cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7065171
title: Prevalence of undiagnosed hypertension and associated factors among Bangladeshi adults

description: These are the dataset and do files for the project titled "Prevalence of undiagnosed hypertension and associated factors among Bangladeshi adults: An analysis of Bangladesh Demographic and Health Survey 2017-2018"
DOI: 10.5066/p9pgovub
title: USGS National and Global Oil and Gas Assessment Project-West Siberian Basin Province of Russia: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables

description: This data release contains the boundaries of assessment units, assessment input data tables and resulting fact sheet data tables for the assessment of undiscovered oil and gas resources in the West Siberian Province in Russia. The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown herein as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. Machine-readable tables are provided that contain the input and results for each assessment unit summarized in the USGS Fact Sheet. Methodology of assessments are documented in USGS Data Series 547 for continuous assessments (https://pubs.usgs.gov/ds/547) and USGS DDS69-D, Chapter 21 for conventional assessments (https://pubs.usgs.gov/dds/dds-069/dds-069-d/REPORTS/69_D_CH_21.pdf). See supplemental information for a detailed list of files included this data release.
DOI: 10.5281/zenodo.7065170
title: Prevalence of undiagnosed hypertension and associated factors among Bangladeshi adults

description: These are the dataset and do files for the project titled "Prevalence of undiagnosed hypertension and associated factors among Bangladeshi adults: An analysis of Bangladesh Demographic and Health Survey 2017-2018"
DOI: 10.6084/m9.figshare.21071137
title: Micromanufactured Tactile Samples for Characterization of Rough and Dry Tactile Perception

description: Raw data of the perception experiments: - Roughness perception of the tactile samples with striped patterns - Dry perception of the tactile samples with random patterns - Dry perception of the tactile samples with square patterns (the piece = the gap) - Dry perception of the tactile samples with square patterns (the variable pieces and gaps)
DOI: 10.6084/m9.figshare.21071137.v1
title: Micromanufactured Tactile Samples for Characterization of Rough and Dry Tactile Perception

description: Raw data of the perception experiments: - Roughness perception of the tactile samples with striped patterns - Dry perception of the tactile samples with random patterns - Dry perception of the tactile samples with square patterns (the piece = the gap) - Dry perception of the tactile samples with square patterns (the variable pieces and gaps)
DOI: 10.48567/qpyg-zn97
title: AGO-4 Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/822m-1y90
title: Baldrick Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.6084/m9.figshare.20658138
title: Amphibian reproductive ecology and egg attendance data

description: Datasets accompanying the article: The reproductive ecology drivers of egg attendance in amphibians (Ecology Letters). Data = Data file Data_key = Description of variables in Data file Data_references = References for Data file Phylogeny_Pyron_2014 = Pruned amphibian phylogeny from Pyron (2014) <em>Systematic Biology</em>, used in analyses
DOI: 10.48567/jx70-nw96
title: Bear Peninsula Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/n3py-qx23
title: Byrd Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.6084/m9.figshare.20171174
title: Specific location of galactosylation in an afucosylated antiviral monoclonal antibody affects its FcγRIIIA

description: Mass Spectrometry Data Intact Mass Specs : 1) <strong>Commercial Syn :</strong> <strong>20220404_Grayson_I01</strong>.raw 2)<strong> Syn-GnF</strong> : <strong>20220404_Grayson_I07</strong>.raw 3) <strong>Syn-Gn</strong> : <strong>20220404_Grayson_I02</strong>.raw 4) <strong>Syn-G0</strong> : <strong>20220404_Grayson_I03</strong>.raw 5) <strong>Syn-G1(3)</strong> : <strong>20220404_Grayson_I04</strong>.raw<strong> </strong> 6) <strong>Syn G1(6):</strong> <strong>20210329_Grayson_17</strong>.raw 7) <strong>Syn G2</strong> : <strong>20210329_Grayson_08</strong>.raw <br> Glycan MS/MS (G1(3)T, G1(6)T): <br> 8) <strong>20201013_11_Roger_G1_6_T.</strong> raw 9) <strong>20201013_08_Roger_G1_3_T</strong>.raw <br>
DOI: 10.48567/a864-dc55
title: Cape Bird Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/91qz-m836
title: Cape Denison Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.5281/zenodo.7065254
title: SciExpeM - 10.5281/zenodo.7065254

description: Jallais, S.; Bonneau, L.; Auzanneau, M.; Naudet, V.; Bockel-Macal, S. - Industrial &Amp; Engineering Chemistry Research, 2002, (41), 5659-5667
DOI: 10.5281/zenodo.7065253
title: SciExpeM - 10.5281/zenodo.7065254

description: Jallais, S.; Bonneau, L.; Auzanneau, M.; Naudet, V.; Bockel-Macal, S. - Industrial &Amp; Engineering Chemistry Research, 2002, (41), 5659-5667
DOI: 10.48567/gn8v-zb43
title: D-10 Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/4ybz-kb87
title: D-47 Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/z8ye-yn41
title: D-85 Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/64c2-me73
title: Dismal Island Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/x7a9-cx26
title: Dome C II Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.5517/ccdc.csd.cc2bt8gx
title: CCDC 2169239: Experimental Crystal Structure Determination

description: Related Article: Liangliang Qi|2022|CSD Communication|||
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: 10.48567/he9m-6207
title: Dome Fuji Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.5517/ccdc.csd.cc2bth5v
title: CCDC 2169447: Experimental Crystal Structure Determination

description: Related Article: Florian Reichenauer, Dieter Schollmeyer, Katja Heinze|2022|CSD Communication|||
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.cc2btkk9
title: CCDC 2169521: Experimental Crystal Structure Determination

description: Related Article: Wen-Hua Chiou|2022|CSD Communication|||
description: Related Article: Yu-Tang Wang, Jui-Lin Wu, Wen-Hua Chiou|2022|Org.Lett.|24|5957|doi:10.1021/acs.orglett.2c02225
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.cc2btlh8
title: CCDC 2169550: Experimental Crystal Structure Determination

description: Related Article: Ari Lehtonen, Reijo Sillanpää|2022|CSD Communication|||
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: 10.48567/wv06-5j20
title: Elaine Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.5517/ccdc.csd.cc2bvpkg
title: CCDC 2170606: Experimental Crystal Structure Determination

description: Related Article: Ferdinand Belaj, Michael Tüchler, Nadia C. Mösch-Zanetti|2022|CSD Communication|||
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: 10.48567/da92-1w75
title: Elizabeth Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/sepw-sj14
title: Emilia Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/nc99-6n46
title: Emma Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.13026/c25q2n
title: VOICED Database

description: This database includes 208 voice samples, from 150 pathological, and 58
healthy voices.
DOI: 10.13026/twfd-kb89
title: VOICED Database

description: This database includes 208 voice samples, from 150 pathological, and 58
healthy voices.
DOI: 10.48567/2xwx-sr41
title: Erin Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/d9ry-4431
title: Ferrell Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/msbx-q537
title: Gill Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/af8k-4a29
title: Harry Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/kch4-z976
title: Henry Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/wyz2-ca88
title: JASE2007 Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/dddw-mx18
title: Janet Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/c2rf-qs15
title: Kathie Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/cfh8-ss54
title: Laurie II Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/0bxt-7b41
title: Lettau Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/fggc-c481
title: Linda Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/286z-y924
title: Lorne Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/p914-jm14
title: Manuela Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/9n5e-re86
title: Marble Point Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/19xg-r977
title: Marble Point II Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/egah-0k48
title: Margaret Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48331/scielodata.bsyfwj/p2ortu
title: S1 Appendix. Search strategies.pdf

description: Appendix 1 - strategies used to search the databases for the systematic review article: "Repercussions of parental self-efficacy on preterm infants' growth after hospital discharge: a systematic review"
DOI: 10.48567/akha-9675
title: Marilyn Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48331/scielodata.bsyfwj/qgbwa0
title: S3 Appendix. Risk of Bias.pdf

description: Appendix 3 - Calculation of the risk of bias of the systematic review article: "Repercussions of parental self-efficacy on preterm infants' growth after hospital discharge: a systematic review"
DOI: 10.48567/r84x-x398
title: Minna Bluff Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/22w4-vj38
title: Mizuho Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/m30f-k372
title: Nico Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/cv7r-bj11
title: PANDA-South Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/krfy-hy22
title: Possession Island Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/qpra-7x18
title: Relay Station Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/vfdv-rj71
title: Sabrina Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.5281/zenodo.7064704
title: Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes, simulation dataset 0.25% spike-in contaminant sequences

description: Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision. Simulation Dataset 0.25% contaminant spike-in.
DOI: 10.48567/5wtn-fs88
title: Schwerdtfeger Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/k042-7790
title: Siple Dome Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/mw3y-sr13
title: Theresa Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/em0t-2y81
title: Thurston Island Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/6my7-ax86
title: Vito Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/gcd0-ab75
title: White Island Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/b2nh-xv08
title: Whitlock Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/z379-vh96
title: Willie Field Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.48567/a3rn-9917
title: Windless Bight Automatic Weather Station, 2022 quality-controlled observational data.
DOI: 10.6084/m9.figshare.20056118
title: Fossil Proctotrupidae (Hymenoptera) in Cretaceous amber

description: <em>Cresogmus</em> <em>grimaldii</em> Rasnitsyn & Kolyada, gen. et sp. nov. is described from the mid-Cretaceous Burmese amber in the tribe Disogmini (subfamily Proctotrupinae) as the first representative of the family Proctotrupidae buried in Cretaceous amber. Diagnostic characters of Disogmini are formulated. <br> Dataset includes source image stacks for the publication.
DOI: 10.6084/m9.figshare.21071257
title: Near-infrared spectroscopy (NIR) for early selection of waxy cassava clones via seed analysis

description: NIRS raw dataset
DOI: 10.13140/rg.2.2.21871.51362
title: Carlina species - Thistles against several diseases
DOI: 10.3886/e179301v1
title: Social Preferences, Peers, Networks, Preference Transmission

description: We study distributional preferences in adolescent peer networks. Using incentivized choices between allocations for themselves and a passive agent, children are classified into efficiency-loving, inequality-loving, inequality-averse, and spiteful types. We find that pairs of students who report a friendship link are more likely to exhibit the same preference type than other students who attend the same school. The relation between types is almost completely driven by inequality-loving and spiteful types. The role of peer networks in explaining distributional preferences goes beyond network composition effects. A low rank in academic performance and a central position within the network relate positively to a higher likelihood of being classified as spiteful. Hence, social hierarchies seem to be correlated with distributional preference types.
DOI: 10.3886/e179301v2
title: Social Preferences, Peers, Networks, Preference Transmission

description: We study distributional preferences in adolescent peer networks. Using incentivized choices between allocations for themselves and a passive agent, children are classified into efficiency-loving, inequality-loving, inequality-averse, and spiteful types. We find that pairs of students who report a friendship link are more likely to exhibit the same preference type than other students who attend the same school. The relation between types is almost completely driven by inequality-loving and spiteful types. The role of peer networks in explaining distributional preferences goes beyond network composition effects. A low rank in academic performance and a central position within the network relate positively to a higher likelihood of being classified as spiteful. Hence, social hierarchies seem to be correlated with distributional preference types.
DOI: 10.6084/m9.figshare.21071284.v1
title: Summary of MAGs from Daisy the digester

description: Excel file with quality statistics and txonomy of metagenome assembled genomes (MAGs) from spades assemblies of samples from Daisy the digester
DOI: 10.34740/kaggle/dsv/4182683
title: Tales from the Pizza Guy
DOI: 10.6084/m9.figshare.16583396
title: Supplemental data network_file.cys

description: Supplemental data file for: "Microbial Community Dynamics of Sequentially Fed Anaerobic Digester Treating Solid Organic Waste" <br>A network of the top 100 ASVs detected among the samples was constructed using the CoNet application in Cytoscape and the co-occurrence network model was displayed by Cytoscape 3.7 using the radial layout. Four methods were used to assess the relationship between ASVs and metadata: Bray Curtis distances, Mutual information and Pearson and Spearman correlations, and three methods were required in order to draw a link between objects (i.e ASVs and metadata). ​<br>The Cytoscape file is provided here.
DOI: 10.6084/m9.figshare.16583396.v3
title: Supplemental data network_file.cys from 16S rRNA ASVs from Daisy the digester

description: Supplemental data file for: "Microbial Community Dynamics of Sequentially Fed Anaerobic Digester Treating Solid Organic Waste"<br> A network of the top 100 ASVs detected among the samples was constructed using the CoNet application in Cytoscape and the co-occurrence network model was displayed by Cytoscape 3.7 using the radial layout. Four methods were used to assess the relationship between ASVs and metadata: Bray Curtis distances, Mutual information and Pearson and Spearman correlations, and three methods were required in order to draw a link between objects (i.e ASVs and metadata).<br> <br> The Cytoscape file is provided here.
DOI: 10.25934/pr00007294.2
title: Available IPD datapackage for study 'A Phase III, Randomized, Double-Blind, Multicenter Study to Evaluate the Efficacy and Safety of Remdesivir Plus Tocilizumab Compared With Remdesivir Plus Placebo in Hospitalized Patients With Severe COVID-19 Pneumonia'

description: This study will evaluate the efficacy and safety of combination therapy with remdesivir plus tocilizumab compared with remdesivir plus placebo in hospitalized patients with COVID-19 pneumonia.
DOI: 10.25934/pr00008342
title: IDENTIFYING TOCILIZUMAB-RESPONSIVE COVID-19 PATIENTS FROM COVACTA, EMPACTA, AND REMDACTA RCTS PRE-RANDOMIZATION DATA

description: Discovering effective treatments of COVID-19 infection is vital.  In the EMPACTA randomized clinical trial (RCT) (NCT04372186) and  the COVACTA RCT (NCT04320615) and the REMDACTA (NCT04409262) RCTs tocilizumab, a monoclonal antibody against the interleukin-6 receptor,  did not improve survival in hospitalized COVID-19 patients with pneumonia.  These RCT failures may indicate that tocilizumab was not effective.  However, alternatively non-specific clinical RCT entry criteria may have enrolled so many patients not responsive to tocilizumab’s IL-6 inhibition that its true treatment effects were blunted.
Hypothesis:  The clinical definitions used as COVACTA, EMPACTA, and REMDACTA RCT entry criteria may have enrolled so many patients whose pathophysiology could not benefit from tocizumab that its true treatment effects were diluted to invisibility.  Previously the SMART prognostic methodology identified 55% of the COVACTA tocilizumab RCT in COVID-19 among whom tocilizumab reduced mortality by over 14%, while in the other COVACTA patients, with placebo mortality 1/3 of that in the responder group, tocilizumab increased mortality by 16%.  The present study proposes to determine whether or not similar cohorts exist in the REMDACTA and EMPACTA RCT’s and if the SMART predictive models are similar in these studies.  If this investigation identifies such patients, then the predictive models generated and validated in the combined databases of the 3 RCTs can be used to match tocilizumab-responsive COVID-19 pneumonia patients with this life-saving treatment.
DOI: 10.5281/zenodo.7064598
title: Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes, simulation dataset 1% spike-in contaminant sequences

description: Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision. Simulation Dataset 1% contaminant spike-in.