Data in Brief最新文献

{"title":"Comprehensive image dataset of flexible pavement: Alligator cracks and edge-breaks from national highway (N6) of urban areas","authors":"Md. Nayem Hossain ,&nbsp;Nakib Aman ,&nbsp;Nymur Rahaman Antor ,&nbsp;Nafisa Tasnim ,&nbsp;Md Zubair Azam ,&nbsp;Sabab Asfaq","doi":"10.1016/j.dib.2026.112531","DOIUrl":"10.1016/j.dib.2026.112531","url":null,"abstract":"<div><div>This data article introduces a structured pavement surface image dataset developed to advance research in automated pavement condition assessment and data-driven road infrastructure monitoring. The dataset comprises three distinct pavement condition categories: (i) alligator cracking, (ii) edge-breaking distress, and (iii) undamaged (intact) pavement surfaces, each representing a prevalent form of pavement deterioration or intact condition typically observed in flexible pavements. The dataset consists of 12,000 raw images (4000 per class) collected under real-world conditions. These images represent the primary scientific contribution of the dataset. All images were standardized through resizing and normalization, and the dataset was partitioned into training, validation, and testing subsets to ensure reproducibility and consistency in data-driven experiments. Pavement images were collected from selected segments of National Highway N6 in Pabna District, Bangladesh, under natural daylight conditions using a smartphone camera during field surveys. Image acquisition was conducted following standard safety practices without disrupting traffic flow. All images were manually reviewed and labelled to ensure annotation accuracy. This dataset is intended to support research on automated pavement crack detection and classification, benchmarking of computer vision and deep learning models, and the development of lightweight and edge-deployable inspection systems.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112531"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185072","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":"An annotated dataset of images of Chinese giant salamanders","authors":"Xinyao Yang ,&nbsp;Junyi Chen ,&nbsp;Didi Lu ,&nbsp;Nanqing Sun ,&nbsp;Mokai Xie ,&nbsp;Haotian Qian","doi":"10.1016/j.dib.2026.112552","DOIUrl":"10.1016/j.dib.2026.112552","url":null,"abstract":"<div><div>The Chinese giant salamander is classified as a Class II protected species in China and is recognized as critically endangered by the International Union for Conservation of Nature (IUCN). Due to their unique behavioral patterns, wild Chinese giant salamanders are primarily nocturnal and inhabit areas characterized by complex terrain, which results in limited detection coverage and significant challenges in observation. Consequently, images of wild Chinese giant salamanders are exceedingly rare, and the scarcity of existing data impedes the advancement and application of deep learning-based object detection models. This study constructs and releases a specialized dataset for Chinese giant salamanders, comprising 1386 images and a total of 1397 annotated bounding boxes. All images represent diverse field scenarios and are meticulously annotated in accordance with YOLO (You Only Look Once) labeling specifications. Annotation files are provided in both PASCAL VOC (Visual Object Classes) and COCO (Common Objects in Context) formats to ensure compatibility with leading detection frameworks, including YOLO v8 and YOLO v11. This dataset aims to offer high-quality, multi-scenario annotated data for research in computer vision and conservation biology, facilitating the training and evaluation of models for intelligent monitoring and species conservation of the Chinese giant salamander, thereby promoting the development of visual recognition technologies for endangered species.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112552"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dataset on ecological health and microbial communities of coastal aquaculture ponds from surrounding region of Sundarban mangroves","authors":"Yash ,&nbsp;Anwesha Ghosh ,&nbsp;Ajanta Dey ,&nbsp;Milon Sinha ,&nbsp;Nimai Bera ,&nbsp;Sabyasachi Chakraborty ,&nbsp;Punyasloke Bhadury","doi":"10.1016/j.dib.2026.112542","DOIUrl":"10.1016/j.dib.2026.112542","url":null,"abstract":"<div><div>Integrated Mangrove Aquaculture (IMA) and Sustainable Aquaculture in Mangrove Ecosystem Fisheries (SAIME) are key activities undertaken across coastal regions globally to meet growing demand for brackish-water aquaculture products through sustainable practices. An in-depth biomonitoring study was conducted to map the ecological health of IMA and non-IMA aquaculture ponds in the surrounding region of the Indian Sundarbans mangroves located along the northeast coast of Bay of Bengal. Surface water samples were collected from six aquaculture ponds, four IMA (IMA_C1, IMA_C3, IMA_DB1, and IMA_DB4) and two non-IMA (C6_NM and DB5_NM) in the month of October 2022, for characterizing niche-specific biological communities using the environmental DNA (eDNA) approach. During sampling, <em>in-situ</em> environmental parameters were recorded. Mangrove litter-derived phenolics (tannic and gallic acids) and dissolved nutrients were estimated using a UV–Vis spectrophotometer, while dissolved organic carbon (DOC) was measured with the elemental analyzer. Metal and metalloid concentrations were determined by inductively coupled plasma mass spectrometry approach (ICP–MS). IMA ponds showed ideal conditions for shrimp aquaculture, with pH ranging from 7.913 to 8.633 and dissolved oxygen (DO) between 5.32 and 6.03 mg/L, indicating no hypoxic conditions despite higher concentrations of phenolics. High-throughput sequencing (HTS) based on Oxford Nanopore Technologies (ONT) sequencing chemistry was undertaken on the MinION platform, revealing the predominance of Proteobacteria among prokaryotes and Bacillariophyta as well as Chlorophyta among eukaryotes from extracted eDNA in each studied pond. Additionally, members of the family Cyprinidae were also detected, reflecting the biodiversity of fish population in these ponds. Functional gene profiling indicated signatures associated with nitrogen, phosphorus, sulphur, potassium and iron acquisition and metabolism, along with pathways related to aromatic compound degradation. Overall, dissolved nutrients, dissolved organic carbon (DOC), metal and metalloid ion concentrations as well as structure and functional profiles of biological communities provide a comprehensive basis for evaluating the ecological health of aquaculture ponds. This study generates important baseline information for long-term monitoring and represents the first eDNA-based high-throughput sequencing assessment of IMA and non-IMA aquaculture ponds from surface water in close proximity to the Sundarbans mangrove.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112542"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive multimodal MRI and EEG-TMS dataset on the impact of parietal cortex inhibition on decision-making under ambiguity","authors":"Alejandra Figueroa-Vargas ,&nbsp;Gabriela Valdebenito-Oyarzo ,&nbsp;María Paz Martínez-Molina ,&nbsp;Francisco Zamorano ,&nbsp;Pablo Billeke","doi":"10.1016/j.dib.2026.112535","DOIUrl":"10.1016/j.dib.2026.112535","url":null,"abstract":"<div><div>In daily life, we often face decisions where potential outcomes are unclear, creating uncertainty. The complete or partial lack of knowledge regarding outcome probabilities—referred to as ambiguity—poses significant challenges for individuals. While recent studies have linked ambiguity in decision-making to neural activity in the parietal cortex, the precise role of this region and its interactions with other brain areas remain poorly understood.</div><div>Here, we present a comprehensive dataset on human decision-making under conditions of risk and ambiguity. The dataset includes two experimental sessions. The first one corresponds to the MRI setting, which includes structural MRI (T1- and T2-weighted images, <em>n</em> = 52), diffusion-weighted imaging (<em>n</em> = 45), and task-based functional MRI (<em>n</em> = 38). The second session corresponds to the EEG setting combined with inhibitory transcranial magnetic stimulation (TMS), targeting two parietal regions and the vertex (<em>n</em> = 24). TMS targets were defined from group-level fMRI activations obtained in the first session and then transformed to individual anatomy. Ten participants completed both fMRI and EEG-TMS recordings.</div><div>This dataset, partially analyzed in previous work, now includes newly acquired and previously unexamined data—such as diffusion-weighted imaging, T2-weighted images—and is fully organized according to the Brain Imaging Data Structure (BIDS) standard. It provides valuable opportunities to investigate the neurobiological decision-making mechanisms under ambiguity, focusing on the parietal cortex.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112535"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The complete mitochondrial genome and phylogenetic analysis of the polychaete Diopatra sp. (Annelida: Onuphidae)","authors":"Bhavya Kachiprath,&nbsp;Chang-Bum Jeong","doi":"10.1016/j.dib.2026.112526","DOIUrl":"10.1016/j.dib.2026.112526","url":null,"abstract":"<div><div>The polychaete genus <em>Diopatra</em> is widely distributed in tropical and subtropical coasts and plays key ecological roles as an ecosystem engineer. Despite &gt;65 recognized species, its taxonomy remains unresolved due to extensive cryptic speciation and limited molecular data. In this study, we sequenced and annotated the complete mitochondrial genome of <em>Diopatra</em> sp. collected from Incheon, South Korea. The mitogenome was 14,985 base pairs in length and contained 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, and two ribosomal RNA (rRNA) genes (<em>rrnS</em> and <em>rrnL</em>), consistent with typical metazoan organization. This mitogenome provides a genetic reference that supports comparative mitogenomic and phylogenetic analyses, as well as the resolution of cryptic diversity and accurate taxonomic assignment in environmental DNA (eDNA)-based biodiversity assessments. Phylogenetic analysis based on concatenated PCG sequences from 37 polychaete mitogenomes representing six families placed <em>Diopatra</em> sp. in a well-supported clade with <em>Diopatra cuprea</em> and <em>Hyalinoecia robusta</em> (Onuphidae) within the subclass Errantia. These findings reinforce the monophyly of <em>Diopatra</em> within Errantia and provide valuable genetic information for resolving the cryptic diversity, phylogenetic relationships, and evolutionary history of polychaetes.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112526"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185144","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":"Two-year daily precipitation stable isotope dataset (δ18O and δ2H) from a continental station in NW Croatia","authors":"Maja Briški,&nbsp;Iva Palatinuš,&nbsp;Petra Bajo,&nbsp;Vlatko Brčić","doi":"10.1016/j.dib.2026.112509","DOIUrl":"10.1016/j.dib.2026.112509","url":null,"abstract":"<div><div>The stable water isotopic composition (δ¹⁸O and δ²H) of daily precipitation from north-western Croatia (near Samobor town) is presented. The dataset includes a total of 288 precipitation samples collected from December 2022 to November 2024. The collection period roughly covered a 24-hour cycle, starting predominantly early in the morning. Stable hydrogen and oxygen isotope analyses of the samples were carried out using a Picarro L2130-i Isotope analyzer, with a precision of 1 ‰ for δ²H and 0.2 ‰ for δ¹⁸O. The raw isotopic data of the precipitation samples are presented in δ-notation (‰) normalized to the international standard VSMOW (Vienna Standard Mean Ocean Water). Additionally, the <span>d</span>-excess values for each sample and the Local meteoric water line (LMWL) were calculated. Presented data were used to investigate the main drivers of stable isotope variability in Croatia and were published in the research article entitled “Assessing the influence of climatic parameters and moisture sources on precipitation isotope composition from central Croatia: Insights from a two-year long daily-resolved dataset“. In addition to studying the isotope effects in modern precipitation, this dataset can also be used in palaeoclimate investigations that utilize natural climate archives, as well as environmental studies, including tracking of water pollutants and water resource management.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112509"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Uav-based multisensor framework for legal industrial Cannabis monitoring and open-access dataset development","authors":"Genta Rexha ,&nbsp;Ina Papadhopulli ,&nbsp;Aleksandër Biberaj ,&nbsp;Elson Agastra ,&nbsp;Enida Sheme ,&nbsp;Elinda Meçe","doi":"10.1016/j.dib.2026.112463","DOIUrl":"10.1016/j.dib.2026.112463","url":null,"abstract":"<div><div>Industrial hemp cultivation is expanding and requires reliable monitoring for legal compliance and agricultural management. This paper presents a standardized UAV-based multisensor framework designed for Cannabis sativa L. It integrates RGB, multispectral, and thermal imaging as core modules, with hyperspectral and LiDAR as optional extensions. The framework sets protocols for sensor integration, flight planning, field measurements, and annotation, ensuring datasets that meet EU altitude limits (≤120 m AGL). Multi-altitude and multi-time-of-day acquisitions are proposed to capture spatial and diurnal variability. These data improve model robustness for phenotyping, stress detection, and THC compliance verification. Potential applications include precision agriculture, breeding, regulatory monitoring, environmental assessment, and illicit crop detection. Open-access datasets generated through this framework will support reproducibility, machine learning development, and collaboration among researchers, farmers, and regulators.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112463"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976673","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":"ConcreteCARB: A comprehensive image dataset of concrete carbonation for computer vision tasks","authors":"José A. Guzmán-Torres,&nbsp;Sandra del C. Arguello-Hernández,&nbsp;Francisco J. Domínguez-Mota,&nbsp;Gerardo Tinoco-Guerrero,&nbsp;Elia M. Alonso-Guzmán","doi":"10.1016/j.dib.2026.112493","DOIUrl":"10.1016/j.dib.2026.112493","url":null,"abstract":"<div><div>The ConcreteCARB dataset provides a comprehensive repository of 903 high-resolution images of concrete surfaces evaluated using the phenolphthalein test for carbonation detection. This data was collected under controlled laboratory conditions and aims to support artificial intelligence applications in civil engineering, especially in structural health monitoring tasks. The images are systematically organized into two distinct classes: “Carbonated Samples” and “No Carbonation Presence,” enabling binary classification approaches. All samples were manually tested, split, and visually labelled by expert engineers to ensure reliable ground-truth classification, in accordance with standardized procedures. The dataset includes images of concrete prism elements fabricated with varying mix designs, incorporating different water-cement ratios and additives, such as industrial silica waste and natural admixtures derived from Opuntia ficus-indica. The specimens were subjected to natural atmospheric carbonation conditions for 180 days, and their carbonation fronts were revealed by phenolphthalein staining. The samples were then split manually with a chisel and hammer, and photographic documentation was performed with a Samsung SM-S901U1 smartphone using predefined settings to ensure consistency and quality across the dataset. ConcreteCARB is intended for researchers, engineers, and data scientists working on machine learning, deep learning, and computer vision solutions for concrete diagnostics. It provides valuable training and benchmarking data for the development of automated detection, classification, and segmentation models for carbonation damage assessment. Furthermore, the dataset can serve as a foundational tool for cross-comparative studies on the efficacy of AI techniques in materials degradation analysis. The openly accessible nature of the dataset through a public repository supports reproducibility and encourages the extension of AI applications in concrete durability and sustainability studies.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112493"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075163","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":"BD Sports-10: A comprehensive video dataset for Bangladeshi sports classification and analysis","authors":"Wazih Ullah Tanzim ,&nbsp;Niloy Barua Supta ,&nbsp;Shifatun Nur Shifa ,&nbsp;Khondaker A. Mamun","doi":"10.1016/j.dib.2025.112442","DOIUrl":"10.1016/j.dib.2025.112442","url":null,"abstract":"<div><div>Bangladesh has diverse and vibrant cultural sports, some of which have gained international recognition in recent years. However, there is a lack of standardized datasets for deep learning and computer vision tasks. To address this gap, BD Sports-10 was developed as a comprehensive dataset for Bangladeshi sports. It consists of ten unique sports categories, with a total of 3000 videos, 300 per class, with a resolution of 1920×1080 pixels and 30 frames per second (FPS). Each sport in the dataset features distinct rules, viewing angles, playground setups, and actions, which also depend on players’ skills. The dataset captures a diverse range of actions, including jumping, running, tagging, throwing, attempting to hit a clay pot, and capturing an opponent before they cross a designated line. BD Sports-10 includes ten traditional and culturally significant sports: <em>Kabaddi, Nouka Baich, Lathi Khela, Kho Kho, Kanamachi, Toilakto Kolagach Arohon (Kolagach), Hari Vanga, Morog Lorai, Lathim,</em> and <em>Joldanga</em>. This standardized and balanced dataset is not only suitable for classification tasks but also for object detection, player tracking, and automated scoring systems. The dataset supports research in deep learning, machine learning, and computer vision by providing ready-to-use scripts, datasets, and preprocessing pipelines that facilitate diverse AI-based experimental workflows.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112442"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075246","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":"Measurement data from full-scale fire experiments of battery electric vehicles and internal combustion engine vehicles","authors":"Nathaniel G. Sauer,&nbsp;Matthew J. DiDomizio,&nbsp;Richard M. Kesler,&nbsp;Shruti Ghanekar,&nbsp;Parham Dehghani,&nbsp;Gavin P. Horn,&nbsp;Adam Barowy","doi":"10.1016/j.dib.2026.112471","DOIUrl":"10.1016/j.dib.2026.112471","url":null,"abstract":"<div><div>Over time, the burning behaviour of passenger vehicles has been influenced by continuous advancements in vehicle design, including changes in materials, manufacturing processes, and the integration of modern lithium-ion battery powertrains. Fire protection engineers, first responders, and other safety professionals currently lack sufficient data to determine whether existing fire protection system designs and firefighting practices effectively mitigate the burning behaviour of modern vehicle fires or to adapt these approaches to any measurable changes in fire dynamics. Eighteen full-scale vehicle fire experiments were conducted in a laboratory environment to obtain a novel data set describing the fire size, thermal hazards, and evolved smoke and particulate species resulting from vehicle fires. Vehicle mass, gas temperature, heat flux, sorbent tube, Fourier-transform infrared spectrometer, and suppression waterflow data are provided in tabular format. Eight vehicle models across six manufacturers were selected based on the most popular battery electric and gasoline powered compact and mid-sized recently sold in North America at the time of writing. Experiments consisted of nine free-burn experiments wherein the gasoline vehicles were ignited in the engine compartment and the electric vehicle battery packs were induced into thermal runaway; these fires progressed unabated until the occurrence of natural flame extinction. Another four experiments simulated electric vehicle fire suppression using ordinary water and traditional vehicle fire suppression techniques. In one additional experiment, an encapsulator firefighting agent was added to the water. The final four experiments consisted of deploying fire blankets over the burning vehicles a single strategy or in combination with water simultaneously applied from beneath. There are many potential uses of this data, but primary uses are expected to include revision of design criteria and guidance within the fire protection engineering community, strategic and tactical decision aids for vehicle fire incident operations, validation of existing (and development of new) fire behavior models, and guidance to vehicle manufacturers for improved fire safety design.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"65 ","pages":"Article 112471"},"PeriodicalIF":1.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075116","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}