Data in Brief最新文献

{"title":"Dataset for common wheat (Triticum aestivum L.) grain and flour characterization using classical and advanced analyses","authors":"Mélanie Munch ,&nbsp;Laura Rezette ,&nbsp;Patrice Buche ,&nbsp;Baptiste Chambrey ,&nbsp;Catherine Deborde ,&nbsp;Stéphane Dervaux ,&nbsp;Sonia Geoffroy ,&nbsp;Kamal Kansou ,&nbsp;Sophie Le Gall ,&nbsp;Laurent Linossier ,&nbsp;Benoit Meleard ,&nbsp;Luc Menut ,&nbsp;Marie-Hélène Morel ,&nbsp;Magalie Weber ,&nbsp;Luc Saulnier","doi":"10.1016/j.dib.2025.111375","DOIUrl":"10.1016/j.dib.2025.111375","url":null,"abstract":"<div><div>As global warming and changing market demand reshape agricultural practices, optimising the quality and utility of crop products, particularly wheat, is becoming increasingly complex and critical. Wheat plays a central role in human and animal nutrition, with its quality influenced by multiple factors at different scales, from grain composition to end-product performance, usually evaluated through sensory evaluation. Understanding the relationship between wheat composition and technological quality is essential for improving product value in agri-food systems. This dataset represents a broad panel of wheat samples encompassing diverse genetic backgrounds grown under varying environmental conditions in France. It collects measurements of grain, flour, dough and bread characteristics, facilitating a comprehensive comparison of wheat quality at different stages of production. The dataset encompasses 35 classical technological tests, 31 detailed compositional analyses—including in-depth characterization of protein composition (glutenin and gliadin), pentosan content measurement, and fatty acid profile analysis—and 37 sensory evaluations from the French Bread baking test providing detailed assessments of flour quality and dough behavior across key bread-making stages. In addition, raw data sets from Alveograph® and Farinograph® tests are included to support the development of innovative quality assessment criteria. This dataset will be valuable not only for the crop industry in its efforts to optimize wheat quality, but also for researchers and data scientists exploring the complex relationships between composition, processing and final bread quality. The data are registered in the French Research Data Gouv public repository and also stored in the PO2 Evagrain database using the PO2/TransformON ontology. The SPO2Q web tool allows for online database consultation, with further access available through the PO2 Manager desktop application.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111375"},"PeriodicalIF":1.0,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403373","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":"Walnut husk transcriptome dataset of codling moth (Cydia pomonella) infestation at different times","authors":"Xiaoyan Cao ,&nbsp;Xiaoqin Ye ,&nbsp;Adil Sattar","doi":"10.1016/j.dib.2025.111366","DOIUrl":"10.1016/j.dib.2025.111366","url":null,"abstract":"<div><div>Walnuts, along with almonds, cashews, and hazelnuts, are renowned as the world's “four famous nuts,” with walnuts being the foremost among them. Walnut fruit is rich in nutrients, including proteins, fats, polyphenols, sugars, phospholipids, melatonin, sterols, flavonoids, iron, zinc, manganese, and other trace elements, as well as dietary fiber. However, the codling moth poses a significant threat to walnut fruits as a major pest. Despite its importance, the transcriptomic changes in walnut husk at different times of codling moth infestation have not been fully explored. In this study, we employed the Illumina NovaSeq 6000 platform to sequence the transcriptome of walnut husk at various time points (0, 12, 24, 36, 48, and 72 hours) after codling moth infestation. The RNA-seq libraries yielded between 41,402,492 and 48,358,932 clean reads, resulting in a total of 120.34 Gb of clean data after filtering out low-quality reads. In total, 936 million reads were generated, with approximately 90% aligning uniquely to the reference genome. Differential expression analysis revealed the number of differentially expressed genes (DEGs) at each time point, including 21 genes associated with plant hormone synthesis. The results of this study provide new insights into the transcriptional changes in walnut husk induced by codling moth infestation and lay a foundation for future research on walnut husk defense mechanisms. The raw FASTQ files from this transcriptome experiment are publicly available in the NCBI Sequence Read Archive (SRA) under the BioProject accession number PRJNA1140835.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111366"},"PeriodicalIF":1.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388463","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":"Sprouting and network data assessed in the chicken aortic ring assay under stimulation with human adipose-derived stem cell secretomes harvested from single cells or spheroids of different sizes","authors":"Petra Wolint ,&nbsp;Silvan Hofmann ,&nbsp;Julia von Atzigen ,&nbsp;Roland Böni ,&nbsp;Iris Miescher ,&nbsp;Pietro Giovanoli ,&nbsp;Maurizio Calcagni ,&nbsp;Maximilian Y. Emmert ,&nbsp;Johanna Buschmann","doi":"10.1016/j.dib.2025.111371","DOIUrl":"10.1016/j.dib.2025.111371","url":null,"abstract":"<div><div>The aortic ring assay is widely used to assess the angiogenic modulation evoked by various drugs. However, different parameters are used as readouts and there is no congruence in terminology. In addition, some researchers use one set of parameters, and other researchers choose parameters that overlap to some extent, but miss a part of these parameters, rendering a direct comparison of the readouts and results difficult [1]. Therefore, we present data acquired in the chicken aortic ring assay that cover the full spectrum of possible readouts – exemplified by stimulation with secretomes harvested from human adipose-derived stem cells, cultivated either as single cell monolayer culture or as 3D spheroids, sized 250 cells/spheroid or 8000 cells/spheroid, respectively.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111371"},"PeriodicalIF":1.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388400","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 annotated ground-based images for the development of contrail detection algorithms","authors":"Nicolas Gourgue ,&nbsp;Olivier Boucher ,&nbsp;Laurent Barthès","doi":"10.1016/j.dib.2025.111364","DOIUrl":"10.1016/j.dib.2025.111364","url":null,"abstract":"<div><div>All economic sectors must understand, measure and mitigate their contributions to climate change. The aviation sector is no exception and has to reduce its CO₂ emissions while also addressing its non-CO₂ effects which are responsible for a significant radiative impact on climate. The most important of these effects is due to the formation of contrails and their transformation into induced cirrus. Many studies have focused on detecting contrails onto satellite images because, taken together, meteorological geostationary and sun-synchronous satellites provide a good monitoring of the Earth's atmosphere, but unfortunately the spatial resolution and temporal sampling of such satellite images are often insufficient to detect contrails right after their formation and attribute a particular contrail to a given flight. The use of ground-based cameras, especially as part of a network, is therefore complementary to satellite imagery and currently represents an important avenue of research for contrail monitoring. In this article we describe a dataset of annotated ground-based hemispheric sky images that can serve as a basis for the training and validation of contrail detection algorithms, in particular those aiming at segmenting contrails using machine learning methods.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111364"},"PeriodicalIF":1.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388152","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":"Maternal health risk factors dataset: Clinical parameters and insights from rural Bangladesh","authors":"Mayen Uddin Mojumdar,&nbsp;Dhiman Sarker,&nbsp;Md Assaduzzaman,&nbsp;Hasin Arman Shifa,&nbsp;Md. Anisul Haque Sajeeb,&nbsp;Oahidul Islam,&nbsp;Md Shadikul Bari,&nbsp;Mohammad Jahangir Alam,&nbsp;Narayan Ranjan Chakraborty","doi":"10.1016/j.dib.2025.111363","DOIUrl":"10.1016/j.dib.2025.111363","url":null,"abstract":"<div><div>Pregnancy-related complications and their consequences pose significant public health challenges, particularly in rural and developing areas where healthcare resources are limited. Monitoring clinical parameters during pregnancy improves diagnosis, treatment, and maternal health prognosis. This database includes records of pregnant patients from Kurigram General Hospital, Bangladesh. It captures core health parameters such as age, blood pressure (systolic and diastolic), blood sugar levels, body temperature, BMI, current mental health status, pre-existing medical history, gestational diabetes status, and heart rate. The diversity of data collected in this dataset is essential for understanding potential health changes associated with pregnancy. It will aid in generating high-risk pregnancy evaluation and prediction models to support clinical management. This dataset is valuable for its potential to serve as a benchmark for comparing maternal health responses across different clinical conditions of patients, thereby contributing to a broader understanding of pregnancy-related complications. The study's preprocessing methods, which included data cleaning, normalization, and encoding, ensured high-quality data for statistical analysis. Initial findings used statistical tests to explore associations within the data. A Chi-Square test analyzed the relationship between preexisting diabetes and risk levels, revealing a significant association with a p-value of 4.85e-119. A Z-test was also conducted to compare clinical parameters between pregnant patients with and without diabetes, with a sample ratio of 337:811. This test showed a significant difference in BMI (body mass index), with a p-value of 2.23e-24, indicating that preexisting diabetes impacts BMI. A T-test for BMI revealed a significant difference, with a p-value of 1.405e-20. These findings further elucidate how specific age and body mass index details influence the risk levels associated with maternal clinical conditions. In summary, this database will be highly valued and a significant asset for research studies on maternal health in pregnant patients, public health strategies, and the enhancing diagnostic and treatment modalities for patients.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111363"},"PeriodicalIF":1.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143347858","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":"DriVQA: A gaze-based dataset for visual question answering in driving scenarios","authors":"Kaavya Rekanar ,&nbsp;John M. Joyce ,&nbsp;Martin Hayes ,&nbsp;Ciarán Eising","doi":"10.1016/j.dib.2025.111367","DOIUrl":"10.1016/j.dib.2025.111367","url":null,"abstract":"<div><div>This paper presents DriVQA, a novel dataset that combines gaze plots and heatmaps with visual question-answering (VQA) data from participants who were presented with driving scenarios. Visual Questioning Answering (VQA) is proposed as a part of the vehicle autonomy trustworthiness and interpretability solution in decision-making by autonomous vehicles. Collected using the Tobii Pro X3-120 eye-tracking device, the DriVQA dataset provides a comprehensive mapping of where participants direct their gaze when presented with images of driving scenes, followed by related questions and answers from every participant. For each scenario, the dataset contains: images of driving situations, associated questions, participant answers, gaze plots, and heatmaps. It is being used to study the subjectivity inherent in VQA. Its detailed gaze-tracking data offers a unique perspective on how individuals perceive and interpret visual scenes, making it an essential resource for training VQA models that rely on human-like attention. The dataset is a valuable tool for investigating human cognition and behaviour in dynamic, real-world scenarios. DriVQA is highly relevant for VQA models, as it allows the systems to learn from human-like attention behaviour when making decisions based on visual input when trained. The dataset has the potential to drive advancements in VQA research and development by improving the safety and intelligence of driving systems through enhanced visual understanding and interaction. DriVQA has significant potential for reuse in various research areas, including the development of advanced VQA models, attention analysis, and human-computer interaction studies. Its comprehensive gaze plots and heatmaps can also be leveraged to improve applications in autonomous driving, driver assistance systems, and cognitive science research, making it a versatile resource for both academic and industrial purposes.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111367"},"PeriodicalIF":1.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388151","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 vocabulary in Uzbek primary education: Extraction and analysis in case of the school corpus","authors":"Khabibulla Madatov ,&nbsp;Sapura Sattarova ,&nbsp;Jernej Vičič","doi":"10.1016/j.dib.2025.111349","DOIUrl":"10.1016/j.dib.2025.111349","url":null,"abstract":"<div><div>The main goal of this research work is to determine the number of new words that a primary school pupil should know/acquire during each academic year. To accomplish this, we have created two datasets. The first dataset was compiled based on the ``Explanatory Vocabulary of the Uzbek Language'' (EDUL). The second dataset was created from 35 primary school textbooks for grades 1-4 approved by the Ministry of Preschool and School Education of the Republic of Uzbekistan, and it was named the ``Uzbek Primary School Corpus'' (UPSC) by authors. Using the ``Comparative Lemma Extraction Method'' (CLEM) proposed by the authors of the article, a vocabulary for grades 1-4 was created, and the problem of determining the number of new words (disregarding word forms as Uzbek is a morphologically rich language) that primary school pupils should learn each academic year was solved.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111349"},"PeriodicalIF":1.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143269021","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":"Unveiling key drivers for social robot adoption in the hospitality sector: Two-phase confirmatory factor analysis and structural equation modeling approach","authors":"Rashmi Ranjan Panigrahi ,&nbsp;Judit Oláh ,&nbsp;Subhodeep Mukherji ,&nbsp;Abdul Bashiru Jibril ,&nbsp;Kiran Cotha","doi":"10.1016/j.dib.2025.111360","DOIUrl":"10.1016/j.dib.2025.111360","url":null,"abstract":"<div><div>This data set measures the hotel industry's intention to adopt social robots. Data was collected from the employees of five-star hotels. Data-based research is based on primary surveys conducted at five-star hotels, and a standardised questionnaire was established to conduct interviews. Following the conclusion of the procedure for collecting the data, a structural equation modelling approach was employed to evaluate the hypothesis. The results provide exploratory factor analysis, confirmatory factor analysis and structural equation modelling. This data set will contribute significantly to the literature on social robots in the hospitality sector. This data set will help the practitioners work on major problem factors for improving the quality of partnering relationships between key participants in their present and future hospitality sectors. By removing or minimizing these problem factors, the practitioners will be contributing considerably towards effective hotel sectors. The data would be valuable for academics and industry professionals working with the hotel business nationally and internationally.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111360"},"PeriodicalIF":1.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388399","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":"Geochemical data of Al-rich diopside pyroxenites from the Premosello mantle peridotite massif, Ivrea-Verbano Zone, Southern Alps","authors":"Abimbola C. Ogunyele ,&nbsp;Alessio Sanfilippo ,&nbsp;Mattia Bonazzi ,&nbsp;Maria C. Lopez Suarez ,&nbsp;Alberto Zanetti","doi":"10.1016/j.dib.2025.111362","DOIUrl":"10.1016/j.dib.2025.111362","url":null,"abstract":"<div><div>Pyroxenites of different generations and composition are usually found within orogenic peridotite massifs and in mantle xenoliths entrained in volcanic rocks. Orogenic peridotite massifs, however, offer great advantages over xenolith studies because structural relationships which formed in the mantle before exhumation are often preserved, and crosscutting relationships between dykes of different generations and composition can be readily observed. Numerous orogenic peridotite massifs occur in the Ivrea-Verbano Zone (IVZ) in the western Southern Alps, providing petrologists, geochemists and geophysicists a natural laboratory to study and understand Earth's mantle processes and evolution. We here report new geochemical data for peculiar Al-rich diopside pyroxenites which crosscut the Premosello mantle peridotite massif in central IVZ close to the transition to the continental crust (i.e., the Moho region). The pyroxenite is composed of Al-rich clinopyroxene (Cpx), spinel (Sp), and amphibole (Amph), with subordinate amounts of olivine (Ol), and occasional orthopyroxene (Opx) as an accessory phase. Electron microprobe (EMP) and laser-ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analysis were performed to measure the major and trace elements contents of the mineral phases of the pyroxenite. Major element composition of each mineral phase is characterized by uniform Mg# (Cpx: 0.88-0.90; Ol: 0.87-0.88; Sp: 0.73-0.77; Amph: 0.84-0.87; Opx: 0.87) and high Al₂O₃ contents (except in Ol). The trace element composition of Cpx and Amph from the Al-rich diopside pyroxenite shows strong rare earth elements (REE) fractionation and enrichments in LREEs and MREEs over the HREEs, and is distinct from other pyroxenite compositions (i.e., Al-augite and Cr-diopside pyroxenites) reported from the Premosello and other IVZ lherzolitic peridotite massifs. The geochemical data presented herein, therefore, offer valuable insights into the compositional variability and formation processes of mantle pyroxenites, and may contribute to unravelling the broader evolutionary history of the Earth's subcontinental lithospheric mantle, in particular at Moho levels.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111362"},"PeriodicalIF":1.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388153","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":"CoAt-Set: Transformed coordinated attack dataset for collaborative intrusion detection simulation","authors":"Aulia Arif Wardana ,&nbsp;Grzegorz Kołaczek ,&nbsp;Parman Sukarno","doi":"10.1016/j.dib.2025.111354","DOIUrl":"10.1016/j.dib.2025.111354","url":null,"abstract":"<div><div>The <strong>CoAt-Set</strong> dataset is a transformed dataset specifically designed for collaborative anomaly detection within Collaborative Intrusion Detection Systems (CIDS). It is developed by extracting and relabeling coordinated attack patterns from well-established datasets, including CIC-ToN-IoT, CIC-IDS2017, CIC-UNSW-NB15, CSE-CIC-IDS2018, CIC-BoT-IoT, Distrinet-CIC-IDS2017, and NF-UQ-NIDS. CoAt-Set focuses on coordinated attack scenarios such as large-scale stealthy scans, worm outbreaks, and distributed denial-of-service (DDoS) attacks, simulating realistic and high-impact threats that commonly observed in modern networks. The transformation process involved organizing coordinated attack behaviors and providing detailed annotations and network traffic features, enhancing its relevance for anomaly detection in collaborative environments. CoAt-Set is compatible with standard machine learning frameworks, offering researchers and practitioners a comprehensive resource for developing, testing, and evaluating CIDS models. It is suitable for various applications, including collective threat intelligence research, analyzing distributed threat patterns, developing machine learning algorithms for distributed systems, and training simulations designed for heterogeneous network environments.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111354"},"PeriodicalIF":1.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143347855","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}