cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8211915
title: Microtremors Data Archive of the 2015 and 2018 NSET – OGS Surveys in Nepal

description: This report describes the datasets of microtremor surveys on the two 2015 and 2018 missions of the National Institute of Oceanography and Applied Geophysics – OGS conducted with National Society for Earthquake Technology – NSET in Nepal at the Kathmandu Basin (2015, 2018) and at two locations: Bharatpur and Damauli (2018). The two institutions involved partly supported the surveys. This work was also partially supported by the FVG Region (Friuli Venezia Giulia - Italy), Regional Law 19/2000, International Development Cooperation and Partnership Activities 2014 – 2017, Decree no. 1134/SG 11.27.2017, pre-number 1010, project IN-EPAL (Iniziativa di Empowerment e Protezione Ambientale Locale). The archive consists of point measurements of seismic noise for Horizontal Vertical Spectral Ratio (HVSR) analysis and array measurements for seismic wave analysis.
DOI: 10.5281/zenodo.8211914
title: Microtremors Data Archive of the 2015 and 2018 NSET – OGS Surveys in Nepal

description: This report describes the datasets of microtremor surveys on the two 2015 and 2018 missions of the National Institute of Oceanography and Applied Geophysics – OGS conducted with National Society for Earthquake Technology – NSET in Nepal at the Kathmandu Basin (2015, 2018) and at two locations: Bharatpur and Damauli (2018). The two institutions involved partly supported the surveys. This work was also partially supported by the FVG Region (Friuli Venezia Giulia - Italy), Regional Law 19/2000, International Development Cooperation and Partnership Activities 2014 – 2017, Decree no. 1134/SG 11.27.2017, pre-number 1010, project IN-EPAL (Iniziativa di Empowerment e Protezione Ambientale Locale). The archive consists of point measurements of seismic noise for Horizontal Vertical Spectral Ratio (HVSR) analysis and array measurements for seismic wave analysis.
DOI: 10.6084/m9.figshare.23620752
title: Raw data from analyses reported in Heuer et al, 2023 synaptic aging manuscript

description: All data corresponding to Heuer et al 2023 synaptic aging manuscript
DOI: 10.6084/m9.figshare.23620752.v1
title: Raw data from analyses reported in Heuer et al, 2023 synaptic aging manuscript

description: All data corresponding to Heuer et al 2023 synaptic aging manuscript
DOI: 10.25345/c5vm4373t
title: MassIVE MSV000092585 - Enhanced Characterization of Lysine-Linked Antibody Drug Conjugates Enabled by Middle-Down Mass Spectrometry
title: HCD Triggered UVPD and EThcD files for characterization of trastuzumab-emtansine (T-DM1)
DOI: 10.5281/zenodo.8135615
title: Dataset for "The causal role of vision in the development of spatial coordinates: Evidence from visually impaired children."

description: Datasets for the paper "The development of allocentric spatial frame in the auditory system":
DOI: 10.5281/zenodo.8135616
title: Dataset for "The causal role of vision in the development of spatial coordinates: Evidence from visually impaired children."

description: Datasets for the paper "The development of allocentric spatial frame in the auditory system":
DOI: 10.5281/zenodo.7199175
title: Effects of audio-motor training on spatial representations in long-term late blindness

description: Datasets for behavioural data: -<em>Auditory horizontal localization task</em> - <em>Auditory vertical localization task</em> - <em>Position matching task</em> - <em>Proprioceptive midline task</em> Dataset for EEG data: - Spatial bisection task: mean ERP amplitude for 50-90ms timew window for each trial, separately for condition, session and roi
DOI: 10.5281/zenodo.7199176
title: Effects of audio-motor training on spatial representations in long-term late blindness

description: Datasets for behavioural data: -<em>Auditory horizontal localization task</em> - <em>Auditory vertical localization task</em> - <em>Position matching task</em> - <em>Proprioceptive midline task</em> Dataset for EEG data: - Spatial bisection task: mean ERP amplitude for 50-90ms timew window for each trial, separately for condition, session and roi
DOI: 10.5281/zenodo.5913237
title: The Development of Adaptation Aftereffects in the Vibrotactile Domain

description: Dataset for the study "The Development of Adaptation Aftereffects in the Vibrotactile Domain".
DOI: 10.5281/zenodo.5913238
title: The Development of Adaptation Aftereffects in the Vibrotactile Domain

description: Dataset for the study "The Development of Adaptation Aftereffects in the Vibrotactile Domain".
DOI: 10.6084/m9.figshare.23834838.v1
title: README file

description: Read me for info on raw dataset
DOI: 10.17894/ucph.f4ed5a3a-af63-4253-99f5-ba0cbd2f31dc
title: Data for Effects of biobased fertilisers on soil physical chemical and biological indicators
DOI: 10.5281/zenodo.8211987
title: spinus_lawrencei_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8211986
title: spinus_lawrencei_spades_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23791719.v2
title: Full genome tailed amplification of arboviruses - protocols

description: Description of the protocols developed within the WallauLab for tailed amplicon sequencing of arboviruses. We tested them using either Nextera Flex or CovidSeq library preparation protocols from Illumina, but it should also work with other NGS platforms and library prep kits.
DOI: 10.25934/pr00007929.2
title: Available datapackage for dataset 'ATLAS_Antifungals'

description: Primary Objective The ATLAS programme monitors changes in antibiotic susceptibility, bacterial resistance trends and emergence of new resistance mechanism for both marketed and in development antibiotics.  In addition, provides genotypic information when tested.  The SENTRY platform data allow for monitoring of antifungal susceptibility and resistance trending of key antifungals.
description: The ATLAS programme is one overall study (formerly TEST, INFORM and AWARE) fulfilling regulatory requirements and supporting appropriate use measures for both marketed antibiotics (Tygacil, Zyvox, Zosyn/Tazocin, Zavicefta, Zinforo, Merrem and others)  by monitoring changes in antibiotic susceptibility, bacterial resistance trends and emergence of new resistance mechanisms.   CLSI breakpoints are utilized but the option exists to analyse the data by using EUCAST breakpoints.   All bacterial isolate identifications and susceptibility profiles are performed by standardized broth microdilution methods by a central lab.  The antifungal data from the SENTRY platform are generated by standardized antifungal susceptibility methods performed at a central laboratory.
DOI: 10.5281/zenodo.8167571
title: Pathways to enhance electrochemical CO2 reduction identified through direct pore-level modeling (data for figures)

description: This is the data used to create the figures in the article "Pathways to enhance electrochemical CO2 reduction identified through direct pore-level modeling". Published in EES Catalysis DOI: 10.1039/d3ey00122a<br> Evan Johnson<br> Etienne Boutin<br> Shuo Liu<br> Sophia Haussener <br> Additional notes are given in the "ReadMe.txt" file.
DOI: 10.5281/zenodo.8167572
title: Pathways to enhance electrochemical CO2 reduction identified through direct pore-level modeling (data for figures)

description: This is the data used to create the figures in the article "Pathways to enhance electrochemical CO2 reduction identified through direct pore-level modeling". Published in EES Catalysis DOI: 10.1039/d3ey00122a<br> Evan Johnson<br> Etienne Boutin<br> Shuo Liu<br> Sophia Haussener <br> Additional notes are given in the "ReadMe.txt" file.
DOI: 10.5281/zenodo.8212032
title: database_caa_ucv

description: This database contains personal data of patients that have received a diagnosis of CAA (cerebral amyloid angiopathy). It includes personal data (e.g. demographics), clinical data (e.g. clinical scales), data regarding medical examination results (e.g. mri data), cognitive data (e.g. neurocognitive tests). The database will be used within the project STRATIF-AI.
DOI: 10.5281/zenodo.8212031
title: database_caa_ucv

description: This database contains personal data of patients that have received a diagnosis of CAA (cerebral amyloid angiopathy). It includes personal data (e.g. demographics), clinical data (e.g. clinical scales), data regarding medical examination results (e.g. mri data), cognitive data (e.g. neurocognitive tests). The database will be used within the project STRATIF-AI.
DOI: 10.6084/m9.figshare.23812830.v37
title: Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiratio

description: Regridding Global CMIP6 GCMs dataset(0.5 degree)Historical dataset:14 CMIP6 GCMs (1850-2014)Future dataset: 14CMIP6 GCMs and 4 SSP scenarios (2015-2100)Composition of dataset: Average temperature, Maximum temperature, Minimum temperature, Windspeed, Relative humidity, Solar radiationIf you are using our codes and dataset, please use the following references:Song, Y.H., Chung, E.S., Shahid, S., Kim, Y.J., Kim, D.K. 2023. Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiration. Scientific Data.<br>
DOI: 10.5281/zenodo.8212044
title: MLS Stakeholder Responses on Youth-to-Senior Transition

description: Survey responses from MLS stakeholders on youth-to-senior transition.
DOI: 10.5281/zenodo.8212043
title: MLS Stakeholder Responses on Youth-to-Senior Transition

description: Survey responses from MLS stakeholders on youth-to-senior transition.
DOI: 10.7910/dvn/gxlzxf/3nonuy
title: AIRBNB.Documentation.pdf

description: This file contains documentation for the Airbnb data files.
DOI: 10.7910/dvn/gxlzxf/4pumkk
title: AIRBNB.Listing.csv

description: This is a listing-level file including variables derived from Airbnb listings and other relevant information collected by Inside Airbnb. Data is in a tabular format.
DOI: 10.7910/dvn/gxlzxf/sccmcf
title: AIRBNB.CT.tab

description: This is a census tract-level file that contains neighborhood ecometrics generated from Airbnb listings in a tabular format.
DOI: 10.7910/dvn/gxlzxf/za7oaw
title: AIRBNB.CT.zip

description: This is a census tract-level shapefile that contains neighborhood ecometrics generated from Airbnb listings in a spatial format.
DOI: 10.25430/researchdata.cab.unipd.it.00000972
title: Klinefelter

description: database of Klinefelter diagnosis communication
DOI: 10.5281/zenodo.8212054
title: database_moyamoya_ucv

description: this database contains personal data of patients who suffer from Moyamoya disease, some of them had neurosurgery. It includes personal data (e.g. demographics), clinical data (e.g. clinical scales), data regarding medical examinations, data regarding the surgical intervention (e.g. intervention type), cognitive data (e.g. neurocognitive tests), psychological data (e.g. derived from psychological tests). The database will be used within the project STRATIF-AI
DOI: 10.5281/zenodo.8212053
title: database_moyamoya_ucv

description: this database contains personal data of patients who suffer from Moyamoya disease, some of them had neurosurgery. It includes personal data (e.g. demographics), clinical data (e.g. clinical scales), data regarding medical examinations, data regarding the surgical intervention (e.g. intervention type), cognitive data (e.g. neurocognitive tests), psychological data (e.g. derived from psychological tests). The database will be used within the project STRATIF-AI
DOI: 10.34740/kaggle/dsv/6243184
title: Mahanagar Yatayat Transport Dataset
DOI: 10.6084/m9.figshare.22802432.v1
title: <strong>One high-quality genome and two transcriptome datasets for two new species of </strong><em><strong>Mantamonas</strong></em><strong>, a deep-branching eukaryote clade</strong>

description: Genome assembly of the nuclear genome of <em>Mantamonas sphyraenae</em> and gene prediction files generated by Braker2 using RNA seq data and proteins as extrinsic evidence. <br> Cleaned transcript sequences of <em>Mantamonas sphyraenae and M. vickermani</em> and candidate coding regions within predicted using Transdecoder v5.5.0 <br> Phylogenomic datasets, concatenated alignment and trees for CRuMs.
DOI: 10.6084/m9.figshare.23835762
title: sorted_RNA_NYU209_S1.bw

description: sorted_RNA_NYU209_S1.bw
DOI: 10.6084/m9.figshare.23835762.v1
title: sorted_RNA_NYU209_S1.bw

description: sorted_RNA_NYU209_S1.bw
DOI: 10.15454/jb2wce/asesex
title: wpo.owl

description: :unav
DOI: 10.57745/deugbx
title: wpo.rdf

description: WPO in RDF format, generated from the Crop Ontology website
DOI: 10.57745/esxoq2
title: wpo.xls

description: WPO in Crop Ontology format, coming from the WPO GIT repository (https://forgemia.inra.fr/urgi-is/ontologies)
DOI: 10.57745/mlf7s3
title: wpo.owl

description: WPO in OWL format, coming from the WPO GIT repository (https://forgemia.inra.fr/urgi-is/ontologies)
DOI: 10.48366/r604077
title: A Catalog of Meta's LLaMA Models

description: In the spirit of building LLMs, Meta AI first introduced LLaMA-1 which was released under a non-commercial license. In subsequent work, Meta AI introduced open-sourced Llama 2 and Llama 2-Chat. Crucially, both models are open sourced with license that authorizes commercial use, marking a significant stride towards fostering transparency and promoting the development of more responsible, replicable LLMs. Evaluation comparisons of open-source models, including Llama 1, Llama 2 base models, MPT (MosaicML), and Falcon on standard academic benchmarks indicate that Llama 2 outperforms other models including Llama 1. This comparison showcases Llama 1 versus 2 on their essential characteristics.
DOI: 10.5281/zenodo.8211425
title: Learning to Isolate Muons in Data

description: This dataset corresponds to "Learning to Isolate Muons in Data" (2306.15737) and is meant for use with the code at https://github.com/Edwit4/learning_to_isolate_muons_in_data/.
DOI: 10.5281/zenodo.8211424
title: Learning to Isolate Muons in Data

description: This dataset corresponds to "Learning to Isolate Muons in Data" (2306.15737) and is meant for use with the code at https://github.com/Edwit4/learning_to_isolate_muons_in_data/.
DOI: 10.5281/zenodo.7881098
title: MBC and ECBL Libraries: outstanding tools for drug discovery

description: Data and scripts to reproduce all the graphics reported in the Manuscript entitled: "MBC and ECBL Libraries: outstanding tools for drug discovery". <strong>List of analyzed DBs:</strong> MBC2016 (Total entries: 1,096 cmpds; 7.39% excluded from properties analysis - QikProp failure). MBC2022 (Total entries: 2,577 cmpds; 3.14% excluded from properties analysis - QikProp failure). ECBL (Total entries: 101,021 cmpds; 0.20% excluded from properties analysis - QikProp failure). ChEMBL v.31 (Total entries 1,908,325 cmpds; 2.97% excluded from properties analysis - QikProp failure). DrugBank v.5.0 (Total entries 10,981 cmpds; 4.13% excluded from properties analysis - QikProp failure). ZINC20 (Total entries 10,723,360 cmpds; 0.61% excluded from properties analysis - QikProp failure). <strong>Files:</strong> <em>QikProp_properties.docx</em>: doc file containing the full list of QikProp properties calculated for each analyzed DB. <em>DATA_comparison.xlsx</em>: excel file containing data used to reproduce plots in <strong>Figure 4</strong> of the MS. <em>Murcko_scaffold_percentages</em>: distribution (%) of the first 50 most populated Murcko scaffolds for MBC2016, MBC2022 and ECBL. <em>Murcko_scaffolds_comparison</em>: distribution (count) of the first 94 common Murcko scaffolds for MBC2016, MBC2022 and ECBL. QikProp properties for all the analyzed DBs (6 files; CSV format). SMILES codes for all the analyzed DBs (6 files; SMI format). <em>joinplots.py</em>: python script to generate the 2D plots in <strong>Figure 2</strong> of the MS. <em>fingerprint_similarity.py</em>: python script to run and generate the Tanimoto similarity plots in <strong>Figure 3</strong> of the MS. <em>calc_kde.py</em>: python script to run kernel density analysis reported in <strong>Figure 5 </strong>of the MS.
DOI: 10.5281/zenodo.8179223
title: MBC and ECBL Libraries: outstanding tools for drug discovery

description: <strong>UPDATE</strong>. New in this revision: python scripts to process DBs and calculate the percentage of molecules which pass the Veber and Ghose filters. - <em>Veber_filter.py</em> ad <em>Ghose filter.py </em>(data presented in <strong>Table 1 </strong>of the MS). Data and scripts to reproduce all the graphics reported in the Manuscript entitled: "MBC and ECBL Libraries: outstanding tools for drug discovery". <strong>List of analyzed DBs:</strong> MBC2016 (Total entries: 1,096 cmpds; 7.39% excluded from properties analysis - QikProp failure). MBC2022 (Total entries: 2,577 cmpds; 3.14% excluded from properties analysis - QikProp failure). ECBL (Total entries: 101,021 cmpds; 0.20% excluded from properties analysis - QikProp failure). ChEMBL v.31 (Total entries 1,908,325 cmpds; 2.97% excluded from properties analysis - QikProp failure). DrugBank v.5.0 (Total entries 10,981 cmpds; 4.13% excluded from properties analysis - QikProp failure). ZINC20 (Total entries 10,723,360 cmpds; 0.61% excluded from properties analysis - QikProp failure). <strong>Files:</strong> <em>QikProp_properties.docx</em>: doc file containing the full list of QikProp properties calculated for each analyzed DB. <em>DATA_comparison.xlsx</em>: excel file containing data used to reproduce plots in <strong>Figure 4</strong> of the MS. <em>Murcko_scaffold_percentages</em>: distribution (%) of the first 50 most populated Murcko scaffolds for MBC2016, MBC2022 and ECBL. <em>Murcko_scaffolds_comparison</em>: distribution (count) of the first 94 common Murcko scaffolds for MBC2016, MBC2022 and ECBL. QikProp properties for all the analyzed DBs (6 files; CSV format). SMILES codes for all the analyzed DBs (6 files; SMI format). <em>joinplots.py</em>: python script to generate the 2D plots in <strong>Figure 2</strong> of the MS. <em>fingerprint_similarity.py</em>: python script to run and generate the Tanimoto similarity plots in <strong>Figure 3</strong> of the MS. <em>calc_kde.py</em>: python script to run kernel density analysis reported in <strong>Figure 5 </strong>of the MS.
description: Revised version of the original publication.
DOI: 10.6084/m9.figshare.14500248
title: Data Repository: " Too young to die: mapping birthing sites of the endangered sandbar shark (Carcharhinus plumbeus) to inform conservation in the Mediterranean Sea"

description: Data repositorty of manuscript titled "Too young to die: mapping birthing sites of the endangered sandbar shark (Carcharhinus plumbeus) to inform conservation in the Mediterranean Sea" by barbato et al.,<br>
DOI: 10.5281/zenodo.7766597
title: Research Excellence Framework (REF) 2021 enhanced submissions dataset

description: An enhanced version of the public REF 2021 submissions dataset, produced by Jisc, which contains metadata for all outputs submitted to the exercise. Metadata has been cleaned and new fields have been added to increase the potential for analytical purposes, e.g. by identifying where the publisher exists as an imprint of a larger parent company. For its own analytical purposes, Jisc focused on long-form output types (books and parts of books), but cleaning measures were performed on the entire dataset, uploaded here.
DOI: 10.5281/zenodo.7766596
title: Research Excellence Framework (REF) 2021 enhanced submissions dataset

description: An enhanced version of the public REF 2021 submissions dataset, produced by Jisc, which contains metadata for all outputs submitted to the exercise. Metadata has been cleaned and new fields have been added to increase the potential for analytical purposes, e.g. by identifying where the publisher exists as an imprint of a larger parent company. For its own analytical purposes, Jisc focused on long-form output types (books and parts of books), but cleaning measures were performed on the entire dataset, uploaded here.
DOI: 10.25345/c5qv3cd92
title: MassIVE MSV000092586 - QC mix; quality control mix of 6 compounds
title: This is the standard QC 6-six mix as a test. This is just a learning tool.
DOI: 10.22002/csh5w-rf132
title: Index Cases first identified by nasal-swab rapid COVID-19 tests had more transmission to household contacts than Cases identified by other test types
DOI: 10.5281/zenodo.8212104
title: MBC and ECBL Libraries: outstanding tools for drug discovery

description: <strong>UPDATE</strong>. New in this revision: python scripts to process DBs and calculate the percentage of molecules which pass the Veber and Ghose filters. Two new DBs were also added and considered for the analysis. Data and scripts to reproduce all the graphics reported in the Manuscript entitled: "MBC and ECBL Libraries: outstanding tools for drug discovery". <strong>List of analyzed DBs:</strong> MBC2016 (Total entries: 1,096 cmpds; 7.39% excluded from properties analysis - QikProp failure). MBC2022 (Total entries: 2,577 cmpds; 3.14% excluded from properties analysis - QikProp failure). ECBL (Total entries: 101,021 cmpds; 0.20% excluded from properties analysis - QikProp failure). ChEMBL v.31 (Total entries 1,908,325 cmpds; 2.97% excluded from properties analysis - QikProp failure). DrugBank v.5.0 (Total entries 10,981 cmpds; 4.13% excluded from properties analysis - QikProp failure). ZINC20 (Total entries 10,723,360 cmpds; 0.61% excluded from properties analysis - QikProp failure). NuBBE (Total entries 2,223 cmpds) - <strong>NEW</strong> Approved drugs (Total entries: 3,140 cmpds) - <strong>NEW</strong> <strong>Files:</strong> <em>QikProp_properties.docx</em>: doc file containing the full list of QikProp properties calculated for each analyzed DB. <em>DATA_comparison.xlsx</em>: excel file containing data used to reproduce plots in <strong>Figure 4</strong> of the MS. <em>Murcko_scaffold_percentages</em>: distribution (%) of the first 50 most populated Murcko scaffolds for MBC2016, MBC2022 and ECBL. <em>Murcko_scaffolds_comparison</em>: distribution (count) of the first 94 common Murcko scaffolds for MBC2016, MBC2022 and ECBL. QikProp properties for all the analyzed DBs (8 files; CSV format). SMILES codes for all the analyzed DBs (8 files; SMI format). <em>joinplots.py</em>: python script to generate the 2D plots in <strong>Figure 2</strong> of the MS. <em>fingerprint_similarity.py</em>: python script to run and generate the Tanimoto similarity plots in <strong>Figure 3</strong> of the MS. <em>calc_kde.py</em>: python script to run kernel density analysis reported in <strong>Figure 5 </strong>of the MS. <em>Veber_filter.py: python script to generate </em>data presented in <strong>Table 1 </strong>of the MS. <strong>(NEW)</strong> <em>Ghose filter.py: python script to generate </em>data presented in <strong>Table 1 </strong>of the MS. <strong>(NEW)</strong>