cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4959881
title: Dataset for manuscript: Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing

description: This dataset comprises:<br><br>(1) shape files of <i>Acacia longifolia</i> and <i>Corema album</i> which were used to fit the generalized additive mixed model (GAMM) to predict <i>C. album</i> foliar δ<sup>15</sup>N<br>(2) raster data used for predictive isoscapes at five study sites<br>(3) the R code used to fit the GAMM and examples how the predictive isoscapes were generated<br>(4) an R Workspace containing the shape files and raster data to be used with (3)<br><br>Please find a detailed description of the methods in our manuscript "Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing".<br>
DOI: 10.6084/m9.figshare.4959881.v1
title: Dataset for manuscript: Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing

description: This dataset comprises:<br><br>(1) shape files of <i>Acacia longifolia</i> and <i>Corema album</i> which were used to fit the generalized additive mixed model (GAMM) to predict <i>C. album</i> foliar δ<sup>15</sup>N<br>(2) raster data used for predictive isoscapes at five study sites<br>(3) the R code used to fit the GAMM and examples how the predictive isoscapes were generated<br>(4) an R Workspace containing the shape files and raster data to be used with (3)<br><br>Please find a detailed description of the methods in our manuscript "Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing".<br>
DOI: 10.6084/m9.figshare.4959872.v2
title: Selected contaminant and non-contaminant organisms - (Item F)

description: Interactive version of Figure 3. in Kirstahler <i>et al.</i> (2018):<br> Contaminant organisms (light grey) were present in higher abundance in DNA extraction controls (green) compared to the endophthalmitis-positive samples (red). The contaminant organisms were detected in similar abundance in the endophthalmitis-negative (yellow) and basal salt solution samples (blue) as in the DNA extraction control samples. Organisms that were detected in higher abundance in patient samples (dark grey), compared to their respective DNA extraction control samples, were not regarded as sample contaminants. Read counts are presented as counts per million in relation to the total non-human read counts per sample, respectively. The interactive version of this figure has incorporated individual sample information, including read counts. For a detailed list of contaminant organisms, see Supplementary Table S5.<br><br><b>Reference</b> <b>Kirstahler P, Bjerrum SS, Friis-Møller A, </b><b>la Cour M, Aarestrup FM, Westh H., and Pamp SJ. (2018) </b>Genomics-Based Identification of Microorganisms in Human Ocular Body Fluid.<b> </b><b>Scientific Reports</b>, doi:10.1038/s41598-018-22416-4.
DOI: 10.6084/m9.figshare.4959872.v1
title: Selected contaminant and non-contaminant organisms - (Item D)

description: Interactive version of Figure 3. in Kirstahler <i>et al.</i> (2017):<br> Contaminant organisms (light grey) were present in higher abundance in DNA extraction controls (green) compared to the endophthalmitis-positive samples (red). The contaminant organisms were detected in similar abundance in the endophthalmitis-negative (yellow) and basal salt solution samples (blue) as in the DNA extraction control samples. Organisms that were detected in higher abundance in patient samples (dark grey), compared to their respective DNA extraction control samples, were not regarded as sample contaminants. Read counts are presented as counts per million in relation to the total non-human read counts per sample, respectively. The interactive version of this figure has incorporated individual sample information, including read counts. For a detailed list of contaminant organisms, see Supplementary Table S5.<br><br><b>Reference</b> <b>Kirstahler P, Bjerrum SS, Friis-Møller A, </b><b>la Cour M, Aarestrup FM, Westh H., and Pamp SJ. (2017) </b>Genomics-Based Identification of Microorganisms in Human Ocular Body Fluid.<b> Journal </b>Vol:Issue page-page.
DOI: 10.6084/m9.figshare.4959839
title: Bumble bee collections data from Big city <i>Bombus</i>: using natural history and land-use history to find significant environmental drivers in bumble-bee declines in urban development

description: Detailed collections data of bumble bee samples used in analysis
DOI: 10.5258/soton/d1523
title: Dataset for: Self-Interference Cancellation and Channel Estimation in Multicarrier-Division Duplex Systems with Hybrid Beamforming

description: This dataset contains: Figure 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12 of the paper "Self-Interference Cancellation and Channel Estimation in Multicarrier-Division Duplex Systems with Hybrid Beamforming. IEEE Access. Each folder is named according to its content, where the curves of each figure are stored in mat files. To regenerate the results, please use the Matlab.
DOI: 10.6084/m9.figshare.4959809
title: DATA.zip

description: <br>1. NODES_PLOSONE contains information about the nodes into the cattle movement network: node identification code, type of node structure (herds, assembly centres, staging points, markets and pastures), node latitude and longitude and outbreak (contains '1' to identify the positive node in Sicily during 2009 and 'Seed' for the first outbreak occurred).<br><br>2. NTW_PLOSONE contains information about animal movements: origin node identification code, destination node identifincation code, number of animals moved and time of the movement.<br><br>3. POP_PLOSONE contains information about node population for each time: node identification code, time and number of animals into the node.
DOI: 10.6084/m9.figshare.4959824
title: Impervious Surface Data from Big city <i>Bombus</i>: using natural history and land-use history to find significant environmental drivers in bumble-bee declines in urban development

description: Site level data of the proportional coverage of impervious surface around each site used in analysis
DOI: 10.6084/m9.figshare.4959791
title: Obesity publications (WoS 2000-2013)

description: List of UT keys of WoS publications 2000-2013 related with obesity for the 6 corpora of the study "Improving fitness: Mapping research priorities against societal needs on obesity", Cassi et al. 2017 <br>
DOI: 10.6084/m9.figshare.4959791.v1
title: Obesity publications (WoS 2000-2013)

description: List of UT keys of WoS publications 2000-2013 related with obesity for the 6 corpora of the study "Improving fitness: Mapping research priorities against societal needs on obesity", Cassi et al. 2017 <br>
DOI: 10.6084/m9.figshare.4959809.v1
title: DATA.zip

description: <br>1. NODES_PLOSONE contains information about the nodes into the cattle movement network: node identification code, type of node structure (herds, assembly centres, staging points, markets and pastures), node latitude and longitude and outbreak (contains '1' to identify the positive node in Sicily during 2009 and 'Seed' for the first outbreak occurred).<br><br>2. NTW_PLOSONE contains information about animal movements: origin node identification code, destination node identifincation code, number of animals moved and time of the movement.<br><br>3. POP_PLOSONE contains information about node population for each time: node identification code, time and number of animals into the node.
DOI: 10.6084/m9.figshare.4959278
title: WTL17_out_YW_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959278.v1
title: WTL17_out_YW_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959266
title: WTL17_out_NF_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959272
title: WTL17_out_NF_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959275
title: WTL17_out_YW_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959266.v1
title: WTL17_out_NF_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959269
title: WTL17_out_VM_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959269.v1
title: WTL17_out_VM_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959272.v1
title: WTL17_out_NF_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959257
title: WTL17_out_VM_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959275.v1
title: WTL17_out_YW_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959233
title: WTL17_out_VMT_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959236
title: WTL17_out_XW4d_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959242
title: WTL17_out_VMT_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959233.v1
title: WTL17_out_VMT_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959236.v1
title: WTL17_out_XW4d_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959242.v1
title: WTL17_out_VMT_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959257.v1
title: WTL17_out_VM_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959221
title: WTL17_out_XW16d_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959224
title: WTL17_out_XW16d_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959227
title: WTL17_out_XW4d_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959215
title: WTL17_out_XW24_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959224.v1
title: WTL17_out_XW16d_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959227.v1
title: WTL17_out_XW4d_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959212
title: WTL17_out_CM_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959215.v1
title: WTL17_out_XW24_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959221.v1
title: WTL17_out_XW16d_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959194
title: WTL17_out_XW06_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959203
title: WTL17_out_CM_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959206
title: WTL17_out_XW24_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959194.v1
title: WTL17_out_XW06_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959203.v1
title: WTL17_out_CM_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959206.v1
title: WTL17_out_XW24_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959212.v1
title: WTL17_out_CM_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959176
title: Duplicated lincRNAs

description: LincRNAs derived from whole-genome duplication (WGD) and tandem duplication (TD).
DOI: 10.6084/m9.figshare.4959185
title: WTL17_out_XW06_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959173
title: WTL17_out_RW_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959176.v1
title: Duplicated lincRNAs

description: LincRNAs derived from whole-genome duplication (WGD) and tandem duplication (TD).
DOI: 10.6084/m9.figshare.4959173.v1
title: WTL17_out_RW_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959185.v1
title: WTL17_out_XW06_01

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959146
title: WTL17_out_XW_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959146.v1
title: WTL17_out_XW_02

description: see Table 1 in Whitt et al. (2017) , JGR
DOI: 10.6084/m9.figshare.4959128
title: WTL17_out_RW_01

description: see Table 1 in Whitt et al. (2017) Synoptic-to-planetary scale wind variability enhances phytoplankton biomass at ocean fronts, JGR
DOI: 10.6084/m9.figshare.4959110
title: WTL17_out_XW12_02

description: see Whitt et al. 2017 table 1
DOI: 10.6084/m9.figshare.4959125
title: WTL17_out_XW_01

description: see whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4959128.v1
title: WTL17_out_RW_01

description: see Table 1 in Whitt et al. (2017) Synoptic-to-planetary scale wind variability enhances phytoplankton biomass at ocean fronts, JGR
DOI: 10.6084/m9.figshare.4959107
title: WTL17_out_XW12_01

description: Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4959110.v1
title: WTL17_out_XW12_02

description: see Whitt et al. 2017 table 1
DOI: 10.6084/m9.figshare.4959125.v1
title: WTL17_out_XW_01

description: see whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4959053
title: WTL17_out_CW

description: see Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4959161.v1
title: UHCL Theses and Dissertations

description: The dataset 20170501TDCollectionWithFaculty.csv includes all master's projects, theses and dissertations submitted to UHCL as of April 2017. Variables include:<br>TITLE: The title of the work, followed by a forward slash and the authorSUBJECT: subjects in Library of Congress classificationIMPRINT: publication year<br>TYPE: thesis, graduate project, or dissertationCollege: college, updated to current college names<br>FORMAT: print or electronicCHAIR: chair/advisorCOCHAIR<br>This dataset has gone through significant processing. Advisor and college names have been extracted from other fields. Chair names have been clustered in OpenRefine to create controlled names (e.g. consistent use of middle initials).<br>The thesisAnalysis.R file shows the code used to generate and clean the dataset, though it has not been commented or cleaned to enable those unfamiliar with it to understand it.
DOI: 10.6084/m9.figshare.4959107.v1
title: WTL17_out_XW12_01

description: Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4959161
title: UHCL Theses and Dissertations

description: The dataset tdsFinal.csv includes all master's projects, theses and dissertations submitted to UHCL as of May 2018. Variables include:<br>bibrecord: The bibliographic record as cataloged by the Neumann Libraryitemrecord: The item record as cataloged by the Neumann Librarytitle: The title of the workauthor: The author of the workcallnumber: The call number of the worknote: The bibliographic notes fieldsubject: subjects in Library of Congress classification as cataloged by the Neumann Library<br>imprint: publication year<br>add.author: The additional author fieldtot.chkout: The total number of checkoutstype: thesis, graduate project, or dissertationcollege: college, updated to current college names<br>link: the hyperlink to the workformat: print or electronicchair: chair/advisor<br><br>This dataset has gone through significant processing, as documented in the thesisCleaning pdf document included in this FigShare fileset. The thesisCleaning.Rmd file is the Markdown file used to generate the PDF.<br>Advisor and college names have been extracted from other fields. Chair names have been clustered in OpenRefine to create controlled names (e.g. consistent use of middle initials).
DOI: 10.6084/m9.figshare.4959053.v1
title: WTL17_out_CW

description: see Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4958996
title: MEP_Questions_Oct2009_Feb2015

description: Questions related to obesity from Members of the European Parliament to the European Commission (October 2009 - February 2014). Data for the study "Improving fitness: Mapping research priorities against societal needs on obesity" Cassi et al. 2017 <br>
DOI: 10.6084/m9.figshare.4959023
title: WTL17_inputfile

description: see Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4958987
title: WTL17_drifters_YW

description: see Whitt et al. 2017 table 1
DOI: 10.6084/m9.figshare.4958993
title: WTL17_drifters_NF

description: see Whitt et al. 2017 table 1
DOI: 10.6084/m9.figshare.4958996.v1
title: MEP_Questions_Oct2009_Feb2015

description: Questions related to obesity from Members of the European Parliament to the European Commission (October 2009 - February 2014). Data for the study "Improving fitness: Mapping research priorities against societal needs on obesity" Cassi et al. 2017 <br>
DOI: 10.6084/m9.figshare.4959023.v1
title: WTL17_inputfile

description: see Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4958987.v1
title: WTL17_drifters_YW

description: see Whitt et al. 2017 table 1
DOI: 10.6084/m9.figshare.4958993.v1
title: WTL17_drifters_NF

description: see Whitt et al. 2017 table 1
DOI: 10.6084/m9.figshare.4958975
title: WTL17_drifters_XW16d

description: see Table 1 of Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958978
title: WTL17_drifters_XW4d

description: see Table 1 of Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958984
title: WTL17_drifters_XW12

description: see Whitt et al. 2017 table 1
DOI: 10.6084/m9.figshare.4958957
title: WTL17_drifters_XW06

description: Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958978.v1
title: WTL17_drifters_XW4d

description: see Table 1 of Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958960
title: WTL17_drifters_XW24

description: Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958975.v1
title: WTL17_drifters_XW16d

description: see Table 1 of Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958984.v1
title: WTL17_drifters_XW12

description: see Whitt et al. 2017 table 1
DOI: 10.6084/m9.figshare.4958945
title: WTL17_drifters_XW

description: Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4958951
title: WTL17_drifters_CM

description: Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4958957.v1
title: WTL17_drifters_XW06

description: Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958939
title: WTL17_drifters_RW

description: Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4958951.v1
title: WTL17_drifters_CM

description: Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4958960.v1
title: WTL17_drifters_XW24

description: Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958933
title: WTL17_drifters_CW

description: Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958939.v1
title: WTL17_drifters_RW

description: Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.4958945.v1
title: WTL17_drifters_XW

description: Whitt et al. 2017 Table 1
DOI: 10.6084/m9.figshare.12905831
title: SNP discovery of Non-redundant ORF unigenes to Gene Ontology, KEGG and Protein Family databases of "De novo assembly of the Brown trout (Salmo trutta m. fario) brain and muscle transcriptome: transcript annotation, tissue differential expression profile and SNP discovery"

description: This data set contains procesed results derived from the SAMtools pipeline of the SNP discovery applied to non-redundant ORF unigenes.1) SNP prediction: Variant call format file "SNP prediction to non-redundant ORF unigene sequence.vcf"2) 150bp sequence surrounding each SNP: Spreadsheet "SNP context sequence.xlsx"<br>
DOI: 10.6084/m9.figshare.4958933.v1
title: WTL17_drifters_CW

description: Whitt et al. 2017
DOI: 10.6084/m9.figshare.4958819
title: O papel dos coletivos educadores na formação de seus integrantes: um estudo no contexto universitário

description: Arquivos suplementares do artigo submetido aos anais do XVI Encontro Paranaense de Educação Ambiental.
DOI: 10.6084/m9.figshare.12905831.v1
title: SNP discovery of Non-redundant ORF unigenes to Gene Ontology, KEGG and Protein Family databases of "De novo assembly of the Brown trout (Salmo trutta m. fario) brain and muscle transcriptome: transcript annotation, tissue differential expression profile and SNP discovery"

description: This data set contains procesed results derived from the SAMtools pipeline of the SNP discovery applied to non-redundant ORF unigenes.1) SNP prediction: Variant call format file "SNP prediction to non-redundant ORF unigene sequence.vcf"2) 150bp sequence surrounding each SNP: Spreadsheet "SNP context sequence.xlsx"<br>
DOI: 10.6084/m9.figshare.4958687
title: Dataset for Plant diversity effect on water quality in wetlands: a meta-analysis based on experimental systems

description: published in Ecological Applications
DOI: 10.6084/m9.figshare.4958819.v1
title: O papel dos coletivos educadores na formação de seus integrantes: um estudo no contexto universitário

description: Arquivos suplementares ao artigo submetido aos anais do XVI Encontro Paranaense de Educação Ambiental.
DOI: 10.6084/m9.figshare.4956785
title: Mumps M protein PDB files

description: Conservation and entropy PDB files for the M protein homology model
DOI: 10.6084/m9.figshare.4956791
title: Mumps V protein PDB files

description: Conservation and entropy PDB files for the V protein homology model
DOI: 10.6084/m9.figshare.4956788
title: Mumps N protein PDB files

description: Conservation and entropy PDB files for the N protein homology model
DOI: 10.6084/m9.figshare.4956791.v1
title: Mumps V protein PDB files

description: Conservation and entropy PDB files for the V protein homology model
DOI: 10.6084/m9.figshare.4956785.v1
title: Mumps M protein PDB files

description: Conservation and entropy PDB files for the M protein homology model
DOI: 10.6084/m9.figshare.4956788.v1
title: Mumps N protein PDB files

description: Conservation and entropy PDB files for the N protein homology model
DOI: 10.6084/m9.figshare.4956776
title: Mumps HN protein PDB files

description: PDB files for the conservation and entropy of the HN protein
DOI: 10.6084/m9.figshare.4956782
title: Words in UHCL Theses and Dissertations

description: This dataset includes only words from thesis and dissertation titles, and is not the full thesis and dissertation dataset with advisors and colleges. To view that, go to https://figshare.com/articles/UHCL_Theses_and_Dissertations/4959161.<br>A dataset including the titles of all graduate projects, theses, and dissertations ever submitted to UHCL was pulled from the library catalog system and read into R. Titles were collapsed into a single vector, and the vector was loaded as a corpus in the tm package. all punctuation was converted to a space, converted to lowercase, and spaces, stopwords, white space, and single characters were removed.<br>Words from titles in all colleges are in the titlewords.csv file. The other four csvs are titles in specific colleges. <br>The Word Cloud was created in Tableau, and is hosted at http://libguides.uhcl.edu/thesesdissertations/titlewordcloud.<br><br>thesisWordCloud.R is the code, and titleWordCloud.pdf is a Markdown document describing the process in a bit more depth.
DOI: 10.6084/m9.figshare.4958687.v1
title: Dataset for Plant diversity and water quality in wetlands: a meta-analysis

description: associated data
DOI: 10.6084/m9.figshare.4956776.v1
title: Mumps HN protein PDB files

description: PDB files for the conservation and entropy of the HN protein