cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/qqycoq/bakhha
title: Cab2_B_0460_V_10014.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/cqnhil
title: Cab2_B_0460_V_17785.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/cs08xu
title: Etna_B_0460_V_04622.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/dw9kvm
title: Ruapehu_19960617_V_55068.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/dzviya
title: Cab2_B_0460_V_17346.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/ethnvv
title: MSH_19800525_A_0135_B_0960.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/ftd9pa
title: Etna_B_0460_V_02531.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/k4sl6u
title: Etna_B_0500_V_02311.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/k9ntej
title: MSH_19800525_A_0060_B_0620.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/ktvqdc
title: MSH_19800525_A_0040_B_0760.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/mmlesd
title: MSH_19800525_A_0130_B_0420.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/nujlzx
title: Cab2_B_0460_V_13320.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/oqnhd3
title: Cab2_B_0460_V_11452.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/pqurxr
title: Cab2_B_0460_V_18000.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/q1qdf6
title: Ruapehu_19960617_V_45873.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/syun53
title: Cab2_B_0460_V_16895.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/tp8vlo
title: Ruapehu_19960617_V_32436.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/tuuyiw
title: Ruapehu_19960617_V_46542.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/tvax32
title: Ruapehu_19960617_V_26092.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/txbthu
title: Etna_B_0460_V_04384.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/urjgeq
title: MSH_19800525_A_0095_B_0320.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/wkevlz
title: MSH_19800525_A_0105_B_0720.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/xptzfu
title: MSH_19800525_A_0090_B_0720.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/z9nwb1
title: MSH_19800525_A_0045_B_0360.txt

description: :unav
DOI: 10.7910/dvn/qqycoq/zlsmqo
title: Ruapehu_19960617_V_53356.txt

description: :unav
DOI: 10.25345/c57q2p
title: MassIVE MSV000084381 - RAW and Supplementary LC-MS/MS data for Canestrari et al.,
title: RAW and Processed (MaxQuant) [LFQ] datasets associated with manuscript. LFQ data were used to identify type and extent of cys regulation from a novel leaderless translated ORF.
DOI: 10.7910/dvn/qqycoq/2zmp6x
title: Etna_B_0460_V_04792.txt

description: :unav
DOI: 10.5281/zenodo.7400926
title: Electrocatalysis at the Polarised Interface between Two Immiscible Electrolyte Solutions (dataset)

description: This is a dataset used to prepare Figure 4 in the review "<strong>Electrocatalysis at the Polarised Interface between Two Immiscible Electrolyte Solutions</strong>", prepared for the journal Current Opinion in Electrochemistry.
description: A.G.-Q. acknowledges funding received from an Irish Research Council (IRC) Government of Ireland Postdoctoral Fellowship Award (grant no. GOIPD/2018/252) and a Marie Skłodowska-Curie Postdoctoral Fellowship (grant no. MSCA-IF-EF-ST 2020/101018277). P.P. acknowledges funding from the Academy Research Fellow funding and project funding by the Academy of Finland (Grants No. 315739 and 334828).
DOI: 10.6084/m9.figshare.21597183
title: Data for Diversity, Inclusion, and Gender References in Undergraduate Economics

description: Survey data for Diversity paper
DOI: 10.6084/m9.figshare.21597183.v4
title: Data for Diversity, Inclusion, and Gender References in Undergraduate Economics

description: Survey data for Diversity paper
DOI: 10.6084/m9.figshare.21597183.v3
title: Data for Diversity, Inclusion, and Gender References in Undergraduate Economics

description: Survey data for Diversity paper
DOI: 10.25919/1gs3-6977
title: Parkes observations for project P574 semester 2023APRS_06

description: We request time to observe 260 pulsars on a regular basis in order to provide the accurate ephemerides necessary for the detection and characterisation of gamma-ray pulsars with the Fermi satellite. The main science goals are to increase the number of known gamma-ray pulsars (both radio loud and radio quiet), to determine accurate pulse profiles, and to characterise their high energy (phase-resolved) spectra. In the radio, the observations will also allow us to investigate: neutron stars and pulsar emission via detecting glitches and determining pulse timing parameters; and the ISM via measuring and monitoring dispersion measures, Faraday rotation measures, and scintillation. To date, we are (co-)authors on over 95 papers arising from the collaboration and P574 data, including four which use UWL observations. The data have contributed to the PhD theses of students from Bordeaux, Manchester, Oxford, Stanford, and Swinburne.
DOI: 10.25919/feb9-ff12
title: Parkes observations for project P1194 semester 2023APRS_23

description: Among nearly 2000 unidentified gamma-ray sources detected with the Fermi Gamma Ray Space Telescope, there are potentially many pulsars. The ultra-wide frequency coverage will enable us to detect MSPs with steep spectrum and avoid difficulties caused by interstellar scintillation and dispersive and scattering smearing. We propose to revisit highly ranked pulsar candidates that remain unidentified. Such a pilot survey will help us designing future searches of the coming 4FGL gamma-ray source catalog using the UWL. We select 11 targets and request 12 hour time in total.
DOI: 10.6084/m9.figshare.23732421
title: Datesets for "Single-cell lipidomics enabled by dual-polarity ionization and ion mobility-mass spectrometry imaging"

description: Single-cell (SC) analysis provides unique insight into individual cell dynamics and cell-to-cell heterogeneity. Here, we utilize trapped ion mobility separation coupled with dual-polarity ionization mass spectrometry imaging (MSI) to enable high throughput <em>in situ</em> profiling of SC lipidome. Multimodal SC imaging, in which dual-polarity-mode MSI is used to perform serial data acquisition runs on individual cells, significantly enhanced SC lipidome coverage. High spatial resolution SC-MSI identifies both inter- and intra-cellular lipid heterogeneity; this heterogeneity is further explicated by Uniform Manifold Approximation and Projection and machine learning-driven classifications. We characterize SC lipidome alteration in response to stearoyl-CoA desaturase 1 (SCD1) inhibition and, additionally, identify layer-specific lipid distribution patterns in mouse cerebellar cortex. This integrated multimodal SC-MSI technology enables high-resolution spatial mapping of intracellular and cell-to-cell lipidome heterogeneity, SC lipidome remodeling induced by pharmacological intervention, and region-specific lipid diversity within tissue.
DOI: 10.25452/figshare.plus.21913062
title: Spin-Boson dataset

description: This data set was generated for the spin-boson model using hierarchical equations of motion method for 1,000 model parameters. The data set contains reduced density matrix of the two-level system. <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6389553 <br> Collection description: Simulations of the dynamics of dissipative quantum systems utilize many methods such as physics-based quantum, semiclassical, and quantum-classical as well as machine learning-based approximations, development and testing of which requires diverse data sets. Here we present a new database QD3SET-1 containing eight data sets of quantum dynamical data for two systems of broad interest, spin-boson (SB) model and the Fenna–Matthews–Olson (FMO) complex, generated with two different methods solving the dynamics, approximate local thermalizing Lindblad master equation (LTLME) and highly accurate hierarchy equations of motion (HEOM). One data set was generated with the SB model which is a two-level quantum system coupled to a harmonic environment using HEOM for 1,000 model parameters. Seven data sets were collected for the FMO complex of different sizes (7- and 8-site monomer and 24-site trimer with LTLME and 8-site monomer with HEOM) for 500–879 model parameters. Our QD3SET-1 database contains both population and coherence dynamics data and part of it has been already used for machine learning-based quantum dynamics studies.
DOI: 10.25452/figshare.plus.21913149
title: Fenna–Matthews–Olson (FMO) datasets

description: The dynamics of the Fenna–Matthews–Olson (FMO) complex. FMO-Ia and FMO-Ib data sets: 7-site FMO model Hamiltonian parametrized by Adolphs and Renger solved with local thermalizing Lindblad master equation approach. FMO-II data set: 7-site FMO model Hamiltonian parametrized by Cho et al. solved with local thermalizing Lindblad master equation approach. FMO-III data set: 8-site FMO model Hamiltonian parametrized by Jia et al. solved with local thermalizing Lindblad master equation approach. FMO-IV data set: 8-site FMO model Hamiltonian parametrized by Olbrich et al. and Busch et al. solved with local thermalizing Lindblad master equation approach. FMO-V data set: FMO trimer based on 8-site model Hamiltonian parametrized by Olbrich et al. and Busch et al. solved with local thermalizing Lindblad master equation approach. FMO-VI data set: 8-site FMO model Hamiltonian parametrized by by Olbrich et al. and Busch et al. solved solved with hierarchical equations of motion approach. Each data set contains reduced density matrix of the electronic 7- or 8-site system. <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6389553 <br> Collection description: Simulations of the dynamics of dissipative quantum systems utilize many methods such as physics-based quantum, semiclassical, and quantum-classical as well as machine learning-based approximations, development and testing of which requires diverse data sets. Here we present a new database QD3SET-1 containing eight data sets of quantum dynamical data for two systems of broad interest, spin-boson (SB) model and the Fenna–Matthews–Olson (FMO) complex, generated with two different methods solving the dynamics, approximate local thermalizing Lindblad master equation (LTLME) and highly accurate hierarchy equations of motion (HEOM). One data set was generated with the SB model which is a two-level quantum system coupled to a harmonic environment using HEOM for 1,000 model parameters. Seven data sets were collected for the FMO complex of different sizes (7- and 8-site monomer and 24-site trimer with LTLME and 8-site monomer with HEOM) for 500–879 model parameters. Our QD3SET-1 database contains both population and coherence dynamics data and part of it has been already used for machine learning-based quantum dynamics studies.<br>
DOI: 10.6084/m9.figshare.23535510
title: Enhancing 7-dehydrocholesterol suppresses brain ferroptosis and tissue injury after neonatal hypoxia-ischemia

description: These data present a study seeking to assess the effects of increasing 7-DHC concentrations for neuroprotection in cell culture and an in vivo neonatal (P9) mouse model of unilateral carotid artery ligation followed by hypoxia (30 min at 8%). The tabs correlate to each of the figures in the manuscript: Tab "fig 1B": shows RSL-3 mediated ferroptosis in HT1080 cells pre-treated for 24 h with vehicle (VEH), 50 nM cariprazine (CAR), 500 nM aripiprazole (ARI), 500 nM trazodone (TRZ) or 50 nM lovastatin (LOV). Cell viability was assessed with Alamar blue. CAR, ARI and TRZ are potent DHCR7-inhibiting medications and significantly suppress ferroptotic induced cell death. LOV is a potent HMGCR inhibitor and it does not prevent ferroptosis, indicating that the ferroptosis suppression is not due to cholesterol deprivation, but to an increase in 7-DHC. Tab "fig 2B": shows HT1080 cells pre-treated with 1, 10 and 25 nM CAR for 24h before ferroptosis was induced with 25 nM RSL-3. Cells were incubated with RSL-3 for 24 h and cell viability was assessed with Alamar blue. Cell viability is significantly increased with CAR pre-treatment. Also shows HT1080 cells treated simultaneously with 25 nM RSL-3 and 1, 10 or 25 nM CAR for 24h (co-treatment with CAR and RSL-3). Cell viability was assessed with Alamar Blue. Tab "fig 3B": shows the effects of CAR on neuronal viability after 4 h of oxygen glucose deprivation (OGD). For the pre-treatment experiments, neurons were treated with vehicle, 1 nM, 10 nM or 25 nM CAR for 48 h before OGD. For the post-treatment experiments, neurons were treated with vehicle, 1 nM, 10 nM or 25 nM 30 min after OGD. Cell viability was assessed 24 h after the termination of OGD and were calculated by dividing the numbers of live neurons after OGD by the number of live neurons of the control (not exposed to OGD). 7-DHC levels were assessed by LC-MS/MS at the endpoint of the experiment. Concentrations of 7-DHC are elevated by CAR administration but consumed by OGD. Tab "fig 4": 7-DHC derived oxysterols are increased in the brain tissue of CAR-treated animals after hypoxic-ischemic brain injury (HIBI). Animals were injected with 0.2 mg/kg of CAR as described in Figure 5A. 7-DHC-derived oxysterols DHCEO and ep7DHC were not detected (NC) in the Sham+vehicle or HIBI+vehicle groups but were detected in both CAR groups. Tab "fig 5B-E": For the pre-treatment experiments, postnatal day 7 (P7) mice were injected with vehicle (VEH) or 0.2 mg/kg CAR 48 h before HIBI. For the post-treatment experiments, mice were injected with vehicle or 0.2 mg/kg CAR 30 min after HIBI. MDA levels assessed by TBARS are decreased in animals treated with CAR, indicating that CAR treatment decreases markers of phospholipid oxidation. Tissue viability assessed by 2,3,5-Triphenyltetrazolium Chloride (TTC) reveals increased tissue viability in HIBI animals treated with CAR.
DOI: 10.6084/m9.figshare.23535510.v1
title: Enhancing 7-dehydrocholesterol suppresses brain ferroptosis and tissue injury after neonatal hypoxia-ischemia

description: These data present a study seeking to assess the effects of increasing 7-DHC concentrations for neuroprotection in cell culture and an in vivo neonatal (P9) mouse model of unilateral carotid artery ligation followed by hypoxia (30 min at 8%). The tabs correlate to each of the figures in the manuscript: Tab "fig 1B": shows RSL-3 mediated ferroptosis in HT1080 cells pre-treated for 24 h with vehicle (VEH), 50 nM cariprazine (CAR), 500 nM aripiprazole (ARI), 500 nM trazodone (TRZ) or 50 nM lovastatin (LOV). Cell viability was assessed with Alamar blue. CAR, ARI and TRZ are potent DHCR7-inhibiting medications and significantly suppress ferroptotic induced cell death. LOV is a potent HMGCR inhibitor and it does not prevent ferroptosis, indicating that the ferroptosis suppression is not due to cholesterol deprivation, but to an increase in 7-DHC. Tab "fig 2B": shows HT1080 cells pre-treated with 1, 10 and 25 nM CAR for 24h before ferroptosis was induced with 25 nM RSL-3. Cells were incubated with RSL-3 for 24 h and cell viability was assessed with Alamar blue. Cell viability is significantly increased with CAR pre-treatment. Also shows HT1080 cells treated simultaneously with 25 nM RSL-3 and 1, 10 or 25 nM CAR for 24h (co-treatment with CAR and RSL-3). Cell viability was assessed with Alamar Blue. Tab "fig 3B": shows the effects of CAR on neuronal viability after 4 h of oxygen glucose deprivation (OGD). For the pre-treatment experiments, neurons were treated with vehicle, 1 nM, 10 nM or 25 nM CAR for 48 h before OGD. For the post-treatment experiments, neurons were treated with vehicle, 1 nM, 10 nM or 25 nM 30 min after OGD. Cell viability was assessed 24 h after the termination of OGD and were calculated by dividing the numbers of live neurons after OGD by the number of live neurons of the control (not exposed to OGD). 7-DHC levels were assessed by LC-MS/MS at the endpoint of the experiment. Concentrations of 7-DHC are elevated by CAR administration but consumed by OGD. Tab "fig 4": 7-DHC derived oxysterols are increased in the brain tissue of CAR-treated animals after hypoxic-ischemic brain injury (HIBI). Animals were injected with 0.2 mg/kg of CAR as described in Figure 5A. 7-DHC-derived oxysterols DHCEO and ep7DHC were not detected (NC) in the Sham+vehicle or HIBI+vehicle groups but were detected in both CAR groups. Tab "fig 5B-E": For the pre-treatment experiments, postnatal day 7 (P7) mice were injected with vehicle (VEH) or 0.2 mg/kg CAR 48 h before HIBI. For the post-treatment experiments, mice were injected with vehicle or 0.2 mg/kg CAR 30 min after HIBI. MDA levels assessed by TBARS are decreased in animals treated with CAR, indicating that CAR treatment decreases markers of phospholipid oxidation. Tissue viability assessed by 2,3,5-Triphenyltetrazolium Chloride (TTC) reveals increased tissue viability in HIBI animals treated with CAR.
DOI: 10.57967/hf/0916
title: MassiveDialogs
DOI: 10.34740/kaggle/dsv/6179206
title: arXiv Dataset
DOI: 10.3886/e189826v1-140341
title: Data and Code For: Rising Markups, Rising Prices?

description: This is a replication package for "Rising Markups, Rising Prices?".
DOI: 10.34740/kaggle/dsv/6179289
title: Youtube Trending Video - Taiwan & Hong Kong
DOI: 10.5281/zenodo.7805016
title: Supplementary Materials and Raw Data for "Automated Test Suite Generation for Software Product Lines based on Quality-Diversity Optimisation"

description: Supplementary Materials and Raw Data for "Automated Test Suite Generation for Software Product Lines based on Quality-Diversity Optimisation" 1. OnlineSupplement.pdf------Online supplementary data for the paper 2. RQ1-4.rar----Raw data for the paper 3. Runtime to generate, optimise and execution test suites.xlsx -----Data used in Section 7 PRACTICAL IMPLICATIONS Source code of the algorithms used to produce these data can be found at GitHub https://github.com/gzhuxiangyi/SPLTestingMAP
DOI: 10.5281/zenodo.7805017
title: Supplementary Materials and Raw Data for "Automated Test Suite Generation for Software Product Lines based on Quality-Diversity Optimisation"

description: Supplementary Materials and Raw Data for "Automated Test Suite Generation for Software Product Lines based on Quality-Diversity Optimisation" 1. OnlineSupplement.pdf------Online supplementary data for the paper 2. RQ1-4.rar----Raw data for the paper Source code of the algorithms used to produce these data can be found at GitHub https://github.com/gzhuxiangyi/SPLTestingMAP
DOI: 10.5281/zenodo.8173441
title: Supplementary Materials and Raw Data for "Automated Test Suite Generation for Software Product Lines based on Quality-Diversity Optimisation"

description: Supplementary Materials and Raw Data for "Automated Test Suite Generation for Software Product Lines based on Quality-Diversity Optimisation" 1. OnlineSupplement.pdf------Online supplementary data for the paper 2. RQ1-4.rar----Raw data for the paper 3. Runtime to generate, optimise and execution test suites.xlsx -----Data used in Section 7 PRACTICAL IMPLICATIONS Source code of the algorithms used to produce these data can be found at GitHub https://github.com/gzhuxiangyi/SPLTestingMAP
DOI: 10.5281/zenodo.8174962
title: Temperament and Character Traits, Alexithymia Levels, and Attachment Styles in Children and Adolescents with Primary Headaches

description: This is the data that supports my research findings for my article.
DOI: 10.5281/zenodo.8174961
title: Temperament and Character Traits, Alexithymia Levels, and Attachment Styles in Children and Adolescents with Primary Headaches

description: This is the data that supports my research findings for my article.
DOI: 10.5281/zenodo.8174967
title: CoastSeg: estimate of zone of potential shoreline change, California and southeast USA Atlantic (FL, GA, SC, NC), in geoJSON format.

description: <em><strong>CoastSeg: estimate of zone of potential shoreline change, California and southeast USA Atlantic (FL, GA, SC, NC), in geoJSON format.</strong></em> Data have been made by Daniel Buscombe, Marda Science. Data cover the shorelines of five states A single geoJSON file per region. Data outline the extent of potential shoreline change. A 30-m vector defining the average shoreline, and a 30-m vector defining the limit of erodible material, were constructed and merged, then buffered, and manually edited. It is designed to be used in conjunction with the program CoastSeg https://github.com/Doodleverse/CoastSeg , for masking shoreline estimates outside of reasonable spatial bounds.
DOI: 10.5281/zenodo.8174966
title: CoastSeg: estimate of zone of potential shoreline change, California and southeast USA Atlantic (FL, GA, SC, NC), in geoJSON format.

description: <em><strong>CoastSeg: estimate of zone of potential shoreline change, California and southeast USA Atlantic (FL, GA, SC, NC), in geoJSON format.</strong></em> Data have been made by Daniel Buscombe, Marda Science. Data cover the shorelines of five states A single geoJSON file per region. Data outline the extent of potential shoreline change. A 30-m vector defining the average shoreline, and a 30-m vector defining the limit of erodible material, were constructed and merged, then buffered, and manually edited. It is designed to be used in conjunction with the program CoastSeg https://github.com/Doodleverse/CoastSeg , for masking shoreline estimates outside of reasonable spatial bounds.
DOI: 10.34740/kaggle/dsv/6179403
title: Nepse floorsheet data
DOI: 10.6084/m9.figshare.23536374.v2
title: Critical current characterisation of Faraday Factory Japan YBCO 2G HTS superconducting wire

description: Detailed measurements of the critical current of a commercial 2G HTS REBCO wire as a function of temperature, magnetic field, and field angle, performed at the Robinson Research Institute of Victoria University of Wellington. <br>
DOI: 10.5281/zenodo.8173634
title: Model Weights for FLAG on the FIN10K Dataset

description: Model weights for FLAG on the FIN10K dataset, including GCN, GAT, GIN, PNA, and GATv2 variants. Files are in pytorch ".pt" format.
DOI: 10.5281/zenodo.8173633
title: Model Weights for FLAG on the FIN10K Dataset

description: Model weights for FLAG on the FIN10K dataset, including GCN, GAT, GIN, PNA, and GATv2 variants. Files are in pytorch ".pt" format.