum ɳ (15.3% at 7.4 m s-1 for weight-specific power) occurring at ecologically relevant flight speeds. Our findings suggest tuning of performance to speeds most relevant for efficient transportation, with implications for modelling flight power based on mechanical models, as ɳ, a fundamental attribute in bird flight energetics, varies across flight speeds.

We provide the data sets used for metabolic and mechanical power measurements, from which energy conversion efficiency was calculated. 
Also we provide a figure compiling all the NaBi experiments included in the analysis as well as the calibration experiment for the NaBi method.
DOI: 10.17632/vdd88gxcm6.1
title: The ionotropic AMPA receptor contributes to autoimmunity via altered regulatory T cell differentiation and function

description: Original Western blot images.
DOI: 10.17632/x5fj5xz47k
title: Trump's Executive Orders - Jan to May 1st 2025

description: Executive orders were extracted from the official repository of the White House, available at https://www.federalregister.gov/presidential-documents/executive-orders, and accessed on May 1st - covering the entire period of Donald J. Trump’s administration up to that date. All executive orders were manually reviewed and classified based on their relevance to trade tariffs, fentanyl, or both, and then organized in a structured spreadsheet for analysis.
DOI: 10.17632/x5fj5xz47k.1
title: Trump's Executive Orders - Jan to May 1st 2025

description: Executive orders were extracted from the official repository of the White House, available at https://www.federalregister.gov/presidential-documents/executive-orders, and accessed on May 1st - covering the entire period of Donald J. Trump’s administration up to that date. All executive orders were manually reviewed and classified based on their relevance to trade tariffs, fentanyl, or both, and then organized in a structured spreadsheet for analysis.
DOI: 10.17632/9wy4zpb3x4
title: PangaFlyIMG

description: The identification and counting of fish are important tools for managing the stock, production, and marketing of aquaculture fish. In commercial establishments, the counting of fingerlings has traditionally been done manually, which can cause stress to the animals and to the labor, in addition to low precision. Automation using computer vision and deep learning models is being increasingly explored. In machine learning for fish detection and counting, a dataset with images of specimens is needed to train the neural network. This dataset with species from the Panga family will be relevant in studies involving learning and training on different types of neural networks for counting and detection. The images were captured at a fish retailer. The company provided the location, the container, and the specimens, with an average length of 3.5 cm. 10 Panga fry were placed in a water container with a blue bottom, measuring 40 cm in diameter, 20 cm in height, and with a total capacity of 25 liters. The camera used to capture the images was fixed at the top, at a height of 60 cm from the container. The camera used was an iPhone XR with 12 megapixels and a resolution of 4608 × 2592 to capture the images. A total of 1,000 images were captured. The images present in the dataset are comprehensive, some have obstructions, low sharpness, and the water used in the container comes from the very recirculation system where the fry were raised, making the database more robust and closer to reality.
DOI: 10.17632/9wy4zpb3x4.1
title: PangaFlyIMG

description: The identification and counting of fish are important tools for managing the stock, production, and marketing of aquaculture fish. In commercial establishments, the counting of fingerlings has traditionally been done manually, which can cause stress to the animals and to the labor, in addition to low precision. Automation using computer vision and deep learning models is being increasingly explored. In machine learning for fish detection and counting, a dataset with images of specimens is needed to train the neural network. This dataset with species from the Panga family will be relevant in studies involving learning and training on different types of neural networks for counting and detection. The images were captured at a fish retailer. The company provided the location, the container, and the specimens, with an average length of 3.5 cm. 10 Panga fry were placed in a water container with a blue bottom, measuring 40 cm in diameter, 20 cm in height, and with a total capacity of 25 liters. The camera used to capture the images was fixed at the top, at a height of 60 cm from the container. The camera used was an iPhone XR with 12 megapixels and a resolution of 4608 × 2592 to capture the images. A total of 1,000 images were captured. The images present in the dataset are comprehensive, some have obstructions, low sharpness, and the water used in the container comes from the very recirculation system where the fry were raised, making the database more robust and closer to reality.
DOI: 10.17632/ck5khk5gjh.1
title: Particle-size fractions of soil organic carbon, microbial and mineral properties of Chernozem topsoil (0–10 cm) under different tillage systems in the Samara region of Russia (Original data)

description: Database includes measured data from 90 spatial sampling points on particle-size fractions of soil organic carbon (POM, MAOM), microbial properties (microbial biomass carbon, basal respiration), soil texture (silt, clay) and mineral composition of Chernozem topsoil (0–10 cm) under conventional tillage and no-tillage (Samara region, Russia). Date of soil sampling was October 2022.