cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26033/rsg7-4f63
title: Visual Imaging and Photometry of (29981) 1999 TD10 Bundle V1.0

description: The outer solar system object (29981) 1999 TD10 was observed in the R band in September 2001, and in B, V, R, and I in October 2002. We derive B-V=0.80+/-0.05mag, V-R=0.48+/-0.05mag, and R-I=0.44+/-0.05mag. Combining our data with the data from Rousselot et. al. 2003, we derive a synodic period of 15.382+/-0.001hr in agreement with the period from Rousselot et. al. 2003. Our observations show no evidence of a coma.
DOI: 10.15482/usda.adc/1529200
title: Data from: Genomic analysis of a malate decarboxylation deficient lactic acid bacterium, Lactiplantibacillus pentosus MU045

description: This is a Microsoft Excel spreadsheet containing raw absorbance data collected from PM01 and PM02A plates in an Omnilog system for Lactiplantibacillus pentosus LA0445 and MU045. Independent duplicates were run for each bacterial culture.
Resources in this dataset:

Resource Title: Omnilog Phenotype Microarray Data for Lactiplantibacillus pentosus LA0445 and MU045
File Name: Omnilog Data for L pentosus LA0445 and MU045.xlsx
DOI: 10.26033/4he8-ck07
title: Visual Imaging and Photometry of (29981) 1999 TD10 Bundle V2.0

description: The outer solar system object (29981) 1999 TD10 was observed in the R band in September 2001, and in B, V, R, and I in October 2002. We derive B-V=0.80+/-0.05mag, V-R=0.48+/-0.05mag, and R-I=0.44+/-0.05mag. Combining our data with the data from Rousselot et. al. 2003, we derive a synodic period of 15.382+/-0.001hr in agreement with the period from Rousselot et. al. 2003. Our observations show no evidence of a coma.
DOI: 10.5281/zenodo.8148653
title: opuntiella_californica_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8148652
title: opuntiella_californica_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23689134.v1
title: <strong>Supplementary file 1</strong>

description: RNA-Sequencing of isolated mouse lung fibroblasts following bleomycin administration or pneumonectomy
DOI: 10.13026/9m3f-ac20
title: Electroencephalogram and eye-gaze datasets for robot-assisted surgery performance evaluation

description: Surgical training and patient safety depend on objective and accurate
performance evaluation. Robot-assisted surgery (RAS) is newer and its training
less well defined, but resources are not easily accessed to support data
collection from participants with various RAS skill levels. This work
describes and makes available for public use electroencephalogram (EEG) and
eye-gaze data collected from 25 participants performing RAS simulator tasks
with varying levels of RAS experience.Twenty-seven tasks from six modules of
the _da Vinci ®;Skills Simulator _™, which are standard elements of most RAS
surgical skills training curricula, were taken into consideration. The dataset
contains performance scores (scale: 0 to 100) generated by the simulator after
each exercise was completed. Each task was completed by the participants at
least twice, and if they weren't able to complete it with a score of 70 (out
of 100) on at least one try, they tried again until they did. The National
Institute of Biomedical Imaging and Bioengineering (NIBIB) and Roswell Park
Comprehensive Cancer Center (RPCCC) supported the collection of data for use
in RAS training, which is why the dataset has been named the NIBIB-RPCCC-RAS
performance evaluation dataset. The dataset contains 1636 EEG recordings (in
the "*.edf" format), 1559 eye-gaze recordings (in the "*.csv" format),
performance scores, and participant demographic data, such as age, gender, and
dominant hand. To our knowledge, this is the first shared dataset that
contains EEG and eye-gaze data from participants with a variety of RAS
experiences who performed all tasks included in the da Vinci simulator
modules.
DOI: 10.5281/zenodo.8148655
title: Flow velocity measured from MacKay River Estuary, Georgia, USA

description: <strong>Title: </strong>Flow velocity measured from MacKay River Estuary, Georgia, USA <strong>Author: </strong>Li, Chunyan <strong>Contact/PI: </strong>Li, C. (cli@lsu.edu) <strong>Description:</strong> The data provided here are measured flow velocity profiles from a moving vessel in the MacKay River Estuary in Georgia, USA. The survey was done on March 31 16, 2003. Time is UTC. There is only 1 file. The instrument was a 1200 kHz RDI ADCP. The file is in ASCII format. It is output from the RDI’s program WinRiver II. The file name is: March31_MackayRiver002_ASC.TXT
DOI: 10.5281/zenodo.8148654
title: Flow velocity measured from MacKay River Estuary, Georgia, USA

description: <strong>Title: </strong>Flow velocity measured from MacKay River Estuary, Georgia, USA <strong>Author: </strong>Li, Chunyan <strong>Contact/PI: </strong>Li, C. (cli@lsu.edu) <strong>Description:</strong> The data provided here are measured flow velocity profiles from a moving vessel in the MacKay River Estuary in Georgia, USA. The survey was done on March 31 16, 2003. Time is UTC. There is only 1 file. The instrument was a 1200 kHz RDI ADCP. The file is in ASCII format. It is output from the RDI’s program WinRiver II. The file name is: March31_MackayRiver002_ASC.TXT
DOI: 10.6084/m9.figshare.23689134
title: <strong>Supplemetary file 2</strong>

description: Table of genes differentially express following both BLM and PNX that were mapped to the upstream regulators <em>TGFB1</em> and <em>TNF</em> showing their log2 fold-change compared to sham mice for either procedure.
DOI: 10.6084/m9.figshare.23689134.v3
title: <strong>Supplemetary file 2</strong>

description: Table of genes differentially express following both BLM and PNX that were mapped to the upstream regulators <em>TGFB1</em> and <em>TNF</em> showing their log2 fold-change compared to sham mice for either procedure.
DOI: 10.6084/m9.figshare.23689134.v2
title: <strong>Supplemetary file 2</strong>

description: Table of genes differentially express following both BLM and PNX that were mapped to the upstream regulators <em>TGFB1</em> and <em>TNF</em> showing their log2 fold-change compared to sham mice for either procedure.
DOI: 10.6084/m9.figshare.23689149
title: <strong>Supplementary file 1</strong>

description: RNA-Sequencing of isolated mouse lung fibroblasts following bleomycin administration or pneumonectomy.
DOI: 10.6084/m9.figshare.23689149.v1
title: <strong>Supplementary file 1</strong>

description: RNA-Sequencing of isolated mouse lung fibroblasts following bleomycin administration or pneumonectomy.
DOI: 10.6084/m9.figshare.23689137
title: <strong>Supplementary file 3</strong>

description: RNA-Sequencing of cultured normal human lung fibroblasts overexpressing ITPKC.
DOI: 10.6084/m9.figshare.23689137.v1
title: <strong>Supplementary file 3</strong>

description: RNA-Sequencing of cultured normal human lung fibroblasts overexpressing ITPKC.
DOI: 10.6084/m9.figshare.23689152
title: <strong>Supplementary file 4</strong>

description: Motif enrichment prediction for genes up-regulated in mouse lung fibroblasts following bleomycin or pneumonectomy
DOI: 10.6084/m9.figshare.23689152.v1
title: <strong>Supplementary file 4</strong>

description: Motif enrichment prediction for genes up-regulated in mouse lung fibroblasts following bleomycin or pneumonectomy
DOI: 10.6084/m9.figshare.23689155
title: <strong>Supplementary file 5</strong>

description: Motif enrichment prediction for genes up-regulated in cultured normal human lung fibroblasts following ITPKC overexpression.
DOI: 10.6084/m9.figshare.23689155.v1
title: <strong>Supplementary file 5</strong>

description: Motif enrichment prediction for genes up-regulated in cultured normal human lung fibroblasts following ITPKC overexpression.
DOI: 10.25345/c5td9nj8d
title: MassIVE MSV000092449 - Effects of SPI1-mediated transcriptome remodeling on Alzheimers disease-related phenotypes in mouse models of Ab amyloidosis
title: SPI1 was recently reported as a genetic risk factor for Alzheimers disease (AD) in large-scale genome-wide association studies. However, it is unknown whether SPI1 should be downregulated or increased to have therapeutic benefits. To investigate the effect of modulating SPI1 levels on AD pathogenesis, we performed extensive biochemical, histological, transcriptomic, and proteomic analyses using both Spi1-knockdown and Spi1-overexpression mouse models. Spi1-knockdown markedly increased insoluble amyloid-b (Ab) levels, amyloid plaque deposition, and gliosis, while Spi1-overexpression significantly decreased these phenotypes and dystrophic neurites. More mechanistic studies identified several biological pathways, such as immune response pathways and complement system, that are regulated by altered Spi1 expression, through proteomics analyses as well as bulk and single-cell transcriptomics data. Our data demonstrate that transcriptional reprogramming may be a feasible therapeutic strategy for AD. This approach could significantly broaden the current notion of druggable targets for AD.
DOI: 10.6084/m9.figshare.23681802
title: Theoretical (Simulated) Spectral Power Distributions for Use in Research

description: This set of theoretical SPDs, intended to represent possible future color-mixed solid-state lighting systems (i.e., using no downcoverter materials), has three parts. First, a Visual Basic subroutine was used to determine a set of 100,000 SPDs. The factors were the number of primaries (three, four, five, six, or seven) and range of FWHM (2-11 nm [narrow], 20-50 nm [medium], 50-100 nm [wide], 2-100 nm [mixed]). Each combination includes 5,000 SPDs. Each primary was generated according a previously documented Gaussian distribution formula, with a random number generator used to vary the peak wavelength between 400 and 700 nm, FWHM within the specified limits, and maximum intensity. SPDs were generated from 380 to 780 nm with an increment of 1 nm. CCT is limited to the range of 2580 to 7042 K, or the extents of ANSI C78.377 nominal CCT bins for 2700 to 6500 K. <em>D</em>uv is limited to the range of 0.006 to -0.018, approximating the limits of ANSI C78.377-2017, including the extended bin range. <br> The second part includes 50,000 SPDs generated using the same algorithm. These SPDs have the same chromaticity limits, feature four primaries, and randomly-generated FWHMs between 1 and 100 nm. <br> A separate set of 15,986 SPDs from previous work comprises the third part. These SPDs are a combination of real and theoretical light sources, with spectral features as narrow as 1 nm FWHM and as wide as 100 nm.
DOI: 10.34740/kaggle/dsv/6136519
title: US counties COVID 19 dataset
DOI: 10.5281/zenodo.8148691
title: enteromius_anoplus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8148690
title: enteromius_anoplus_zanfona_1.fasta.gz

description: .
DOI: 10.6078/m7668b9h
title: A first approximation of population distributions on the International Space Station
DOI: 10.5281/zenodo.8148705
title: Adolescent pregnancies in Panama (2010-2019)

description: This data describe the evolution of the adolescent pregnancy situation from 2010 to 2019. It is essential for the description of this problem in the territory of Panama. This data was provided for research purposes by the National Institute of Statistics and Census of Panama. It was provided to the principal investigator. The data is protected and cannot be shared. A formal application is necessary to process through the INEC
DOI: 10.5281/zenodo.8148704
title: Adolescent pregnancies in Panama (2010-2019)

description: This data describe the evolution of the adolescent pregnancy situation from 2010 to 2019. It is essential for the description of this problem in the territory of Panama. This data was provided for research purposes by the National Institute of Statistics and Census of Panama. It was provided to the principal investigator. The data is protected and cannot be shared. A formal application is necessary to process through the INEC
DOI: 10.21227/rr8k-5r07
title: Productive Crop Field

description: In precision agriculture, detecting productive crop fields is an essential practice that allows the farmer to evaluate operating performance separately and compare different seed varieties, pesticides, and fertilizers. However, manually identifying productive fields is often time-consuming, costly, and subjective. Previous studies explore different methods to detect crop fields using advanced machine learning algorithms to support the specialists’ decisions, but they often lack good quality labeled data. In this context, we propose a high-quality dataset generated by machine operation combined with Sentinel-2 images tracked over time. As far as we know, it is the first one to overcome the lack of labeled samples by using this technique. In sequence, we apply a semi-supervised classification of unlabeled data and state-of-the-art supervised and self-supervised deep learning methods to detect productive crop fields automatically. Finally, the results demonstrate high accuracy in Positive Unlabeled learning, which perfectly fits the problem where we have high confidence in the positive samples. Best performances have been found in Triplet Loss Siamese given the existence of an accurate dataset and Contrastive Learning considering situations where we do not have a comprehensive labeled dataset available.
DOI: 10.5281/zenodo.8148727
title: BASE DE DATOS DE ARTÍCULOS DE BIENESTAR PSICOLÓGICO Y ESTRÉS

description: ARTÍCULOS REALIZADOS POR LA BASE DE DATOS EBSCO, SCIELO, ALICIA Y REDALYC DE ARTICULOS QUE ESTUDIARON EL BIENESTAR PSICOLOGICO Y EL ESTRES EN LOS AÑOS 2016 AL 2023
DOI: 10.5281/zenodo.8148726
title: BASE DE DATOS DE ARTÍCULOS DE BIENESTAR PSICOLÓGICO Y ESTRÉS

description: ARTÍCULOS REALIZADOS POR LA BASE DE DATOS EBSCO, SCIELO, ALICIA Y REDALYC DE ARTICULOS QUE ESTUDIARON EL BIENESTAR PSICOLOGICO Y EL ESTRES EN LOS AÑOS 2016 AL 2023
DOI: 10.5281/zenodo.8148723
title: Simulation data for Pitx1-ORCA-2023

description: Data from polymer simulations using loop extrusion or polymer microphase separation to understand the mechanisms of TAD bypass in genome folding. Simulations are described in detail in our work investigating the Pitx1 domain 3D organization in mouse hindlimb and forelimb.
DOI: 10.5281/zenodo.8148722
title: Simulation data for Pitx1-ORCA-2023

description: Data from polymer simulations using loop extrusion or polymer microphase separation to understand the mechanisms of TAD bypass in genome folding. Simulations are described in detail in our work investigating the Pitx1 domain 3D organization in mouse hindlimb and forelimb.
DOI: 10.5281/zenodo.8148721
title: Data for the analyses

description: This archive contains the data for the manuscript submitted to GMD journal.
DOI: 10.5281/zenodo.8148720
title: Data for the analyses

description: This archive contains the data for the manuscript submitted to GMD journal.
DOI: 10.6084/m9.figshare.23688960
title: Figures Raw Data

description: Excel data from Manuscript Figures
DOI: 10.6084/m9.figshare.23688960.v1
title: Figures Raw Data

description: Excel data from Manuscript Figures
DOI: 10.5281/zenodo.8148775
title: BASE DE DATOS DE ARTÍCULOS DE BIENESTAR PSICOLÓGICO Y ESTRÉS

description: ARTÍCULOS REALIZADOS POR LA BASE DE DAOS EBSCO, SCIELO, ALICIA Y REDALYC DE ARTÍCULOS QUE ESTUDIARON EL BIENESTAR PSICOLÓGICO Y ESTRÉS EN LOS AÑOS 2017 AL 2023
DOI: 10.5281/zenodo.8148774
title: BASE DE DATOS DE ARTÍCULOS DE BIENESTAR PSICOLÓGICO Y ESTRÉS

description: ARTÍCULOS REALIZADOS POR LA BASE DE DAOS EBSCO, SCIELO, ALICIA Y REDALYC DE ARTÍCULOS QUE ESTUDIARON EL BIENESTAR PSICOLÓGICO Y ESTRÉS EN LOS AÑOS 2017 AL 2023
DOI: 10.18112/openneuro.ds004187.v1.0.2
title: LGN Layers Data
DOI: 10.34740/kaggle/dsv/6136802
title: Youtube Trending Video - Taiwan & Hong Kong
DOI: 10.18739/a2kw57k57
title: Ice-wedge polygon detection in satellite imagery from pan-Arctic regions, Permafrost Discovery Gateway, 2001-2021

description: Data are available for download at http://arcticdata.io/data/10.18739/A2KW57K57 Permafrost can be indirectly detected via remote sensing techniques through the presence of ice-wedge polygons, which are a ubiquitous ground surface feature in tundra regions. Ice-wedge polygons form through repeated annual cracking of the ground during cold winter days. In spring, the cracks fill in with snowmelt water, creating ice wedges, which are connected across the landscape in an underground network and that can grow to several meters depth and width. The growing ice wedges push the soil upwards, forming ridges that bound low-centered ice-wedge polygons. If the top of the ice wedge melts, the ground subsides and the ridges become troughs and the ice-wedge polygons become high-centered. Here, a Convolutional Neural Network is used to map the boundaries of individual ice-wedge polygons based on high-resolution commercial satellite imagery obtained from the Polar Geospatial Center. This satellite imagery used for the detection of ice-wedge polygons represent years between 2001 and 2021, so this dataset represents ice-wedge polygons mapped from different years. This dataset does not include a time series (i.e. same area mapped more than once). The shapefiles are masked, reprojected, and processed into GeoPackages with calculated attributes for each ice-wedge polygon such as circumference and width. The GeoPackages are then rasterized with new calculated attributes for ice-wedge polygon coverage such a coverage density. This release represents the region classified as “high ice” by Brown et al. 1997. The dataset is available to explore on the Permafrost Discovery Gateway (PDG), an online platform that aims to make big geospatial permafrost data accessible to enable knowledge-generation by researchers and the public. The PDG project creates various pan-Arctic data products down to the sub-meter and monthly resolution. Access the PDG Imagery Viewer here: https://arcticdata.io/catalog/portals/permafrost Data limitations in use: This data is part of an initial release of the pan-Arctic data product for ice-wedge polygons, and it is expected that there are constraints on its accuracy and completeness. Users are encouraged to provide feedback regarding how they use this data and issues they encounter during post-processing. Please reach out to the dataset contact or a member of the PDG team via support@arcticdata.io.
DOI: 10.5517/ccdc.csd.cc2ffw92
title: CCDC 2247664: Experimental Crystal Structure Determination

description: Related Article: Takayuki Ohyoshi, Hidetada Iizumi, Shu Hosono, Hikaru Tano, Hideo Kigoshi|2023|Org.Lett.|25|4725|doi:10.1021/acs.orglett.3c01692
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.cc2fkrc4
title: CCDC 2251386: Experimental Crystal Structure Determination

description: Related Article: Edgar Zander, Jonas Bresien, Vladimir V. Zhivonitko, Johannes Fessler, Alexander Villinger, Dirk Michalik, Axel Schulz|2023|J.Am.Chem.Soc.|145|14484|doi:10.1021/jacs.3c03928
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.cc2fkrd5
title: CCDC 2251387: Experimental Crystal Structure Determination

description: Related Article: Edgar Zander, Jonas Bresien, Vladimir V. Zhivonitko, Johannes Fessler, Alexander Villinger, Dirk Michalik, Axel Schulz|2023|J.Am.Chem.Soc.|145|14484|doi:10.1021/jacs.3c03928
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.cc2fkrf6
title: CCDC 2251388: Experimental Crystal Structure Determination

description: Related Article: Edgar Zander, Jonas Bresien, Vladimir V. Zhivonitko, Johannes Fessler, Alexander Villinger, Dirk Michalik, Axel Schulz|2023|J.Am.Chem.Soc.|145|14484|doi:10.1021/jacs.3c03928
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.cc2fkrg7
title: CCDC 2251389: Experimental Crystal Structure Determination

description: Related Article: Edgar Zander, Jonas Bresien, Vladimir V. Zhivonitko, Johannes Fessler, Alexander Villinger, Dirk Michalik, Axel Schulz|2023|J.Am.Chem.Soc.|145|14484|doi:10.1021/jacs.3c03928
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.cc2fkrh8
title: CCDC 2251390: Experimental Crystal Structure Determination

description: Related Article: Edgar Zander, Jonas Bresien, Vladimir V. Zhivonitko, Johannes Fessler, Alexander Villinger, Dirk Michalik, Axel Schulz|2023|J.Am.Chem.Soc.|145|14484|doi:10.1021/jacs.3c03928
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.cc2fkrj9
title: CCDC 2251391: Experimental Crystal Structure Determination

description: Related Article: Edgar Zander, Jonas Bresien, Vladimir V. Zhivonitko, Johannes Fessler, Alexander Villinger, Dirk Michalik, Axel Schulz|2023|J.Am.Chem.Soc.|145|14484|doi:10.1021/jacs.3c03928
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.cc2fkrkb
title: CCDC 2251392: Experimental Crystal Structure Determination

description: Related Article: Edgar Zander, Jonas Bresien, Vladimir V. Zhivonitko, Johannes Fessler, Alexander Villinger, Dirk Michalik, Axel Schulz|2023|J.Am.Chem.Soc.|145|14484|doi:10.1021/jacs.3c03928
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.