Data in Brief最新文献

{"title":"Plastic debris dataset on the Seine riverbanks: up to 38,000 pre-production plastic pellets reported per square meter","authors":"Romain Tramoy ,&nbsp;Laurent Colasse ,&nbsp;Johnny Gasperi ,&nbsp;Bruno Tassin","doi":"10.1016/j.dib.2025.111735","DOIUrl":"10.1016/j.dib.2025.111735","url":null,"abstract":"<div><div>Plastic pollution in rivers is a major source for plastic pollution into the ocean. However, it is now recognized that plastics may accumulate in rivers for years, especially in estuaries, before reaching the ocean. This long residence time favours fragmentation of macroplastics into smaller and smaller pieces, but relative data are still carse. Here we present data from the downstream part of the Seine estuary in a historical deposit full of plastic debris, with the highest concentration of industrial plastic pellet ever reported in France. Plastic debris (down to 6 mm according to sieving limits) were classified using the updated European classification J-list. The sampled site is located close to the river mouth within a national natural reserve, surrounded by international harbour activities and two major industrial plastic producers: Total Energy and Exxon Mobil. A surface of only 1 m² was sampled in a visual maximum of plastic pollution. Over 100,000 plastic debris were counted or estimated when it comes to plastic debris &lt;6 mm. Items were classified and weighted by category for a total mass higher than 4 kg. By mass (count), 24 % (38 %) of total plastic debris were pre-production plastic pellets, 21 % (1 %) were unidentified, colourful, plastic fragments (<em>≥</em><span><math><mspace></mspace></math></span>2.5 cm), and 19 % (33 %) were unidentified, colourful, plastic fragments (&lt;2.5 cm).</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111735"},"PeriodicalIF":1.0,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242659","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 on investigation of metabolomics and ionomics of Humulus lupulus grown in India","authors":"Tripti Singh,&nbsp;Ashwani Mathur","doi":"10.1016/j.dib.2025.111737","DOIUrl":"10.1016/j.dib.2025.111737","url":null,"abstract":"<div><div>The article reports data on chemical profiling of aqueous, methanolic, and n-hexane extract of field cultivated male <em>Humulus lupulus</em> using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). Also, the elemental profiling of the soil was carried out using Inductively coupled plasma mass spectrometry (ICP-MS). The elemental analysis revealed the soil to be rich in iron, calcium, magnesium, sodium, and potassium while trace elements like copper, cobalt, zinc, and molybdenum comparatively were found to be in lesser amounts. The diverse catalogues of compounds, identified in plant extracts, belong to different phytocompound groups, including phenolics, flavonoids, fatty acids, and alcohol derivatives. The compounds, such as Trans-2-methyl-4-n-pentylthiane, 2-Azido-2,4,4,6,6,8,8-heptamethylnonane were identified (with a similarity score &gt; 65) in n-hexane, while compounds like Arsenous acid, tris(trimethylsilyl) ester and (Tris(tert-butyldimethylsilyloxy) arsane were identified in methanolic extract. The aqueous extract revealed compounds such as 2-Amino-1,3,4-octadecanetriol and Safingol with the highest peak area run in positive mode while Oleanolic acid and Gingerol have the highest peak area run in negative mode. The suggestive association between soil elemental composition, abiotic factors and plant germplasm, on phytochemical profile is proposed.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111737"},"PeriodicalIF":1.0,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144291204","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":"Experimental dataset of fluid flow and heat transfer in a shallow packed bed at low Reynolds numbers","authors":"Anika Weber ,&nbsp;Sebastian Schürg ,&nbsp;Timo Roeder ,&nbsp;Johannes Grobbel ,&nbsp;Martina Neises-von Puttkamer ,&nbsp;Christian Sattler","doi":"10.1016/j.dib.2025.111743","DOIUrl":"10.1016/j.dib.2025.111743","url":null,"abstract":"&lt;div&gt;&lt;div&gt;This article presents an experimental campaign on the transient behaviour of a packed bed, which is filled with spherical particles and is subjected to heating and cooling with air as the heat transfer fluid. The investigation focuses on a shallow bed with a diameter twice its height, a geometry alike to cost effective thermal energy storage systems, where the bed-to-particle diameter ratio is typically also large.&lt;/div&gt;&lt;div&gt;The packed bed is heated from ambient temperature to temperatures up to &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mn&gt;773&lt;/mn&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mi&gt;K&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; using hot air from an air heater. Then, when a specified shutdown criterion is reached, the heater is turned off and the bed is cooled by air with nearly ambient temperature. Following this procedure, 9 experiments have been conducted. The fluid velocity into the packed bed was conditioned to be almost homogeneous, which is achieved by wire screens and checked for in detailed flow pretests.&lt;/div&gt;&lt;div&gt;For each of the 9 experiments, the generated data consists of measurements of various temperatures, pressures, ambient conditions and air mass flow, all collected about 60 times per second during the whole experiment, i.e. from the beginning of heating to the end of cooling, which takes up to 300 minutes. Operational data of heater and blower are saved as well. Data is presented in form of tables (CSV,ASCII).&lt;/div&gt;&lt;div&gt;To collect the data, extensive instrumentation is employed, including more than 40 thermocouples, which are placed within the packed bed at multiple circumferential, radial, and axial positions and within the insulation, as well as above and below the bed. Pressure transducers are installed up- and downstream of the packed bed. A long-range infrared camera has an unobstructed view to the bed surface, enabling the investigation of average bed surface temperature, and thus, adding value to the point measurement data of the thermocouples.&lt;/div&gt;&lt;div&gt;Additionally, the publication includes data on material properties of insulation and particles. For example, bulk density was measured by pouring particles in a defined volume and measuring their mass. Particle size distribution and sphericity is evaluated based on image analysis and 3614 random selected particles. Here, raw data of the evaluation as well as the respective images can be found in the accompanying data set. Regarding other data such as specific heat capacity and thermal conductivity, relevant information is presented in form of equations and values. Particle emissivity is measured in-house with a simplified experimental setup, that is adaptable to other materials.&lt;/div&gt;&lt;div&gt;The detailed presentation of experimental methodology, material properties, flow pretests with and without fluid homogenization screens installed, and exemplary result description, ensures the results are suitable for validating advanced models such as detailed simulations based on Computational Fluid Dynamics (CFD) coupled with th","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111743"},"PeriodicalIF":1.0,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263683","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":"DiaBD: A diabetes dataset for enhanced risk analysis and research in Bangladesh","authors":"Tabia Tanzin Prama ,&nbsp;Md. Jobayer Rahman ,&nbsp;Marzia Zaman ,&nbsp;Farhana Sarker ,&nbsp;Khondaker A. Mamun","doi":"10.1016/j.dib.2025.111746","DOIUrl":"10.1016/j.dib.2025.111746","url":null,"abstract":"<div><div>Diabetes is a chronic condition affecting millions worldwide and severely impacts health and quality of life. According to the International Diabetes Federation (IDF), over 463 million adults, which is 9.3% of the global population, live with diabetes. Diabetes ranks among the most prevalent chronic diseases and was the ninth-leading cause of mortality in 2019, with 4.2 million deaths reported. This article introduces DiaBD, a novel dataset of 5,288 patient records from Bangladesh, designed to address critical gaps in diabetes research and aid in healthcare planning, risk analysis, and predictive modelling. The dataset comprises 14 attributes including age, gender, clinical vitals (pulse rate, systolic and diastolic blood pressure, glucose levels), anthropometrics (height, weight, body mass index (BMI)), family history of diabetes and hypertension, cardiovascular disease (CVD), and stroke, with a dependent attribute, Diabetic, indicates whether an individual has diabetes or not. The dataset ensures demographic diversity and precise measurements, supporting the study of diabetes and its related health issues. Features like CVD and stroke enable broader research on comorbidities. This dataset facilitates machine learning applications, risk assessment, and personalized healthcare strategies. Researchers can explore the links between diabetes, hypertension, CVD, and stroke, while healthcare providers and policymakers can leverage DiaBD to identify trends, allocate resources efficiently, and enhance public health strategies.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111746"},"PeriodicalIF":1.0,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331350","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":"SPAS-Dataset-BD: Dataset for smart precision agriculture system in Bangladesh","authors":"Rup Chowdhury ,&nbsp;Fernaz Narin Nur ,&nbsp;Muhammad Nazrul Islam ,&nbsp;Md. Nazmul Islam ,&nbsp;Prapti Das ,&nbsp;Arafat Sahin Afridi","doi":"10.1016/j.dib.2025.111727","DOIUrl":"10.1016/j.dib.2025.111727","url":null,"abstract":"<div><div>Precision agriculture harnesses data-driven techniques to optimize crop production, resource use, and sustainability. However, low-income countries like Bangladesh face a shortage of localized, high-quality datasets that reflect regional agroclimatic conditions and cropping practices. To address this gap, we present SPAS-Dataset-BD, a robust dataset compiled through a hybrid approach: secondary extraction from the Bangladesh Bureau of Statistics (BBS) 2022 Yearbook and primary on-field surveys of 223 farmers across ten diverse districts. The dataset comprises 4191 records over 73 crop types, with 12 agronomic and environmental features, including underrepresented species. Robustness is demonstrated via threshold-based missing-value handling (&lt;5 % deletion, targeted imputation), hash-based deduplication, and cross-validation against official statistics. We illustrate potential applications, in machine learning (73-class crop classification, yield forecasting) and IoT-driven irrigation scheduling. SPAS-Dataset-BD’s scale, methodological transparency, and contextual richness make it a valuable resource for precision agriculture research and policy-making in South Asia.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111727"},"PeriodicalIF":1.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263676","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 non-linear household loads for Validation of Active Power Filters","authors":"Vrindarani Nuñez-Ramírez ,&nbsp;Néstor F. Guerrero-Rodríguez ,&nbsp;Rafael Omar Batista-Jorge ,&nbsp;Robert Mercado-Ravelo ,&nbsp;Francisco A. Ramírez-Rivera ,&nbsp;Julio A. Ferreira ,&nbsp;Rubén D. Ramos-Ciprian ,&nbsp;Enrique Reyes-Archundia","doi":"10.1016/j.dib.2025.111728","DOIUrl":"10.1016/j.dib.2025.111728","url":null,"abstract":"<div><div>This paper presents a dataset of non-linear household loads in Santo Domingo, Dominican Republic, obtained through a structured data collection and processing methodology. The dataset comprises high-resolution voltage and current waveforms, along with key electrical parameters such as harmonic profiles, voltage, current, frequency, and crest factors. Measurements were conducted using the METREL MI 2883 power quality analyzer on seven representative household devices: a refrigerator, air conditioner, smart TV, microwave oven, smartphone charger, laptop charger, and uninterruptible power supply (UPS). These devices were selected to capture the diversity of modern household loads, which contribute to harmonic distortion and impact power quality. The dataset enables studies on power quality analysis, and harmonic mitigation strategies. It is particularly suited for validating active power filters, modeling real-world non-linear loads in advanced simulations such as Controller Hardware-In-the-Loop (CHIL). The dataset is openly available for further research applications in power system studies, filter design validation, and energy efficiency analysis.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111728"},"PeriodicalIF":1.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242658","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":"Effects of fresh and fermented olive oil solid waste on nitrogen use efficiency in wheat: A dataset","authors":"Abd Al Karim Jaafar ,&nbsp;Akram Al-Balkhi ,&nbsp;Andrés Rodríguez-Seijo","doi":"10.1016/j.dib.2025.111742","DOIUrl":"10.1016/j.dib.2025.111742","url":null,"abstract":"<div><div>Olive Oil Solid Waste (OSW) is a valuable agricultural by-product that can be used as a source of organic matter and nutrients for crops. However, the efficiency of OSW in providing nitrogen to plants depends on its decomposition rate and how nitrogen is available. Here, we investigated the nitrogen utilization coefficient (NUC) from fresh and fermented OSW added to calcareous soil planted with durum wheat (Triticum durum cv Sham 3). Our data showed that the NUC of fermented OSW was significantly higher than that of fresh OSW, with values of 50.15 % and 35.36 %, respectively. This difference was attributed to the enhanced biodegradation of fermented OSW, which resulted in the release of more nitrogen in a form that was readily available for plants.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111742"},"PeriodicalIF":1.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271224","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":"PAP900: A dataset of semantic relationships between affective words in Portuguese","authors":"André Fernandes dos Santos ,&nbsp;José Paulo Leal ,&nbsp;Rui Alexandre Alves ,&nbsp;Teresa Jacques","doi":"10.1016/j.dib.2025.111726","DOIUrl":"10.1016/j.dib.2025.111726","url":null,"abstract":"<div><div>The PAP900 dataset centers on the semantic relationship between affective words in Portuguese. It contains 900 word pairs, each annotated by at least 30 human raters for both semantic similarity and semantic relatedness. In addition to the semantic ratings, the dataset includes the word categorization used to build the word pairs and detailed sociodemographic information about annotators, enabling the analysis of the influence of personal factors on the perception of semantic relationships. Furthermore, this article describes in detail the dataset construction process, from word selection to agreement metrics.</div><div>Data was collected from Portuguese university psychology students, who completed two rounds of questionnaires. In the first round annotators were asked to rate word pairs on either semantic similarity or relatedness. The second round switched the relation type for most annotators, with a small percentage being asked to repeat the same relation. The instructions given emphasized the differences between semantic relatedness and semantic similarity, and provided examples of expected ratings of both.</div><div>There are few semantic relations datasets in Portuguese, and none focusing on affective words. PAP900 is distributed in distinct formats to be easy to use for both researchers just looking for the final averaged values and for researchers looking to take advantage of the individual ratings, the word categorization and the annotator data. This dataset is a valuable resource for researchers in computational linguistics, natural language processing, psychology, and cognitive science.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111726"},"PeriodicalIF":1.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242657","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":"Population data of 23 Y chromosome STR loci for Kyrgyz population from Kyrgyzstan","authors":"Zhainagul Isakova ,&nbsp;Alizhan Bukayev ,&nbsp;Moldobek Irsaliev ,&nbsp;Zhaxylyk Sabitov ,&nbsp;Maxat Zhabagin","doi":"10.1016/j.dib.2025.111706","DOIUrl":"10.1016/j.dib.2025.111706","url":null,"abstract":"<div><div>Y-chromosomal short tandem repeats (Y-STRs) serve as essential markers in forensic genetics, population studies, and paternal lineage reconstruction due to their strict uniparental inheritance and high discriminatory power. Despite their global relevance, Central Asian populations, particularly the Kyrgyz, remain underrepresented in major Y-STR reference databases. These population data represent 23 Y-STR loci from 514 unrelated Kyrgyz males sampled from three geographically distinct regions: Northern East (<em>N</em> = 134), Northern West (<em>N</em> = 183), and Southern Kyrgyzstan (<em>N</em> = 197). Genotyping was conducted using the PowerPlex Y23 System, and the resulting dataset has been submitted to the Y Chromosome Haplotype Reference Database (YHRD) to strengthen forensic and anthropological research in the region. A total of 346 unique haplotypes were identified, demonstrating high haplotype diversity (HD = 0.981–0.990) and discrimination capacity (64–70 %). AMOVA analysis indicates that the division of Kyrgyz populations into northern and southern groups does not accurately represent their genetic structure, as over 99 % of genetic variation is distributed within subpopulations, indicating weak differentiation and substantial shared paternal ancestry among the regional Kyrgyz groups. The analysis also identifies four dominant haplogroup clusters (R1a, C2a, N1, and R1b), providing valuable insights into the historical and demographic dynamics of the Kyrgyz people. This dataset enhances our understanding of Kyrgyz genetic diversity, contributes to forensic applications, and fills a critical gap in population genetic research on Central Asian lineages.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111706"},"PeriodicalIF":1.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263677","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":"Development of longitudinal datasets (2000–2020) with high spatiotemporal resolution for air pollution exposure assessment in Canada","authors":"Anas Alhusban ,&nbsp;Yasar Burak Oztaner ,&nbsp;Markey Johnson ,&nbsp;Mastaneh Rezasefat ,&nbsp;Negin Hojjatzadeh ,&nbsp;Israa Moussa ,&nbsp;Mahsa Soleimani ,&nbsp;Saeed Nadi ,&nbsp;Shunliu Zhao ,&nbsp;Hwashin Shin ,&nbsp;Joyce J.Y. Zhang ,&nbsp;Amir Hakami","doi":"10.1016/j.dib.2025.111730","DOIUrl":"10.1016/j.dib.2025.111730","url":null,"abstract":"<div><div>We developed datasets intended to aid and inform, health and epidemiological studies in Canada by providing highly resolved spatiotemporal concentrations for regulated air pollutants (fine particulate matter PM_2.5, nitrogen dioxide NO₂, and ozone O₃) across Canada. Daily estimates were generated at various spatial resolutions for the years 2000 through 2020. The datasets are based on simulations of the US EPA’s Community Multiscale (CMAQ) model at 12 km horizontal resolution. In an effort to increase the accuracy and spatial resolution of the exposure estimates, especially in complex urban environments, we used statistical and machine learning methods to downscale CMAQ outputs to finer resolutions. Downscaling relies on raw CMAQ results, high-resolution land-use datasets, existing concentrations datasets, and observations from the National Air Pollution Surveillance (NAPS) network. Widely used machine learning (ML) algorithms like random forest and gradient boosting were chosen and proved to be promising. Generated datasets at various spatial resolutions (census divisions, postal codes, gridded 12 km, or 1 km) showed adequate statistical performance and clear representations of spatial features associated with pollutant emissions.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111730"},"PeriodicalIF":1.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263685","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}