cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.a9ugcr
title: Occurrence Download

description: A dataset containing 207 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-70.63619 -33.35689,-70.42023 -33.35689,-70.42023 -33.23204,-70.63619 -33.23204,-70.63619 -33.35689))",
 "TaxonKey is Buteo polyosoma (Quoy & Gaimard, 1824)"
 ]
}

 The dataset includes 207 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021248-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.24578746
title: CI/CD repositories from GitHub

description: Dataset containing CI/CD repositories
DOI: 10.6084/m9.figshare.24578752
title: CI/CD repositories with tool history

description: CI/CD repositories from GitHub with tool history
DOI: 10.5281/zenodo.10145090
title: Detecting Usage Protocol Violations in Deep Learning Applications

description: This repo contains a replication package of the "Detecting Usage Protocol Violations in Deep Learning Applications" paper.
In the paper, we use two benchmarks:  

The first benchmark we used from NeuraLint can be found under the director name Benchmark1/SOSamples
The second benchmark we used from Humbatova et al. can be found under the director name Benchmark2/SOSamples
To reproduce the results in the paper:  

Download the NeuralStateAnalysis Zip file.
Extract the file and go to the NeuralStateAnlaysis directory.
( Optional ) Install the requirements by running 'Pip install requirements.txt.' N.B: The requirements.txt file is already in this repo.

To run NeuralState on Benchmark1:

Go to Benchmark1/SOSamples directory,
Open any of the programs you want to run,
Set the path: Path-to-folder/NeuralStateAnalysis/
Then, do 'python program_id.' Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you'll be able to reproduce results.
To run NeuralState on Benchmark2:

Go to Benchmark2/SOSamples directory,
Open any of the programs you want to run,
Set the path: Path-to-folder/NeuralStateAnalysis/
Then, do 'python program_id.' Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you'll be able to reproduce results.
DOI: 10.5281/zenodo.10145089
title: Detecting Usage Protocol Violations in Deep Learning Applications

description: This repo contains a replication package of the "Detecting Usage Protocol Violations in Deep Learning Applications" paper.
In the paper, we use two benchmarks:  

The first benchmark we used from NeuraLint can be found under the director name Benchmark1/SOSamples
The second benchmark we used from Humbatova et al. can be found under the director name Benchmark2/SOSamples
To reproduce the results in the paper:  

Download the NeuralStateAnalysis Zip file.
Extract the file and go to the NeuralStateAnlaysis directory.
( Optional ) Install the requirements by running 'Pip install requirements.txt.' N.B: The requirements.txt file is already in this repo.

To run NeuralState on Benchmark1:

Go to Benchmark1/SOSamples directory,
Open any of the programs you want to run,
Set the path: Path-to-folder/NeuralStateAnalysis/
Then, do 'python program_id.' Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you'll be able to reproduce results.
To run NeuralState on Benchmark2:

Go to Benchmark2/SOSamples directory,
Open any of the programs you want to run,
Set the path: Path-to-folder/NeuralStateAnalysis/
Then, do 'python program_id.' Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you'll be able to reproduce results.
DOI: 10.6084/m9.figshare.23929551.v2
title: Supplementary Data for Kogay and Zhaxybayeva (2023)

description: <b>GTA head-tail cluster genes:</b><b>GTA_aln.zip: </b>Multiple sequence alignments of 14 GTA head-tail cluster genes selected to represent 293 OTUs. The alignments are in FASTA format.<b>GTA_uncstr_trees.zip: </b>Phylogenetic trees of 14 GTA head-tail cluster genes reconstructed under unconstrained topological search. The trees are in Newick format.<b>GTA_cstr_trees.zip: </b>Phylogenetic trees of 11 reference GTA genes, whose topology was constrained to match the reference phylogenomic tree. The trees are in Newick format.<b>Reference phylogenomic dataset:</b><b>reference_tree.zip: </b>Concatenated alignment of 84 phylogenetic marker genes found in 293 alphaproteobacterial genomes, in FASTA format (reference_tree_alignment.fasta). Reference phylogenomic tree reconstructed from the alignment, in Newick format (reference_tree_rooted.treefile).<b>1,470 alphaproteobacterial gene families:</b><b>OG_seq.zip: </b>Amino acid sequences of 1,470 gene families that are found in at least 50% of analyzed alphaproteobacterial genomes. The sequences are in FASTA format.<br><br><b>OG_cstr_trees.zip: </b>Phylogenetic trees of 1,470 gene families, whose topology was constrained to match the reference phylogenomic tree. The trees are in Newick format.<b>Evolutionary Rate Covariation analyses:</b><b>ERC_results_all.txt.zip: </b>Covariation of evolutionary rates for all pairwise gene comparisons of 11 reference GTA genes and 1,470 gene families.<b>Networks for </b><b><i>Phaeobacter inhibens</i></b><b>, </b><b><i>Caulobacter crescentus</i></b><b> and </b><b><i>Dinoroseobacter shibae</i></b><b>:</b><b>networks.zip: </b>co-evolutionary networks and their subnetworks of nodes with unambiguous GOG assignment, protein-protein interaction networks, fitness networks, and assignments of COG functional categories to nodes. Networks are in the “edge list” format.
DOI: 10.6084/m9.figshare.23929551
title: Supplementary Data for Kogay and Zhaxybayeva (2023)

description: <b>GTA head-tail cluster genes:</b><b>GTA_aln.zip: </b>Multiple sequence alignments of 14 GTA head-tail cluster genes selected to represent 293 OTUs. The alignments are in FASTA format.<b>GTA_uncstr_trees.zip: </b>Phylogenetic trees of 14 GTA head-tail cluster genes reconstructed under unconstrained topological search. The trees are in Newick format.<b>GTA_cstr_trees.zip: </b>Phylogenetic trees of 11 reference GTA genes, whose topology was constrained to match the reference phylogenomic tree. The trees are in Newick format.<b>Reference phylogenomic dataset:</b><b>reference_tree.zip: </b>Concatenated alignment of 84 phylogenetic marker genes found in 293 alphaproteobacterial genomes, in FASTA format (reference_tree_alignment.fasta). Reference phylogenomic tree reconstructed from the alignment, in Newick format (reference_tree_rooted.treefile).<b>1,470 alphaproteobacterial gene families:</b><b>OG_seq.zip: </b>Amino acid sequences of 1,470 gene families that are found in at least 50% of analyzed alphaproteobacterial genomes. The sequences are in FASTA format.<br><br><b>OG_cstr_trees.zip: </b>Phylogenetic trees of 1,470 gene families, whose topology was constrained to match the reference phylogenomic tree. The trees are in Newick format.<b>Evolutionary Rate Covariation analyses:</b><b>ERC_results_all.txt.zip: </b>Covariation of evolutionary rates for all pairwise gene comparisons of 11 reference GTA genes and 1,470 gene families.<b>Networks for </b><b><i>Phaeobacter inhibens</i></b><b>, </b><b><i>Caulobacter crescentus</i></b><b> and </b><b><i>Dinoroseobacter shibae</i></b><b>:</b><b>networks.zip: </b>co-evolutionary networks and their subnetworks of nodes with unambiguous GOG assignment, protein-protein interaction networks, fitness networks, and assignments of COG functional categories to nodes. Networks are in the “edge list” format.
DOI: 10.6084/m9.figshare.23929551.v1
title: Supplementary Data for Kogay and Zhaxybayeva (2023)

description: <b>GTA head-tail cluster genes:</b><b>GTA_aln.zip: </b>Multiple sequence alignments of 14 GTA head-tail cluster genes selected to represent 293 OTUs. The alignments are in FASTA format.<b>GTA_uncstr_trees.zip: </b>Phylogenetic trees of 14 GTA head-tail cluster genes reconstructed under unconstrained topological search. The trees are in Newick format.<b>GTA_cstr_trees.zip: </b>Phylogenetic trees of 11 reference GTA genes, whose topology was constrained to match the reference phylogenomic tree. The trees are in Newick format.<b>Reference phylogenomic dataset:</b><b>reference_tree.zip: </b>Concatenated alignment of 84 phylogenetic marker genes found in 293 alphaproteobacterial genomes, in FASTA format (reference_tree_alignment.fasta). Reference phylogenomic tree reconstructed from the alignment, in Newick format (reference_tree_rooted.treefile).<b>1,470 alphaproteobacterial gene families:</b><b>OG_seq.zip: </b>Amino acid sequences of 1,470 gene families that are found in at least 50% of analyzed alphaproteobacterial genomes. The sequences are in FASTA format.<br><br><b>OG_cstr_trees.zip: </b>Phylogenetic trees of 1,470 gene families, whose topology was constrained to match the reference phylogenomic tree. The trees are in Newick format.<b>Evolutionary Rate Covariation analyses:</b><b>ERC_results_all.txt.zip: </b>Covariation of evolutionary rates for all pairwise gene comparisons of 11 reference GTA genes and 1,470 gene families.<i><b>Phaeobacter inhibens</b></i><b>’ networks:</b><b>networks.zip: </b>co-evolutionary network and its subnetwork of nodes with unambiguous GOG assignment, protein-protein interaction network, fitness network, and assignments of COG functional categories to nodes. Networks are in the “edge list” format.
DOI: 10.5517/ccdc.csd.cc27qpxl
title: CCDC 2077400: Experimental Crystal Structure Determination

description: Related Article: Meng Wang, Lin Wang, Haoyuan Wu, Jing Sun, Xiaoxuan Xu, Shuo Guo, Yanyuan Jia, Simin Li, Zong-Jie Guan, Hui Shen|2023|Nanoscale|15|17818|doi:10.1039/D3NR02196C
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.cc2g3qlx
title: CCDC 2267699: Experimental Crystal Structure Determination

description: Related Article: Masatoshi Kawahata, Haruka Yamamoto, Masahide Tominaga, Kentaro Yamaguchi|2023|CrystEngComm|25|6137|doi:10.1039/D3CE00775H
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.cc2g3qmy
title: CCDC 2267700: Experimental Crystal Structure Determination

description: Related Article: Masatoshi Kawahata, Haruka Yamamoto, Masahide Tominaga, Kentaro Yamaguchi|2023|CrystEngComm|25|6137|doi:10.1039/D3CE00775H
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.cc2g3qnz
title: CCDC 2267701: Experimental Crystal Structure Determination

description: Related Article: Masatoshi Kawahata, Haruka Yamamoto, Masahide Tominaga, Kentaro Yamaguchi|2023|CrystEngComm|25|6137|doi:10.1039/D3CE00775H
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.cc2g3qp0
title: CCDC 2267702: Experimental Crystal Structure Determination

description: Related Article: Masatoshi Kawahata, Haruka Yamamoto, Masahide Tominaga, Kentaro Yamaguchi|2023|CrystEngComm|25|6137|doi:10.1039/D3CE00775H
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.cc2g3qq1
title: CCDC 2267703: Experimental Crystal Structure Determination

description: Related Article: Masatoshi Kawahata, Haruka Yamamoto, Masahide Tominaga, Kentaro Yamaguchi|2023|CrystEngComm|25|6137|doi:10.1039/D3CE00775H
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.cc2g3qr2
title: CCDC 2267704: Experimental Crystal Structure Determination

description: Related Article: Masatoshi Kawahata, Haruka Yamamoto, Masahide Tominaga, Kentaro Yamaguchi|2023|CrystEngComm|25|6137|doi:10.1039/D3CE00775H
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.cc2g5ss7
title: CCDC 2269689: Experimental Crystal Structure Determination

description: Related Article: Sven M. Papidocha, Hendrik H. Bulthaupt, Erick M. Carreira|2023|Angew.Chem.,Int.Ed.|62|e202310149|doi:10.1002/anie.202310149
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10145293
title: RPM2

description: RepeatModeler2 results
DOI: 10.5281/zenodo.10145294
title: RPM2

description: RepeatModeler2 results
DOI: 10.6084/m9.figshare.24578782
title: Psychotherapy Dropout Among Service Members and Veterans: A Systematic Review and Meta-analysis (Dataset)

description: This meta-analysis evaluated dropout among service members and veterans who intitiated outpatient therapy.
DOI: 10.25573/data.24319078
title: Skimming genomes for systematics and DNA barcodes of corals

description: 1: Numerous genomic methods developed over the past two decades have enabled the discovery and extraction of orthologous loci to help resolve phylogenetic relationships across various taxa and scales. Genome skimming (or low-coverage whole genome sequencing) remains a low-cost, promising method to not only extract high-copy loci, but also 100s to 1000s of phylogenetically informative single-copy nuclear loci (e.g., ultraconserved elements [UCEs] and exons) from contemporary and historical museum samples. The subphylum Anthozoa, which includes important ecosystem engineers (e.g., stony corals, black corals, anemones and octocorals) in the marine environment, is in critical need of phylogenetic resolution and thus might benefit from a genome-skimming approach. 2: Genome skimming was conducted on 242 hexacorals and octocorals collected from 1890 to 2022. Using previously developed target-capture baitsets, we bioinformatically obtained UCEs and exons from the genome-skimming data and incorporated them with data from previously published target-capture studies. We also extracted partial to whole mitogenomes and nuclear rRNA genes from the skim data.3: The mean number of UCE and exon loci extracted from the genome skimming data was 1,837 ± 662 SD for octocorals and 1,422 ± 720 loci for hexacorals; phylogenetic relationships were well resolved within each class. A mean of 1,422 ± 720 loci were obtained from the historical museum specimens, with 1,253 loci recovered from the oldest specimen collected in 1886 and 1,336 loci recovered from a holotype. The nuclear rRNA genes and the majority of mitochondrial genes were successfully obtained from &gt;95% of samples. Out of 99 circularized mitogenomes, 88% were recovered in samples from which we obtained &gt;15M paired-end (PE) reads (&gt;30M total reads); there was more variability in whether mitogenomes were circularized or not in samples with &lt;15M PE reads. 4: Bioinformatically pulling UCEs, exons, mitochondrial genomes, and nuclear rRNA genes from genome skimming is a viable and low-cost option for phylogenetic studies. This approach can be used to review and support taxonomic revisions and reconstruct evolutionary histories, including historical museum and type specimens.
DOI: 10.25573/data.24319078.v1
title: Skimming genomes for systematics and DNA barcodes of corals

description: 1: Numerous genomic methods developed over the past two decades have enabled the discovery and extraction of orthologous loci to help resolve phylogenetic relationships across various taxa and scales. Genome skimming (or low-coverage whole genome sequencing) remains a low-cost, promising method to not only extract high-copy loci, but also 100s to 1000s of phylogenetically informative single-copy nuclear loci (e.g., ultraconserved elements [UCEs] and exons) from contemporary and historical museum samples. The subphylum Anthozoa, which includes important ecosystem engineers (e.g., stony corals, black corals, anemones and octocorals) in the marine environment, is in critical need of phylogenetic resolution and thus might benefit from a genome-skimming approach. 2: Genome skimming was conducted on 242 hexacorals and octocorals collected from 1890 to 2022. Using previously developed target-capture baitsets, we bioinformatically obtained UCEs and exons from the genome-skimming data and incorporated them with data from previously published target-capture studies. We also extracted partial to whole mitogenomes and nuclear rRNA genes from the skim data.3: The mean number of UCE and exon loci extracted from the genome skimming data was 1,837 ± 662 SD for octocorals and 1,422 ± 720 loci for hexacorals; phylogenetic relationships were well resolved within each class. A mean of 1,422 ± 720 loci were obtained from the historical museum specimens, with 1,253 loci recovered from the oldest specimen collected in 1886 and 1,336 loci recovered from a holotype. The nuclear rRNA genes and the majority of mitochondrial genes were successfully obtained from &gt;95% of samples. Out of 99 circularized mitogenomes, 88% were recovered in samples from which we obtained &gt;15M paired-end (PE) reads (&gt;30M total reads); there was more variability in whether mitogenomes were circularized or not in samples with &lt;15M PE reads. 4: Bioinformatically pulling UCEs, exons, mitochondrial genomes, and nuclear rRNA genes from genome skimming is a viable and low-cost option for phylogenetic studies. This approach can be used to review and support taxonomic revisions and reconstruct evolutionary histories, including historical museum and type specimens.
DOI: 10.17909/2w3j-gp03
title: MIRI data of WASP-39

description: Transmission spectroscopy data for WASP-39b taken with JWST/MIRI-LRS (slitless).
DOI: 10.13012/d4gy-4g41
title: The HathiTrust Research Center BookNLP Dataset for English-Language Fiction
DOI: 10.5281/zenodo.10145288
title: Dataset for "Mitigating stimulated Brillouin scattering in multimode fibers with focused output via wavefront shaping"

description: Experimental and numerical data associated with "Mitigating stimulated Brillouin scattering in multimode fibers with focused output via wavefront shaping"
DOI: 10.5281/zenodo.8350623
title: Dataset for "Mitigating stimulated Brillouin scattering in multimode fibers with focused output via wavefront shaping"

description: Experimental and numerical data associated with "Mitigating stimulated Brillouin scattering in multimode fibers with focused output via wavefront shaping"
DOI: 10.5281/zenodo.8350624
title: Dataset for "Mitigating stimulated Brillouin scattering in multimode fibers with focused output via wavefront shaping"

description: Experimental and numerical data associated with "Mitigating stimulated Brillouin scattering in multimode fibers with focused output via wavefront shaping"
DOI: 10.5281/zenodo.10142450
title: single-molecule chirality data

description: single-molecule electrical data for chirality discrimination
all the data are zip file.
mono amino acid: Ala.zip, Arg.zip, Asn.zip, Asp.zip, Cys.zip, Gln.zip, Glu.zip, His.zip, Ile.zip, Leu.zip, Lys.zip, Met.zip, Phe.zip, Pro.zip, Ser.zip, Thr.zip, Trp.zip, Tyr.zip, Val.zip
mixed four kinds of amino acid data#1: D_Y_L_SHF.zip
mixed four kinds of solution#2: L_F_D_LPY.zip
video data: Single Molecule Electrical Measurement by MCBJ.zip
DOI: 10.5281/zenodo.7042282
title: single-molecule chirality data

description: single-molecule electrical data for chirality discrimination
all the data are zip file.
mono amino acid: Ala.zip, Arg.zip, Asn.zip, Asp.zip, Cys.zip, Gln.zip, Glu.zip, His.zip, Ile.zip, Leu.zip, Lys.zip, Met.zip, Phe.zip, Pro.zip, Ser.zip, Thr.zip, Trp.zip, Tyr.zip, Val.zip
mixed four kinds of amino acid data#1: D_Y_L_SHF.zip
mixed four kinds of solution#2: L_F_D_LPY.zip
video data: Single Molecule Electrical Measurement by MCBJ.zip
DOI: 10.5281/zenodo.7042283
title: single-molecule chirality data

description: single-molecule electrical data for chirality discrimination all the data are zip file. mixed solution data#1: D_Y_L_SHF mixed solution#2: L_F_D_LPY
DOI: 10.5281/zenodo.10140825
title: Pre-Processed Data Sets for Marine Spatial Planning of a Wave-Powered Aquaculture Farm in the Northeast U.S.

description: These data sets are intended for marine spatial planning applications including the modeling of wave-powered aquaculture farms. They work in tandem with the Python model developed by the SEA Lab to evaluate potential sites for this development in the Northeastern U.S. The code for this model is available on GitHub at https://github.com/symbiotic-engineering/aquaculture, and details about the data and model are discussed in several related publications.
DOI: 10.5281/zenodo.10140826
title: Pre-Processed Data Sets for Marine Spatial Planning of a Wave-Powered Aquaculture Farm in the Northeast U.S.

description: These data sets are intended for marine spatial planning applications including the modeling of wave-powered aquaculture farms. They work in tandem with the Python model developed by the SEA Lab to evaluate potential sites for this development in the Northeastern U.S. The code for this model is available on GitHub at https://github.com/symbiotic-engineering/aquaculture, and details about the data and model are discussed in several related publications.
DOI: 10.34740/kaggle/ds/4014009
title: RUL Dataset from Continuous Casting Machine
DOI: 10.5281/zenodo.10138990
title: Supplementary data
DOI: 10.5281/zenodo.10145348
title: Supplementary data
DOI: 10.18434/mds2-3073
title: Data for "Quadrature-Based Compressive Sensing Guarantees for Bounded Orthonormal Systems", to be submitted to IEEE Signal Processing Letters
DOI: 10.6084/m9.figshare.24555883
title: Smith-Vidaurre_et_al_2023_ABISSMALMethodsPaper

description: We make data available for a manuscript associated with the development of an automated behavioral tracking system: ABISSMAL (Automated Behavioral tracking by Integrating Sensors that Survey Movements Around a target Location). More information about these datasets is available in the README files.