Data in Brief最新文献

{"title":"Osteometric dataset of rodent skeletal collections from Armenia (1940–1981)","authors":"Nina H. Manaseryan,&nbsp;Luba V. Balyan,&nbsp;Mamikon G. Ghasabyan,&nbsp;Maria A. Kumelova,&nbsp;Andranik A. Gyonjyan","doi":"10.1016/j.dib.2026.113112","DOIUrl":"10.1016/j.dib.2026.113112","url":null,"abstract":"<div><div>This data article presents a comprehensive osteometric dataset of Rodentia specimens curated at the Institute of Zoology, Armenia. The dataset comprises detailed cranial and postcranial measurements from 211 individuals, representing 27 species across 5 families. Collected over a 41-year period (1940–1981) throughout Armenia, the material includes standardized raw measurements of the skull, scapula, humerus, ulna, pelvis, femur, and tibia, following established zoological protocols. As the largest rodent osteological collection in the region, this dataset serves as a vital open-access comparative resource for ecological and archaeozoological studies, particularly for the taxonomic identification of fragmented Holocene faunal remains.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113112"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148733644","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":"Complete plastome data of Saccharum hybrid cultivar VMC 76–16, a valuable genomic resource for investigating evolutionary relationships among modern sugarcane cultivars in Indonesia","authors":"Tiara Putria Judith,&nbsp;Widhi Dyah Sawitri,&nbsp;Oliv Nurul Kanaya,&nbsp;Boon Chin Tan,&nbsp;Kah Ooi Chua,&nbsp;Ganies Riza Aristya","doi":"10.1016/j.dib.2026.113115","DOIUrl":"10.1016/j.dib.2026.113115","url":null,"abstract":"<div><div>Sugarcane (<em>Saccharum</em> hybrid) is one of the world's most important sugar-producing crops and a valuable genomic resource for supporting molecular characterization and breeding programs. This article describes the complete chloroplast genome (plastome) dataset of the Indonesian sugarcane cultivar VMC 76–16, an introduced cultivar with desirable agronomic traits, including high sucrose content, early maturity, and tolerance to several major diseases. The plastome was assembled from paired-end DNBSEQ sequencing data comprising approximately 1.5 Gb of raw data generated from 5000,000 paired-end reads (2 × 150 bp). The assembled plastome is 141,181 bp in length with an overall GC content of 38.0% and exhibits the typical quadripartite structure, consisting of an 83,047 bp large single-copy (LSC) region, a 12,544 bp small single-copy (SSC) region, and two 22,795 bp inverted repeat (IR) regions. Genome annotation identified 135 genes, including 87 protein-coding genes, 40 transfer RNA genes, and eight ribosomal RNA genes. The dataset also includes comparative relative synonymous codon usage (RSCU) analysis of all available <em>Saccharum</em> plastomes retrieved from the NCBI database, simple sequence repeat (SSR) identification, and plastome-based phylogenetic analyses of <em>Saccharum</em> hybrid cultivar VMC 76–16 together with representative taxa of the tribe Andropogoneae. These data provide a genomic resource for comparative genomics, molecular characterization, phylogenetic analyses, plastome evolution studies, and future sugarcane breeding research.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113115"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148733645","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 RNA-seq profiles from THP-1-derived macrophages pretreated with AZD7648 and stimulated with CT DNA","authors":"Qiang Li,&nbsp;Pei-Wen Zhan,&nbsp;Xian Hong,&nbsp;Yong-Pei Li,&nbsp;Xin-Yue Pei,&nbsp;Xiao-Hui Du,&nbsp;Ming Sui,&nbsp;Tao Wang","doi":"10.1016/j.dib.2026.113124","DOIUrl":"10.1016/j.dib.2026.113124","url":null,"abstract":"<div><div>This article describes an RNA-seq dataset generated from THP-1-derived macrophages under four treatment conditions: untreated control, DNA-dependent protein kinase catalytic subunit (DNA-PKcs) inhibitor AZD7648 alone, calf thymus DNA (CT DNA) alone, and AZD7648 pretreatment followed by CT DNA stimulation. Each condition included three biological replicates, yielding 12 transcriptome samples in total. Libraries were sequenced on the Illumina NovaSeq 6000 platform using paired-end 150-bp reads. The dataset includes raw sequencing reads, gene-level expression matrices, and associated quality control metrics. All RNA samples exhibited RIN values between 9.5 and 9.9. Clean reads ranged from 54.83 to 70.25 million per sample, with Q30 values of 97.18%-97.34%, total mapping rates of 98.24%-98.51%, and unique mapping rates of 95.55%-95.81%. This dataset provides a resource for comparative transcriptomic analyses of cytosolic DNA stimulation and DNA-PKcs inhibition in macrophage cells and may support reuse in studies of innate immune signaling, cytosolic DNA sensing, and pathway-focused reanalysis.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113124"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148733649","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 vector dataset of the high-speed road network in Poland integrated with commissioning year information (1936–2023)","authors":"Katarzyna Krasnodębska,&nbsp;Przemysław Śleszyński,&nbsp;Johannes H. Uhl,&nbsp;Łukasz Kubiak","doi":"10.1016/j.dib.2026.113235","DOIUrl":"10.1016/j.dib.2026.113235","url":null,"abstract":"<div><div>The High-Speed Road Network Vector Data with Construction Year Attribution for Poland (HiRoN-PL) provide spatially and temporally explicit data documenting the development of the high-speed road network in Poland between 1936 and 2023. The dataset is distributed in GeoPackage format containing vector line features representing the time-stamped high-speed road network in Poland. HiRoN-PL road geometries are derived from OpenStreetMap (OSM) ‘<em>way’</em> objects corresponding to high-speed road classes in Poland, namely motorways and expressways (dual carriageways). The selected OSM road sections were aligned with authoritative data provided by the General Directorate for National Roads and Motorways (GDDKiA), the central authority responsible for national roads in Poland. First, the authoritative GDDKiA road geometries were attributed with commissioning dates based on expert interpretation of information from GDDKiA records, public registers, and verified crowdsourced data sources. Second, the geometry of OSM road sections was adjusted to reflect distinct construction phases as defined by the authoritative data. The resulting OSM-derived road network was then assigned with temporal attributes, including the year, month, and day of commissioning, as well as the road segment name, class, and the names of the road junctions that designate the starting and ending nodes of each segment. The dataset includes additional attributes, such as the length of each section and identifiers linking to the source OSM and authoritative data. HiRoN-PL allows for spatial-historical analyses of transport infrastructure development at a national level, enabling multi-temporal accessibility modelling and assessment of transportation efficiency over time. The dataset can be used to support analyses related to the monitoring of land use changes, the impact of transport and planning policies, or the effects and impacts of European Union investment policies. Data (version 1.1) are publicly available at <span><span>https://doi.org/10.5281/zenodo.19570041</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113235"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148940410","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":"IrriDrone: Overhead drone-based video dataset for precision sprinkler irrigation assessment","authors":"Somayeh Afshar,&nbsp;Mohsen Ramezani,&nbsp;Kaveh Mollazade,&nbsp;Atefe Moradiani","doi":"10.1016/j.dib.2026.113208","DOIUrl":"10.1016/j.dib.2026.113208","url":null,"abstract":"<div><div>Efficient water management in agriculture is a growing concern due to increasing water scarcity and over-reliance on groundwater resources. Despite advances in remote sensing and drone-based monitoring, the lack of standardized and publicly available datasets for vision-based sprinkler irrigation analysis has limited progress in the development of data-driven irrigation management systems. In this work, we present IrriDrone, a new dataset comprising aerial videos and corresponding quantitative water-discharge measurements collected from real-world sprinkler irrigation operations in carrot, potato, and alfalfa fields. Three operational pressure conditions were established by simultaneously operating 3, 6, or 9 sprinklers under an unchanged pump setting, representing high, intermediate, and low pressure per sprinkler, respectively; the corresponding discharge rates were determined in liters per second using a repeated volumetric measurement. The dataset captures variations in sprinkler configuration, drone flight altitude (35, 45, and 55 m), and time of day, and includes GPS metadata and paired video versions with and without manually defined circular overlays representing the irrigation spray boundaries. By providing aerial visual data together with corresponding quantitative irrigation measurements, the dataset supports the development and evaluation of machine learning and computer vision methods for irrigation monitoring and precision water management. The dataset includes continuous recordings covering sprinkler rotations, allowing flexible temporal segmentation for diverse downstream research tasks. To the best of our knowledge, IrriDrone is among the first publicly available datasets to combine overhead drone video with corresponding water-discharge measurements under real agricultural conditions.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113208"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148951903","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":"PhishVN: A time-stamped Vietnamese URL phishing dataset with impersonation-scenario labels and confidence tiers","authors":"Thai Nguyen Vu","doi":"10.1016/j.dib.2026.113195","DOIUrl":"10.1016/j.dib.2026.113195","url":null,"abstract":"<div><div>PhishVN is an open phishing-website dataset localised to the Vietnamese context, compiled from public national and community threat feeds and allow-lists. Its core is a <em>time-stamped, verified</em> URL table of 18,997 records (2587 phishing from the national feed, 16,410 legitimate), extended by an explicitly-tagged <em>bronze</em> expansion stratum, community-reported domains from the ChongLuaDao project (with per-domain first-seen dates reconstructed for <span><math><mrow><mo>∼</mo><mn>50</mn></mrow></math></span>% from public archival traces) and recent OpenPhish URLs, for 53,116 records in total, each described by a 21-feature lexical/infrastructure schema that is <em>aligned with the CompPhish dataset</em> to enable cross-dataset study. Phishing URLs are drawn from the National Cyber Security Centre feed (Tin Nhiem Mang); legitimate URLs form three explicitly-tagged strata of increasing difficulty: the certified “trusted organisation” directory (easy, curated), a <span>.vn</span>-filtered Tranco slice (popular sites Vietnamese users actually visit), and a global Tranco sample (hard, traffic-based negatives that break the “non-<span>.vn</span> implies phishing” shortcut), to strengthen external validity. Every record carries an impersonation-<em>scenario</em> label (bank, government, tax, e-commerce, telecom, delivery, social, gaming) inferred from brand tokens in the URL, and a <em>label-confidence tier</em>(gold/silver/bronze) derived from the source’s verification status. Records carrying a source-attested event date (the national-feed core phishing, the certified organisations and the date-reconstructed half of the bronze stratum) are ordered temporally and split <em>with grouping by registrable domain</em>, so that near-duplicate campaign subdomains never span train and test; records whose registrable-domain group carries no attested event date (most of the web-whitelist and top-list negatives, and a small undated remainder of the bronze stratum) are placed into splits by grouped random assignment. We release the datasheet, the full collection and processing pipeline, and reproducible URL baseline detectors reported with multi-seed spreads and bootstrap confidence intervals. A <em>preliminary</em> multi-modal companion additionally pairs 868 URLs across both classes (209 phishing, 659 benign) with the rendered page HTML and a screenshot; the text-message and email channels are left to a planned extension.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113195"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148951905","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":"Citywide traffic sensor network in Nova Gorica, Slovenia: 2025-2026 telraam S2 dataset","authors":"Tomaž Berčič,&nbsp;Marko Stavrev,&nbsp;M. Arch","doi":"10.1016/j.dib.2026.113190","DOIUrl":"10.1016/j.dib.2026.113190","url":null,"abstract":"<div><div>This article describes a multimodal traffic dataset collected through a network of 26 Telraam S2 sensors deployed across Nova Gorica, Slovenia, within the framework of the Interreg Central Europe EnCLOD project. The network comprises 23 indoor window-mounted units and 3 experimental outdoor units, installed along arterial corridors, residential connectors, and sections of the city's ring road. Each Telraam S2 device is a low-cost, citizen-science-oriented Internet of Things (IoT) traffic counter equipped with a Kendryte K210 edge AI chip that performs real-time object detection and classification directly on-device, transmitting only anonymized, aggregated counts via a built-in cellular connection (LTE-M/NB-IoT). The dataset contains 15-minute interval time-series records for each sensor location. Each record includes directional counts for pedestrians, bicycles, motorcycles, cars, light trucks, trucks, buses, trailers, tractors, and strollers, as well as a consolidated night-time detection category. Derived metrics include car speed distribution histograms in 10 km/h bins and the V85 (85th percentile) speed per interval. Accompanying metadata provide sensor coordinates, street names, segment identifiers, installation type, and uptime quality indicators. No images or video are stored or transmitted by the devices; all processing occurs on board, ensuring compliance with privacy regulations. The data were exported from the Telraam dashboard and are archived as structured Excel (.xlsx) files, with CSV mirrors, on Zenodo under a CC BY-NC 4.0 license. This is the first fine-grained, multi-modal urban traffic dataset for Nova Gorica, a city that previously lacked systematic traffic monitoring infrastructure. The dataset is suitable for reuse in transport modelling, modal share analysis, speed behaviour assessment, air-quality exposure linkage, and urban mobility planning, and may serve as a reference for replicating low-cost distributed sensor deployments in comparable European cities.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113190"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148951947","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":"The PIRAGUA_indicators dataset: Streamflow indices of the Pyrenees rivers (1950–2019)","authors":"Leticia Palazón,&nbsp;Ane Zabaleta,&nbsp;Iñaki Antigüedad,&nbsp;Luis Javier Lambán,&nbsp;Jorge Jódar,&nbsp;Vivien Hakoun,&nbsp;Pierre Le Cointe,&nbsp;Yvan Caballero,&nbsp;Santiago Beguería","doi":"10.1016/j.dib.2026.113159","DOIUrl":"10.1016/j.dib.2026.113159","url":null,"abstract":"<div><div>This paper presents a database of descriptive statistics and trend analyses performed on long-term records of streamflow (93 stations) and groundwater levels (29 monitoring wells) across the Pyrenean region (France, Spain and Andorra). Whereas streamflow time series generally cover several decades, groundwater level records are shorter and often discontinuous, yet they provide valuable insights into aquifer dynamics. The dataset includes 19 streamflow and groundwater indicators based on daily data, representative of mean, high, and low flows, allowing a complete characterisation of streamflow regimes of the Pyrenean rivers. Additionally, trend magnitudes and significance levels, derived using standardized non-parametric tests, are provided for each of the indicators. The analyses were conducted over multiple time windows of different lengths, all ending in 2019, and applied at both annual (hydrological year: October–September) and monthly scales. The set of indicators provides a consistent framework for assessing spatial and temporal patterns of hydrological change in mountain catchments.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113159"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148844857","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 publications and patents on quantum error correction (1995–2025)","authors":"Saikat Barua,&nbsp;Humayra Shemushee","doi":"10.1016/j.dib.2026.113149","DOIUrl":"10.1016/j.dib.2026.113149","url":null,"abstract":"<div><div>This article presents a harmonized corpus of scholarly publications and patents concerning quantum error correction, the encoding techniques that protect quantum information against noise and that underpin the pursuit of fault-tolerant quantum computation. The corpus spans 1 January 1995 to 31 December 2025 and contains 16,274 records: 14,385 scholarly publications harvested from OpenAlex and enriched from Crossref, and 1889 United States patent publications retrieved from Google Patents Public Data. Publications were collected by matching twenty scope phrases against titles and abstracts, intersected with a quantum-computing topic to suppress unrelated matches; patents were collected under the Cooperative Patent Classification class for quantum error correction. Both record types were mapped onto a common eighteen-field schema, deduplicated within type, and assigned to one of three retrieval tiers according to the strength of the topical match. Each record carries subfield tags and flags marking machine-learning decoder records and adjacent-topic mentions. The precision of the core tier was assessed by manual annotation of a stratified sample, and inter-annotator agreement was measured. The corpus, its variable dictionary, provenance metadata, validation samples, and the complete construction notebook are openly available, supporting reuse in scientometrics, patent analysis, and text mining of the field.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113149"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148844858","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":"TSD-DDoS: A time-series dataset for TCP flooding attack detection and severity assessment for server health monitoring","authors":"Sajja Ratan Kumar,&nbsp;Valli Kumari Vatsavayi","doi":"10.1016/j.dib.2026.113155","DOIUrl":"10.1016/j.dib.2026.113155","url":null,"abstract":"<div><div>Distributed Denial-of-Service (DDoS) attacks continue to threaten the availability of networked services by overwhelming server resources with malicious traffic. Among the different attack vectors, TCP flooding attacks remain particularly critical because TCP forms the backbone of reliable Internet services, such as web applications, cloud back-end systems, enterprise platforms, and many blockchain-based applications. Although several benchmark datasets exist for DDoS attack detection, most of them are flow-based and primarily support attack classification, offering a limited scope for analyzing how an ongoing attack impacts server health over time.</div><div>This data article introduces TSD-DDoS, a time-series dataset specifically developed to fill a crucial gap in the detection of TCP flooding attacks and assessment of their severity in relation to server health. Unlike conventional flow-level datasets, TSD-DDoS organizes network traffic into fixed 5-second intervals. This temporal aggregation enables continuous monitoring of traffic patterns and provides direct insights into the progression and impact of TCP flooding on server performance and availability. By capturing the evolving nature of attacks over time, TSD-DDoS opens new avenues for research into time-aware detection mechanisms and server health monitoring, areas that are underrepresented in existing benchmark datasets.</div><div>The dataset was constructed using packet capture (PCAP) files from the CICDDoS2019 benchmark dataset. The selected PCAP files were replayed at network speeds of up to 20 Gbps using the <em>tcpreplay</em> tool, whereas traffic capture was performed using <em>Wireshark</em>, a widely recognized packet analysis tool. The collected traffic was divided into successive 5-second intervals, and for each window, aggregated TCP statistics were extracted, specifically the counts of TCP-SYN, TCP-SYN-ACK, TCP-ACK, TCP-RST, and total TCP packets.</div><div>Each interval was labeled as either <em>normal</em> or <em>attack</em> traffic, with an additional annotation indicating the server health status: Good, Fair, Serious, or Critical. These labels allowed for a clear temporal analysis of both the presence of attacks and the progression of severity.</div><div>By offering structured, labelled, and time-indexed TCP traffic data, <strong>TSD-DDoS</strong> enables the development and evaluation of ML-based intrusion detection systems, time-sensitive server health monitoring tools, and adaptive resource management strategies. This is especially valuable in cloud and virtualized environments, where effective mitigation and scaling decisions rely on understanding how attacks evolve over time rather than on isolated flow-level metrics.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113155"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148844861","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}