cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25573/serc.20060585.v6
title: 2022 Water Level Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2022 water level data collected on CS475A instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060585.v5
title: 2022 Water Level Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2022 water level data collected on CS475A instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20054420.v6
title: 2022 Water Quality Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2022 water quality data collected on a YSI EXO2 multiparameter sonde at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). The figshare resource also contains quality control metadata to assist interpretation and analysis. Review the "readme.txt" file for more information. Location: 38.886928, -76.540172
DOI: 10.5281/zenodo.7510185
title: Microwave Single Scattering Properties Database (Horizontally Aligned Aggregates of Dendrites)

description: The database contains physical and microwave single scattering properties of horizontally aligned frozen hydrometeors as large as 11 cm in diameter. A description of the aggregation model used for particle generation can be found in:<br> Leinonen, J., and Szyrmer, W. (2015), Radar signatures of snowflake riming: A modeling study, <em>Earth and Space Science</em>, 2, 346– 358, doi:10.1002/2015EA000102.<br> The code used for particle generation is freely available at: https://github.com/jleinonen/aggregation The scattering properties of particles were computed using discrete dipole approximation using ADDA software package (https://github.com/adda-team/adda) Terminal velocity of snowflakes was computed using 4 hydrodynamical models that were implemented as a part of snowScat library (https://github.com/OPTIMICe-team/snowScatt) Approximately one half of the snowflake structure files and one quarter of scattering properties (for X, Ku, Ka and W band) were generated for the publication of Leinonen and Szyrmer (2015). The remaining part of the dataset was generated using the ALICE High Performance Computing Facility at the University of Leicester.
DOI: 10.25573/serc.20060759
title: 2022 Meteorological Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 meteorological data collected on WXT536 instrumentation at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). Location: 9.350822, -82.257853
DOI: 10.25573/serc.20060759.v6
title: 2022 Meteorological Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 meteorological data collected on WXT536 instrumentation at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). Location: 9.350822, -82.257853
DOI: 10.25573/serc.20060759.v5
title: 2022 Meteorological Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 meteorological data collected on WXT536 instrumentation at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). Location: 9.350822, -82.257853
DOI: 10.25573/serc.20060690
title: 2022 Water Level Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 water level data collected on CS475A instrumentation at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). Location: 9.350822, -82.257853
DOI: 10.25573/serc.20060690.v6
title: 2022 Water Level Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 water level data collected on CS475A instrumentation at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). Location: 9.350822, -82.257853
DOI: 10.25573/serc.20060690.v5
title: 2022 Water Level Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 water level data collected on CS475A instrumentation at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). Location: 9.350822, -82.257853
DOI: 10.25573/serc.20060225.v5
title: 2022 Water Quality Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 water quality data collected on a YSI EXO2 multiparameter sonde at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). The figshare resource also contains quality control metadata to assist interpretation and analysis. Review the "readme.txt" file for more information. QAQC is on-going, and this resource will be updated monthly. Location: 9.350822, -82.257853
DOI: 10.6084/m9.figshare.20459172
title: Supplemental file 6_GOBP_VSMC_LgVSmall.csv

description: GO BP pathway analysis between large and small arteries in rat mesenteric arteries (smooth muscle cells)
DOI: 10.6084/m9.figshare.20459172.v2
title: Supplemental file 6_GOBP_VSMC_LgVSmall.csv

description: GO BP pathway analysis between large and small arteries in rat mesenteric arteries (smooth muscle cells)
DOI: 10.5281/zenodo.7506657
title: CREMMA Medieval - abbr and expan altos

description: This data set is derived from the CREMMA-Medieval dataset (https://github.com/HTR-United/cremma-medieval). It was modified to include both abbreviated and expanded forms in separated ALTO, for HTR training experiments. The original data set was created with the support of the <em>DIM MAP</em> in the context of the CREMMA project (https://www.dim-map.fr/projets-soutenus/cremma/).<br> This version was prepared in March-June 2022 as part of the research for the following paper: <strong>Camps</strong>, Jean-Baptiste, Chahan<strong> Vidal-Gorène</strong>, Dominique <strong>Stutzmann</strong>, Marguerite <strong>Vernet</strong>, and Ariane <strong>Pinche</strong>. « Data Diversity in Handwritten Text Recognition: Challenge or Opportunity? » In <em>Digital Humanities 2022. Conference Abstracts (The University of Tokyo, Japan, 25-29 July 2022)</em>, published by DH2022 Local Organizing Committee, 160‑65. Tokyo, 2022. https://dh2022.dhii.asia/dh2022bookofabsts.pdf#page=162 and https://dh2022.dhii.asia/abstracts/files/CAMPS_Jean_Baptiste_Data_Diversity_in_handwritten_text_recog.html. If you use this dataset, please quote: <pre>@incollection{dh2022_local_organizing_committee_data_2022, address = {Tokyo}, title = {Data {Diversity} in handwritten text recognition: challenge or opportunity?}, url = {https://dh2022.dhii.asia/dh2022bookofabsts.pdf}, language = {en}, urldate = {2022-08-02}, booktitle = {Digital {Humanities} 2022. {Conference} {Abstracts} ({The} {University} of {Tokyo}, {Japan}, 25-29 {July} 2022)}, author = {Camps, Jean-Baptiste and Vidal-Gorène, Chahan and Stutzmann, Dominique and Vernet, Marguerite and Pinche, Ariane}, editor = {{DH2022 Local Organizing Committee}}, year = {2022}, pages = {160--165}, } </pre> <br> <strong>Folders</strong><br> <strong>img</strong><br> Folder with the scans of the base documents. <strong>alto</strong><br> ALTO files, in abbreviated and expanded text form, with or without normalisations. For more details, please see the aforementioned paper.
description: {"references": ["amps, Jean-Baptiste, Chahan Vidal-Gor\u00e8ne, Dominique Stutzmann, Marguerite Vernet, and Ariane Pinche. \u00ab\u00a0Data Diversity in Handwritten Text Recognition: Challenge or Opportunity?\u00a0\u00bb In Digital Humanities 2022. Conference Abstracts (The University of Tokyo, Japan, 25-29 July 2022), published by DH2022 Local Organizing Committee, 160\u201165. Tokyo, 2022. https://dh2022.dhii.asia/dh2022bookofabsts.pdf#page=162 and https://dh2022.dhii.asia/abstracts/files/CAMPS_Jean_Baptiste_Data_Diversity_in_handwritten_text_recog.html."]}
DOI: 10.5281/zenodo.7506656
title: CREMMA Medieval - abbr and expan altos

description: This data set is derived from the CREMMA-Medieval dataset (https://github.com/HTR-United/cremma-medieval). It was modified to include both abbreviated and expanded forms in separated ALTO, for HTR training experiments. The original data set was created with the support of the <em>DIM MAP</em> in the context of the CREMMA project (https://www.dim-map.fr/projets-soutenus/cremma/).<br> This version was prepared in March-June 2022 as part of the research for the following paper: <strong>Camps</strong>, Jean-Baptiste, Chahan<strong> Vidal-Gorène</strong>, Dominique <strong>Stutzmann</strong>, Marguerite <strong>Vernet</strong>, and Ariane <strong>Pinche</strong>. « Data Diversity in Handwritten Text Recognition: Challenge or Opportunity? » In <em>Digital Humanities 2022. Conference Abstracts (The University of Tokyo, Japan, 25-29 July 2022)</em>, published by DH2022 Local Organizing Committee, 160‑65. Tokyo, 2022. https://dh2022.dhii.asia/dh2022bookofabsts.pdf#page=162 and https://dh2022.dhii.asia/abstracts/files/CAMPS_Jean_Baptiste_Data_Diversity_in_handwritten_text_recog.html. If you use this dataset, please quote: <pre>@incollection{dh2022_local_organizing_committee_data_2022, address = {Tokyo}, title = {Data {Diversity} in handwritten text recognition: challenge or opportunity?}, url = {https://dh2022.dhii.asia/dh2022bookofabsts.pdf}, language = {en}, urldate = {2022-08-02}, booktitle = {Digital {Humanities} 2022. {Conference} {Abstracts} ({The} {University} of {Tokyo}, {Japan}, 25-29 {July} 2022)}, author = {Camps, Jean-Baptiste and Vidal-Gorène, Chahan and Stutzmann, Dominique and Vernet, Marguerite and Pinche, Ariane}, editor = {{DH2022 Local Organizing Committee}}, year = {2022}, pages = {160--165}, } </pre> <br> <strong>Folders</strong><br> <strong>img</strong><br> Folder with the scans of the base documents. <strong>alto</strong><br> ALTO files, in abbreviated and expanded text form, with or without normalisations. For more details, please see the aforementioned paper.
description: {"references": ["amps, Jean-Baptiste, Chahan Vidal-Gor\u00e8ne, Dominique Stutzmann, Marguerite Vernet, and Ariane Pinche. \u00ab\u00a0Data Diversity in Handwritten Text Recognition: Challenge or Opportunity?\u00a0\u00bb In Digital Humanities 2022. Conference Abstracts (The University of Tokyo, Japan, 25-29 July 2022), published by DH2022 Local Organizing Committee, 160\u201165. Tokyo, 2022. https://dh2022.dhii.asia/dh2022bookofabsts.pdf#page=162 and https://dh2022.dhii.asia/abstracts/files/CAMPS_Jean_Baptiste_Data_Diversity_in_handwritten_text_recog.html."]}
DOI: 10.6084/m9.figshare.21830430
title: AuSWS_measurements_AB_N.zip

description: Good and Null measurements of Australian SWS studies by Ba et al.
DOI: 10.6084/m9.figshare.21830430.v1
title: AuSWS_measurements_AB_N.zip

description: Good and Null measurements of Australian SWS studies by Ba et al.
DOI: 10.6084/m9.figshare.20459184
title: Supplemental file 5_GOBP_EC_LgVSmall.csv

description: GO BP pathway analysis between large and small arteries in rat mesenteric arteries (endothelial cells)
DOI: 10.6084/m9.figshare.20459184.v2
title: Supplemental file 5_GOBP_EC_LgVSmall.csv

description: GO BP pathway analysis between large and small arteries in rat mesenteric arteries (endothelial cells)
DOI: 10.6084/m9.figshare.20459184.v3
title: Supplemental file 5_GOBP_EC_LgVSmall.csv

description: GO BP pathway analysis between large and small arteries in rat mesenteric arteries (endothelial cells)
DOI: 10.5281/zenodo.7509021
title: ICEBEAR 3D coherent scatter radar data for 2020, 2021

description: Daily ICEBEAR 3D data for 2020, 2021, organized in nx12 matrices where n is the number of observations (echoes) in any given day. The columns are Year (UT) Month (UT) Day (UT) Hour (UT) Minute (UT) Second (UT) Longitude [degrees] Latitude[degrees] Altitude [km]* Doppler velocity [m/s] SNR [dB] Beam number (1 = east, 2 = center, 3 = west) * The west-beam altitudes are anomalous.
DOI: 10.6084/m9.figshare.21830433
title: HCW SPSS SHEET.sav

description: Data to measure perceived stress, burnout and resilience in Kashmiri healthcare workers and explore the relationship of burnout with various socio-demographic, work-related and pandemic related factors.
DOI: 10.6084/m9.figshare.20331234
title: Identification of key candidate genes for wing length-related traits by whole-genome resequencing in 772 geese

description: 1. A total of 772, 420-day-old Xingguo grey geese (XGG) were sequenced using a low-depth (~1 x) whole-genome resequencing strategy to reveal the genetic mechanism of wing length-related traits by genome-wide association analysis (GWAS). 2. The results showed that 119 SNPs had genome-wide significance for wing length in five regions of chromosome 4, of which the most significant locus (P = 7.95E-11) was located upstream of <i>RBM47</i> and explained 7.3% of the phenotypic variation. 3. A total of 219 SNPs located on chromosome 4 were associated with 2-joint-wing length, of which four SNPs reached the genome-wide significant level. However, for the length of 1-joint-wing and primary feather, we did not detect any associated locus. 4. Six promising candidate genes, <i>RBM47, SLAIN2, GRXCR1, SLC10A4, APBB2</i> and <i>NSUN7</i> on chromosome 4, may play an important role in the growth and development of feathers, muscles and bones.
DOI: 10.6084/m9.figshare.20331234.v2
title: Identification of key candidate genes for wing length-related traits by whole-genome resequencing in 772 geese

description: 1. A total of 772, 420-day-old Xingguo grey geese (XGG) were sequenced using a low-depth (~1 x) whole-genome resequencing strategy to reveal the genetic mechanism of wing length-related traits by genome-wide association analysis (GWAS). 2. The results showed that 119 SNPs had genome-wide significance for wing length in five regions of chromosome 4, of which the most significant locus (P = 7.95E-11) was located upstream of <i>RBM47</i> and explained 7.3% of the phenotypic variation. 3. A total of 219 SNPs located on chromosome 4 were associated with 2-joint-wing length, of which four SNPs reached the genome-wide significant level. However, for the length of 1-joint-wing and primary feather, we did not detect any associated locus. 4. Six promising candidate genes, <i>RBM47, SLAIN2, GRXCR1, SLC10A4, APBB2</i> and <i>NSUN7</i> on chromosome 4, may play an important role in the growth and development of feathers, muscles and bones.
DOI: 10.6084/m9.figshare.20384073
title: miRNA-mRNA associations with inosine monophosphate specific deposition in the muscle of Jingyuan chicken

description: 1. Inosine monophosphate (IMP), is an essential component for meat flavour and microRNAs (miRNAs) play a vital role in its post-transcriptional regulation. However, the mechanism of how miRNA expression affects muscle-specific IMP deposition is unclear. 2. The following study performed transcriptome sequencing and bioinformatics analysis of breast and leg muscle, which have significantly different IMP content in Jingyuan chicken. The differential miRNA-mRNAs were screened out and correlation analysis with IMP content was performed. 3. A total of 39 differentially expressed miRNAs (DE miRNAs) and 666 differentially expressed mRNAs (DE mRNAs) were identified between breast muscles and leg muscles. Using miRNA-mRNA integrated analysis, 29 miRNA-target gene pairs were obtained, composed of 13 DE miRNAs and 28 DE mRNAs. Next, purine metabolism, glycolysis/gluconeogenesis, pyruvate metabolism and the biosynthesis of amino acid pathways as necessary for muscle IMP-specific deposition were identified. The differentially expressed gene <i>PKM2</i>, which was significantly enriched in all four pathways, is involved in IMP anabolism in the form of energy metabolism and enzyme activity regulation. The correlation analysis suggested that the gga-miR-107-3p-KLHDC2 negative interaction may be a key regulator in IMP deposition. 4. This study explores the functional mechanism of IMP-specific deposition in Jingyuan chicken muscles at the miRNA and mRNA levels and highlights multiple candidate miRNAs and mRNAs for molecular-assisted breeding.
DOI: 10.6084/m9.figshare.20384073.v2
title: miRNA-mRNA associations with inosine monophosphate specific deposition in the muscle of Jingyuan chicken

description: 1. Inosine monophosphate (IMP), is an essential component for meat flavour and microRNAs (miRNAs) play a vital role in its post-transcriptional regulation. However, the mechanism of how miRNA expression affects muscle-specific IMP deposition is unclear. 2. The following study performed transcriptome sequencing and bioinformatics analysis of breast and leg muscle, which have significantly different IMP content in Jingyuan chicken. The differential miRNA-mRNAs were screened out and correlation analysis with IMP content was performed. 3. A total of 39 differentially expressed miRNAs (DE miRNAs) and 666 differentially expressed mRNAs (DE mRNAs) were identified between breast muscles and leg muscles. Using miRNA-mRNA integrated analysis, 29 miRNA-target gene pairs were obtained, composed of 13 DE miRNAs and 28 DE mRNAs. Next, purine metabolism, glycolysis/gluconeogenesis, pyruvate metabolism and the biosynthesis of amino acid pathways as necessary for muscle IMP-specific deposition were identified. The differentially expressed gene <i>PKM2</i>, which was significantly enriched in all four pathways, is involved in IMP anabolism in the form of energy metabolism and enzyme activity regulation. The correlation analysis suggested that the gga-miR-107-3p-KLHDC2 negative interaction may be a key regulator in IMP deposition. 4. This study explores the functional mechanism of IMP-specific deposition in Jingyuan chicken muscles at the miRNA and mRNA levels and highlights multiple candidate miRNAs and mRNAs for molecular-assisted breeding.
DOI: 10.6084/m9.figshare.20331410
title: miR-181a-5p can inhibit the proliferation and promote the differentiation of chicken primary myoblasts

description: 1. Myoblast proliferation and differentiation is one of the most important biological processes in the development of skeletal muscle. MicroRNAs (miRNAs) play a crucial role in this process. 2. In this study, the expression level of miR-181a-5p was detected, which found that miR-181a-5p was expressed differently in different tissues, different embryonic ages, and different differentiation stages of primary myoblasts in Gushi chickens. 3. The effect of miR-181a-5p was further investigated on chicken primary myoblasts (CPMs). The results of cell counting kit-8 (CCK-8), 5-ethynyl-2’-deoxyuridine (EdU) and cell cycle showed that miR-181a-5p could inhibit the proliferation of CPM. The miR-181a-5p promoted the expression of <i>MYOD, MYOG</i>, and <i>MYHC</i>. MYHC protein immunofluorescence experiments showed that miR-181a-5p increased the area of myotubes. 4. In total, 63 potential target genes of miR-181a-5p in <i>mRNA</i> transcriptome data analysis were identified. Functional enrichment analysis was performed on these target genes, and <i>ASNS, SMYD1</i>, and <i>FOS</i> were found to play regulatory roles in biological processes such as muscle development. It was speculated that miR-181a-5p played a role in myoblast development through these genes. 5. In conclusion, miR-181a-5p can inhibit the proliferation of chicken myoblasts and promote the differentiation of chicken myoblasts. This study laid the foundation for further research on the regulatory mechanism of miR-181a-5p in the development of skeletal muscle and the formation of excellent meat quality traits in Gushi chicken.
DOI: 10.6084/m9.figshare.20459196
title: Supplemental file 4_VSMC_ALL_LgVSmall.csv

description: all genes identified in smooth muscle between large and small mesenteric arteries of rat
DOI: 10.6084/m9.figshare.20459196.v2
title: Supplemental file 4_VSMC_ALL_LgVSmall.csv

description: all genes identified in smooth muscle between large and small mesenteric arteries of rat
DOI: 10.6084/m9.figshare.20465250
title: Supplemental file 4b_VSMC_Biomarker

description: highly expressed gene comparing rat mesenteric artery smooth muscle between large and small arteries
DOI: 10.6084/m9.figshare.20465250.v1
title: Supplemental file 4b_VSMC_Biomarker

description: highly expressed gene comparing rat mesenteric artery smooth muscle between large and small arteries
DOI: 10.6084/m9.figshare.20459211
title: Supplemental file 2_VSMC_DEG_LgVSmall.csv

description: DEG in smooth muscle between large and small rat mesenteric arteries
DOI: 10.6084/m9.figshare.20459211.v2
title: Supplemental file 2_VSMC_DEG_LgVSmall.csv

description: DEG in smooth muscle between large and small rat mesenteric arteries
DOI: 10.6084/m9.figshare.20459127
title: Supplemental file 1_EC_DEG_LgVSmall.csv

description: DEG between large and small rat mesenteric arteries
DOI: 10.6084/m9.figshare.20459127.v2
title: Supplemental file 1_EC_DEG_LgVSmall.csv

description: DEG between large and small rat mesenteric arteries
DOI: 10.6084/m9.figshare.20459109
title: Supplement table 1.pdf

description: Phenotype gene markers in VSMC subclusters
DOI: 10.6084/m9.figshare.20459109.v2
title: Supplement table 1.pdf

description: Phenotype gene markers in VSMC subclusters
DOI: 10.5517/ccdc.csd.cc2c523r
title: CCDC 2179613: Experimental Crystal Structure Determination

description: Related Article: Yifei Sun, Sanjit Das, Spenser R. Brown, Emily R. Blevins, Fengrui Qu, Nicholas A. Ward, Shawn Aiden Gregory, Chance M. Boudreaux, Yonghyun Kim, Elizabeth T. Papish|2023|J.Inorg.Biochem.|240|112110|doi:10.1016/j.jinorgbio.2022.112110
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c524s
title: CCDC 2179614: Experimental Crystal Structure Determination

description: Related Article: Yifei Sun, Sanjit Das, Spenser R. Brown, Emily R. Blevins, Fengrui Qu, Nicholas A. Ward, Shawn Aiden Gregory, Chance M. Boudreaux, Yonghyun Kim, Elizabeth T. Papish|2023|J.Inorg.Biochem.|240|112110|doi:10.1016/j.jinorgbio.2022.112110
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.7510148
title: Supplementary Information - Digital Annex

description: Thesis entitled "Natural History, Biogeography and Evolution of the Iberian white oak syngameon"
DOI: 10.5281/zenodo.7510149
title: Supplementary Information - Digital Annex

description: Thesis entitled "Natural History, Biogeography and Evolution of the Iberian white oak syngameon"
DOI: 10.5287/bodleian:6gen5egox
title: Deep Antimicrobial Susceptibility Phenotyping (DASP) Training and Evaluation Dataset, and Trained Models.
DOI: 10.15468/4zmakh
title: Jardín Botánico Carlos Thays. Colección de Nativas Vivas

description: Jardín Botánico Carlos Thays. Colección de Nativas Vivas
DOI: 10.5519/qd.kjbkty37
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.7510016
title: buteogallus_lacernulatus_zanfona_1.fasta

description: .
DOI: 10.5281/zenodo.7510015
title: buteogallus_lacernulatus_zanfona_1.fasta

description: .
DOI: 10.18112/openneuro.ds004042.v1.0.1
title: FilmFestival