cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3466622
title: A new eomysticetid from the Oligocene Kokoamu Greensand of New Zealand and a review of the Eomysticetidae (Mammalia, Cetacea)

description: Eomysticetids represent a worldwide, short-lived radiation of archaic baleen-bearing mysticetes that elucidate morphofunctional shifts and ontogenetic change amongst early Neoceti. Fossils of eomysticetids are now recorded from Oligocene marine rocks along the margins of the North Pacific (Japan), North Atlantic (South Carolina), and the Southern Ocean (New Zealand). The assemblage from New Zealand is diverse, with five species in three genera present during the Duntroonian stage (Chattian, 27.3–25.2 Ma). A new genus and species of eomysticetid from the lower Kokoamu Greensand of New Zealand, <i>Matapa waihao</i> gen. et sp. nov., increases the known diversity of Southern Hemisphere eomysticetids. <i>Matapa</i> uniquely exhibits a rounded margin of the occipital shield, and shares a mosaic of features seen in Northern Hemisphere eomysticetids such as a large squamosal prominence, an inflated and posteriorly rounded paroccipital process, and a double-faced posterior bullar facet with longitudinal ridges. The holotype specimen of <i>Matapa waihao</i> is ontogenetically immature, but ontogenetically static tympanoperiotic characters that diagnose this new species are shared by referred adult specimens. <i>Matapa</i> is uppermost Whaingaroan (28.1–27.3 Ma) in age, the oldest eomysticetid from New Zealand. Fossils of <i>Matapa</i> are recovered from both the modern west and east coast of New Zealand which, during the Oligocene, were on the margin of the Southern Ocean. Inclusion of <i>Matapa</i> within an earlier published cladistic analysis recovers <i>Matapa</i> as the earliest diverging member of the New Zealand eomysticetid clade, and confirms eomysticetid monophyly. The taxonomy, morphology and geochronological age of all known eomysticetids are reviewed. http://zoobank.org/urn:lsid:zoobank.org:pub:EE1CB5CC-618B-4ABA-9D97-5B9DEDD3470E
DOI: 10.6084/m9.figshare.3466622.v1
title: A new eomysticetid from the Oligocene Kokoamu Greensand of New Zealand and a review of the Eomysticetidae (Mammalia, Cetacea)

description: Eomysticetids represent a worldwide, short-lived radiation of archaic baleen-bearing mysticetes that elucidate morphofunctional shifts and ontogenetic change amongst early Neoceti. Fossils of eomysticetids are now recorded from Oligocene marine rocks along the margins of the North Pacific (Japan), North Atlantic (South Carolina), and the Southern Ocean (New Zealand). The assemblage from New Zealand is diverse, with five species in three genera present during the Duntroonian stage (Chattian, 27.3–25.2 Ma). A new genus and species of eomysticetid from the lower Kokoamu Greensand of New Zealand, <i>Matapa waihao</i> gen. et sp. nov., increases the known diversity of Southern Hemisphere eomysticetids. <i>Matapa</i> uniquely exhibits a rounded margin of the occipital shield, and shares a mosaic of features seen in Northern Hemisphere eomysticetids such as a large squamosal prominence, an inflated and posteriorly rounded paroccipital process, and a double-faced posterior bullar facet with longitudinal ridges. The holotype specimen of <i>Matapa waihao</i> is ontogenetically immature, but ontogenetically static tympanoperiotic characters that diagnose this new species are shared by referred adult specimens. <i>Matapa</i> is uppermost Whaingaroan (28.1–27.3 Ma) in age, the oldest eomysticetid from New Zealand. Fossils of <i>Matapa</i> are recovered from both the modern west and east coast of New Zealand which, during the Oligocene, were on the margin of the Southern Ocean. Inclusion of <i>Matapa</i> within an earlier published cladistic analysis recovers <i>Matapa</i> as the earliest diverging member of the New Zealand eomysticetid clade, and confirms eomysticetid monophyly. The taxonomy, morphology and geochronological age of all known eomysticetids are reviewed. http://zoobank.org/urn:lsid:zoobank.org:pub:EE1CB5CC-618B-4ABA-9D97-5B9DEDD3470E
DOI: 10.6084/m9.figshare.3466619
title: Strain gradient development in 3-dimensional extracellular matrix scaffolds during <i>in vitro</i> mechanical stimulation

description: This study analyzed strain variations in 3D ECM scaffolds using a membrane-adherent model (MM) and a direct elongation model (DM). Computational models were solved for target strains from 1 to 10% at varied scaffold thicknesses and intra-scaffold slices. DM strain profiles were uniform within the scaffold and independent of thickness. However, a wide range of strains developed with substantial volume experiencing significantly off-target strain. MM strain profiles varied throughout the scaffold, exhibiting significantly reduced average strain with increasing thickness. These findings are important for tissue engineering studies since biological responses are commonly attributed to a single strain level that only partially describes the mechanical condition, making it difficult to develop precise causal relationships. Spatial strain variations and reduced average strain may warrant targeted sampling for cell response and should be taken into consideration by investigators using large-volume 3D scaffolds when engineering mechanically sensitive tissues.
DOI: 10.6084/m9.figshare.3466619.v2
title: Strain gradient development in 3-dimensional extracellular matrix scaffolds during <i>in vitro</i> mechanical stimulation

description: This study analyzed strain variations in 3D ECM scaffolds using a membrane-adherent model (MM) and a direct elongation model (DM). Computational models were solved for target strains from 1 to 10% at varied scaffold thicknesses and intra-scaffold slices. DM strain profiles were uniform within the scaffold and independent of thickness. However, a wide range of strains developed with substantial volume experiencing significantly off-target strain. MM strain profiles varied throughout the scaffold, exhibiting significantly reduced average strain with increasing thickness. These findings are important for tissue engineering studies since biological responses are commonly attributed to a single strain level that only partially describes the mechanical condition, making it difficult to develop precise causal relationships. Spatial strain variations and reduced average strain may warrant targeted sampling for cell response and should be taken into consideration by investigators using large-volume 3D scaffolds when engineering mechanically sensitive tissues.
DOI: 10.6084/m9.figshare.3466538
title: SUS.pdf

description: <br><br><br><br><br>vd .. c
DOI: 10.6084/m9.figshare.3466538.v1
title: SUS.pdf

description: <br><br><br><br><br>vd .. c
DOI: 10.6084/m9.figshare.3466415.v2
title: Supplementary Material 1_HUAS

description: This file contains information that defines the catchment population for 10 hospitals that conducted diarrhea surveillance from Jan. 1st 2012 through Dec. 31st 2013 at Pudong.
DOI: 10.6084/m9.figshare.3466385
title: Representaciones Avanzadas.mp4

description: video realmol<br><br>
DOI: 10.6084/m9.figshare.3466385.v1
title: Representaciones Avanzadas.mp4

description: video realmol<br><br>
DOI: 10.6084/m9.figshare.3466361
title: Statistical supplement to: Mechanical constraints on flight at high elevation decrease maneuvering performance of hummingbirds

description: Data and R script of analyses in support of the study: "Mechanical constraints on flight at high elevation decrease maneuvering performance of hummingbirds"<br>Study authors: Paolo S. Segre, Roslyn Dakin, Tyson J. G. Read, Andrew D. Straw, Douglas L. Altshuler<br>
DOI: 10.6084/m9.figshare.3466361.v1
title: Statistical supplement to: Mechanical constraints on flight at high elevation decrease maneuvering performance

description: Data and R script of analyses in support of the study: "Mechanical constraints on flight at high elevation decrease maneuvering performance"<br>Study authors: Paolo S. Segre, Roslyn Dakin, Tyson J. G. Read, Andrew D. Straw, Douglas L. Altshuler<br>
DOI: 10.6084/m9.figshare.3466361.v2
title: Statistical supplement to: Mechanical constraints on flight at high elevation decrease maneuvering performance

description: Data and R script of analyses in support of the study: "Mechanical constraints on flight at high elevation decrease maneuvering performance"<br>Study authors: Paolo S. Segre, Roslyn Dakin, Tyson J. G. Read, Andrew D. Straw, Douglas L. Altshuler<br>
DOI: 10.6084/m9.figshare.3466361.v3
title: Statistical supplement to: Mechanical constraints on flight at high elevation decrease maneuvering performance

description: Data and R script of analyses in support of the study: "Mechanical constraints on flight at high elevation decrease maneuvering performance"<br>Study authors: Paolo S. Segre, Roslyn Dakin, Tyson J. G. Read, Andrew D. Straw, Douglas L. Altshuler<br>
DOI: 10.6084/m9.figshare.3466319
title: Kite-based Structure-from-Motion survey of southern North Core Banks, North Carolina, USA, 10/24/2015

description: Digital Surface Model (DSM), Orthophoto, Ground Control Point (GCP) coordinates (recorded using an RTK GNSS system), Structure-from-Motion report (with relevant parameters and spatial accuracy) and raw aerial images from a kite-based survey of the beach at the sourthern end of North Core banks, NC on October 24, 2015. DSM and Orthophoto was constructed with 16 GCPs. GCP coordinates are given in NC State Plane Coordinate system, NAD 83. Vertical datum is NAVD88
DOI: 10.6084/m9.figshare.3466265.v2
title: Voted Most Popular: CVs in Scholars@Duke

description: Presentation for the 2016 VIVO conference<br>
DOI: 10.6084/m9.figshare.3466055
title: Metabolic Pathway Prediction of UniProtKB Prokaryotic Data

description: Pathway Prediction tool for UniProtKB data along with comparison results to Rule_Base, HAMAP_Rule and SAAS on multiple prokaryotic organisms.
DOI: 10.6084/m9.figshare.3466055.v1
title: arba.zip

description: Pathway Prediction tool for UniProtKB data along with comparison results to Rule_Base, HAMAP_Rule and SAAS on multiple prokaryotic organisms.
DOI: 10.6084/m9.figshare.3466055.v2
title: Metabolic Pathway Prediction of UniProtKB Prokaryotic Data

description: Pathway Prediction tool for UniProtKB data along with comparison results to Rule_Base, HAMAP_Rule and SAAS on multiple prokaryotic organisms.
DOI: 10.6084/m9.figshare.3466025
title: Analysis dataset for the paper "Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks"

description: This dataset contains additional files related to the paper<br><br>E. Sebestyén*, B. Singh*, B. Miñana, A. Pagès, F. Mateo, M. A. Pujana, J. Valcárcel, E. Eyras (2016) Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks. <i>Genome Res</i>, <b>26</b>: 732-744, doi:10.1101/gr.199935.115<br><br>It contains the following tar.gz archives:<br><br><b>GR-Sebestyen-2016-TCGA-correlations.tgz</b> contains the Spearman correlation of the alternative splicing event PSI values with the expression z-score of the differentially expressed RBPs in a particular tumor type.<br><br><b>GR-Sebestyen-2016-TCGA-deltapsi.tgz</b> contains the differential splicing analysis results of the events between the tumor and normal conditions in a particular tumor type.<br><br><b>GR-Sebestyen-2016-TCGA-diffexp.tgz</b> contains the differential expression analysis results of all genes between the tumor and normal conditions in a particular tumor type.<br> <br><b>GR-Sebestyen-2016-TCGA-motif.tgz</b> contains the fasta sequence of all event types, and the number of RNAcompete motifs found in the events using FIMO.<br><br><b>GR-Sebestyen-2016-TCGA-psi.tgz</b> contains the PSI values of all events in all samples processed in a particular tumor type.<br><br><b>GR-Sebestyen-2016-TCGA-tpm.tgz</b> contains the TPM values of all isoforms in all samples processed in a particular tumor type. <br><br><b>GR-Sebestyen-2016-TCGA-zscore.tgz</b> contains the expression z-score of all genes in all samples processed in a particular tumor type.<br><br><b>GR-Sebestyen-2016-TCGA-fimo.tgz</b> contains the original RNAcompete FIMO results for all event types.<br><br>For details on data generation, see the Genome Research paper. <br><br>The data presented here are based upon data generated by the TCGA Research Network: <strong>http://cancergenome.nih.gov</strong><br><br>If you reuse the data, please cite the Genome Research paper.<br>
DOI: 10.6084/m9.figshare.3466025.v1
title: Analysis dataset for the paper "Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks"

description: This dataset contains additional files related to the paper<br><br>E. Sebestyén*, B. Singh*, B. Miñana, A. Pagès, F. Mateo, M. A. Pujana, J. Valcárcel, E. Eyras (2016) Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks. <i>Genome Res</i>, <b>26</b>: 732-744, doi:10.1101/gr.199935.115<br><br>It contains the following tar.gz archives:<br><br><b>GR-Sebestyen-2016-TCGA-correlations.tgz</b> contains the Spearman correlation of the alternative splicing event PSI values with the expression z-score of the differentially expressed RBPs in a particular tumor type.<br><br><b>GR-Sebestyen-2016-TCGA-deltapsi.tgz</b> contains the differential splicing analysis results of the events between the tumor and normal conditions in a particular tumor type.<br><br><b>GR-Sebestyen-2016-TCGA-diffexp.tgz</b> contains the differential expression analysis results of all genes between the tumor and normal conditions in a particular tumor type.<br> <br><b>GR-Sebestyen-2016-TCGA-motif.tgz</b> contains the fasta sequence of all event types, and the number of RNAcompete motifs found in the events using FIMO.<br><br><b>GR-Sebestyen-2016-TCGA-psi.tgz</b> contains the PSI values of all events in all samples processed in a particular tumor type.<br><br><b>GR-Sebestyen-2016-TCGA-tpm.tgz</b> contains the TPM values of all isoforms in all samples processed in a particular tumor type. <br><br><b>GR-Sebestyen-2016-TCGA-zscore.tgz</b> contains the expression z-score of all genes in all samples processed in a particular tumor type.<br><br><b>GR-Sebestyen-2016-TCGA-fimo.tgz</b> contains the original RNAcompete FIMO results for all event types.<br><br>For details on data generation, see the Genome Research paper. <br><br>The data presented here are based upon data generated by the TCGA Research Network: <strong>http://cancergenome.nih.gov</strong><br><br>If you reuse the data, please cite the Genome Research paper.<br>
DOI: 10.6084/m9.figshare.3465992
title: time_resolutions.txt

description: The files <code>cluster_labels.txt</code> and <code>time_resolutions.txt</code> contain the cluster labels for each event and the time resolutions learned from all events, respectively.<code>cluster_labels.txt</code> contains one integer number per line, from 0 to 19. In line <i>i</i>, the cluster label in that line corresponds to the event ID number <i>i</i>.<code>time_resolutions.txt</code> contains one floating point number per line, indicating the time resolution learned for all events, in minutes. There are 20 numbers in the file, one per line, in increasing order, with at most 13 decimal numbers after the point.
DOI: 10.6084/m9.figshare.3465986
title: cluster_labels.txt

description: The files <code>cluster_labels.txt</code> and <code>time_resolutions.txt</code> contain the cluster labels for each event and the time resolutions learned from all events, respectively.<code>cluster_labels.txt</code> contains one integer number per line, from 0 to 19. In line <i>i</i>, the cluster label in that line corresponds to the event ID number <i>i</i>.<code>time_resolutions.txt</code> contains one floating point number per line, indicating the time resolution learned for all events, in minutes. There are 20 numbers in the file, one per line, in increasing order, with at most 13 decimal numbers after the point.
DOI: 10.6084/m9.figshare.3465992.v1
title: time_resolutions.txt

description: The files <code>cluster_labels.txt</code> and <code>time_resolutions.txt</code> contain the cluster labels for each event and the time resolutions learned from all events, respectively.<code>cluster_labels.txt</code> contains one integer number per line, from 0 to 19. In line <i>i</i>, the cluster label in that line corresponds to the event ID number <i>i</i>.<code>time_resolutions.txt</code> contains one floating point number per line, indicating the time resolution learned for all events, in minutes. There are 20 numbers in the file, one per line, in increasing order, with at most 13 decimal numbers after the point.
DOI: 10.6084/m9.figshare.3465986.v1
title: cluster_labels.txt

description: The files <code>cluster_labels.txt</code> and <code>time_resolutions.txt</code> contain the cluster labels for each event and the time resolutions learned from all events, respectively.<code>cluster_labels.txt</code> contains one integer number per line, from 0 to 19. In line <i>i</i>, the cluster label in that line corresponds to the event ID number <i>i</i>.<code>time_resolutions.txt</code> contains one floating point number per line, indicating the time resolution learned for all events, in minutes. There are 20 numbers in the file, one per line, in increasing order, with at most 13 decimal numbers after the point.
DOI: 10.6084/m9.figshare.3465974
title: Early prediction and characterization of high-impact world events using social media

description: This dataset consists on 5234 news events obtained from Twitter. The file <code>tweets.csv.gz</code> (available upon request via email to the authors) contains a CSV file, called <code>tweets.csv</code>, with all the tweets IDs corresponding to each event in <code>events.csv</code>. The format of each line of the file is the following:tweet_id, event_idWhere:<code></code>tweet_id is an long number indicating the Twitter ID of the given tweet. Using the Twitter REST API it is possible to retrieve all the information about the given tweet.<code></code>event_id corresponds to the event ID of the given tweet. The file events.csv.gz contains a CSV file, called events.csv with all the news events captured from Twitter since August, 2013 until June, 2014. The format of each line of the file is the following: <br> event_ID,date,total_keywords,total_tweets,keywords <br> Where: event_ID is an integer which identifies the corresponding event. There are 5234 events, then event_ID ranges from 1 to 5234. date is the date of the event or connected component. The format is YYYY-MM-DD. total_keywords is an integer indicating how many keywords are in the event or connected component. total_tweets is an integer indicating how many tweets belongs to this event. keywords is a string containing total keywords keywords. There is a semicolon between two keywords. <br> The files cluster_labels.txt and time_resolutions.txt contain the cluster labels for each event and the time resolutions learned from all events, respectively. cluster_labels.txt contains one integer number per line, from 0 to 19. In line <i>i</i>, the cluster label in that line corresponds to the event ID number <i>i</i>. time_resolutions.txt contains one floating point number per line, indicating the time resolution learned for all events, in minutes. There are 20 numbers in the file, one per line, in increasing order, with at most 13 decimal numbers after the point. <br>
DOI: 10.6084/m9.figshare.3465974.v3
title: Early prediction and characterization of high-impact world events using social media

description: This dataset consists on 5234 news events obtained from Twitter, along with the tweets talking about them. <br> The file tweets.csv.gz contains a CSV file, called tweets.csv, with all the tweets IDs corresponding to each event in events.csv. The format of each line of the file is the following: <br> tweet_ID, event_ID <b></b><br> Where: tweet_ID is an long number indicating the Twitter ID of the given tweet. Using the Twitter REST API it is possible to retrieve all the information about the given tweet. event_ID corresponds to the event ID of the given tweet. <br> The file events.csv.gz contains a CSV file, called events.csv with all the news events captured from Twitter since August, 2013 until June, 2014. The format of each line of the file is the following: <br> event_ID,date,total_keywords,total_tweets,keywords <br> Where: event_ID is an integer which identifies the corresponding event. There are 5234 events, then event_ID ranges from 1 to 5234. date is the date of the event or connected component. The format is YYYY-MM-DD. total_keywords is an integer indicating how many keywords are in the event or connected component. total_tweets is an integer indicating how many tweets belongs to this event. keywords is a string containing total keywords keywords. There is a semicolon between two keywords. <br> The files cluster_labels.txt and time_resolutions.txt contain the cluster labels for each event and the time resolutions learned from all events, respectively. cluster_labels.txt contains one integer number per line, from 0 to 19. In line <i>i</i>, the cluster label in that line corresponds to the event ID number <i>i</i>. time_resolutions.txt contains one floating point number per line, indicating the time resolution learned for all events, in minutes. There are 20 numbers in the file, one per line, in increasing order, with at most 13 decimal numbers after the point. <br>
DOI: 10.6084/m9.figshare.3465932
title: events.csv.gz

description: EventsThe file <code>events.csv.gz</code> contains a CSV file, called <code>events.csv</code> with all the news events captured from Twitter since August, 2013 until June, 2014. The format of each line of the file is the following:<code>event_ID,date,total_keywords,total_tweets,keywords</code>Where:<code>event_ID </code>is an integer which identifies the corresponding event. There are 5234 events, then <code>event_ID</code> ranges from 1 to 5234. <code>date</code> is the date of the event or connected component. The format is <code>YYYY-MM-DD</code>.<code>total_keywords</code> is an integer indicating how many keywords are in the event or connected component.<code>total_tweets</code> is an integer indicating how many tweets belongs to this event.<code>keywords</code> is a string containing <code>total keywords</code> keywords. There is a semicolon between two keywords.
DOI: 10.6084/m9.figshare.3465932.v1
title: events.csv.gz

description: EventsThe file <code>events.csv.gz</code> contains a CSV file, called <code>events.csv</code> with all the news events captured from Twitter since August, 2013 until June, 2014. The format of each line of the file is the following:<code>event_ID,date,total_keywords,total_tweets,keywords</code>Where:<code>event_ID </code>is an integer which identifies the corresponding event. There are 5234 events, then <code>event_ID</code> ranges from 1 to 5234. <code>date</code> is the date of the event or connected component. The format is <code>YYYY-MM-DD</code>.<code>total_keywords</code> is an integer indicating how many keywords are in the event or connected component.<code>total_tweets</code> is an integer indicating how many tweets belongs to this event.<code>keywords</code> is a string containing <code>total keywords</code> keywords. There is a semicolon between two keywords.
DOI: 10.6084/m9.figshare.3465923
title: Regioselective Mitsunobu Reaction of Partially Protected Uridine

description: Mitsunobu reaction of partially acylated uridine proceeds with high regioselectivity for intramolecular S<sub>N</sub>2 anhydro linkage closuring. Under the reaction conditions, an isomeric mixture of diacyl uridine derivatives with either free 2′- or 3′-hydroxyl group was transformed into a single cyclonucleosidic product, 2,2′-anhydro-3′,5′-di-O-acyluridine. This paper presents a possible mechanism of the reactions, the explanation of observed phenomenon based on semiempirical and density functional theory (DFT) calculations and possible utility of this synthetic pathway.