cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.24858
title: Data for article "Supersymmetric Landau Levels in Photonic Dirac Metasurfaces"
title: Data for article "Supersymmetric Landau Levels in Photonic Dirac Metasurfaces"

description: The complete datasets supporting the findings reported in "Supersymmetric Landau Levels in Photonic Dirac Metasurfaces".This comprehensive dataset archive encompasses:1. all computational results, numerical simulations, and experimental measurements presented in the manuscript;2. raw experimental outputs.
description: The complete datasets supporting the findings reported in "Supersymmetric Landau Levels in Photonic Dirac Metasurfaces".This comprehensive dataset archive encompasses:1. all computational results, numerical simulations, and experimental measurements presented in the manuscript;2. raw experimental outputs.
DOI: 10.57760/sciencedb.35688
title: Icing image of Baoji power transmission line in January 2025
title: 2025 年 1 月宝鸡输电线覆冰图像

description: Collected by the "Ice Observing Elf" image sensor installed on the research area line for real-time monitoring of ice cover thickness. The data processing and analysis methods are as follows: meteorological data is located and matched with stations using the Haversine formula, evaluated for reliability using weighted methods, and finely processed using interpolation methods. It is then input into the WRF numerical weather model to simulate key meteorological elements; The icing image is preprocessed, wire pixel extraction, and width measurement are completed through machine vision technology to calculate the icing thickness; After feature engineering processing, multi-source data is used to train the XGBoost risk assessment model. The final results show that after fine processing of meteorological data, the relative error is ≤ 10%, the monitoring error of ice cover thickness is ≤ 3%, and the prediction error is ≤ 5%. The visualization system based on the three types of data can accurately predict and grade the probability of ice cover tripping for 1-3 hours and 3-6 hours, providing reliable data support for intelligent operation and maintenance of the power grid. 
description: Collected by the "Ice Observing Elf" image sensor installed on the research area line for real-time monitoring of ice cover thickness. The data processing and analysis methods are as follows: meteorological data is located and matched with stations using the Haversine formula, evaluated for reliability using weighted methods, and finely processed using interpolation methods. It is then input into the WRF numerical weather model to simulate key meteorological elements; The icing image is preprocessed, wire pixel extraction, and width measurement are completed through machine vision technology to calculate the icing thickness; After feature engineering processing, multi-source data is used to train the XGBoost risk assessment model. The final results show that after fine processing of meteorological data, the relative error is ≤ 10%, the monitoring error of ice cover thickness is ≤ 3%, and the prediction error is ≤ 5%. The visualization system based on the three types of data can accurately predict and grade the probability of ice cover tripping for 1-3 hours and 3-6 hours, providing reliable data support for intelligent operation and maintenance of the power grid.
DOI: 10.57760/sciencedb.35685
title: Meteorological data monitored by various meteorological stations in Baoji City from 2017 to 2025
title: 2017-2025 年宝鸡市内 各个气象站监测的气象数据

description: Including parameters related to icing such as temperature, relative humidity, precipitation, and wind speed, real-time data is updated hourly and integrated and stored through SQLite database, sourced from Baoji Meteorological Bureau and surrounding meteorological stations of the target transmission line area 
description: Including parameters related to icing such as temperature, relative humidity, precipitation, and wind speed, real-time data is updated hourly and integrated and stored through SQLite database, sourced from Baoji Meteorological Bureau and surrounding meteorological stations of the target transmission line area
DOI: 10.57760/sciencedb.35458
title: Tumor Growth Simulation and MRI in Gliomas
title: Tumor Growth Simulation and MRI in Gliomas

description: Simulation-Based Study of Tumor Growth Patterns and Their MRI Manifestations in Low- versus High-Grade Gliomas
description: Simulation-Based Study of Tumor Growth Patterns and Their MRI Manifestations in Low- versus High-Grade Gliomas
DOI: 10.57760/sciencedb.35662
title: Upregulation of TRIM38 by α-Hederin inhibits endoplasmic reticulum stress and improves liver fibrosis
title: Upregulation of TRIM38 by α-Hederin inhibits endoplasmic reticulum stress and improves liver fibrosis

description: All raw data and uncropped, unprocessed Western blot images
description: All raw data and uncropped, unprocessed Western blot images
DOI: 10.57760/sciencedb.35640
title: Single-cell Sequencing of Mouse Liver
title: Single-cell Sequencing of Mouse Liver

description: This dataset comprises single-cell RNA sequencing (scRNA-seq) data derived from the livers of mice in both the ACLF (Acute-on-Chronic Liver Failure) model group and a normal control group. The ACLF mouse model was established following established protocols in the literature. By performing single-cell capture and sequencing of liver cells from both groups, we have constructed a high-resolution atlas of the hepatic microenvironment. This work provides a fundamental data resource for elucidating the pathological mechanisms of ACLF and identifying potential therapeutic targets.
description: This dataset comprises single-cell RNA sequencing (scRNA-seq) data derived from the livers of mice in both the ACLF (Acute-on-Chronic Liver Failure) model group and a normal control group. The ACLF mouse model was established following established protocols in the literature. By performing single-cell capture and sequencing of liver cells from both groups, we have constructed a high-resolution atlas of the hepatic microenvironment. This work provides a fundamental data resource for elucidating the pathological mechanisms of ACLF and identifying potential therapeutic targets.
DOI: 10.57760/sciencedb.xbyxb.00188
title: TyG Index Instrumental Variable SNP Dataset Based on UK Biobank
title: 基于 UK Biobank 数据库的 TyG 指数工具变量 SNP 数据集

description: This dataset is based on publicly available genome-wide association studies (GWAS) data from the UK Biobank, with the core being single nucleotide polymorphism (SNP) instrumental variables associated with the triglyceride glucose (TyG) index. The original dataset was based on 192 TyG related SNPs screened from 273368 European populations (40-69 years old) (screening criteria: P&lt;10 ⁻⁸, F&gt;10 to avoid weak instrumental variable bias, r ²&lt;0.01 and kb=10000 to remove linkage disequilibrium, and to exclude metabolic confounding sites such as BMI and blood pressure). After further quality control, Mendelian random multi-directional residual and outlier test (MR-PRESSO) was used to remove outlier SNPs (rs2081687, rs483082), and the allele information of the outcome variable (non-alcoholic fatty liver disease) GWAS data was matched. After removing palindromic structure SNPs, 139 valid SNPs were ultimately retained. The dataset provides detailed records of key genetic information such as effect allele (EA), other allele (OA), effect value (BETA), standard error (SE), and associated P-value for each SNP. It can be directly used for Mendelian randomization causal inference studies of TyG index and metabolic diseases (such as non-alcoholic fatty liver disease) in two samples, providing high-quality genetic tool variable support for etiological exploration of related diseases. 
description: This dataset is based on publicly available genome-wide association studies (GWAS) data from the UK Biobank, with the core being single nucleotide polymorphism (SNP) instrumental variables associated with the triglyceride glucose (TyG) index. The original dataset was based on 192 TyG related SNPs screened from 273368 European populations (40-69 years old) (screening criteria: P&lt;10 ⁻⁸, F&gt;10 to avoid weak instrumental variable bias, r ²&lt;0.01 and kb=10000 to remove linkage disequilibrium, and to exclude metabolic confounding sites such as BMI and blood pressure). After further quality control, Mendelian random multi-directional residual and outlier test (MR-PRESSO) was used to remove outlier SNPs (rs2081687, rs483082), and the allele information of the outcome variable (non-alcoholic fatty liver disease) GWAS data was matched. After removing palindromic structure SNPs, 139 valid SNPs were ultimately retained. The dataset provides detailed records of key genetic information such as effect allele (EA), other allele (OA), effect value (BETA), standard error (SE), and associated P-value for each SNP. It can be directly used for Mendelian randomization causal inference studies of TyG index and metabolic diseases (such as non-alcoholic fatty liver disease) in two samples, providing high-quality genetic tool variable support for etiological exploration of related diseases.
DOI: 10.15468/dl.9serw2
title: Occurrence Download

description: A dataset containing 2207193 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Synedrellopsis grisebachii, Tilesia baccata, Tripsacum lanceolatum, Triraphis andropogonoides, Urochloa arrecta, Urochloa jubata, Urochloa mollis, Urochloa oligobrachiata, Urochloa paucispicata, Urochloa plantaginea, Urochloa platyphylla, Urochloa dura, Urochloa trichopus, Vachellia caven, Vellosiella spathacea, Veronica javanica, Zephyranthes chlorosolen, Vachellia aroma, Acaena argentea, Acmella glaberrima, Agrostis vinealis, Alisma lanceolatum, Alopecurus aequalis, Ambrosia arborescens, Ammannia latifolia, Antidesma bunius, Aphanes arvensis, Apium prostratum, Arctotis acaulis, Argyranthemum frutescens, Aristotelia chilensis, Arnica angustifolia, Atriplex rosea, Bidens laevis, Bidens pseudocosmos, Bothriochloa laguroides, Bothriochloa saccharoides, Bromus lanceolatus, Calendula tripterocarpa, Catabrosa aquatica, Cenchrus myosuroides, Centaurium littorale, Chenopodium carnosulum, Chenopodium vulvaria, Clematis bonariensis, Clematis campestris, Crepis pulchra, Crotalaria grahamiana, Croton setigerus, Cupressus goveniana, Cynoglossum creticum, Cynoglossum zeylanicum, Cynosurus cristatus, Cyperus articulatus, Cyperus laevigatus, Cyperus squarrosus, Daucus pusillus, Deschampsia setacea, Digitaria aequiglumis, Eleocharis montana, Eleocharis palustris, Epilobium obscurum, Eragrostis elongata, Eriochloa montevidensis, Euphorbia falcata, Euphorbia platyphyllos, Festuca filiformis, Festuca juncifolia, Freesia refracta, Galium divaricatum, Galium parisiense, Gentiana prostrata, Gynerium sagittatum, Hordeum secalinum, Hypericum inodorum, Elymus hystrix, Iberodes linifolia, Indigofera truxillensis, Knautia integrifolia, Lampranthus multiradiatus, Lathyrus cicera, Leontodon hirtus, Leontodon taraxacoides, Leucojum vernum, Linum catharticum, Logfia gallica, Lotus angustissimus, Lupinus albus, Lythrum album, Lythrum maritimum, Lythrum portula, Madia sativa, Malva nicaeensis, Medicago monspeliaca, Microchloa indica, Myosotis laxa, Myosotis ramosissima, Myosotis stricta)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2207193 records from 4703 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004310-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/456ypf72fv.1
title: Health System in Syria 2000 - 2024

description: Dataset for a research project on the health system in Syria 2000 - 2024: a systematic review
DOI: 10.17632/456ypf72fv.2
title: Health System in Syria 2000 - 2024

description: Dataset for a research project on the health system in Syria 2000 - 2024: a systematic review
DOI: 10.15468/dl.ewd86k
title: Occurrence Download

description: A dataset containing 4369997 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "HasCoordinate is true",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2020",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 4369997 records from 181 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001403-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/8z8thsd2d7.1
title: Zhi Yubo_URL of Master thesis_2025

description: Current researches focus on understanding influencer marketing, the theories behind it and factors that contributes to the success of such campaigns. Even though many articles and research papers do acknowledge that relationship of the 2 parties is important and essential for influencer marketing, however, very few or no researches directly conduct empirical analysis on whether relationship between KOLs and their followers indeed influence and to what magnitude influence the success of influencer marketing campaigns and eventually impacting brand’s choice of marketing tactic or KOLs to choose. 
This study in the form of case study with KOLs on Instagram and Red platform will help to fill this void by addressing this issue which is underexplored currently and provide a deep-dive into the relationship between influencers and its followers and the impact on their followers. Together with the deep-dive, the paper will also include researches on other factors that will affect the effectiveness of influencer marketing. Empirical evidence from this research confirms that KOLs’ ability to influence their followers will impact the outcome of influencer marketing, but only effective through certain methods. Specifically, focusing on two largest social platform, Instagram and Red, the paper found that post content alignment with KOL’s persona and write-up or message interactivity are two influencing factors in determining the success of influencer marketing. While other factors such as relationship built between the KOL and followers does not seem to influence the outcome of future campaigns, potentially suggesting that past relationship built between the KOL and her followers has a short-horizon of influences, as the benefits of strong relationship with the followers seem not carry forward. The findings in this paper offer marketers and KOLs theoretical guidance for conducting influencer marketing campaigns on Instagram and Red as well as in the global and China market. 
Keywords: Brand marketing strategy, Influencer Marketing, key opinion leader, Social Media Platforms, Consumer BehaviorM
DOI: 10.15468/dl.2rxhqm
title: Occurrence Download

description: A dataset containing 1642 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((123.80328 14.25231,132.02528 41.18237,100.92465 47.61699,94.96667 36.17766,89.72365 15.08643,98.6756 1.47229,112.12486 13.69538,107.02039 19.17518,112.42513 21.80249,123.80328 14.25231))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Sinosenecio oldhamianus"
 ]
}

 The dataset includes 1642 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030825-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17600249
title: Data supporting publication: Permittivity-asymmetric qBIC metasurfaces  for refractive index sensing
DOI: 10.5281/zenodo.17600248
title: Data supporting publication: Permittivity-asymmetric qBIC metasurfaces  for refractive index sensing
DOI: 10.6084/m9.figshare.30609980
title: Supplementary Material for: Evaluation of Biopsy-Based Molecular Risk Prediction in Crescentic Glomerulonephritis

description: Novel molecular tools have the potential to improve current clinical and histology-based risk classification systems for various medical renal diseases including glomerulonephritis (GN). We aimed to assess the utility of gene expression for improving biopsy-based risk prediction in patients with GN with and without crescent formation. This retrospective case-control study used NanoString nCounter to measure the expression of 54 previously described inflammation, nephron injury, endothelium, and crescent-related genes in 335 archival, formalin-fixed paraffin-embedded native kidney biopsies, including a 288-biopsy discovery cohort representing a broad spectrum of crescentic GN subtypes, and an independent 47-biopsy validation cohort focused on ANCA-associated crescentic GN. Clinical, histologic, and gene expression data were compared. Discovery cohort analysis demonstrated increased expression of 13 genes in crescentic GN cases that developed end-stage renal disease (ESRD) versus those that did not (FDR&lt;0.05). Within the 75-biopsy subset of ANCA-associated crescentic GN cases in the discovery cohort, this 13-gene set was found to be independently predictive of ESRD in multivariate Cox proportional hazards regression analysis (p=0.015), with significant differentiation of high and low risk patients in Kaplan-Meier renal survival analysis (log rank test, p=0.002). However, validation cohort analysis did not demonstrate significant improvement in risk stratification with the 13-gene set when compared with established clinicopathologic models. These results suggest that biopsy-based gene expression may provide the opportunity for improved risk stratification in crescentic GN; however, the genes evaluated in this study appear to have limited added clinical utility over existing risk scores.
DOI: 10.6084/m9.figshare.30609980.v1
title: Supplementary Material for: Evaluation of Biopsy-Based Molecular Risk Prediction in Crescentic Glomerulonephritis

description: Novel molecular tools have the potential to improve current clinical and histology-based risk classification systems for various medical renal diseases including glomerulonephritis (GN). We aimed to assess the utility of gene expression for improving biopsy-based risk prediction in patients with GN with and without crescent formation. This retrospective case-control study used NanoString nCounter to measure the expression of 54 previously described inflammation, nephron injury, endothelium, and crescent-related genes in 335 archival, formalin-fixed paraffin-embedded native kidney biopsies, including a 288-biopsy discovery cohort representing a broad spectrum of crescentic GN subtypes, and an independent 47-biopsy validation cohort focused on ANCA-associated crescentic GN. Clinical, histologic, and gene expression data were compared. Discovery cohort analysis demonstrated increased expression of 13 genes in crescentic GN cases that developed end-stage renal disease (ESRD) versus those that did not (FDR&lt;0.05). Within the 75-biopsy subset of ANCA-associated crescentic GN cases in the discovery cohort, this 13-gene set was found to be independently predictive of ESRD in multivariate Cox proportional hazards regression analysis (p=0.015), with significant differentiation of high and low risk patients in Kaplan-Meier renal survival analysis (log rank test, p=0.002). However, validation cohort analysis did not demonstrate significant improvement in risk stratification with the 13-gene set when compared with established clinicopathologic models. These results suggest that biopsy-based gene expression may provide the opportunity for improved risk stratification in crescentic GN; however, the genes evaluated in this study appear to have limited added clinical utility over existing risk scores.
DOI: 10.13140/rg.2.2.16854.72003
title: LIST OF FORENSIC MEDICINE JOURNALS
DOI: 10.7910/dvn/dibx7s
title: Replication Data for: Blame Shifting in Autocracies Following Large-scale Disasters: Evidence from Turkey

description: Large-scale disasters, particularly when handled poorly, often spark popular outrage and threaten an autocrat’s hold on power. Autocrats frequently employ blame shifting strategies to redirect public anger and weather these storms. We examine whether blame shifting after a large-scale disaster helps or hurts an autocrat’s popularity through a mixed-methods research design in the electoral autocracy of Turkey in April-July 2023, following the February 2023 earthquakes. An online survey experiment (n=3,839) identifies the effects of blaming the aftermath of the earthquake on the opposition, a force majeure, private construction companies, or a government minister, while focus groups explore the mechanisms behind these effects. We find that blaming the opposition or a force majeure leads to a backlash, especially among those more able to critically evaluate information. Focus groups reveal that these backlash effects are driven by voters’ dismay at electoral opportunism and the incumbent’s polarizing language following a large-scale disaster.
DOI: 10.5281/zenodo.17579537
title: MixIT: Post-pandemic social contacts in Italy

description: MixIT social contact data.

These data contain social contact data collected by Fondazione Bruno Kessler and Bocconi University in Italy across two waves. The first wave ran in March 2022, the second in March-April 2023.

Data are formatted according to the standards of the SocialcontactData collection.
For more details about the collection, processing and analysis of the data, please refer to and cite the Manuscript titled "Post-pandemic social contacts in Italy: implications for distancing measures on in-person school and work attendance".
DOI: 10.5281/zenodo.17579536
title: MixIT: Post-pandemic social contacts in Italy

description: MixIT social contact data.

These data contain social contact data collected by Fondazione Bruno Kessler and Bocconi University in Italy across two waves. The first wave ran in March 2022, the second in March-April 2023.

Data are formatted according to the standards of the SocialcontactData collection.
For more details about the collection, processing and analysis of the data, please refer to and cite the Manuscript titled "Post-pandemic social contacts in Italy: implications for distancing measures on in-person school and work attendance".
DOI: 10.17605/osf.io/d5mg6
title: American Nations Project

description: These publicly available data were used to conduct an analysis of the association between different regional "American Nations" (as defined by Colin Woodard, at the county level) and measures of health and health status.
DOI: 10.15468/dl.vxj8mc
title: Occurrence Download

description: A dataset containing 86 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((121.35062 5.14272,90.38078 23.89508,84.69822 0.31259,105.43946 -22.41761,121.0665 -17.8715,121.35062 5.14272))",
 "TaxonKey is Peronema canescens"
 ]
}

 The dataset includes 86 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030830-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.