cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13139/ornlnccs/1975202
title: EAGLE-I Power Outage Data 2014 - 2022

description: The provided EAGLE-I historic dataset includes eight years of power outage information at the county level from 2014 to 2022 at 15-minute intervals collected by the EAGLE-I program at ORNL. The data has been collected from utilityâs public outage maps using an ETL process. The dataset details FIPS code, county name, state name, total number of customers without power, and a date/timestamp. Also included is the EAGLE-I coverage of each state for each year. For detailed metadata, refer to the metadata DOI.
DOI: 10.6084/m9.figshare.23232830
title: Code and data for covariance analysis of the Xray attosecond pump/probe experiment

description: This item contains 2 files : <br> - 'Run24.npz' : is a dataset used for the Demonstration of a Time-Resolved Experiment using Xray attosecond pulse pair from FEL. It contains two raw arrays. The first array is the raw photon spectra recorded on a shot to shot basis and the second array is the time of flights recorded for each shot. <br> - The 'Covariance_Demonstration_of_attosecond_Xray_FEL_pump_probe.ipynb' : is a Jupyter notebook that uses the Run24 file and process the data in order to do covariance analysis and extract the binding energy of a carbon 1s photoelectron feature.
DOI: 10.5281/zenodo.7971106
title: Data from; Concentration-Dependent Impact of Green Tea Catechin Gargling on Acute Upper Respiratory Tract Infections: An Exploratory Randomized Controlled Trial

description: We conducted an open-label randomized study (UMIN000045060). The target population consisted of 209 students from the University of Shizuoka and Meiji University, who were randomly assigned to high-catechin (70 participants, approximate catechin concentration: 76.4 mg/dL), low-catechin (69 participants, approximate catechin concentration: 30.8 mg/dL), and a control water gargling (70 participants, catechin concentration: 0 mg/dL) groups. All participants gargled water or GT thrice daily for 12 weeks between December 2021 and February 2022. The symptoms experienced by participants who developed URTI during the study period were recorded on a survey form. The primary endpoint of URTI occurred in 6 (9.1%), 7 (10.8%), and 11 (15.7%) participants in the high-catechin, low-catechin, and water groups, respectively (Fisher's exact test for the overall group: <em>p</em>=0.482). Cox proportional hazards analysis, using background factors and prevention status as covariates, revealed a hazard ratio of 0.57 (95% CI: 0.21–1.55, <em>p</em>=0.261) for the high-catechin vs. water group and 0.54 (95% CI: 0.20–1.50, <em>p</em>=0.341) for the low-catechin vs. water group.
DOI: 10.5281/zenodo.7971105
title: Data from; Concentration-Dependent Impact of Green Tea Catechin Gargling on Acute Upper Respiratory Tract Infections: An Exploratory Randomized Controlled Trial

description: We conducted an open-label randomized study (UMIN000045060). The target population consisted of 209 students from the University of Shizuoka and Meiji University, who were randomly assigned to high-catechin (70 participants, approximate catechin concentration: 76.4 mg/dL), low-catechin (69 participants, approximate catechin concentration: 30.8 mg/dL), and a control water gargling (70 participants, catechin concentration: 0 mg/dL) groups. All participants gargled water or GT thrice daily for 12 weeks between December 2021 and February 2022. The symptoms experienced by participants who developed URTI during the study period were recorded on a survey form. The primary endpoint of URTI occurred in 6 (9.1%), 7 (10.8%), and 11 (15.7%) participants in the high-catechin, low-catechin, and water groups, respectively (Fisher's exact test for the overall group: <em>p</em>=0.482). Cox proportional hazards analysis, using background factors and prevention status as covariates, revealed a hazard ratio of 0.57 (95% CI: 0.21–1.55, <em>p</em>=0.261) for the high-catechin vs. water group and 0.54 (95% CI: 0.20–1.50, <em>p</em>=0.341) for the low-catechin vs. water group.
DOI: 10.5281/zenodo.7860475
title: Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

description: Incorporating 1D genome sequence and 3D chromatin structure information to predict the epigenetic profile, as a result of the noncoding variant.
DOI: 10.5281/zenodo.7872096
title: Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

description: ncVarPred-1D3D: The data used for testing the inconsistency among genome sequence, epigenetic profile, and later, to show its relation to 3D chromatin structure can be found in sanity_check_data.tar.gz. Some trained model for noncoding mutation effect prediction (mapping genome sequence to epigenetic profile) can be found in trained_model.tar.gz. The training data can be found in training_data.tar.gz. And some noncoding variants effect prediction results, e.g. eQTL and pathogenic variant prediction, can be replicated using the data shared in ncVar_data.tar.gz.
description: {"references": ["Tan, Wuwei, and Yang Shen. \"Multimodal learning of noncoding variant effects using genome sequence and chromatin structure.\" bioRxiv (2022): 2022-12."]}
DOI: 10.6084/m9.figshare.23239879
title: Additional file 2 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 2: Table S1. Differential expression analysis of circRNAs in NES differentiation. a. Hotspot host genes which generated over 10 circRNAs. b. Pairwise differential expressionanalysis of circRNAs at D28 of differentiation compared to NES. c. Pairwise DE analysis of circRNAs at D5 of differentiation compared to NES. d. Pairwise DE analysis of circRNAs at D28 compared to D5 of differentiation. e. Likelihood ratio test DE circRNA analysis of all time points. f. Clustering of LRT results.
DOI: 10.6084/m9.figshare.23239879.v1
title: Additional file 2 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 2: Table S1. Differential expression analysis of circRNAs in NES differentiation. a. Hotspot host genes which generated over 10 circRNAs. b. Pairwise differential expressionanalysis of circRNAs at D28 of differentiation compared to NES. c. Pairwise DE analysis of circRNAs at D5 of differentiation compared to NES. d. Pairwise DE analysis of circRNAs at D28 compared to D5 of differentiation. e. Likelihood ratio test DE circRNA analysis of all time points. f. Clustering of LRT results.
DOI: 10.6084/m9.figshare.23239882
title: Additional file 3 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 3: Table S2. Gene ontology analysis of circRNAs differentially expressed during differentiation. a. Biological processes enriched among host genes of Cluster 1 cicrRNAs. b. Positive gene set enrichment analysis of D28 compared to NES circRNA host genes. c. Positive gene set enrichment analysis of D5 compared to NES circRNA host genes. d. Biological processes enriched among host genes of Cluster2 circRNAs.
DOI: 10.6084/m9.figshare.23239882.v1
title: Additional file 3 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 3: Table S2. Gene ontology analysis of circRNAs differentially expressed during differentiation. a. Biological processes enriched among host genes of Cluster 1 cicrRNAs. b. Positive gene set enrichment analysis of D28 compared to NES circRNA host genes. c. Positive gene set enrichment analysis of D5 compared to NES circRNA host genes. d. Biological processes enriched among host genes of Cluster2 circRNAs.
DOI: 10.6084/m9.figshare.23239885
title: Additional file 4 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 4: Table S3. Collated list of Schizophrenia risk genes. a. Gene list. b. Source studies.
DOI: 10.6084/m9.figshare.23239885.v1
title: Additional file 4 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 4: Table S3. Collated list of Schizophrenia risk genes. a. Gene list. b. Source studies.
DOI: 10.6084/m9.figshare.23239888
title: Additional file 5 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 5: Table S4. Analysis of linear RNA expression in NES differentiation. a. Differential expression analysis of linear RNAs at D28 compared to NES. b. Positive gene set enrichment analysis of linear RNAs at D28 compared to NES.
DOI: 10.6084/m9.figshare.23239888.v1
title: Additional file 5 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 5: Table S4. Analysis of linear RNA expression in NES differentiation. a. Differential expression analysis of linear RNAs at D28 compared to NES. b. Positive gene set enrichment analysis of linear RNAs at D28 compared to NES.
DOI: 10.6084/m9.figshare.23239891
title: Additional file 6 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 6: Table S6. Prediction of circRNA:miRNA:mRNA interactions. a. Collated list of miRNAs linked to neurodevelopment. b. Reference studies for miRNA list. c. miRNA sites predicted in DEcircs. d. miRNA sites predicted in 3'UTRs of differentially expressed mRNAs. e. circRNA:miRNA:mRNA interactions with correlated expression during differentiation.
DOI: 10.6084/m9.figshare.23239891.v1
title: Additional file 6 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 6: Table S6. Prediction of circRNA:miRNA:mRNA interactions. a. Collated list of miRNAs linked to neurodevelopment. b. Reference studies for miRNA list. c. miRNA sites predicted in DEcircs. d. miRNA sites predicted in 3'UTRs of differentially expressed mRNAs. e. circRNA:miRNA:mRNA interactions with correlated expression during differentiation.
DOI: 10.6084/m9.figshare.23239894
title: Additional file 7 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 7: Table S7. Prediction of RNA binding proteinmotifs in circRNAs and their flanking introns. a. Significantly enriched RBP motifs within sequences of differentially expressed circRNA subsets. b. SFPQ target selection from positive circRNA sequences increased at Day 28 compared to Day 5. c. TIAL1 target selection from positive Cluster 1 circRNA sequences and circRNA sequences increased at Day 28 compared to Day 5. d. Significantly enriched RBP motifs within flanking intron sequences of circRNA increased at Day 28 compared to NES.
DOI: 10.6084/m9.figshare.23239894.v1
title: Additional file 7 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 7: Table S7. Prediction of RNA binding proteinmotifs in circRNAs and their flanking introns. a. Significantly enriched RBP motifs within sequences of differentially expressed circRNA subsets. b. SFPQ target selection from positive circRNA sequences increased at Day 28 compared to Day 5. c. TIAL1 target selection from positive Cluster 1 circRNA sequences and circRNA sequences increased at Day 28 compared to Day 5. d. Significantly enriched RBP motifs within flanking intron sequences of circRNA increased at Day 28 compared to NES.
DOI: 10.6084/m9.figshare.23239900
title: Additional file 8 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 8. Support data values. Description: Supporting individual data values for figures and supplementary figures depicting mean values.
DOI: 10.6084/m9.figshare.23239900.v1
title: Additional file 8 of Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

description: Additional file 8. Support data values. Description: Supporting individual data values for figures and supplementary figures depicting mean values.
DOI: 10.5281/zenodo.7975777
title: Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

description: ncVarPred-1D3D: The data used for testing the inconsistency among genome sequence, epigenetic profile, and later, to show its relation to 3D chromatin structure can be found in sanity_check_data.tar.gz. Some trained model for noncoding mutation effect prediction (mapping genome sequence to epigenetic profile) can be found in CNN_MLP, CNN_GCN, CNN_RNN_MLP, CNN_RNN_GCN.tar.gz. The trained model for pathogenic variants prediction can be found in fewshot_pathogenic_model.tar.gz. The training data can be found in training_data.tar.gz. Some noncoding variant effects prediction results, e.g. eQTL and pathogenic variants, can be replicated using the data shared in ncVar_data.tar.gz.
description: {"references": ["Tan, Wuwei, and Yang Shen. \"Multimodal learning of noncoding variant effects using genome sequence and chromatin structure.\" bioRxiv (2022): 2022-12."]}
DOI: 10.5281/zenodo.7860474
title: Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

description: ncVarPred-1D3D: The data used for testing the inconsistency among genome sequence, epigenetic profile, and later, to show its relation to 3D chromatin structure can be found in sanity_check_data.tar.gz. Some trained model for noncoding mutation effect prediction (mapping genome sequence to epigenetic profile) can be found in CNN_MLP, CNN_GCN, CNN_RNN_MLP, CNN_RNN_GCN.tar.gz. The trained model for pathogenic variants prediction can be found in fewshot_pathogenic_model.tar.gz. The training data can be found in training_data.tar.gz. Some noncoding variant effects prediction results, e.g. eQTL and pathogenic variants, can be replicated using the data shared in ncVar_data.tar.gz.
description: {"references": ["Tan, Wuwei, and Yang Shen. \"Multimodal learning of noncoding variant effects using genome sequence and chromatin structure.\" bioRxiv (2022): 2022-12."]}
DOI: 10.14457/nida.the.2018.160
title: The innovation of social media and digital narcissism
DOI: 10.14457/nida.the.2018.161
title: A model for development of the Thai-Japanese creative muay Thai tourism marketing network
DOI: 10.14457/nida.the.2018.162
title: The process of communication in airline business's management of crisis in social media
DOI: 10.14457/nida.the.2018.163
title: Youth radio programs during the insurgency in three Southern border provinces of Thailand
DOI: 10.14457/nida.the.2018.164
title: The effects of critical factors on the organizational change of garment companies in Thailand
DOI: 10.14457/nida.the.2018.165
title: The role of civil perceptions of peace, value, and interest in conflict resolution in the Southern border provinces of Thailand
DOI: 10.14457/nida.the.2018.166
title: A Study of the effects of leadership on organizational effectiveness: a case study of non-profit organizations regarding sexually-diverse groups in Thailand
DOI: 10.14457/nida.the.2018.167
title: Technology transfer derived from foreign direct investment (FDI) in the Thai Automotive Industry
DOI: 10.14457/nida.the.2018.168
title: The impacts of human resource management practices and leader-member exchange on the provincial waterworks authority's employees' attitudes and behaviors
DOI: 10.14457/nida.the.2018.169
title: กระบวนการสื่อสารการตลาดผ่านสื่อสังคมออนไลน์ของละครเวทีในประเทศไทย
DOI: 10.14457/nida.the.2018.170
title: การศึกษาการกำกับดูแลการเแพร่เสียงแพร่ภาพในระบบ OTT ของประเทศไทย
DOI: 10.14457/nida.the.2018.171
title: แนวทางการปฏิรูปกฎหมายทางการประกอบธุรกิจด้านการค้าบริการของคนต่างด้าว
DOI: 10.14457/nida.the.2018.172
title: มาตรการทางกฎหมายเพื่อควบคุมงบประมาณแผ่นดินประเภทงบกลางรายการเงินสำรองจ่ายเพื่อกรณีฉุกเฉินหรือจำเป็น
DOI: 10.14457/nida.the.2018.173
title: มาตรการทางกฎหมายในการคุ้มครองสิทธิและสงเคราะห์ผู้พ้นโทษ
DOI: 10.34740/kaggle/dsv/5787174
title: 🇺🇦 Ukraine Conflict Twitter Dataset
DOI: 10.5281/zenodo.7976363
title: Data from: 'Potential non-linearities in the high latitude circulation and ozone response to Stratospheric Aerosol Injection'

description: Data used in: 'Potential non-linearities in the high latitude circulation and ozone response to Stratospheric Aerosol Injection' by Bednarz et al., 2023, submitted to Geophysical Research Letters.
DOI: 10.5281/zenodo.7797563
title: The MAPLE Benchmark for Graph Mining

description: This repository contains the graph format of MAPLE (a large-scale collection of scientific papers across 19 scientific fields), which can serve as a comprehensive evaluation benchmark for graph mining tasks (e.g., node classification, link prediction) in the scientific domain. MAPLE was introduced in the WWW 2023 paper "The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study", available at https://arxiv.org/abs/2302.03341. The original format of MAPLE used for text mining tasks (e.g., multi-label text classification) can be found at https://zenodo.org/record/7611544. Please refer to https://github.com/yuzhimanhua/MAPLE for more details on the data format. If you find MAPLE useful, please cite our paper: <pre><code>@inproceedings{zhang2023effect, title={The effect of metadata on scientific literature tagging: A cross-field cross-model study}, author={Zhang, Yu and Jin, Bowen and Zhu, Qi and Meng, Yu and Han, Jiawei}, booktitle={WWW'23}, pages={1626--1637}, year={2023} }</code></pre>
DOI: 10.5281/zenodo.7787730
title: The MAPLE Benchmark for Graph Mining

description: This repository contains the graph format of MAPLE (a large-scale collection of scientific papers across 19 scientific fields), which can serve as a comprehensive evaluation benchmark for graph mining tasks (e.g., node classification, link prediction) in the scientific domain. MAPLE was introduced in the WWW 2023 paper "The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study", available at https://arxiv.org/abs/2302.03341. The original format of MAPLE used for text mining tasks (e.g., multi-label text classification) can be found at https://zenodo.org/record/7611544. Please refer to https://github.com/yuzhimanhua/MAPLE for more details on the data format. If you find MAPLE useful, please cite our paper: <pre><code>@inproceedings{zhang2023effect, title={The effect of metadata on scientific literature tagging: A cross-field cross-model study}, author={Zhang, Yu and Jin, Bowen and Zhu, Qi and Meng, Yu and Han, Jiawei}, booktitle={WWW'23}, pages={1626--1637}, year={2023} }</code></pre>
DOI: 10.5281/zenodo.7611544
title: The MAPLE Benchmark for Scientific Literature Tagging

description: This repository contains the MAPLE benchmark introduced in the WWW 2023 paper "The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study", available at https://arxiv.org/abs/2302.03341. It covers papers from 19 scientific fields for large-scale multi-label scientific paper classification. Please refer to https://github.com/yuzhimanhua/MAPLE for more details on the data format and usage. If you would like to use MAPLE for graph mining tasks (e.g., node classification, link prediction), please refer to the graph format of MAPLE: https://zenodo.org/record/7797563 If you find MAPLE useful, please cite our paper: <pre><code>@inproceedings{zhang2023effect, title={The effect of metadata on scientific literature tagging: A cross-field cross-model study}, author={Zhang, Yu and Jin, Bowen and Zhu, Qi and Meng, Yu and Han, Jiawei}, booktitle={WWW'23}, pages={1626--1637}, year={2023} }</code></pre>
DOI: 10.5281/zenodo.7611543
title: The MAPLE Benchmark for Scientific Literature Tagging

description: This repository contains the MAPLE benchmark introduced in the WWW 2023 paper "The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study", available at https://arxiv.org/abs/2302.03341. It covers papers from 19 scientific fields for large-scale multi-label scientific paper classification. Please refer to https://github.com/yuzhimanhua/MAPLE for more details on the data format and usage. If you would like to use MAPLE for graph mining tasks (e.g., node classification, link prediction), please refer to the graph format of MAPLE: https://zenodo.org/record/7797563 If you find MAPLE useful, please cite our paper: <pre><code>@inproceedings{zhang2023effect, title={The effect of metadata on scientific literature tagging: A cross-field cross-model study}, author={Zhang, Yu and Jin, Bowen and Zhu, Qi and Meng, Yu and Han, Jiawei}, booktitle={WWW'23}, pages={1626--1637}, year={2023} }</code></pre>
DOI: 10.6084/m9.figshare.23243492
title: Supplementary Material for: Association of self-reported nighttime sleep duration with chronic kidney disease: China Health and Retirement Longitudinal Study

description: Introduction: The cohort study aimed to assess the association of nighttime sleep duration and the change in nighttime sleep duration with chronic kidney disease (CKD), and whether the association between nighttime sleep duration and CKD differed by daytime napping. Methods: This study included 11677 individuals of the China Health and Retirement Longitudinal Study (CHARLS) and used data from the 2011 baseline survey and four follow-up waves. Nighttime sleep duration was divided into three groups: short (&lt;7h per night), optimal (7-9h), and long nighttime sleep duration (&gt;9h). Daytime napping was divided into two groups: no nap, with a nap. We used Cox proportional hazards model to examine the effect of nighttime sleep duration at baseline and change in nighttime sleep duration on incident CKD, and a joint effect of nighttime sleep duration and nap time on onset CKD. Results: With a follow-up of 7 years, the incidence of CKD among those with short, optimal and long nighttime sleep duration was 9.89, 6.75, and 9.05 per 1000 person-years, respectively. Compared to individuals with optimal nighttime sleep duration, short nighttime sleepers had a 44% higher risk of onset CKD (hazard ratio [HR]: 1.44, 95% Confidence intervals [CIs]:1.21-1.72). Compared to participants with persistent optimal nighttime sleep duration, those with persistent short or long nighttime sleep duration had an increased risk of incident CKD (HR:1.44, 95%CI:1.15-1.80). We found a lower incidence of CKD in participants with short nighttime sleep duration and a nap (HR:0.74, 95%CI:0.60-0.93), compared to those with short nighttime sleep duration and no nap. Discussion/Conclusion: Short nighttime sleep duration and persistent long or short nighttime sleep duration were associated with a higher risk of onset CKD. Keeping persistent optimal nighttime sleep duration may help reduce CKD risk later in life. Daytime napping may be protective against onset CKD.