Data in Brief最新文献

{"title":"Dataset on experimental investigation of temperature mediated variations in the chemical composition of bio-oil from pyrolysis of wheat bran","authors":"Priya Kaushik,&nbsp;Ashwani Mathur","doi":"10.1016/j.dib.2026.113120","DOIUrl":"10.1016/j.dib.2026.113120","url":null,"abstract":"<div><div>The article reports data on the chemical profiling of Bio-Oil, produced as one of the byproducts from the pyrolysis of sieved wheat bran (particle size range (250–500 µm)), at two different temperatures, <em>viz.</em> 500 °C and 800 °C. The chemical composition of the oil fraction was determined using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC–MS). The catalogues of organic compounds observed in GC-MS analysis of the two Bio-Oil fractions revealed relatively higher numbers of compounds in the sample obtained on pyrolysis at 800 °C than in the oil obtained on pyrolysis at 500 °C The GC–MS analysis of wheat bran bio-oils produced at 500 and 800 °C revealed oxygenated compounds (3-furanmethanol and 1,4:3,6-dianhydro-α-D-glucopyranose), sulfur-containing compounds (trans-2,4-dimethylthiane S,S-dioxide), nitrogen-containing compounds (urea, imidazole, dimethylpyridine derivates and pyrozolinone derivatives) and minor hydrocarbons. These compounds originated primarily from the thermal degradation of cellulose, hemicellulose, proteins and amino acids while higher pyrolysis temperatures promoted secondary cracking and cyclization reactions. Several boron-containing compounds were also tentatively identified by NIST library matching and should be interpreted with caution. Alternatively, LC-MS analysis had shown similar trend with common organic compounds, including 2,4-Xylidine; Dimethylpyrazine; 2,4-Diaminotoluene; N-Methylcaprolactam; and Quinoline. The identified compounds demonstrate the conversion of wheat bran biomass into a range of value-added organic constituents through pyrolytic reactions. The results presented herein serve as a stepping stone to strengthen research on scalable process development for the valorisation of agro-waste, such as wheat bran, thereby minimizing the environmental burden.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113120"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148778059","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":"CleanCam: A labelled underwater image dataset for camera-viewport fouling assessment in aquaculture monitoring","authors":"Khoa Nguyen,&nbsp;Anh Hoang,&nbsp;Nhat-Anh Tran,&nbsp;Nguyet-Anh Tran,&nbsp;Minh-Hoang Pham,&nbsp;Khoi Phan,&nbsp;Van-Dinh Nguyen,&nbsp;Dzung V. Dinh,&nbsp;Cuong Do","doi":"10.1016/j.dib.2026.113137","DOIUrl":"10.1016/j.dib.2026.113137","url":null,"abstract":"<div><div>CleanCam is a labelled underwater image dataset for assessing fouling on camera viewports in aquaculture monitoring. Real images were sampled every 10 s from fixed underwater videos recorded by two camera nodes in golden pompano (<em>Trachinotus blochii</em>) rearing tanks at the Research Institute for Aquaculture No. 1 in Hai Phong, Viet Nam. The real subset contains 18,972 RGB JPEG images collected across 20 effective collection days and annotated on a five-level ordinal scale from L1 clean to L5 heavy obstruction. The labels describe material attached to the camera viewport, rather than generic image quality. Temporal context was used during annotation to distinguish persistent viewport deposits from turbidity, suspended particles, lighting variation, and other water-column effects. The release also includes 3,600 split-consistent synthetic images for Levels 3 to 5, giving 22,572 images in total. The Zenodo package provides image folders, image-level metadata, synthetic provenance records, deterministic capture-disjoint train, validation, and test splits, a data dictionary, release manifests, and documentation. The accompanying public code reproduces the manuscript figures and tables and supports release validation, dataset characterization, synthetic-subset analysis, and reference classification workflows. CleanCam can be reused for ordinal image classification, cleaning/no-cleaning threshold studies, synthetic augmentation experiments, leakage-aware benchmarking, and image-stream quality control in long-term aquatic monitoring systems.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113137"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148778127","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 curated dataset of Abstract Syntax Tree-based structural dependency graphs and object-oriented metrics for 21 open-source Java systems","authors":"Marcos Cordeiro de Brito Jr.,&nbsp;Leandro Augusto da Silva","doi":"10.1016/j.dib.2026.113290","DOIUrl":"10.1016/j.dib.2026.113290","url":null,"abstract":"<div><div>This article describes a curated dataset of structural dependency graphs and object-oriented metrics extracted from 21 open-source Java systems. Each repository was analyzed at a fixed commit using a deterministic AST-based static analysis pipeline. For every project, the dataset provides a weighted directed GraphML file encoding class-to-class structural dependencies, with node-level metrics (LCOM4, CBO, RFC, NOM, NOA) embedded as node attributes, together with execution metadata documenting repository URL, commit hash, extraction date, tool and dependency versions, and a configuration hash that makes the analysis parameters independently verifiable. The selected systems cover distinct domains, including build tools, frameworks, distributed platforms, and utility libraries, and range in size from 43 to 29,695 classes. All artifacts correspond to dataset version v1.0.1 and are publicly available through a Zenodo repository (DOI: <span><span>https://doi.org/10.5281/zenodo.18744312</span><svg><path></path></svg></span>). The dataset was generated using JASTG v1.0.0 (commit b62a943), providing version-level traceability between code and data. The dataset is intended for use in graph-based modularity analysis, community detection, and architectural structure mining on Java code representations.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113290"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149143440","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":"EVIORA-HAR: A multimodal dataset for elderly activity recognition and safety-controlled fall detection using wearable inertial sensors and multi-view cameras","authors":"Iwan Kurnianto Wibowo,&nbsp;Chastine Fatichah,&nbsp;Nanik Suciati","doi":"10.1016/j.dib.2026.113285","DOIUrl":"10.1016/j.dib.2026.113285","url":null,"abstract":"<div><div>EVIORA-HAR is a multimodal dataset for human activity recognition and fall detection that combines wearable inertial sensing with multi-view RGB video. The data were collected from 104 participants comprising 71 older adults aged 60–93 years performing activities of daily living and 33 healthy adults aged 18–24 years performing safety-controlled fall scenarios. Daily activities were recorded in residential homes and elderly care environments, whereas fall scenarios were acquired in a controlled indoor environment for participant safety. Five wearable inertial measurement unit nodes were attached to the chest, waist, right hand, right thigh, and left ankle. Visual data were captured using three camera configurations: a full-view static camera, a partially occluded static camera, and a dynamic pan-tilt-zoom camera that followed participant movement. Video was recorded at 1280 × 720 resolution and 60 frames per second, while inertial data were recorded at 60 Hz. The dataset contains untrimmed coarse-grained recordings and trimmed fine-grained activity segments representing walking, postural states, postural transitions, and forward, sideward, and backward falls. The trimmed data comprise 11 fine-grained activity classes. Using FV Cam as the reference distribution, the dataset contains 340 walk segments (68.72 min), 323 stand-to-sit (18.18 min), 314 sit-to-stand (16.60 min), 330 sit-to-lay (21.58 min), 321 lay-to-sit (20.31 min), 347 stand (48.17 min), 823 lay (118.59 min), 657 sit (91.58 min), 170 fall-forward (9.45 min), 150 fall-sideward (8.23 min), and 160 fall-backward segments (9.03 min). The released data include privacy-protected RGB videos, inertial signal files, pose-estimation outputs, activity labels encoded in the directory structure and file names, and consistent identifiers supporting modality correspondence. These data can be reused for wearable-sensor, video-based, skeleton-based, multi-view, occlusion-aware, dynamic-camera, and multimodal human activity recognition and fall-detection research.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113285"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149143441","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":"Multi-omics datasets of paddy field soils to support functional and ecological analysis of microbial communities","authors":"Qinghong Qian,&nbsp;Fangyu Mo,&nbsp;Fei Xu,&nbsp;Longjiang Fan","doi":"10.1016/j.dib.2026.113298","DOIUrl":"10.1016/j.dib.2026.113298","url":null,"abstract":"<div><div>Soil microbial communities are essential for ecosystem functioning and crop productivity. This dataset consists of 8 soil samples collected from four paddy field plots in Zhejiang, China, including organic and conventional management types during the winter fallow period under sunny conditions. For each plot, soil was sampled from two points at 10 cm depth, resulting in a total of 8 samples. Each sample was subjected to both metagenomic and metatranscriptomic sequencing, generating 16 datasets in total. DNA and RNA were extracted using standardized protocols, followed by Illumina PE150 sequencing. The metagenomic and metatranscriptomic data passed quality control and meet standard sequencing metrics, providing high-quality raw reads, assembled contigs, cDNA libraries, and gene expression matrices. These datasets are a reusable resource for studies on rice soil microbial communities and can support integration with other multi-omics data, such as proteomics or single-cell genomics, for broader investigations into soil microbial diversity and function.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113298"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149143446","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 multilingual annotated dataset for metadata extraction from Persian, Arabic and English scientific articles: header and reference section annotations","authors":"Arash Yousefi Jordehi,&nbsp;Reza Fallah,&nbsp;Ebrahim Nikmard,&nbsp;Mahsa Hosseini Khasheh Heyran,&nbsp;Seyed Abolghasem Mirroshandel","doi":"10.1016/j.dib.2026.113275","DOIUrl":"10.1016/j.dib.2026.113275","url":null,"abstract":"<div><div>This data article describes a multilingual annotated dataset for training and evaluating metadata extraction systems for scientific articles written in Persian, Arabic and English. The dataset consists of 635 JSON files, one per scientific article, holding the annotations of the article header and of the reference section. The article-level language distribution is 352 Persian (55.4 %), 142 English (22.4 %) and 141 Arabic (22.2 %). Of the 635 articles, 621 contain annotated reference sections; the remaining 14 contain header annotations only. In total, 17,832 individual reference strings are annotated, comprising 8476 Persian (47.5 %), 5741 Arabic (32.2 %) and 3615 English (20.3 %) strings. Header annotations cover seven metadata fields: title, authors, affiliations, abstract, keywords, venue information and DOI. Reference annotations cover twelve metadata fields: title, authors, journal or conference name, volume, issue number, page range, year, DOI, publisher, book identifier, organisation and reference type, alongside the raw reference string. The source articles were retrieved from open-access repositories covering &gt;580 conferences and journals. Annotation was carried out over a period of more than twelve months by a team of ten annotators using a purpose-built Java labelling tool with color-coded tagging, and every annotated file was checked against its source PDF in a dedicated review phase. Each file is self-contained: it stores the annotated text spans verbatim together with their labels, so the original PDF is not required in order to use the data. The format can be consumed directly by sequence labelling methods such as conditional random fields, recurrent neural networks, transformer-based token classifiers and large language models. The data can be reused to develop and benchmark metadata extraction and citation parsing systems and to support indexing in digital libraries and scholarly search services covering Persian and Arabic literature.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113275"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149054163","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":"Needle bearing endurance test data for early fault detection during oscillating movements","authors":"Timur Seferli,&nbsp;Jens Windelberg,&nbsp;Andreas Bierig","doi":"10.1016/j.dib.2026.113268","DOIUrl":"10.1016/j.dib.2026.113268","url":null,"abstract":"<div><div>In aviation, there is a transition to more electric aircraft (MEA) for commercial aircraft, as electric powered components promise an increase in operational efficiency. These components are being integrated into the primary and secondary flight control system. The adaptation of electromechanical actuators (EMAs), for instance, can enhance maintainability, reliability and reduce the overall aircraft weight. However, the service life of such an actuator depends on the failure mechanisms of its components. During operation, bearings are critical components because they experience short-stroke movements that may lead to early failure due to fretting corrosion. Under these conditions, the amplitude of the oscillation, the frequency and the applied load vary. To ensure the safe and reliable operation of EMAs, it is necessary to implement an early fault detection mechanism and to improve oscillating bearing lifetime calculation. For accurate prediction of the remaining useful life (RUL), high-fidelity and reliable data are essential. Vibration measurements or analyses of torque signals are frequently used for this purpose. Thus, this data article presents a dataset of eight independent run-to-failure experimental data. The performance of needle bearings was tested using different lubricants. In these tests, the bearings were radial preloaded with 9 to 19.4 kN, the oscillation angle varied between 10° and 20°, and frequencies of 5 Hz and 10 Hz were applied. This article provides measurements of acceleration, temperature, positional displacement, torque fluctuation, and radial movement dynamics obtained from oscillating needle bearings. This dataset serves as a valuable resource to improve the understanding of signal characteristics associated with bearing degradation and fault progression. The results from different tested initial parameters can be leveraged to develop and validate RUL predictive models in various industrial and aerospace engineering applications.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113268"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149054164","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":"Pilot drive-test LTE handover dataset for radio measurement analysis in urban Bangladesh","authors":"M.M. Sadman Shafi,&nbsp;K.M. Istiaque,&nbsp;Shafayet Sadik Sowad,&nbsp;Tasnia Siddiqua Ahona,&nbsp;Mubtasim Labib,&nbsp;Yasin Hasan Saad,&nbsp;Md Nazakat Eram,&nbsp;Mohammad T. Kawser","doi":"10.1016/j.dib.2026.113220","DOIUrl":"10.1016/j.dib.2026.113220","url":null,"abstract":"<div><div>This article presents a pilot Long Term Evolution (LTE) drive-test dataset collected from a real urban cellular network in Dhaka, Bangladesh. The dataset contains field measurements of radio signal conditions, Layer-3 measurement reports, and handover statistics obtained using professional drive-testing tools including XCAL-M software and Samsung Exynos-based user equipment. Measurements were recorded during multiple drive-test sessions along a 13 km urban route, producing timestamped observations of key radio parameters such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Carrier-to-Interference-plus-Noise Ratio (CINR), and serving/neighbor cell identifiers. The dataset is organized into raw and processed directories containing dynamic radio management (DRM) log files, Layer-3 measurement reports, handover event statistics, and tabular datasets to support reproducibility and flexible analysis. The processed dataset demonstrates an example preprocessing workflow including filtering, timestamp alignment, interpolation of missing signal values, and handover labeling with Time-to-Trigger (TTT) context. Due to the limited size of the dataset, it is primarily intended for exploratory analysis, mobility characterization, small-scale machine learning experiments, reinforcement learning environments, and educational research in cellular network engineering. By providing both raw drive-test logs and structured datasets, this resource supports reproducible studies of LTE handover behavior and urban radio environments.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113220"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149006292","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 long-term, analysis-ready dataset of rice phenology in middle and lower reaches of the Yangtze River Plain of China from 1981 to 2024","authors":"Quan-Jun Zhang,&nbsp;Dong-Li Wu","doi":"10.1016/j.dib.2026.113310","DOIUrl":"10.1016/j.dib.2026.113310","url":null,"abstract":"<div><h3>Background</h3><div>Quantifying the impact of climate change on rice production, a cornerstone of global food security, requires long-term, spatially explicit, and readily analyzable phenological data. While the Middle and Lower Yangtze River Plain (MLYRP) is China's primary rice bowl, a critical gap persists: the lack of a publicly available, multi-decadal, station-based dataset that provides not only raw phenological dates but also curated statistical trends for the entire growth cycle, tailored for immediate reuse by the research community.</div></div><div><h3>The dataset</h3><div>To bridge this gap, we present “MLYRP-rice phenology data”, a foundational dataset characterizing rice phenology dynamics across the MLYRP from 1981 to 2024. Derived from rigorously quality-controlled records of 95 national agrometeorological stations, this dataset is architected for reuse, offering two synergistic products: (1) A visualization collection comprising 2,432 high-resolution graphs that intuitively depict the probability distribution and temporal trends of 11 phenological stages and 3 growth phase lengths via kernel density estimation and linear regression. (2) A machine-actionable statistical core, structured as an Excel spreadsheet, which provides the complete results of the linear trend analysis (including slope, intercept, R², F-value, and p-value) for every station and variable.</div></div><div><h3>Value and potential for reuse</h3><div>This dataset transcends a mere data compilation by delivering an analysis-ready product. It is designed as a community benchmark to directly facilitate crop model validation, climate-impact meta-analyses, remote sensing product verification, and data-driven agricultural adaptation planning. By providing pre-computed, statistically robust trends, “MLYRP-rice phenology data” establishes an indispensable empirical foundation for detecting and attributing climate impacts on one of the world's most critical agricultural systems.</div></div><div><h3>Availability</h3><div>The dataset is open-access and available at <span><span>https://doi.org/10.57760/sciencedb.25297</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113310"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149202026","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":"AryWiki-Instruct: A high-fidelity instruction tuning dataset for Moroccan Arabic (Darija)","authors":"Safouane Boudakkou,&nbsp;Abdelaaziz El Hibaoui","doi":"10.1016/j.dib.2026.113140","DOIUrl":"10.1016/j.dib.2026.113140","url":null,"abstract":"<div><div>This article presents AryWiki-Instruct, a high-fidelity instruction tuning dataset for Moroccan Arabic (Darija), comprising 46,590 Question and Answer (QA) pairs. The dataset was derived from a snapshot of the Moroccan Arabic Wikipedia (<em>arywiki</em>) and generated using <em>the Gemini-2.5-Flash</em> model via a Context Aware batch processing architecture. The data creation process involved parsing raw XML Wikipedia dumps, filtering for script consistency and token density, and applying a Context Injection generation strategy to prevent coreference ambiguity. To ensure high information density, the raw generated output (82,500 pairs) was subjected to a rigorous automated quality assurance pipeline. This pipeline utilized a hierarchical trigger confirmation algorithm to remove repetitive administrative census noise and employed composite embedding based clustering (<em>multilingual-e5-large</em>) for semantic deduplication. The final dataset is formatted as a JSONL file, providing paired instructions and responses alongside their taxonomic categories. This dataset provides a native first culturally grounded resource designed to facilitate the supervised fine tuning of Large Language Models (LLMs) in Maghrebi dialects, circumventing the syntactic limitations of translated English instruction sets.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113140"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148733271","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}