cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/83ddtt4prk.1
title: Decoupling reaction rate and diffusion limitation to fast-charging electrodes by extended modeling of cyclic voltammetry data

description: All data shown in "Decoupling reaction rate and diffusion limitation to fast-charging electrodes by extended modeling of cyclic voltammetry data".
DOI: 10.17632/83ddtt4prk.2
title: Decoupling reaction rate and diffusion limitation to fast-charging electrodes by extended modeling of cyclic voltammetry data

description: All data shown in "Decoupling reaction rate and diffusion limitation to fast-charging electrodes by extended modeling of cyclic voltammetry data".
DOI: 10.17632/2zkv76fxd2.1
title: Psychometric Validation of the Kazakh BDI

description: 115 female breast cancer patients were tested twice with the Kazakh version of the Beck Depression Inventory (BDI-II). After completing the BDI-II questionnaire on Day 1 patients were asked to complete the Hamilton Depression Rating Scale (HDRS). HDRS was administered as a gold standard for the clinical diagnosis of a depressive disorder by the physician, who was blind to the results of the questionnaire. T
DOI: 10.17632/4h56fwxwjp.1
title: Processing Directional Information in Stimuli Inhibits the Spatial Association of Luminance Levels

description: The datas of article published in attention, perception, & Psychophysics in 2022
DOI: 10.17632/44jzzmczgj.1
title: Fully Untethered Battery-free Wearable Biomonitoring Stickers via Printed Stretchable Antenna and Far-Field Energy Harvesting

description: We demonstrate untethered battery-free patches through a series of printed and stretchable antennas for far-field energy harvesting. We introduce digitally fabricated stretchable antennas through low-cost and scalable techniques, i.e. extrusion printing or laser patterning. Here is the relevant data for dipole and PIFA antennas used in the elaboration of the manuscript. It contains the VNA tests for 1) PIFA stretch testing. 2) PIFA antenna made of Cu. 3) PIFA antennas made of Ag. 4) Dipole antenna with foam seperator. 5) Dipole antenna first test without seperator. Also, 6) Simulated PIFA result.
DOI: 10.17632/nw593889ff.1
title: Breast feeding in Kuwait

description: the data collected from 316 mothers and their newborn infants in Al-Sabah Maternity Hospital during December 2015 to August 2019. Mothers who had full-term babies (37+ weeks) and babies with a normal birth weight (≥2.5 Kg) were eligible to participate in the study. Information was collected using an interview-based questionnaire. The questionnaire included three sections. The first section contained information about the newborn such as birthdate, sex, weight, height, and gestational age. The second and third sections addressed general information concerning the mother and father, such as their birthdate, nationality, weight, height, education level, monthly income, and residence. All statistical analyses were performed using SAS version 9.4 (SAS Institute). All tests were two-sided, and a p-value of <0.05 was considered statistically significant.
DOI: 10.17632/nw593889ff.2
title: Breast feeding in Kuwait

description: the data collected from 316 mothers and their newborn infants in Al-Sabah Maternity Hospital during December 2015 to August 2019. Mothers who had full-term babies (37+ weeks) and babies with a normal birth weight (≥2.5 Kg) were eligible to participate in the study. Information was collected using an interview-based questionnaire. The questionnaire included three sections. The first section contained information about the newborn such as birthdate, sex, weight, height, and gestational age. The second and third sections addressed general information concerning the mother and father, such as their birthdate, nationality, weight, height, education level, monthly income, and residence. All statistical analyses were performed using SAS version 9.4 (SAS Institute). All tests were two-sided, and a p-value of <0.05 was considered statistically significant.
DOI: 10.17632/2d95dztpxn.1
title: Data for "A decomposition of the atmospheric and surface contributions to the outgoing longwave radiation"

description: 1. olr_fir_mir_toa_atm_sfc_2013_annualmean_all_clr.nc
2. olr_fir_mir_atm_trop_stra_2013_annualmean_all_clr.nc
3. raddp_fluxdp_4d_2013_annualmean_all_clr.nc
4. tau_tr_dtrdp_dtrdz_ptau1_2013_annualmean_total_fir_mir_all_clr.nc
5. tau_tr_dtrdp_dtrdz_ptau1_2013_annualmean_globalmean_band_all_clr.nc
6. tau_tr_dtrdp_dtrdz_ptau1_2013_annualmean_globalmean_total_fir_mir_all_clr.nc
7. tr_dtrdz_inferred_gpoints_2013_01_clr.nc
8. cf_wf_2013_annualmean_globalmean_total_fir_all.nc
9. cre_olr_fir_mir_sfc_atm_layers_2013_annualmean.nc
10. cre_raddp_fluxdp_4d_2013_annualmean_all_clr.nc


1. total OLR, FIR, MIR at the TOA, ATM or SFC, with the postfix of _clr in variable's name representing results in clear sky (figure1, table1, figure5, figrueS6). 
2. total OLR, FIR, MIR in the  ATM, in the troposphere or stratosphere (figureS9)
3. radiance intensity and flux intensity per 100hPa thickness layer in the ATM, and vertical integrated ATM contribution and SFC contribution in each spectral band (figire2, figure4, figureS7, figureS8)
4-6 optical depth (tau), transmittance (tr), weighting function (dtr/dp, dtr/dz) in different bands (figure2, figureS3, figureS4, figureS5, figureS7)
7. transmittance (tr) and weighting function (dtr/dz) from the inferred method or averaged from the g-pointsin Jan 2013 in clear sky, with the postfix _g calculated from the g-points.
8. contribution function (eq. 4) and weighting function (eq. 5) (figure 3)
9. cloud radaitive forcing in total OLR, fir and mir at the TOA, ATM (whole ATM+different layers) or SFC (figure8, figureS11, tableS2)
10. CRE of radiance intensity and flux intensity per 100hPa thickness layer in the ATM, and vertical integrated ATM contribution and SFC contribution in each spectral band (figure6, figure7, figureS10)
DOI: 10.17632/2d95dztpxn.2
title: Data for "A decomposition of the atmospheric and surface contributions to the outgoing longwave radiation"

description: 1. olr_fir_mir_toa_atm_sfc_2013_annualmean_all_clr.nc
2. olr_fir_mir_atm_trop_stra_2013_annualmean_all_clr.nc
3. raddp_fluxdp_4d_2013_annualmean_all_clr.nc
4. tau_tr_dtrdp_dtrdz_ptau1_2013_annualmean_total_fir_mir_all_clr.nc
5. tau_tr_dtrdp_dtrdz_ptau1_2013_annualmean_globalmean_band_all_clr.nc
6. tau_tr_dtrdp_dtrdz_ptau1_2013_annualmean_globalmean_total_fir_mir_all_clr.nc
7. tr_dtrdz_inferred_gpoints_2013_01_clr.nc
8. cf_wf_2013_annualmean_globalmean_total_fir_all.nc
9. cre_olr_fir_mir_sfc_atm_layers_2013_annualmean.nc
10. cre_raddp_fluxdp_4d_2013_annualmean_all_clr.nc


1. total OLR, FIR, MIR at the TOA, ATM or SFC, with the postfix of _clr in variable's name representing results in clear sky (figure2, table1, figure6, figrueS6).
2. total OLR, FIR, MIR in the  ATM, in the troposphere or stratosphere (figureS10)
3. radiance intensity and flux intensity per 100hPa thickness layer in the ATM, and vertical integrated ATM contribution and SFC contribution in each spectral band (figire3, figure5, figureS7, figureS8)
4-6 optical depth (tau), transmittance (tr), weighting function (dtr/dp, dtr/dz) in different bands (figure3, figureS3, figureS4, figureS5)
7. transmittance (tr) and weighting function (dtr/dz) from the inferred method or averaged from the g-points in Jan 2013 in clear sky, with the postfix _g calculated from the g-points (figureS4).
8. contribution function (eq. 4) and weighting function (eq. 5) (figure 4)
9. cloud radaitive forcing in total OLR, fir and mir at the TOA, ATM (whole ATM+different layers) or SFC (figure9, figureS11, tableS2)
10. CRE of radiance intensity and flux intensity per 100hPa thickness layer in the ATM, and vertical integrated ATM contribution and SFC contribution in each spectral band (figure7, figure8, figureS9)
DOI: 10.17632/2d95dztpxn.3
title: Data for "A decomposition of the atmospheric and surface contributions to the outgoing longwave radiation"

description: 1. olr_fir_mir_toa_atm_sfc_2013_annualmean_all_clr.nc
2. olr_fir_mir_atm_trop_stra_2013_annualmean_all_clr.nc
3. raddp_fluxdp_4d_2013_annualmean_all_clr.nc
4. tau_tr_dtrdp_dtrdz_ptau1_2013_annualmean_total_fir_mir_all_clr.nc
5. tau_tr_dtrdp_dtrdz_ptau1_2013_annualmean_globalmean_band_all_clr.nc
6. tau_tr_dtrdp_dtrdz_ptau1_2013_annualmean_globalmean_total_fir_mir_all_clr.nc
7. tr_dtrdz_inferred_gpoints_2013_01_clr.nc
8. cf_wf_2013_annualmean_globalmean_total_fir_all.nc
9. cre_olr_fir_mir_sfc_atm_layers_2013_annualmean.nc
10. cre_raddp_fluxdp_4d_2013_annualmean_all_clr.nc


1. total OLR, FIR, MIR at the TOA, ATM or SFC, with the postfix of _clr in variable's name representing results in clear sky (figure2, table1, figure6, figrueS6).
2. total OLR, FIR, MIR in the  ATM, in the troposphere or stratosphere (figureS10)
3. radiance intensity and flux intensity per 100hPa thickness layer in the ATM, and vertical integrated ATM contribution and SFC contribution in each spectral band (figire3, figure5, figureS7, figureS8)
4-6 optical depth (tau), transmittance (tr), weighting function (dtr/dp, dtr/dz) in different bands (figure3, figureS3, figureS4, figureS5)
7. transmittance (tr) and weighting function (dtr/dz) from the inferred method or averaged from the g-points in Jan 2013 in clear sky, with the postfix _g calculated from the g-points (figureS4).
8. contribution function (eq. 4) and weighting function (eq. 5) (figure 4)
9. cloud radaitive forcing in total OLR, fir and mir at the TOA, ATM (whole ATM+different layers) or SFC (figure9, figureS11, tableS2)
10. CRE of radiance intensity and flux intensity per 100hPa thickness layer in the ATM, and vertical integrated ATM contribution and SFC contribution in each spectral band (figure7, figure8, figureS9)
DOI: 10.17632/z3xfxnrbz7.1
title: Palaemon metabolome

description: Gill, hepatopancreas, nervous gland, muscle and gonad lC-HRMS-based metabolomics of mature male and female Palaemon serratus
DOI: 10.17632/9m3jzh7jr3.1
title: soft skills

description: soft skills
DOI: 10.17632/j4m9nyy3fb.1
title: LINF_320016400

description: small nuclear ribonucleoprotein | SmG
Leishmania infantum (strain JPCM5)
DOI: 10.5255/ukda-sn-855534
title: Qualitative Individual Reports with Global Virtual Team Participants, 2019

description: The collection includes a total of 274 individual qualitative reports reflecting on each participant's experience of having worked in a global virtual team (GVT) environment through their participation in the VIBu 2019 project. 204 participants — organised in 16 GVTs, dispersed between Austria, Finland, the UK and the USA — took part. Participants were asked to complete two individual reports; one after each VIBu simulation day. Of the 204 participants, 164 submitted a report after the first simulation day, and 110 after the second one. Therefore, a total of 274 reports were collected. Reports were on average two pages long each. Due to confidentiality promised during the data collection process the data cannot be archived.
DOI: 10.17632/k292fcmxz2.1
title: LINF_320016800

description: mitochondrial carrier protein | MCP2
Leishmania infantum (strain JPCM5)
DOI: 10.17632/sy5wphyhnc.1
title: LINF_320016900

description: mitochondrial carrier protein | MCP2
Leishmania infantum (strain JPCM5)
DOI: 10.17632/5w8sbkpb9c.1
title: LINF_320016600

description: ubiquitin-protein ligase | HECT7
Leishmania infantum (strain JPCM5)
DOI: 10.17632/2x32y4rvjv.1
title: LINF_320017100

description: kinetoplast polyadenylation/uridylation factor 2 (KPAF2)
Leishmania infantum (strain JPCM5)
DOI: 10.17632/7f4gsbhrpp.1
title: Short prokaryotic Argonaute systems trigger cell death upon detection of invading DNA 

description: These files contain the data described in the manuscript "Short prokaryotic Argonaute systems trigger cell death upon detection of invading DNA".
DOI: 10.17632/gzy6fckmb7.1
title: Survey to integrate IoT in cultural game authoring tool

description: This is a survey that demonstrates the interest in integrating Internet-of-Thing (IoT) in a serious 3D game authoring tool for cultural awareness.
DOI: 10.17632/8ffrgcmjkm.1
title: Depth_Camera_Dataset

description: The dataset contains RGB and depth version video frames of
various hand movements captured with the Intel RealSense Depth
Camera D435. The camera has two channels for collecting both
RGB and depth frames at the same time. A large dataset is cre-
ated for accurate classification of hand gestures under complex
backgrounds. The dataset is made up of 29718 frames from
RGB and depth versions corresponding to various hand ges-
tures from different people collected at different time instances
with complex backgrounds. Hand movements corresponding
to scroll-right, scroll-left, scroll-up, scroll-down, zoom-in, and
zoom-out are included in the data. Each sequence has data of 40
frames, and there is a total of 662 sequences corresponding to
each gesture in the dataset
DOI: 10.17632/8ffrgcmjkm.2
title: Depth_Camera_Dataset

description: The dataset contains RGB and depth version video frames of
various hand movements captured with the Intel RealSense Depth
Camera D435. The camera has two channels for collecting both
RGB and depth frames at the same time. A large dataset is cre-
ated for accurate classification of hand gestures under complex
backgrounds. The dataset is made up of 29718 frames from
RGB and depth versions corresponding to various hand ges-
tures from different people collected at different time instances
with complex backgrounds. Hand movements corresponding
to scroll-right, scroll-left, scroll-up, scroll-down, zoom-in, and
zoom-out are included in the data. Each sequence has data of 40
frames, and there is a total of 662 sequences corresponding to
each gesture in the dataset
DOI: 10.24378/exe.4164
title: Second DiCE expert survey 2022

description: This is responses of the second DiCE expert survey, conducted May-June 2022
description: This is the responses of the second DiCE expert survey, conducted May-June 2022
DOI: 10.5281/zenodo.7050266
title: Host removal database: Homo sapiens, Sars-Cov-2, PhiX174

description: 💾 <strong>cleanup-db</strong> Kraken2 database, built upon a viral sequence masked human reference from: Handley, Scott A. (2020). <strong>Virus+ Sequence Masked Human Reference Genome (hg19)</strong> (1.0) [Data set]. Zenodo. [10.5281/zenodo.4116107] but separating chromosomes as artificial taxa to allow for QC, and includes Sars-Cov-2 and PhiX 174 💾 <strong>gutcheck-db</strong> A very small DB containg some common gut bacteria and Human and Murine mitochondrial genome: <em>Akkermansia muciniphila</em> <em>Bacteroides fragilis</em> <em>Bifidobacterium longum</em> <em>Blautia obeum strain</em> <em>Escherichia coli</em> <em>Enterococcus faecium</em> <em>Prevotella copri</em> See: https://github.com/telatin/cleanup
description: {"references": ["Handley, Scott A. (2020). Virus+ Sequence Masked Human Reference Genome (hg19) (1.0) [Data set]. Zenodo. [10.5281/zenodo.4116107]"]}
DOI: 10.5281/zenodo.7044071
title: Host removal database: Homo sapiens, Sars-Cov-2, PhiX174

description: 💾 <strong>cleanup-db</strong> Kraken2 database, built upon a viral sequence masked human reference from: Handley, Scott A. (2020). <strong>Virus+ Sequence Masked Human Reference Genome (hg19)</strong> (1.0) [Data set]. Zenodo. [10.5281/zenodo.4116107] but separating chromosomes as artificial taxa to allow for QC, and includes Sars-Cov-2 and PhiX 174 💾 <strong>gutcheck-db</strong> A very small DB containg some common gut bacteria and Human and Murine mitochondrial genome: <em>Akkermansia muciniphila</em> <em>Bacteroides fragilis</em> <em>Bifidobacterium longum</em> <em>Blautia obeum strain</em> <em>Escherichia coli</em> <em>Enterococcus faecium</em> <em>Prevotella copri</em> See: https://github.com/telatin/cleanup
description: {"references": ["Handley, Scott A. (2020). Virus+ Sequence Masked Human Reference Genome (hg19) (1.0) [Data set]. Zenodo. [10.5281/zenodo.4116107]"]}
DOI: 10.6084/m9.figshare.20942938
title: coral_data

description: Data simulated from https://github.com/rneuhausler/coralModel-TDA-study
DOI: 10.6084/m9.figshare.20942938.v1
title: coral_data

description: Data simulated from https://github.com/rneuhausler/coralModel-TDA-study
DOI: 10.34740/kaggle/dsv/4164328
title: Elon Musk Tweets
DOI: 10.5281/zenodo.6393488
title: SDSS Galaxy Subset

description: The Sloan Digital Sky Survey (SDSS) is a comprehensive survey of the northern sky. This dataset contains a subset of this survey, of 43274 objects classified as galaxies, it includes a CSV file with a collection of information and a set of files for each object, namely JPG image files, FITS and spectra data. This dataset is used to train and explore the astromlp-models collection of deep learning models for galaxies characterisation. The dataset includes a CSV data file where each row is an object from the SDSS database, and with the following columns (note that some data may not be available for all objects): <strong>objid</strong>: unique SDSS object identifier <strong>mjd</strong>: MJD of observation <strong>plate</strong>: plate identifier <strong>tile</strong>: tile identifier <strong>fiberid</strong>: fiber identifier <strong>run</strong>: run number <strong>rerun</strong>: rerun number <strong>camcol</strong>: camera column <strong>field</strong>: field number <strong>ra</strong>: right ascension <strong>dec</strong>: declination <strong>class</strong>: spectroscopic class (only objetcs with GALAXY are included) <strong>subclass</strong>: spectroscopic subclass <strong>modelMag_u</strong>: better of DeV/Exp magnitude fit for band u <strong>modelMag_g</strong>: better of DeV/Exp magnitude fit for band g <strong>modelMag_r</strong>: better of DeV/Exp magnitude fit for band r <strong>modelMag_i</strong>: better of DeV/Exp magnitude fit for band i <strong>modelMag_z</strong>: better of DeV/Exp magnitude fit for band z <strong>redshift</strong>: final redshift from SDSS data z <strong>stellarmass</strong>: stellar mass extracted from the eBOSS Firefly catalog <strong>w1mag</strong>: WISE W1 "standard" aperture magnitude <strong>w2mag</strong>: WISE W2 "standard" aperture magnitude <strong>w3mag</strong>: WISE W3 "standard" aperture magnitude <strong>w4mag</strong>: WISE W4 "standard" aperture magnitude <strong>gz2c_f</strong>: Galaxy Zoo 2 classification from Willett et al 2013 <strong>gz2c_s</strong>: simplified version of Galaxy Zoo 2 classification (labels set) Besides the CSV file a set of directories are included in the dataset, in each directory you'll find a list of files named after the <strong>objid </strong>column from the CSV file, with the corresponding data, the following directories tree is available: <pre><code class="language-bash">sdss-gs/ ├── data.csv ├── fits ├── img ├── spectra └── ssel</code></pre> Where, <strong>img</strong>: RGB images from the object in JPEG format, 150x150 pixels, generated using the SkyServer DR16 API <strong>fits</strong>: FITS data subsets around the object across the u, g, r, i, z bands; cut is done using the ImageCutter library <strong>spectra</strong>: full best fit spectra data from SDSS between 4000 and 9000 wavelengths <strong>ssel</strong>: best fit spectra data from SDSS for specific selected intervals of wavelengths discussed by Sánchez Almeida 2010
DOI: 10.5281/zenodo.6501642
title: SDSS Galaxy Subset

description: The Sloan Digital Sky Survey (SDSS) is a comprehensive survey of the northern sky. This dataset contains a subset of this survey, of 60247 objects classified as galaxies, it includes a CSV file with a collection of information and a set of files for each object, namely JPG image files, FITS and spectra data. This dataset is used to train and explore the astromlp-models collection of deep learning models for galaxies characterisation. The dataset includes a CSV data file where each row is an object from the SDSS database, and with the following columns (note that some data may not be available for all objects): <strong>objid</strong>: unique SDSS object identifier <strong>mjd</strong>: MJD of observation <strong>plate</strong>: plate identifier <strong>tile</strong>: tile identifier <strong>fiberid</strong>: fiber identifier <strong>run</strong>: run number <strong>rerun</strong>: rerun number <strong>camcol</strong>: camera column <strong>field</strong>: field number <strong>ra</strong>: right ascension <strong>dec</strong>: declination <strong>class</strong>: spectroscopic class (only objetcs with GALAXY are included) <strong>subclass</strong>: spectroscopic subclass <strong>modelMag_u</strong>: better of DeV/Exp magnitude fit for band u <strong>modelMag_g</strong>: better of DeV/Exp magnitude fit for band g <strong>modelMag_r</strong>: better of DeV/Exp magnitude fit for band r <strong>modelMag_i</strong>: better of DeV/Exp magnitude fit for band i <strong>modelMag_z</strong>: better of DeV/Exp magnitude fit for band z <strong>redshift</strong>: final redshift from SDSS data z <strong>stellarmass</strong>: stellar mass extracted from the eBOSS Firefly catalog <strong>w1mag</strong>: WISE W1 "standard" aperture magnitude <strong>w2mag</strong>: WISE W2 "standard" aperture magnitude <strong>w3mag</strong>: WISE W3 "standard" aperture magnitude <strong>w4mag</strong>: WISE W4 "standard" aperture magnitude <strong>gz2c_f</strong>: Galaxy Zoo 2 classification from Willett et al 2013 <strong>gz2c_s</strong>: simplified version of Galaxy Zoo 2 classification (labels set) Besides the CSV file a set of directories are included in the dataset, in each directory you'll find a list of files named after the <strong>objid </strong>column from the CSV file, with the corresponding data, the following directories tree is available: <pre><code class="language-bash">sdss-gs/ ├── data.csv ├── fits ├── img ├── spectra └── ssel</code></pre> Where, each directory contains: <strong>img</strong>: RGB images from the object in JPEG format, 150x150 pixels, generated using the SkyServer DR16 API <strong>fits</strong>: FITS data subsets around the object across the u, g, r, i, z bands; cut is done using the ImageCutter library <strong>spectra</strong>: full best fit spectra data from SDSS between 4000 and 9000 wavelengths <strong>ssel</strong>: best fit spectra data from SDSS for specific selected intervals of wavelengths discussed by Sánchez Almeida 2010 <strong>Changelog</strong> v0.0.2 - Increase number ob objects to ~60k.. v0.0.1 - Initial import.