Data in Brief最新文献

{"title":"Fluorescence data of natural organic matter in groundwater from the Fontaine de Vaucluse karst system (2020 to 2021): Excitation-emission matrix (EEM) and 2D spectra at 254 nm excitation wavelength","authors":"Leïla Serène ,&nbsp;Christelle Batiot-Guilhe ,&nbsp;Naomi Mazzilli ,&nbsp;Christophe Emblanch","doi":"10.1016/j.dib.2025.111493","DOIUrl":"10.1016/j.dib.2025.111493","url":null,"abstract":"<div><div>This dataset provides bimonthly fluorescence data from February 2020 to October 2021 at 4 springs, 1 loss and 9 unsaturated zone flows of the Fontaine de Vaucluse karst system (France). The data correspond to Excitation Emission Matrices (EEM) and emission spectra at 254 nm excitation wavelength of organic matter fluorescence. Analyses were performed with a SHIMADZU RF-5301 PC spectrofluorometer at the following wavelengths: EEM at λ_ex= [220; 450] nm, interval=10 nm; λ_em= [250; 550] nm, interval=1 nm; and 2D emission spectra at λ_ex=254nm, λ_em= [250; 530] nm, interval=1 nm. Milli-Q water EEMs are also provided, one for each day of analysis, to allow later correction of the Raman diffraction. Only raw data are provided to allow the user to adapt the corrections to his purpose. The originality of this dataset is the 20-months monitoring of different types of karst waters, from the saturated zone (springs with small or large catchments) to the unsaturated zone which was exceptionally accessible thanks to the Low Noise Underground Laboratory (LSBB, <span><span>https://lsbb.cnrs.fr/</span><svg><path></path></svg></span>). This dataset was carried out to question the use of the main fluorescence indices (FI, BIX, HIX, [1] and to develop a new index to assess the qualitative groundwater transit time [2,3]. The use of this dataset could be extended to fields other than hydrogeology, such as pedology, microbiology or hydrobiology. It could be usefull to improve the understanding of the carbon cycle as carbon is the main atom constituting organic matter and fluorescence allows the characterization of the molecular structure of the molecule.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111493"},"PeriodicalIF":1.0,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696170","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":"Bangla-REX: A distinct dataset for Bangla relation extraction","authors":"Nishat Tasnim ,&nbsp;Asraf Ullah Rahat ,&nbsp;Tanjim Taharat Aurpa ,&nbsp;Md Musfique Anwar","doi":"10.1016/j.dib.2025.111480","DOIUrl":"10.1016/j.dib.2025.111480","url":null,"abstract":"<div><div>Bangla REX introduces a significant dataset designed specifically for relation extraction tasks in the Bangla language, addressing a critical lack of resources in this domain. To the best of our knowledge, this dataset fills an important gap by providing comprehensive support for advanced relation extraction methodologies. The dataset comprises 90,441 text entries, available in structured formats. Alongside this, a Bangla Knowledge Base (KB) containing 63,256 entries has been developed to automate the corpus annotation with relation tags.</div><div>The dataset is developed to support the accurate extraction and classification of various semantic relations within Bangla textual data. It includes categories such as movie actors, place of birth, movie directors, writers, places of death, company locations, and founders. Bangla REX is a valuable resource for researchers and practitioners in natural language processing, offering standardized benchmarks and detailed annotations to advance relation extraction techniques for Bangla. It aims to foster research and enable practical applications, contributing to the development of Bangla NLP and multilingual information processing.</div><div>The dataset is compiled from reliable sources, including Bangla Wikipedia and Wikidata, and has been annotated to ensure accuracy and relevance. Each relation category contains numerous labeled examples, providing a strong foundation for training and evaluating relation extraction models. Bangla REX seeks to promote innovation in NLP research and support the development of tools tailored to the Bangla language.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111480"},"PeriodicalIF":1.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725447","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":"A benchmark dataset for objective quality assessment of view synthesis for neural radiance field (NeRF)","authors":"Chibuike Onuoha ,&nbsp;Shihao Luo ,&nbsp;Jean Flaherty ,&nbsp;Truong Thu Huong ,&nbsp;Pham Ngoc Nam ,&nbsp;Truong Cong Thang","doi":"10.1016/j.dib.2025.111484","DOIUrl":"10.1016/j.dib.2025.111484","url":null,"abstract":"<div><div>Neural Radiance Fields (NeRF) are revolutionizing diverse fields such as autonomous driving, education, and virtual reality (VR). As their applications expand, the ability to accurately evaluate the quality of NeRF-generated content becomes essential. Currently, there are only a few datasets for NeRF quality evaluation. Also, while existing quality datasets primarily utilize processed video sequences (PVS) as stimuli, real-world scenarios often involve uneven camera trajectories, underscoring the need for alternative approaches to subjective quality assessment. This study proposes a quality dataset for assessing the quality of NeRF. The dataset was generated by varying quality parameters in SOTA NeRF models to create different quality levels. A subjective experiment was conducted to obtain human opinion scores for the distorted NeRF. The subjective data were processed in accordance with International Telecommunication Union (ITU) guidelines to derive mean opinion scores (MOS. The datasets and findings not only offer insights into the performance of NeRF models but also serve as valuable resources for developing quality assessment models.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111484"},"PeriodicalIF":1.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696165","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":"Agricultural load cycles: Tractor mission profiles from recorded GNSS and CAN bus data","authors":"Korbinian Götz,&nbsp;Andrew Kusuma,&nbsp;Adrian Dörfler,&nbsp;Markus Lienkamp","doi":"10.1016/j.dib.2025.111494","DOIUrl":"10.1016/j.dib.2025.111494","url":null,"abstract":"<div><div>Agriculture is one of the main sources of greenhouse gas emissions, with agricultural machinery playing an important role through the combustion of fossil fuels. On the upside, many farmers invest in their own renewable energy generation. To leverage the renewable produced energy and cut emissions, a promising solution is the electrification of tractors. With the advent of tractor electrification, the necessity to define the requirements of an electrified tractor emerges. In contrast to automotive and truck engineering, where the usage patterns are narrow, and testing is standardized through load cycles as the WLTP and VECTO LongHaul, the agricultural application of tractors includes a wide variability of operating conditions. Since there are no standardized, publicly available agricultural load cycles, we equipped, during a one-year period, five tractors (77–240 kW) on a farm in the South of Germany with high-resolution GNSS loggers and collected the CAN bus data from the J1939 engine bus and the ISOBUS. The data collected is enriched with information about the tractor models and implements used. Hence, the load and usage information in real-field operation is suitable as input for the development of electrified tractors.</div><div>A total of 862 h of operation data has been recorded and constitutes one of the most comprehensive open datasets to date for high-resolution data of agricultural tractors. This dataset provides engine and load parameters, auxiliary power supply, and GNSS information for multiple different agricultural fields. Its applications include the simulation of electrification for agricultural tractors, load cycle construction, modeling of farming processes, the analysis of agricultural production indicators, or path planning for autonomy.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111494"},"PeriodicalIF":1.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715854","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":"Dataset for small object detection with shadow (SODwS)","authors":"Shahbe Mat-Desa ,&nbsp;Wan-Noorshahida Mohd-Isa ,&nbsp;Petra Gomez-Krämer ,&nbsp;M. Roslee ,&nbsp;Noramiza Hashim ,&nbsp;Junaidi Abdullah ,&nbsp;Aziah Ali ,&nbsp;Zarina Che-Embi ,&nbsp;Amalina Ibrahim","doi":"10.1016/j.dib.2025.111482","DOIUrl":"10.1016/j.dib.2025.111482","url":null,"abstract":"<div><div>Detecting small objects in aerial images poses several challenges, including issues with resolution limitations, scale variability, background clutter, and object occlusion. Annotated datasets for small objects in aerial images are often scarce, complicating the training and validation of detection models. This article introduces a new dataset specifically designed for small object detection in low-altitude aerial images. It addresses the challenges posed by shadows, including their impact on object visibility, by including images that capture small objects obscured with shadows. The dataset also features ground-truth shadow maps to support research in shadow detection. This dataset offers potential for future research and serves as a resource for transfer learning.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111482"},"PeriodicalIF":1.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715998","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":"Dataset of the effect of sulfur dosage in solid rubber compound and vulcanizate in rubberrized asphalt properties","authors":"Henry Prastanto ,&nbsp;Illah Sailah ,&nbsp;Ono Suparno ,&nbsp;Madi Hermadi","doi":"10.1016/j.dib.2025.111461","DOIUrl":"10.1016/j.dib.2025.111461","url":null,"abstract":"<div><div>The characteristics of natural rubber greatly influence the quality of asphalt modified with natural rubber. This research uses natural rubber of the Technical Specified Rubber (TSR) 20 type, which in Indonesia is called Standard Indonesian Rubber (SIR) 20 as the raw material. The sulfur vulcanization material is expected to increase crosslinks so that it can increase the resistance of natural rubber to hot asphalt and can improve the quality of rubberized asphalt. This research was designed by varying the sulfur dosage and vulcanization duration. The sulfur dosage used varies, namely 5; 10; 15; 20 parts per hundreed rubber (phr). The duration of vulcanization time at 140 °C for each dose of sulfur is 0;30;60;90;120 min. The compound or vulcanisate is then mixed into the asphalt at a temperature of 160–170 °C with a dose of 2 % rubber and 98 % asphalt. Based on the research results, it is known that increasing the sulfur dosage and vulcanization time duration produces rubber that is more resistant to oil through testing for solubility and swelling in toluene. The unvulcanized compound dissolves in toluene, while the vulcanizate swelling ratio decreases with increasing sulfur dosage (790 to 482 %). Increasing the sulfur dosage and the duration of vulcanization time produces harder rubber so that the duration of mixing into asphalt increases from 1.5 h to 5.5 h. The addition of sulfur dosage and vulcanization time duration can increase the original Performance Grade (PG) and PG after Rolling Thin Film Oven Test (RTFOT) when compared to original asphalt. Original PG of rubberized asphalt obtained from this research is 69.8 to 90.4 °C compared to original asphalt PG which is only 66.7 °C. PG after RTFOT was obtained between 60.3 to 88.4 °C compared to original asphalt PG which was only 64 °C. This research data can be useful in the design of rubber compounds and vulcanizates which can be selected by considering process engineering, processing machines and economic aspects in the production of rubberized asphalt.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111461"},"PeriodicalIF":1.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735314","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":"Swahili questions and answers dataset for aflatoxin knowledge domain","authors":"Pamela Chogo,&nbsp;Elizabeth Mkoba,&nbsp;Neema Kassim","doi":"10.1016/j.dib.2025.111475","DOIUrl":"10.1016/j.dib.2025.111475","url":null,"abstract":"<div><div>Aflatoxin contamination is a challenge facing food security, health, and trade in Tanzania and other parts of the world. This contamination affects maize, groundnuts, and other crops and animal products. Once contamination occurs, the contaminated crops and animal products become toxic causing illness or death to humans and animals who consume them. Lack of awareness and knowledge of the contamination is seen to be one of the reasons for its continued occurrence. Various awareness-creation and knowledge-sharing techniques have been used but the situation is still not appealing. For this case, the use of a Natural Language Processing (NLP) chatbot in sharing aflatoxin knowledge is proposed. This is because NLP chatbots have been successful in knowledge sharing in various contexts. This data article presents a Swahili text-based aflatoxin knowledge questions and answers dataset. Data were collected through 7 focus group discussion (FGD) sessions conducted in Arusha, Dodoma, Mtwara, Tabora, Morogoro, and Iringa regions in Tanzania. Respondents for the study were farmers, traders, and consumers of maize and groundnuts. The collected data were processed and analyzed using R qualitative data analysis tool. This allowed the identification of 6 themes with respective questions under each theme. The questions were shared with experts through 9 interview sessions and the experts gave answers to the questions. The set of questions and answers were then translated into Swahili language using google translate and manual verification. Finally, an aflatoxin knowledge dataset containing 221 paired questions and answers organized into 6 knowledge areas Swahili dataset was developed. With this dataset, an NLP-based chatbot that uses Swahili language can be developed. This will be beneficial to farmers, traders, consumers, researchers, and policymakers. They can use it to learn more about aflatoxin and be able to make informed decisions. Moreover, the dataset can be adopted and modified to create NLP chatbots that can share aflatoxin knowledge in other languages apart from Swahili. The dataset also contributes to the availability of Swahili language datasets.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111475"},"PeriodicalIF":1.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725545","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":"Dataset on effect of cadmium and lead on chemical reactivity of selected heterocyclic compounds as potential dipeptidyl peptidase III inhibitors using insilico method","authors":"Kehinde Adeola Bolaji ,&nbsp;Abel Kolawole Oyebamiji ,&nbsp;Godwin Oladele Olutona","doi":"10.1016/j.dib.2025.111481","DOIUrl":"10.1016/j.dib.2025.111481","url":null,"abstract":"<div><div>The role played by heterocyclic compounds in drug design and discovery remain crucial globally. In this work, the effect of cadmium and lead were investigated on the chemical reactivity of selected heterocyclic compounds with potential anti-dipeptidyl peptidase III activity using <em>insilico</em> method. Various software such as Spartan 14 (for optimization), molecular operating environment (moe) (for induced fit docking) and ADMETSar (pharmacokinetic examination) were used to execute the investigations. Three descriptors (highest occupied molecular orbital energy (EHOMO); lowest unoccupied molecular orbital energy (ELUMO) and energy gap) were observed among others for selected compounds without any foreign attachment, selected compounds with cadmium and selected compounds with lead. The calculated descriptors revealed that cadmium had a great effect on compound <strong>7</strong> in term of HOMO energy and energy gap. Also, it was observed that cadmium altered the ability of compound 5 in term LUMO energy. The selected compounds were docked against dipeptidyl peptidase III and the scoring was reported. More so, pharmacokinetic examination of ligands with highest binding affinity was reported and compared to the report for the reference molecules.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111481"},"PeriodicalIF":1.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724957","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":"A dataset of characterization factors for biodiversity impact assessment in OpenLCA and LCA for experts","authors":"Julian Quandt ,&nbsp;Jan Paul Lindner ,&nbsp;Nico Mumm","doi":"10.1016/j.dib.2025.111496","DOIUrl":"10.1016/j.dib.2025.111496","url":null,"abstract":"<div><div>The accelerating loss of biodiversity and ongoing ecosystem degradation rank among the most pressing global challenges today. Life Cycle Assessment (LCA) has emerged as a pivotal tool for evaluating the environmental sustainability of production systems; however, the integration of biodiversity impact assessments into LCA studies remains constrained by significant data gaps, limited spatial resolution, and methodological complexity. This dataset addresses these challenges by providing and integrating ready-to-use characterization factors for biodiversity impact assessment in current LCA software packages.</div><div>Characterization factors (CF) were calculated for land occupation flows of three LCA databases (Agribalyse 3.1.1, Ecoinvent 3.10, and Sphera LCA For Experts) following the Biodiversity Value Increment (BVI) method. The CF are applicable at global and country level, considering both land-use intensity and location. The integration into current LCA Software packages (OpenLCA 2.1.0 and Sphera LCA For Experts), enhances accessibility for LCA practitioners, supporting more comprehensive evaluations especially in terms of biodiversity impact assessments.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111496"},"PeriodicalIF":1.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696169","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":"URDD: An open dataset for urban roadway disease detection and classification","authors":"Shuaiqi Liu ,&nbsp;Wenjing Jiang ,&nbsp;Yue Yu ,&nbsp;Lei Ren ,&nbsp;Chunbo Li ,&nbsp;Qi Hu","doi":"10.1016/j.dib.2025.111499","DOIUrl":"10.1016/j.dib.2025.111499","url":null,"abstract":"<div><div>Urban traffic accidents have become more common in recent years due to the rising number of motorized vehicles, climate change, and outdated subsurface drainage systems. Traditional road disease detection methods involve collecting road data using ground-penetrating radar and manually analyzing the data. This process is time-consuming and subjective. Deep learning, especially convolutional neural networks (CNNs), has proven highly effective in image recognition and object detection. By applying these techniques to road disease detection, both the efficiency and accuracy of detection can be significantly improved. To support this, we have created a specialized road disease dataset designed for object detection and classification tasks. The release of this dataset aims to promote the use of artificial intelligence (AI) in autonomous road disease detection and classification, enhancing detection efficiency and contributing to better urban road maintenance and management.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111499"},"PeriodicalIF":1.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715852","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}