cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5127073.v1
title: Supplementary Material for: Staphylococcal Exotoxins Induce Interleukin 22 in Human Th22 Cells

description: <b><i>Background:</i></b> We have shown previously that T cells from atopic dermatitis (AD) patients produce more IL-22 upon staphylococcal exotoxin stimulation compared to psoriasis patients and healthy controls. The role of staphylococcal exotoxins on polarized memory T helper (Th)22 cells which are enriched in inflamed AD skin remains elusive. Our aim was to investigate IL-22 production in response to staphylococcal enterotoxin B (SEB) and α-toxin stimulation in human memory T cells and polarized Th22 cells. <b><i>Methods:</i></b> IL-22 induction was investigated in human peripheral blood-derived CD4+CD45RO+CD45RA- T cells and polarized Th22 cells after SEB and sublytic α-toxin stimulation in a time-dependent manner at the mRNA and protein (ELISA) levels. <b><i>Results:</i></b> Th22 cells secreted more IL-22 compared to freshly isolated peripheral blood-derived memory T cells. SEB and α-toxin induced IL-22 in memory T cells as well as in Th22 cells. More IL-22 was induced by SEB and α-toxin in freshly isolated peripheral blood memory T cells compared to Th22 cells derived from memory T cells in long-term cell culture without polarization and Th22 cells under Th22-promoting conditions with IL-6 and TNF-α. No differences in IL-22 induction by staphylococcal exotoxins were observed between cells from AD compared to psoriasis patients and healthy controls. <b><i>Conclusions:</i></b> Increased IL-22 secretion can promptly be induced by staphylococcal exotoxins in skin infiltrating CD4+CD45RO+CD45RA- memory T cells and can potentially amplify chronic skin inflammation in AD in the context of bacterial colonization and infection. This should be investigated further in detail in lesional skin of AD and psoriasis patients.
DOI: 10.6084/m9.figshare.28490141.v1
title: Gut microbiological

description: Diabetes is a chronic disease characterised by hyperglycaemia, which has been demonstrated to cause damage to the intestinal barrier and an imbalance in the flora. Furthermore, damage to the intestinal barrier can distort the intestinal environment and gut microbiota, thereby exacerbating the symptoms of diabetes.
DOI: 10.6084/m9.figshare.17143289.v1
title: Head Tissue Template

description: <b>Method</b>The method of Brudfors et. al. (2020) was used to construct a tissue probability map from T2-weighted and PD-weighted scans of the first 64 subjects from the IXI dataset, along with the T1-weighted scans of the next 64 IXI subjects. The 15 training subjects' scans from the MICCAI Challenge Dataset were also included in the template construction. Default settings were used throughout, except for the regularisation for the diffeomorphic registration, which was set to be higher than the default settings (``Shape Regularisation'' on the user interface was set to [0.0001 0.5 0.5 0.0 1.0]). After merging several of the automatically identified tissue classes, the tissue probability map has 1 mm isotropic resolution, dimensions of 191x243x229 voxels and consists of 11 tissue types, three of which approximately correspond with brain tissues.<br><br>This image (roughly) contains the logarithms of the tissue probabilities, which can be recovered using a softmax (exp(mu)/(sum(exp(mu)+1)).<br><b>Reference</b>Brudfors M, Balbastre Y, Flandin G, Nachev P, Ashburner J. Flexible Bayesian Modelling for Nonlinear Image Registration. In International Conference on Medical Image Computing and Computer-Assisted Intervention 2020 Oct 4 (pp. 253-263). Springer, Cham.<br><br>
DOI: 10.6084/m9.figshare.4805836.v1
title: Automated Fiber Quantification (AFQ) tract profiles for the 8 corpus callosum segments in old (age &gt; 13.0 yrs.) and young (age &lt;= 13.0 yrs.) participants

description: <pre>Shown are the Automated Fiber Quantification (AFQ) tract profiles for the 8 corpus callosum segments in old (age &gt; 13.0 yrs.) and young (age &lt;= 13.0 yrs.) participants. Plotted are FA, RD, AD, and MD (± SE) along the core of the fiber tract (y-axis) at 100 equidistant points (x-axis). The left hemisphere is on the left (location 0 - 49) and the right hemisphere is on the right (location 51 - 100) with midsagittal at location 50.</pre>
DOI: 10.17632/573fvyvhs9
title: ЭФФЕКТИВНОСТЬ ИСПОЛЬЗОВАНИЯ ТРУДОВЫХ РЕСУРСОВ В СЕЛЬСКОМ ХОЗЯЙСТВЕ: ОСНОВНЫЕ КРИТЕРИИ И ПРИОРИТЕТЫ

description: производство, эффективность, человеческие ресурсы, демография, кадровая политика
DOI: 10.17632/kx3c6hdrjf
title: The trace of the trees: A historically situated geospatial assessment of deforestation in Bosawas biosphere reserve

description: This is the dataset for the research article: The trace of the trees: A historically situated geospatial assessment of deforestation in Bosawas biosphere reserve. The research combines two independently generated high-resolution land cover maps and agrarian census data to assess the extent of deforestation that has affected Bosawas from 1990 to 2022. The dataset contains the study region's land cover maps and the consolidated agrarian census data utilized in the research, as well as the code used to process them.
DOI: 10.17632/4jvt4d724h
title: Understanding and confronting reality and challenges in the Gray Zone on today modern warfare

description: Overview on the situation on Gray Zone and third parties conflict
DOI: 10.17632/r6db558376
title: Dataset of Jordanian Road Traffic Accidents Reports

description: The dataset utilized for this research consists of data on traffic accidents in Jordan, sourced from the JO-Traffic-Accidents-Dataset (JO-TAD). This dataset was procured from the Central Traffic Department, Public Security Directorate, Amman-Jordan. JO-TAD contains 73,095 accident reports recorded in 2018, specifically focusing on incidents transpiring in January, June, and September. These months correspond to three distinct seasons: winter, summer, and fall, respectively.

The Jordanian Road Traffic Accidents reports Dataset is publicly available as an Excel file (JO_traffic_accidents_dataset.xlsx) and a CSV file (Accident_raw_data_En.csv) . The JO_traffic_accidents_dataset.xlsx file includes several individual Excel sheets that contain: (1) the raw primary data for traffic accident reports, (2) the encoded dataset, and (3) the associated features encoding key. 
As per the JO-Traffic-Accidents-Dataset (JO-TAD), it exclusively encompasses records pertaining to drivers and lacks any details regarding passengers involved in the accidents. The raw dataset comprises various labels, providing information about the accidents. This includes accident type, date, injury severity (ranging from simple to medium, severe, and fatal), road lanes, road surface description, road type, road properties, driver license type, travel speed, light condition, weather condition, driver errors, city, vehicle type, vehicle country of origin, number of cars involved, driver age, and driver sex.

This extensive dataset can be used by researchers and policymakers to explore accident mortality patterns at various geographical and time scales, as well as to assess the success of measures aimed at reducing road fatalities.
DOI: 10.17632/zrc982rvjm
title: MeLB Raw DNA Methylation Data; Herrgott et al., 2023

description: Raw cfDNA methylation data associated with 234 liquid biopsy serum and plasma collections from meningioma (MNG; n=93) and non-MNG (Other CNS diseases, glioma, pituitary tumors; n = 141) are located in folder 'LB IDATs'.   Raw DNA methylation data associated with tumor tissue collections from meningioma (MNG; n=88) are located in folder 'Tissue IDATs'. Additional generated random forest machine learning classifiers (d-MeLB & p-MeLB) are provided (Classifiers.zip).
DOI: 10.6084/m9.figshare.22769399.v1
title: FRESCO- A research and development framework for integrated project delivery

description: Integration, innovation, and collaboration within construction projects have been the subject of a growing body of research as a direct response to the notorious fragmentation and inherent performance issues of the construction industry. New delivery methods, such as integrated project delivery (IPD), have emerged among potential solutions to overcome these issues. The number of studies published on IPD has increased rapidly in recent years, covering many components of this collaborative approach. However, IPD is relatively novel and thereby emerging, with potential for advancement. This study aims to map topics covered in recent research on IPD and connect them to various practical elements of this approach in order to identify areas of practice that require further development. To achieve this goal, a research and development framework for IPD named “FRESCO” was developed that builds upon past research efforts and helps to analyze, research, and implement this innovative project delivery approach. Based on a systematic literature review of IPD research from 2017 to 2021, thematic analysis was performed on a total of 141 journal articles and conference papers to identify and define a practice-motivated theme-based framework. The framework was validated using data from three IPD case studies. The research findings identified a framework with six primary themes and 19 sub-topics that relate to well-explored and under-researched practice areas.
DOI: 10.6084/m9.figshare.28398056.v3
title: 2.85M reaction mechanisms from the USPTO reaction dataset

description: ** Full dataset available after the review processReaction mechanisms of 226,669 reactions in USPTO-480K reaction dataset<sup>1</sup> originally extracted from US patents (USPTO) reaction dataset<sup>2</sup> generated by MechFinder<sup>3</sup> to train Reactron. This dataset includes approximately 2.85 million mechanistic steps.Reference:1.Jin, W., Coley, C., Barzilay, R., & Jaakkola, T. (2017). Predicting organic reaction outcomes with weisfeiler-lehman network. <i>Advances in neural information processing systems</i>, <i>30</i>.Lowe, Daniel (2017). Chemical reactions from US patents (1976-Sep2016). figshare. Dataset. https://doi.org/10.6084/m9.figshare.5104873.v1Chen, S., Babazade, R., Kim, T., Han, S., & Jung, Y. (2024). A large-scale reaction dataset of mechanistic pathways of organic reactions. <i>Scientific Data</i>, <i>11</i>(1), 863.
DOI: 10.17632/3v9kj944d4
title: Data for: Microstructural origins of the high mechanical damage tolerance of NbTaMoW refractory high-entropy alloy thin films

description: Data contains the processed and raw micrographs, the raw results from measurements and a pdf files with the routes for reproducing the synthesis and characterisation results obtained with the NbTaMoW refractory high-entropy alloy thin film research.
DOI: 10.6084/m9.figshare.26403217.v1
title: <sub>Data from: Phylogenomics, reticulation, and biogeographical history of Elaeagnaceae</sub>

description: This archive contains code and data used for the paper "Phylogenomics, reticulation, and biogeographical history of Elaeagnaceae"(Gu, Wei; Zhang, Ting; Liu, Shui-Yin; Tian, Qin1; Yang, Chen-Xuan; Lu, Qing; Fu, Xiao-Gang; Kates, Heather; Stull, Gregory; Soltis, Pamela; Soltis, Douglas; Folk, Ryan; Guralnick, Robert; Li, De-Zhu; Yi, Ting-Shuang), Plant Diversity, 2024.This work focuses on the phylogenetic relationships within Elaeagnaceae, hybridizations, origination and dispersals of the family, and presents the most comprehensive phylogenetic framework for Elaeagnaceae to date, offers new insights into previously unresolved relationships in Elaeagnus, and provides a foundation for further studies on classification, evolution, biogeography, and conservation of Elaeagnaceae.
DOI: 10.6084/m9.figshare.3513515.v1
title: Appendix A. Quantifying spatial patterns in community characteristics and estimating latitudinal and depth gradients in catch per unit effort (CPUE) and probability of occurrence using generalized additive models.

description: Quantifying spatial patterns in community characteristics and estimating latitudinal and depth gradients in catch per unit effort (CPUE) and probability of occurrence using generalized additive models.
DOI: 10.17632/knk7pd6gvn
title: Table 1_Detection of Mpox by PCR from the skin and oropharynx over the course of infection: a prospective study.

description: Table 1
DOI: 10.17632/v4dbzs6d9b
title: Geochemical data on Cr-spinel in micrometeorites from modern Antarctic sedimentary deposits

description: This data repository contains back-scattered electron images for all 27 micrometeorites containing Cr-spinel studied in Van Maldeghem et al., 2024 (EPSL). The study analyzed Cr-spinel grains in a selection of micrometeorites from the Sør Rondane and Transantarctic Mountains (Antarctica) in order to determine their composition, formation and potential terrestrial alteration. We supply two geochemical datasets, both as excel spreadsheets. The first dataset (EMPA data) contains the electron microprobe data obtained using a JEOL JXA-8200 electron micro probe analyzer at the National institute of Polar Research (Tokyo, Japan). The second dataset contains the triple oxygen isotope ratios measured at the Centre de Recherches Pétrographiques et Géochimiques (Nancy, France).
DOI: 10.6084/m9.figshare.28615457.v2
title: 城市群的品牌旅游竞争力

description: 旅游品牌影响力：城市在国内外旅游市场的知名度、游客满意度、品牌美誉度等。旅游业发展 ： 旅游增加值、旅游收入、接待游客数量等。品牌与创意产业：文化遗产数量、文化和旅游融合指数等。基础设施和服务：酒店数量、景区评级、交通便利程度等。长三角城市群中27个城市的数据主要来源于政府统计年鉴、旅游行业报告、互联网搜索指数、社交媒体数据等，可用于城市旅游品牌评价、政策制定、市场营销、学术研究等领域，为城市品牌建设和文化旅游产业发展提供数据支撑。
DOI: 10.6084/m9.figshare.7116710.v1
title: ANALISIS PÁGINA INICIO YOUTUBE .xlsx

description: Resultados del análisis del artículo: <b>Entre el “Broadcast Yourself” y “Broadcast Whatever”: la página de inicio de <i>YouTube </i>como síntesis de su estrategia empresarial.</b><b></b>
DOI: 10.17632/gxvc3n42rk
title: Dataset of Exploring Consumer Perspective on Bittersweet by Najla: A Data-Driven Analysis Using Naive Bayes

description: This dataset contains consumer reviews of Bittersweet by Najla, a popular dessert brand in Indonesia, collected from three major platforms: Tokopedia, PergiKuliner, and GoFood. The reviews are in Bahasa Indonesia and reflect customer opinions on various aspects of the brand, including product quality, taste, pricing, and overall satisfaction. The research hypothesis suggests that consumer sentiment is mostly positive, with strengths in taste, packaging, and variety, while concerns related to pricing and texture consistency may contribute to negative feedback. By analyzing these reviews, this study seeks to uncover recurring themes and factors that influence purchasing decisions.

Data collection was conducted through web scraping using Octoparse, covering a period from January 2022 to October 2024. Initially, 1,400 reviews were gathered, but after filtering out duplicates, irrelevant entries, and incomplete data, the final dataset consists of 1,314 reviews. The dataset is structured with three main attributes: a unique Review ID, the Platform (Tokopedia, PergiKuliner, or GoFood), and the Review Text in its original form. The sentiment classification (positive or negative) has not yet been assigned, allowing for further analysis using machine learning or natural language processing techniques.

Preliminary observations indicate a mix of positive and negative feedback. Many consumers praise the taste, packaging, and product quality, while concerns over pricing and texture consistency appear frequently in negative reviews. Differences in feedback across platforms also suggest variations in customer expectations and experiences, particularly regarding delivery and service quality on food-ordering platforms.

This dataset holds significant value for various applications. Researchers can use it for sentiment analysis studies, particularly in Indonesia’s F&B industry, to understand consumer preferences and market trends. Businesses can analyze the data to identify key customer concerns, refine pricing strategies, and improve overall product consistency. Additionally, the dataset can serve as a training set for machine learning models in sentiment classification. Companies looking to enhance their digital marketing strategies can leverage these insights to optimize brand positioning and better understand consumer behavior. By exploring customer feedback, this dataset provides a foundation for improving customer satisfaction, strengthening brand loyalty, and guiding data-driven decision-making in the dessert industry.
DOI: 10.6084/m9.figshare.5367289.v1
title: Fig.4 (EIAV infection)

description: 2016.05.12 - infection 6 doses EIAV 293T clones GG
DOI: 10.17632/5xtcz3t8w5
title: Data for: Datasets on the GRP of Russian regions, GRP sectoral composition and growth rates in 2013 - 2018

description: Statistical data on the gross regional product of Russian regions obtained from EMISS – a Rosstat electronic database. The data were subjected to initial statistical processing. EMISS data on GRP per capita were used for calculating gross value added per capita and per employee for different economic sectors.
DOI: 10.17632/ng33vg479n
title: Experimental data on trial-by-trial AI assistance, feedback, human confidence and decisions during an AI-assisted decision-making chess puzzle task

description: The data are collected from a human subjects experiment to examine how human confidence in AI and self-confidence change and impact their decision-making during an AI-assisted decision-making task. The experimental task includes three practice and 30 experimental chess puzzle problems, which 100 participants are asked to solve with AI assistance. For each problem, the goal is to make the best next chess move given a board state. The participants first select an independent move (bmove1), receive AI suggestion (aisugg), make a final move (bmove2) , receive feedback on the final move (feedback2), and report their self-confidence (selfconf) and confidence in AI (aiconf). All of these data indicated in the parentheses are recorded in the dataset, as well as some other information including opponent's last move (wmove),  top seven moves with the highest evaluation scores (allgoodmoves), ranking of the AI suggestion (multiPV), goodness of the independent move (feedback1), chess board state before opponent's last move (fen before white move), and chess board state before the participants' move (fen before black move). There are two experimental conditions which differ in the order in which the AI performance (i.e., accuracy of AI suggestions) changes: 1) high-performing (80% accuracy) to low-performing AI (20% accuracy) and 2) low-performing (20%) to high-performing (80%) AI. Each CSV datafile ("data#_#") contains each participant's data, where the first # in the filename indicates the participant number and the second # indicates the condition number. For more detailed description of the dataset and the experiment, please refer to the Data In Brief article (publication in process) and the original research article (https://doi.org/10.1016/j.chb.2021.107018). This dataset can be utilized in various domains such as human-computer interaction, psychology, computer science, and team management in engineering/business that seek to understand human cognition and behavior in human-AI collaboration contexts.
DOI: 10.17632/nnph98d3kc
title: SyntheticIndoorObjectDetectionDataset

description: The dataset was collected from the MyNursingHome dataset, available at https://data.mendeley.com/datasets/fpctx3svzd/1 , and curated to develop a synthetic indoor object detection dataset for autonomous mobile robots, or robots, for supporting researchers in detecting and classifying objects for computer vision and pattern recognition. From the original dataset containing 25 object categories, we selected six key categories—basket bin (499 images), sofa (499 images), human (499 images), table (500 images), chair (496 images), and door (500 images). Initially, we collected a total of 2,993 images from these categories; however, during the annotation process using Roboflow, we rejected 1 sofa, 10 tables, 9 chairs, and 12 door images due to quality concerns, such as poor image resolution or difficulty in identifying the object, resulting in a final dataset of 2,961 images. To ensure an effective training pipeline, we divided the dataset into 70% training (2,073 images), 20% validation (591 images), and 10% test (297 images). Preprocessing steps included auto-orientation and resizing all images to 640×640 pixels to maintain uniformity. To improve generalization for real-world applications, we applied data augmentation techniques, including horizontal and vertical flipping, 90-degree rotations (clockwise, counter-clockwise, and upside down), random rotations within -15° to +15°, shearing within ±10° horizontally and vertically, and brightness adjustments between -15% and +15%. This augmentation process expanded the dataset to 7,107 images, with 6,219 images for training (88%), 597 for validation (8%), and 297 for testing (4%). Moreover, this well-annotated, preprocessed, and augmented dataset significantly improves object detection performance in indoor settings.
DOI: 10.17632/zfjzsmn262
title: Supplementary Materials: Skin cancer prevalence and risk among foreign-born people living in the US

description: Supplementary Materials: Demographic Characteristics (Table 1) and Skin Cancer Prevalence and Risk Factors with Differing Markers of Acculturation (Table 2)
DOI: 10.17632/97n9gxp5hz
title: Data for "Unraveling characteristics of the dominant light absorbing organic aerosols in wildfire smoke"

description: Data for the refractive index from EELS analysis and from TEM analysis of particles. Data obtained from the NASA DC8 is uploaded on the FIREX-AQ repository here: https://www-air.larc.nasa.gov/cgi-bin/ArcView/firexaq