cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14502474.v3
title: Genetic data for Aurelia systematics

description: Sequence sets, alignments and tree files associated with <b>Lawley, J.W., Gamero-Mora, E., Maronna, M.M., Chiaverano, L.M., Stampar, S.N., Hopcroft, R.R., Collins, A.G., Morandini, A.C. 2021. The importance of molecular characters when morphological variability hinders diagnosability: systematics of the moon jellyfish genus <i>Aurelia </i>(Cnidaria: Scyphozoa). PeerJ https://doi.org/10.7717/peerj.11954</b>.<br><b>See below a description of the attached files</b>. When applicable, just replace the word (Marker) for 16S, COI, ITS1 or 28S (for COI files, disregard the "-ip_ia1" that appears in parentheses in filenames). For relevant codes used for molecular analyses based on these files see github.com/lawleyjw/Aurelia.<br>- (Marker)-Aurelia-seqs.fasta - Sequence set used to generate (Marker)-Aurelia(-ip_ia1).fasta. Sequence IDs normally appear as "&gt;(isolate/acession)-(previous species ID)-(sampling locality)".<br>- (Marker)-Aurelia-seqs-UPDATED.fasta - Same sequence set as above, but sequence IDs appear with updated species names as "&gt;(accession)-(updated species ID)|(previous sequence ID, as in (Marker)-Aurelia-seqs.fasta above)".<br>- (Marker)-Aurelia(-ip_ia1).fasta - Alignment used to generate (Marker)-Aurelia.tre. Sequence IDs normally appear as "&gt;(isolate/acession)-(previous species ID)-(sampling locality)".<br>- (Marker)-Aurelia(-ip_ia1)-UPDATED.fasta - Same alignment as above, but sequence IDs appear with updated species names as "&gt;(accession)-(updated species ID)|(previous sequence ID, as in (Marker)-Aurelia(-ip_ia1).fasta above)".<br>- (Marker)-Aurelia.tre - Parsimony tree file in Newick format with branch lengths, derived from (Marker)-Aurelia(-ip_ia1).fasta; for Goodman-Bremer support values and bootstrap resampling frequencies see Fig. S4-S7 in Lawley et al. (2021).<br>- concat-Aurelia.nex - Concatenated sequence matrix in Nexus file (from Sequence Matrix), including sequences of all markers (based on single-marker alignments) for some representative specimens of each species. This file was used to generate concat-Aurelia.tre and concatML-Aurelia.tre. For details on species composition and species ID see Table S5 in Lawley et al. (2021).<br>- concat-Aurelia.tre - Concatenated parsimony tree file in Newick format with branch lengths, derived from concat-Aurelia.nex. For Goodman-Bremer support values and bootstrap resampling frequencies see Fig. 9 in Lawley et al. (2021).<br>- concatML-Aurelia.tre - Concatenated maximum likelihood tree file in Nexus format (from FigTree), derived from concat-Aurelia.nex, including SH-aLRT and ultrafast bootstrap values, respectively (see Fig. S3 in Lawley et al., 2021).
DOI: 10.6084/m9.figshare.14502474.v2
title: Genetic data for Aurelia systematics

description: Alignments and tree files associated with Lawley, J.W., Gamero-Mora, E., Maronna, M.M., Chiaverano, L.M., Stampar, S.N., Hopcroft, R.R., Collins, A.G., Morandini, A.C. 2021. The importance of molecular characters when morphological variability hinders diagnosability: systematics of the moon jellyfish genus <i>Aurelia </i>(Cnidaria: Scyphozoa). PeerJ https://doi.org/10.7717/peerj.11954.
DOI: 10.5281/zenodo.4302650
title: Projeto CCL

description: Test Bank
DOI: 10.5281/zenodo.4302649
title: Projeto CCL

description: Test Bank
DOI: 10.5281/zenodo.5513066
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.5281/zenodo.5513073
title: Supporting Information for "Machine Learning interpretation of the correlation between infrared emission features of interstellar polycyclic aromatic hydrocarbons"

description: This is the supporting information for the article "Machine Learning interpretation of the correlation between infrared emission features of interstellar polycyclic aromatic hydrocarbons". It contains: In Supporting_Information.pdf: 1. A map of the correlation between descriptors. 2. A spectral distribution. 3. An explanation of the file example_code.zip. In example_code.zip: An example code of a machine learning model based on ECFP and corresponding input files.
DOI: 10.5281/zenodo.5513072
title: Supporting Information for "Machine Learning interpretation of the correlation between infrared emission features of interstellar polycyclic aromatic hydrocarbons"

description: This is the supporting information for the article "Machine Learning interpretation of the correlation between infrared emission features of interstellar polycyclic aromatic hydrocarbons". It contains: In Supporting_Information.pdf: 1. A map of the correlation between descriptors. 2. A spectral distribution. 3. An explanation of the file example_code.zip. In example_code.zip: An example code of a machine learning model based on ECFP and corresponding input files.
DOI: 10.6084/m9.figshare.16632781
title: De novo assembly and annotation of the mangrove cricket (Apteronemobius asahinai) genome

description: The mangrove cricket, Apteronemobius asahinai, is an endemic species of mangrove forest floors. This cricket shows a circatidal rhythm in its locomotor activity, with a period of approximately 12.6 h. Little is known about the molecular mechanisms underlying the circatidal rhythm. We presented the draft genome of the mangrove cricket to facilitate future molecular studies. We predicted 28,831 protein-coding genes. We annotated predicted genes via a BLASTP search against the UniProtKB/SwissProt Database and via a search of the Pfam database using InterProScan.<br>
DOI: 10.6084/m9.figshare.14746179.v2
title: Data required for Salix

description: <b>Files of reference genome data used in analysis</b><br>filename: Ssuchowensis.V4.1.zipdescriptions: original data downloaded from ftp://plantgenie.org/Data/PopGenIE/Salix-suchowensis, version 4.1, the reference genome is given as "Ssuchowensis_4.fa" in FASTA format<br><b>Files of alignments and scripts used to produce ontogenetic tree in Figure 4.</b>filename: Figure4 Data.zipdescriptions: <b>Figure_4.alignments.fas</b> - file contains alignments used to construct the ontogenetic tree, fasta format; <b>Figure_4.snv_mut.txt</b> - SNV mutations used to generate the alignments; <b>Figure_4.sample_panel.list</b> - sample list to be shown in the ontogenetic tree; <b>mutation2cns.pl </b> - a custom script to generate the alignments by concatenating the SNV mutations for each sample (use reference allele for non-mutated samples), usage: "perl mutation2cns.pl --input Figure_4.snv_mut.txt -s Figure_4.sample_panel.list &gt; Figure_4.alignments.fas"; <b>MyPerl</b> - custom PERL module accompany "mutation2cns.pl", need to be placed in the same folder with script or in the default PERL library path<br><b>Regional BAM files contain mapped reads of 17 BR-m mutation sites</b>filename: BAM.zipdescriptions: The 55 regional BAM files were extracted from original BAM files to only include mapping results covering the 17 BR-M mutation sites (including 10kb flanking regions). Each file was generated using codes below (the "target-region.bed" is in the format: "chrom mut_pos-10001 mut_position+10000") samtools view BAMFILE -b -L <b>target-region.bed</b> &gt;OUTPUT samtools index BAMFILE<br><b>IGV snapshots of all 17 BR-m mutations</b>filename: IGV snapshot.zipdescriptions: Screen snapshot of 17 BR-m mutation sites (+/- 55bp) from IGV (version 2.3.90, https://software.broadinstitute.org/software/igv/), in png format. All 55 samples for each mutation are shown in a single figure, with each panel presents mapping results of one sample.<br><b>Other related files</b><br><b>Corresponded_sample_IDs.xlsx</b> - Excel file contains the corresponded sample id used in the BAM file (a short sample ID with only cutting ID) and in the paper (a full sample ID with both branch ID and cutting ID)<br><b>BR-m_mutations.Sample_readcounts.xlsx</b> - Excel file contains the detailed readcounts (number of reads for reference [i.e., ancestral ] allele and for mutation allele) of 17 BR-m mutations across 54 samples (except one poorly sequenced root sample)<br><b>Figure S4.BR-m.PCR.pptx</b>Powerpoint version for Figure S4 in paper, preview in figshare will cause partial dislocation, so we recommend to download for watching<b>Figure S5.BR-m.PCR_clone.pptx</b><br>Powerpoint version for Figure S5 in paper, preview in figshare will cause partial dislocation, so we recommend to download for watching<b><br></b>
DOI: 10.6084/m9.figshare.13369595.v1
title: tRNA annotation bed file

description: compiled from GtRNAdb 2.0 hg19 version <br>http://gtrnadb.ucsc.edu/genomes/eukaryota/Hsapi19/hg19-tRNAs.tar.gz <br>
DOI: 10.5281/zenodo.5348484
title: Spatial Distribution and Habitat Usage of <i>Coryphopterus personatus</i> and <i>C. hyalinus</i> in Turneffe Atoll, Belize

description: Data used to develop 3D models of coral reefs using structure-from-motion photogrammetry. The data used to generate photogrammetry models are pictures of the reef from ~1 m above the substratum and coordinates of ground control points for each of twelve distinct ~20 m x 10 m reef areas. The photogrammetry workflow to create the digital models included photo alignment, followed by geometry building, and lastly texture building using Agisoft Pro. Additionally included are the orthomosaics and digital elevation models derived from the 3D models and training data used to build a classification algorithm to classify reef vs sand benthic types using the site orthomosaics. Finally, the location and sizes of mixed shoals of <em>Coryphopterus personatus</em> and <em>Coryphopterus hyalinus</em> are included. All data were collected from Turneffe Atoll (17.3638° N, 87.8581° W), Belize in January 2017. These data are used in conjunction to develop a habitat usage model to understand what features of coral reefs are correlated with the distribution of <em>C. personatus</em>/<em>hyalinus. </em>All code associated with the analysis can be found here: https://github.com/jdselwyn/Habitat_Usage.
DOI: 10.5281/zenodo.5348483
title: Spatial Distribution and Habitat Usage of <i>Coryphopterus personatus</i> and <i>C. hyalinus</i> in Turneffe Atoll, Belize

description: Data used to develop 3D models of coral reefs using structure-from-motion photogrammetry. The data used to generate photogrammetry models are pictures of the reef from ~1 m above the substratum and coordinates of ground control points for each of twelve distinct ~20 m x 10 m reef areas. The photogrammetry workflow to create the digital models included photo alignment, followed by geometry building, and lastly texture building using Agisoft Pro. Additionally included are the orthomosaics and digital elevation models derived from the 3D models and training data used to build a classification algorithm to classify reef vs sand benthic types using the site orthomosaics. Finally, the location and sizes of mixed shoals of <em>Coryphopterus personatus</em> and <em>Coryphopterus hyalinus</em> are included. All data were collected from Turneffe Atoll (17.3638° N, 87.8581° W), Belize in January 2017. These data are used in conjunction to develop a habitat usage model to understand what features of coral reefs are correlated with the distribution of <em>C. personatus</em>/<em>hyalinus. </em>All code associated with the analysis can be found here: https://github.com/jdselwyn/Habitat_Usage.
DOI: 10.14457/cu.the.1975.3
title: แนวโน้มการเลือกวิชาเอกและวิชาโทของนักเรียนครู
DOI: 10.14457/cu.the.1980.13
title: ความสัมพันธ์ระหว่างลายมือกับท่าจับดินสอของเด็ก
DOI: 10.14457/cu.the.1978.8
title: ความสัมพันธ์ระหว่างองค์ประกอบทางสังคมกับสัมฤทธิผลของนักเรียนชั้นประถมศึกษาปีที่ 7 อำเภอธัญบุรี จังหวัดปทุมธานี
DOI: 10.14457/cu.the.1984.32
title: ความต้องการกำลังคนในธุรกิจพาณิชย์นาวีไทย
DOI: 10.6084/m9.figshare.14746179.v3
title: Data required for Salix

description: <b>Files of reference genome data used in analysis</b><br>filename: Ssuchowensis.V4.1.zipdescriptions: original data downloaded from ftp://plantgenie.org/Data/PopGenIE/Salix-suchowensis, version 4.1, the reference genome is given as "Ssuchowensis_4.fa" in FASTA format<br><b>Files of alignments and scripts used to produce ontogenetic tree in Figure 4.</b>filename: Figure4 Data.zipdescriptions: <b>Figure_4.alignments.fas</b> - file contains alignments used to construct the ontogenetic tree, fasta format; <b>Figure_4.snv_mut.txt</b> - SNV mutations used to generate the alignments; <b>Figure_4.sample_panel.list</b> - sample list to be shown in the ontogenetic tree; <b>mutation2cns.pl </b> - a custom script to generate the alignments by concatenating the SNV mutations for each sample (use reference allele for non-mutated samples), usage: "perl mutation2cns.pl --input Figure_4.snv_mut.txt -s Figure_4.sample_panel.list &gt; Figure_4.alignments.fas"; <b>MyPerl</b> - custom PERL module accompany "mutation2cns.pl", need to be placed in the same folder with script or in the default PERL library path<br><b>Regional BAM files contain mapped reads of 17 BR-m mutation sites</b>filename: BAM.zipdescriptions: The 55 regional BAM files were extracted from original BAM files to only include mapping results covering the 17 BR-M mutation sites (including 10kb flanking regions). Each file was generated using codes below (the "target-region.bed" is in the format: "chrom mut_pos-10001 mut_position+10000") samtools view BAMFILE -b -L <b>target-region.bed</b> &gt;OUTPUT samtools index BAMFILE<br><b>IGV snapshots of all 17 BR-m mutations</b>filename: IGV snapshot.zipdescriptions: Screen snapshot of 17 BR-m mutation sites (+/- 55bp) from IGV (version 2.3.90, https://software.broadinstitute.org/software/igv/), in png format. All 55 samples for each mutation are shown in a single figure, with each panel presents mapping results of one sample.<br><b>Sanger sequencing data for BR-m mutation sites' verification</b><b><br></b><b>#Monoclone</b>Sanger sequencing data of monoclonal PCR product for 8 BR-m mutations sites in ab1 type.<br><br><b>#PCR</b>Sanger sequencing data of 12 BR-m mutations sites in ab1 type.<br><b>Other related files</b><br><b>Corresponded_sample_IDs.xlsx</b> - Excel file contains the corresponded sample id used in the BAM file (a short sample ID with only cutting ID) and in the paper (a full sample ID with both branch ID and cutting ID)<br><b>BR-m_mutations.Sample_readcounts.xlsx</b> - Excel file contains the detailed readcounts (number of reads for reference [i.e., ancestral ] allele and for mutation allele) of 17 BR-m mutations across 54 samples (except one poorly sequenced root sample)<br><b>Figure S4.BR-m.PCR.pptx</b>Powerpoint version for Figure S4 in paper, preview in figshare will cause partial dislocation, so we recommend to download for watching<b>Figure S5.BR-m.PCR_clone.pptx</b><br>Powerpoint version for Figure S5 in paper, preview in figshare will cause partial dislocation, so we recommend to download for watching
DOI: 10.15473/1818911
title: Reference Model 1 Scaled Geometry (RM1: Tidal Current Turbine)

description: Contains the Reference Model 1 (RM1) scaled scale geometry files of the Tidal Current Turbine, developed by the Reference Model Project (RMP). These scaled geometry files are saved as SolidWorks assembly, IGS, and STEP files, and require a CAD program to view. The scaled RM1 device was tested at the Saint Anthony Falls Laboratory (SAFL) at the University of Minnesota flume, details of which are described in the included journal article. The scale of the geometries included in this submission are at a 1:40 scale compared to the full scale geometry. This data was generated upon completion of the project on September 30, 2014. The Reference Model Project (RMP), sponsored by the U.S. Department of Energy (DOE), was a partnered effort to develop open-source MHK point designs as reference models (RMs) to benchmark MHK technology performance and costs, and an open-source methodology for design and analysis of MHK technologies, including models for estimating their capital costs, operational costs, and levelized costs of energy. The point designs also served as open-source test articles for university researchers and commercial technology developers. The RMP project team, led by Sandia National Laboratories (SNL), included a partnership between DOE, three national laboratories, including the National Renewable Energy Laboratory (NREL), Pacific Northwest National Laboratory (PNNL), and Oak Ridge National Laboratory (ORNL), the Applied Research Laboratory of Penn State University, and Re Vision Consulting. Reference Model 1 (RM1) is a dual variable-speed variable-pitch (VSVP) axial-flow tidal turbine device, designed for the Tacoma Narrows tidal current energy resource site in Puget Sound, Washington. RM1 comprises a monopile foundation and a crossarm assembly to mount the two rotors. The cross-arm assembly is nearly neutrally buoyant so the attached rotors can be recovered and redeployed with a minimal amount of lifting crane capacity; therefore, the design minimizes the handling requirements during deployment and recovery, which reduces overall cost in all O&M activities including access to the power conversion chain (PCC).
DOI: 10.15473/1818912
title: Reference Model 2 Scaled Geometry (RM2: River Current Turbine)

description: Contains the Reference Model 2 (RM2) scaled scale geometry files of the River Current Turbine, developed by the Reference Model Project (RMP). These scaled geometry files are saved as SolidWorks assembly, IGS, and STEP files, and require a CAD program to view. The scaled RM2 device was tested at the Saint Anthony Falls Laboratory (SAFL) at the University of Minnesota flume. The scale of the geometries included in this submission are at a 1:15 scale compared to the full scale geometry. This data was generated upon completion of the project on September 30, 2014. The Reference Model Project (RMP), sponsored by the U.S. Department of Energy (DOE), was a partnered effort to develop open-source MHK point designs as reference models (RMs) to benchmark MHK technology performance and costs, and an open-source methodology for design and analysis of MHK technologies, including models for estimating their capital costs, operational costs, and levelized costs of energy. The point designs also served as open-source test articles for university researchers and commercial technology developers. The RMP project team, led by Sandia National Laboratories (SNL), included a partnership between DOE, three national laboratories, including the National Renewable Energy Laboratory (NREL), Pacific Northwest National Laboratory (PNNL), and Oak Ridge National Laboratory (ORNL), the Applied Research Laboratory of Penn State University, and Re Vision Consulting. Reference Model 2 (RM2) is a variable speed dual-rotor cross-flow river turbine that is deployed at the water?s surface. It was designed for deployment at a reference site modeled after a reach in the Mississippi River near Baton Rouge, Louisiana. The rotors are anchored to a two-pontoon vessel platform. Surface deployment of the turbine minimizes the handling requirements during deployment and recovery and reduces overall costs for all O&M activities, including allowing for easy access to the power conversion chain (PCC). The design (two rotors per platform) also reduces the environmental footprint and associated environmental compliance costs.
DOI: 10.6084/m9.figshare.14746179
title: Data required for Salix

description: <b>Files of reference genome data used in analysis</b><br>filename: Ssuchowensis.V4.1.zipdescriptions: original data downloaded from ftp://plantgenie.org/Data/PopGenIE/Salix-suchowensis, version 4.1, the reference genome is given as "Ssuchowensis_4.fa" in FASTA format<br><b>Files of alignments and scripts used to produce ontogenetic tree in Figure 4.</b>filename: Figure4 Data.zipdescriptions: <b>Figure_4.alignments.fas</b> - file contains alignments used to construct the ontogenetic tree, fasta format; <b>Figure_4.snv_mut.txt</b> - SNV mutations used to generate the alignments; <b>Figure_4.sample_panel.list</b> - sample list to be shown in the ontogenetic tree; <b>mutation2cns.pl </b> - a custom script to generate the alignments by concatenating the SNV mutations for each sample (use reference allele for non-mutated samples), usage: "perl mutation2cns.pl --input Figure_4.snv_mut.txt -s Figure_4.sample_panel.list &gt; Figure_4.alignments.fas"; <b>MyPerl</b> - custom PERL module accompany "mutation2cns.pl", need to be placed in the same folder with script or in the default PERL library path<br><b>Regional BAM files contain mapped reads of 17 BR-m mutation sites</b>filename: BAM.zipdescriptions: The 55 regional BAM files were extracted from original BAM files to only include mapping results covering the 17 BR-M mutation sites (including 10kb flanking regions). Each file was generated using codes below (the "target-region.bed" is in the format: "chrom mut_pos-10001 mut_position+10000") samtools view BAMFILE -b -L <b>target-region.bed</b> &gt;OUTPUT samtools index BAMFILE<br><b>IGV snapshots of all 17 BR-m mutations</b>filename: IGV snapshot.zipdescriptions: Screen snapshot of 17 BR-m mutation sites (+/- 55bp) from IGV (version 2.3.90, https://software.broadinstitute.org/software/igv/), in png format. All 55 samples for each mutation are shown in a single figure, with each panel presents mapping results of one sample.<br><b>Sanger sequencing data for BR-m mutation sites' verification</b><b><br></b><b>#Monoclone</b>Sanger sequencing data of monoclonal PCR product for 8 BR-m mutations sites in ab1 type.<br><br><b>#PCR</b>Sanger sequencing data of 12 BR-m mutations sites in ab1 type.<br><b>Other related files</b><br><b>Corresponded_sample_IDs.xlsx</b> - Excel file contains the corresponded sample id used in the BAM file (a short sample ID with only cutting ID) and in the paper (a full sample ID with both branch ID and cutting ID)<br><b>BR-m_mutations.Sample_readcounts.xlsx</b> - Excel file contains the detailed readcounts (number of reads for reference [i.e., ancestral ] allele and for mutation allele) of 17 BR-m mutations across 54 samples (except one poorly sequenced root sample)<br><b>Figure S4.BR-m.PCR.pdf</b>Fig. S4 Sanger chromatogram traces of assessed BR-m mutations.<b>Figure S5.BR-m.PCR_clone.pdf</b><br>Fig. S5 Sanger sequencing results of monoclonal PCR products for BR-m mutations.<br>