Data in Brief最新文献

{"title":"ALERT: A benchmark Bengali dataset for identifying and categorizing religiously aggressive texts","authors":"Suhana Binta Rashid ,&nbsp;Bibhas Roy Chowdhury Piyas ,&nbsp;Sadia Rahman ,&nbsp;Bijoy Roy Chowdhury Preenon","doi":"10.1016/j.dib.2025.112094","DOIUrl":"10.1016/j.dib.2025.112094","url":null,"abstract":"<div><div>The widespread proliferation of religiously aggressive contents on social media platforms poses significant threats to societal harmony and communal solidarity. It often incites religious animosity, provokes violence and disseminates life-threatening messages that intensifies societal divisions and undermines social harmony. Despite significant advancements in identifying such contents in high-resource languages like English, there exists a notable scarcity of resources for regional languages like Bengali which constrains the development of effective detection and prevention tools. To address this gap, we introduce ALERT (Analysis of Linguistic Extremism in Religious Texts), a newly developed Bengali dataset along with English translation which includes 4027 annotated instances classified into four categories: hate speech (995), vandalism (909), atrocity (1117), and no aggression (1006). The dataset was sourced from many online platforms, including Facebook, YouTube, online news websites, blogs and group chats. Each of the instances in the dataset was annotated by any two annotators from the list of four having diverse religious, ethnic, geographical, and academic backgrounds. Any conflicts or disagreements between annotators during the annotation process were resolved through consultation with a domain expert. The preprocessing stages include the elimination of English words, duplication and alphanumeric characters to ensure data integrity. The dataset attains a Cohen’s kappa score of 72 % that signifies a strong inter-annotator agreement and a Jaccard similarity score between 16 % and 23 % which reflects the degree of overlap between classes. Moreover, Experiments with various machine learning, deep learning and transformer-based models yield promising results. ALERT serves as a benchmark dataset for religiously aggressive text classification that may contribute to the advancement of research in this field. The dataset is publicly accessible for research purposes to promote innovation and collaboration within the Bengali NLP community.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112094"},"PeriodicalIF":1.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145218708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microbial Community Profiles of Biofilms from Hot Springs: 16S and 18S rRNA Amplicon Sequencing Data.","authors":"Nur Azmira Alea Nurhazli, Jia Hao Tan, Mohd Farizal Kamaroddin, Mohd Shahir Shamsir, Amira Suriaty Yaakop, Kian Mau Goh","doi":"10.1016/j.dib.2025.112093","DOIUrl":"10.1016/j.dib.2025.112093","url":null,"abstract":"<p><p>This article presents microbial diversity data from biofilms collected from the sides or outflows of several Malaysian hot springs, with temperatures ranging from 38 to 56 °C and pH values between 7.1 and 8.7. Genomic DNA was extracted from the biofilms and subjected to 16S V3-V4 and 18S V4 amplicon sequencing using the Illumina NovaSeq 6000 platform. Reads were processed with various bioinformatic tools including QIIME2, and eventually, amplicon sequence variants (ASVs) were identified. In almost all analyzed biofilms, approximately 50% of the total ASVs belonged to <i>Cyanobacteriota</i> and <i>Chloroflexota,</i> except for one biofilm, labeled DTO, which was dominated by <i>Pseudomonadata</i> and <i>Cyanobacteriota</i>. Besides bacteria, the data also suggest the presence of various eukaryotic organisms, including small animals such as nematodes, rotifers, and arthropods; fungi and fungus-like organisms such as <i>Ascomycota, Zoopagomycota, Oomycota,</i> and <i>Cryptomycota</i>; as well as photosynthetic eukaryotes from the <i>Viridiplantae</i> group. This dataset serves as a valuable resource for microbial ecology studies in hot spring biofilms and is openly available for reuse, providing a foundation for future research on microbial diversity and functional roles in geothermal ecosystems.</p>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"62 ","pages":"112093"},"PeriodicalIF":1.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12495045/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145231740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Air-to-ground channel dataset via UAV-aided measurements in multiple scenarios","authors":"Hangang Li ,&nbsp;Kai Mao ,&nbsp;Xiaomin Chen ,&nbsp;Hanpeng Li ,&nbsp;Hanwen Xu ,&nbsp;Shaolong Zhang ,&nbsp;Boyu Hua ,&nbsp;Qiuming Zhu","doi":"10.1016/j.dib.2025.112086","DOIUrl":"10.1016/j.dib.2025.112086","url":null,"abstract":"<div><div>Low-altitude communication networks are emerging to facilitate reliable connectivity for aerial platforms, where a deep understanding of the radio propagation channel is fundamental for the design and optimization of the communication systems. In this study, a self-developed air-to-ground (A2G) channel sounder is employed to conduct field measurements under three typical communication scenarios, i.e., sports field, farmland, and over-water. In each scenario, channel measurement data are collected at different flight heights of the unmanned aerial vehicle (UAV), i.e., 10 m and 15 m. A dataset of measured channel impulse responses (CIRs) is constructed accordingly. Under each scenario, hundreds of CIR snapshots are recorded, where each CIR snapshot has a size of 1 × 200. Each CIR snapshot is also labeled with corresponding global positioning system (GPS) locations and time, where time represents the seconds elapsed since the start of the measurement. All data are stored in .xls format. Unlike most existing A2G channel measurement datasets that are limited to a single scenario or UAV altitude, our dataset simultaneously encompasses diverse scenarios and multiple flight heights at 3.6 GHz, which enhances its value for reproducibility and broad applicability in future channel modeling and system-level evaluations. The dataset is validated through on-site monitoring and repeated measurements when anomalies were detected, and its practical utility is demonstrated through the analysis of power delay profiles and path loss. This dataset provides a realistic representation of height-dependent A2G channel characteristics in diverse environments and reveals both the propagation delay and attenuation of multipath components, offering direct insights into the fundamental behavior of A2G propagation. The dataset also offers valuable references for system design and optimization of the A2G link of the low-altitude communication.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112086"},"PeriodicalIF":1.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145218710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A geocoded dataset of primary health care clinics in Brazil","authors":"Bruno Wichmann ,&nbsp;Roberta Moreira Wichmann ,&nbsp;Tiago Almeida de Oliveira ,&nbsp;Crysttian Arantes Paixão","doi":"10.1016/j.dib.2025.112085","DOIUrl":"10.1016/j.dib.2025.112085","url":null,"abstract":"<div><div>We develop a geocoded dataset of primary health care clinics in Brazil. We merge data from three publicly available sources. The first is the National Registry of Healthcare Facilities (CNES-ST), which collects the location (state, municipality, and 8-digit postal code) of all health care facilities, public or private, operating in Brazil. The second is the National Registry of Addresses for Statistical Purposes (IBGE-CNEFE), which contains the geographic coordinates of all addresses in Brazil (including 8-digit postal codes) and serves as the basis for the Brazilian census. Our approach aggregates individual (address-level) coordinates to the 8-digit postal code, and assigns coordinates to primary care clinics based on each clinics’ postal code. Using data from a third source, the IBGE shapefiles, we estimate the area of postal codes to evaluate the precision of our geo-referencing method. The unique facility identification number (cnes number) can be used to merge our georeferenced data with other publicly available databases of the Brazilian Unified Health System. The final dataset is an unbalanced panel with monthly observations about 293,698 primary care clinics’ locations (i.e. coordinates), from January 2018 to December 2023, totalling 15,455,219 observations.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112085"},"PeriodicalIF":1.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145218808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Survey data on ventilation provision and use in homes in Great Britain","authors":"Cairan A. Van Rooyen ,&nbsp;Tim Sharpe","doi":"10.1016/j.dib.2025.112090","DOIUrl":"10.1016/j.dib.2025.112090","url":null,"abstract":"<div><div>This article describes data collected from an online questionnaire survey of 2, 039 adults in England, Wales, and Scotland (Great Britain) to assess the provision and use of mechanical ventilation, trickle vents, and windows in their homes. The survey was deployed on the 17th of June 2022 and collected data across four categories: socioeconomic and demographic characteristics, dwelling features, ventilation practices, and other contextual factors. The questionnaire included 65 questions and had a median completion time of 12 minutes, with all respondents completing the survey.</div><div>The dataset is broadly representative of the British population and housing typologies. It provides valuable insights into the relationships between dwellings, occupants, their ventilation provision, and behaviours. The data is stored in a comma-separated values (.csv) file containing 396 variables, with responses formatted as binary, continuous, discrete, categorical, and free-text.</div><div>This dataset can be utilised by academics for indoor environmental quality and energy modelling to refine assumptions about ventilation provision and practices. Public health professionals can use the data to estimate the health impacts of exposure to indoor pollutants, which can result from poor ventilation provision and to develop targeted health information. Government can use this evidence to inform policies and strategies aimed at improving ventilation in existing homes. The dataset is accessible through the Mendeley Data repository.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112090"},"PeriodicalIF":1.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145218704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dataset on characterisation of microbiome of prostate tissue and expressed prostatic secretions","authors":"Olayemi O. Akinnola ,&nbsp;Abosede E. Samuel ,&nbsp;Conrad A. Omonhinmin","doi":"10.1016/j.dib.2025.112098","DOIUrl":"10.1016/j.dib.2025.112098","url":null,"abstract":"<div><div>Prostate cancer (PCa) is the second most prevalent cancer in men, particularly affecting those of Black African descent. Nigeria currently has the fourth highest risk for PCa mortality in the world. The microbiome of the prostate has emerged as a critical factor in understanding the aetiology and progression of prostate diseases, such as prostate cancer (PCa), benign prostatic hyperplasia (BPH) , benign stromal hyperplasia (BSH) and prostatitis (PRO). This study to comparatively characterise the microbiome present in prostate tissue and expressed prostatic secretion (EPS) from 30 study subjects diagnosed with PCa, BPH, BSH and PRO and sampled from the urology clinic of Lagos State University Teaching Hospital Ikeja. Bacterial species community composition and diversity were analysed based on 16S rRNA metagenome nucleotide data to ensure the accuracy, reproducibility, and broader applicability of microbiological and genomic research. Data information allows for precise identification of organisms at the species or strain level, essential for verifying experimental results and comparisons of the isolated organism's genome with related strains, providing insights into genetic diversity, virulence factors, and metabolic pathways of the sample population microbiome.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112098"},"PeriodicalIF":1.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145218707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dataset of transcribed Indonesian stand-up comedy videos with audience laughter annotations from Kompas TV’s YouTube channel","authors":"Supriyono ,&nbsp;Aji Prasetya Wibawa ,&nbsp;Suyono ,&nbsp;Fachrul Kurniawan ,&nbsp;Andri Pranolo ,&nbsp;Nahdi Saubari ,&nbsp;Kunfeng Wang","doi":"10.1016/j.dib.2025.112079","DOIUrl":"10.1016/j.dib.2025.112079","url":null,"abstract":"<div><div>This dataset presents a large-scale compilation of Indonesian stand-up comedy video transcripts collected from Kompas TV’s official YouTube channel. A total of 3934 videos were processed, capturing over 2.8 million words, 6124 sentences, and 17,394 annotated audience laughter events. Each entry includes the video title, URL, the number of laughter instances, the original transcript, and a cleaned version suitable for downstream natural language processing (NLP) tasks. Data collection employed Python-based web scraping, followed by pre-processing routines such as timestamp and tag removal, whitespace normalization, and character cleaning. The dataset supports research in humor detection, speech emotion recognition, and cultural studies of performative discourse in Indonesian. It is particularly valuable for low-resource language NLP development and training models on informal spoken content. Researchers may utilize the dataset for sentiment analysis, summarization, laughter prediction, and sociolinguistic exploration. This openly accessible resource is hosted on Mendeley Data and adheres to ethical standards, with no personal identifiers and full compliance with platform redistribution policies. The dataset fills a notable gap in Indonesian language corpora, particularly in the entertainment and humor domain, providing a foundation for both academic and applied research in computational linguistics and human-cantered AI.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112079"},"PeriodicalIF":1.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145263597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data showing effects of resolvin D5 on prostaglandin E2 mediated inhibition of fMet-Leu-Phe induced activation of the NADPH oxidase in human neutrophils","authors":"Wenyan Li ,&nbsp;Claes Dahlgren ,&nbsp;Huamei Forsman","doi":"10.1016/j.dib.2025.112080","DOIUrl":"10.1016/j.dib.2025.112080","url":null,"abstract":"<div><div>Regulation of the reactive oxygen species (ROS) producing NADPH oxidase, expressed in neutrophils, is essential for a balance between the proinflammatory antimicrobial host defence and the resolving reactivity that limits tissue destructing inflammatory processes. Peripheral blood neutrophils of healthy adults were isolated from buffy coats obtained from the blood bank at Sahlgrenska University Hospital, using a standard density-gradient centrifugation protocol. The neutrophils were activated by fMet-Leu-Phe (fMLF) a peptide recognized by formyl peptide receptor 1 (FPR1). Signals generated downstream of the agonist occupied FPR1 activate the NADPH oxidase in the neutrophil plasma membrane. The release of ROS by fMLF activated neutrophils was measured in real time using a very sensitive isoluminol-amplified chemiluminescence system, expressed in light units (Mega counts per minute; Mcpm), and the peak value levels of the responses were determined. The activation signals generated by FPR1 were inhibited (reduced peak values) by the agonist occupied EP₄, a neutrophil receptor for prostaglandin E₂ (PGE₂). The inhibitory effect of PGE₂ was expected to be increased (positively modulated) by Resolvin D₅ (RvD₅), generated from the omega-3 fatty acid docosahexaenoic acid and a member of the group of specialized pro-resolving lipids. The dataset presented in the article includes raw data on the effects of RvD₅ on the inhibitory activity of PGE₂. The reuse of data indicating a lack of inhibition of a negative allosteric modulator on ROS production in neutrophils is high and multifaceted across several different research domains such as drug development (drug effects lies elsewhere or should be re-evaluated) and immunological research (neutrophil studies and animal models and as reference for testing the robustness or specificity of other ROS-detecting assays or biosensors).</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112080"},"PeriodicalIF":1.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A dataset for climate, land, energy and water systems modelling in Lao PDR","authors":"Annie Flint Smith ,&nbsp;Kane Alexander ,&nbsp;Fernando A. Plazas-Niño ,&nbsp;Mark Howells","doi":"10.1016/j.dib.2025.112084","DOIUrl":"10.1016/j.dib.2025.112084","url":null,"abstract":"<div><div>Policymaking often treats economic and resource sectors in isolation of one another, neglecting to consider the interconnections between a country’s climate, land, energy and water (CLEW) systems. This approach can lead to system inefficiencies and unintended consequences, as the synergies and trade-offs between sectors are overlooked. A nexus-thinking approach addresses this issue by considering multiple resources and their interlinkages in the analytical and decision-making processes, enabling policymakers to make more informed decisions. This article presents a dataset containing techno-economic data inputs specific to the Lao PDR’s (Laos’) CLEW systems, in the context that Laos’ policymaking has traditionally treated sectors independently. The CLEWs systems data were collected from various open-access resources, including online repositories and national reports, with the objective to facilitate integrated resource system modelling assessments for Laos that incorporate a nexus-thinking approach. To support this objective, this article also describes the calculations used to process raw data to meet typical systems modelling software requirements, using the Open-Source Energy Modelling Systems (OSeMOSYS) framework as a reference. By including greenhouse gas emission factors, this dataset provides the basis for long-term scenario planning that can inform Laos’ national decarbonisation strategy, whilst accounting for other potential cross-sector dynamics. The structure and documentation of this dataset also has significant reuse potential, as it lays the foundation for other researchers to replicate similar CLEW datasets for resource system assessments in other countries with similar economic and environmental backgrounds.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112084"},"PeriodicalIF":1.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145263481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Environmental Protection Agency (EPA) Dynamically Downscaled Ensemble (EDDE) version 2: A 3D physics-based dataset for projections of future extreme weather events","authors":"Megan S. Mallard ,&nbsp;Tanya L. Spero ,&nbsp;Jared H. Bowden ,&nbsp;Jeff Willison ,&nbsp;Kathy Brehme ,&nbsp;Lara J. Reynolds","doi":"10.1016/j.dib.2025.112070","DOIUrl":"10.1016/j.dib.2025.112070","url":null,"abstract":"<div><div>The U.S. Environmental Protection Agency (EPA) Dynamically Downscaled Ensemble version 2 (EDDEv2) contains 3D physics-based projections of future conditions and extreme events over a model domain with 12-km grid spacing covering most of North America and focusing on the contiguous U.S. (CONUS). The Weather Research and Forecasting (WRF) model is used to downscale global projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over a 30-year historical period (1985–2014) and a 75-year future period (2025–2099) under multiple Shared Socioeconomic Pathways. The output from WRF is further processed to create self-describing netCDF files conforming to the Climate and Forecasting System (CF) standards. A subset of EDDEv2 data is available with free egress via Amazon Web Services (AWS) Open Data Project at temporal frequencies ranging from 5 min to monthly. In addition to key variables like precipitation and 2-m temperature, EDDEv2 also contains other dynamically consistent atmospheric and soil fields that can support subsequent modeling applications, including humidity, winds, radiative variables, heat fluxes, and soil temperature and moisture, among others. The continuous, high-frequency data through the end of the century make EDDEv2 well-suited to explore potential changes to localized extreme events that can occur over a range of timescales, including heat extremes and flooding. The use of a large suite of variables facilitates modeling potential impacts on agriculture, infrastructure, and ecosystems, among other applications.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112070"},"PeriodicalIF":1.4,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}