cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5255/ukda-sn-855729
title: COVID-19 and Rough Sleepers: A Pilot Randomised Controlled Trial of Models of Housing and Support To Reduce Risks of COVID-19 Infection and Homelessness: Moving On Study, 2020-2022

description: This trial outlines a unique time limited opportunity to conduct the first ever randomised controlled trial in the UK, to evaluate the feasibility and acceptability of randomising participants to Settled Accommodation (SA) or Temporary Accommodation (TA) with the aim of preventing COVID-19 infection and reducing housing instability. The study’s primary objectives were to assess the following: 1. The feasibility of recruiting local authorities and eligible participants to the study. 2. Recruitment rates of participants and retention through 3 months and 6 months post randomisation follow-up data collection. 3. The acceptability of the study and its processes, including randomisation, to single homeless households and local authorities and their willingness to participate in a definitive trial. In addition, the study also aims to assess the following Secondary objectives: 1. Adherence to the study allocation, reach and fidelity (i.e. whether SA is delivered as intended, works as hypothesized, is scalable and sustainable). 2. The feasibility and acceptability of proposed outcome measures for a definitive trial, including resource use and health-related quality of life data, as methods to measure effectiveness of the intervention and to conduct an embedded health economic evaluation within a definitive RCT. 3. The feasibility and acceptability of linkage to routinely collected data within a definitive RCT by assessing whether (a) participants are willing to consent for their data to be linked and (b) personal identifiers can be linked to NHS Digital routine datasets. Quantitative data was collected at baseline and follow-up at 3 and 6 months. 50 participants were invited to complete outcome measures. These participants completed the questionnaire over the telephone with trained members of staff based at the University. Data was entered into Qualtrics application system and used to collect consent and questionnaire response data. The trial explored past and current experiences of homeless individuals in relation to a range of life domains, including; housing, health, adverse life experiences such as imprisonment, and substance misuse. Participants were also invited to take part in qualitative interviews to discuss the acceptability of the study and its processes, including randomisation, and their willingness to participate in a definitive trial. They were also asked about their experience of services and provision. Data from 14 participants and 1 researcher in the Moving On Study was gathered.
DOI: 10.6084/m9.figshare.19653993.v3
title: Durations of Mitosis and Cytokinesis for Control & TTFields-Exposed HeLa and MCF-10A Cells

description: Data obtained in live-cell imaging experiments with HeLa cells exposed to TTFields using the Novocure inovitro live system. The data was analyzed to determine the durations of mitosis and cytokinesis in both unexposed and TTFields-exposed HeLa and MCF-10A cells.
DOI: 10.6084/m9.figshare.19626690.v3
title: Supplementary Table 1

description: List of eligible studies, variables description, and statistical models
DOI: 10.5066/p94gugib
title: Ecological modeling output for the Lake Okeechobee System Operating Manual iterations 1 and 2 (of 3), 2021

description: Ecological models facilitate the evaluation and assessment of alternative approaches to restore the Greater Everglades ecosystem. Joint Ecosystem Modeling (JEM) provides ecological models tailored to address specific management issues. The multi-agency REstoration, COordination and VERification (RECOVER) science team uses ecological models (i.e., ecological planning tools) to evaluate the potential effects of projects in the Comprehensive Everglades Restoration Plan (CERP) on natural resources. The planning agencies and bureaus involved in CERP desire to also use these ecological planning tools for the evaluation of alternative water control plans to be performed by the Lake Okeechobee System Operating Manual (LOSOM) Project Delivery [...]
DOI: 10.6084/m9.figshare.20737885
title: wug.csv

description: Data on the performance of monolingual Italian children with and without dyslexia in morphological awareness tasks eliciting inflection or derivation of nonwords modeled after Italian
DOI: 10.6084/m9.figshare.20737885.v1
title: wug.csv

description: Data on the performance of monolingual Italian children with and without dyslexia in morphological awareness tasks eliciting inflection or derivation of nonwords modeled after Italian
DOI: 10.6084/m9.figshare.20751103
title: data palinuro organized.xlsx

description: This dataset represents a monitoring study conducted in Cape Palinuro, Souther Italy. The study was about the distribution of Euphorbia dendroides in a mixed-species grassland.
DOI: 10.5281/zenodo.6303947
title: Long-read DNA-Seq of SmAP1 knockout strains

description: Halobacterium salinarum knockout strains (delta-Ura3: control; delta-Ura3/delta-SmAP1: SmAP1 knockout) were cultured in uracil-supplemented (50 μg/mL) complex medium (CM) until mid-exponential phase (OD600nm = 0.5). The cultures were grown at 37C, under light exposure, and with constant agitation (125 RPM). We collected 2 mL samples and submitted them to DNA extraction using the DNeasy Blood & Tissue kit (QIAGEN), according to the manufacturer's instructions for Gram-negative bacteria. We tested DNA samples for purity and quantity using spectrophotometric and fluorimetric methods, respectively. The samples were prepared for long-read sequencing following the 1D native barcoding genomic DNA protocol using SQK-LSK108 and EXP-NBD103 (Oxford Nanopore Technologies). The equimolar pool of barcoded samples was sequenced using a MinION Mk1B instrument (Oxford Nanopore Technologies) in an FLO-MIN106 flow cell for 24 hours. Three biological replicates were sequenced for each one of the strains (control and SmAP1 knockout). This repository stores the partitioned (eleven parts: aa-ak) compressed directory (tar.gz) containing all the raw reads (fast5 format) output by the MinKNOW software. <strong>Experimental design:</strong> <strong>Barcode</strong> <strong>Description</strong> Barcode 01 Control, biological replicate 1 Barcode 02 Control, biological replicate 2 Barcode 03 Control, biological replicate 3 Barcode 04 SmAP1 knockout, biological replicate 1 Barcode 05 SmAP1 knockout, biological replicate 2 Barcode 06 SmAP1 knockout, biological replicate 3 <strong>Instructions to merge files and extract:</strong> 1. Download all the files available in this Zenodo entry (smap1_ko_exp_fast5.tar.gz.part_a*; from aa to ak; eleven files) to your preferred directory; 2. Execute the following commands using a Linux or OSX terminal: <pre><code class="language-bash"># concatenate all the files into a single one cat smap1_ko_exp_fast5.tar.gz.part_a* &gt; smap1_ko_exp_fast5.tar.gz # extract the merged file tar zxvf smap1_ko_exp_fast5.tar.gz</code></pre>
DOI: 10.5281/zenodo.6303948
title: Long-read DNA-Seq of SmAP1 knockout strains

description: Halobacterium salinarum knockout strains (delta-Ura3: control; delta-Ura3/delta-SmAP1: SmAP1 knockout) were cultured in uracil-supplemented (50 μg/mL) complex medium (CM) until mid-exponential phase (OD600nm = 0.5). The cultures were grown at 37C, under light exposure, and with constant agitation (125 RPM). We collected 2 mL samples and submitted them to DNA extraction using the DNeasy Blood & Tissue kit (QIAGEN), according to the manufacturer's instructions for Gram-negative bacteria. We tested DNA samples for purity and quantity using spectrophotometric and fluorimetric methods, respectively. The samples were prepared for long-read sequencing following the 1D native barcoding genomic DNA protocol using SQK-LSK108 and EXP-NBD103 (Oxford Nanopore Technologies). The equimolar pool of barcoded samples was sequenced using a MinION Mk1B instrument (Oxford Nanopore Technologies) in an FLO-MIN106 flow cell for 24 hours. Three biological replicates were sequenced for each one of the strains (control and SmAP1 knockout). This repository stores the partitioned (eleven parts: aa-ak) compressed directory (tar.gz) containing all the raw reads (fast5 format) output by the MinKNOW software. <strong>Experimental design:</strong> <strong>Barcode</strong> <strong>Description</strong> Barcode 01 Control, biological replicate 1 Barcode 02 Control, biological replicate 2 Barcode 03 Control, biological replicate 3 Barcode 04 SmAP1 knockout, biological replicate 1 Barcode 05 SmAP1 knockout, biological replicate 2 Barcode 06 SmAP1 knockout, biological replicate 3 <strong>Instructions to merge files and extract:</strong> 1. Download all the files available in this Zenodo entry (smap1_ko_exp_fast5.tar.gz.part_a*; from aa to ak; eleven files) to your preferred directory; 2. Execute the following commands using a Linux or OSX terminal: <pre><code class="language-bash"># concatenate all the files into a single one cat smap1_ko_exp_fast5.tar.gz.part_a* &gt; smap1_ko_exp_fast5.tar.gz # extract the merged file tar zxvf smap1_ko_exp_fast5.tar.gz</code></pre>
DOI: 10.22024/unikent/01.01.455
title: Intrinsic Dimension Estimations released for Fondue: an algorithm to find the optimal dimensionality of the latent representations of variational autoencoders

description: This repository contains more than 35,000 intrinsic dimension estimations used in "Fondue: an algorithm to find the optimal dimensionality of the latent representations of variational autoencoders".
DOI: 10.6084/m9.figshare.20751181
title: TIC and ICE Analysis Material

description: Dataset and code used to reproduce figures and tables presented in a paper.
DOI: 10.6084/m9.figshare.20748847
title: Data_logistic regressions_Reproductive Senescence in Polar Bears in a Variable Environment

description: Thise csv files contain the capture data and the environmental data used in the logistic regression of litter production and the logistic regression of litter size. <br> <strong>CR_f_lone_or_w_coys.csv</strong>: includes all females captured alone or with cubs-of-the-year between 2000 and 2022. <br> unique_ID: unique ID of the capture (ID of the bear and date of capture) date: date of capture year: year of capture day_number: day of year of capture (with 1 corresponding to January 1) ID_NR: ID of the bear lat: latitude (decimal degrees) lon: longitude (decimal degrees) age: age at capture s_length: straight line body length cub_status: reproductive status at capture, "n" = no cubs, "c" = with cubs of the year cub_number: number of cubs accompanying the female at capture <br> <br> <strong>CR_f_w_coys.csv</strong>: includes all females captured with cubs-of-the-year between 1992 and 2022 <br> unique_ID: unique ID of the capture (ID of the bear and date of capture) date: date of capture year: year of capture day_number: day of year of capture (with 1 corresponding to January 1) ID_NR: ID of the bear lat: latitude (decimal degrees) lon: longitude (decimal degrees) age: age at capture s_length: straight line body length cub_status: reproductive status at capture, "n" = no cubs, "c" = with cubs of the year cub_number: number of cubs accompanying the female at capture sea <br> <strong>sea_ice_data</strong>: contains the sea ice-related metrics <br> DateBreakUp: day of year (with 1 corresponding to January 1) of sea-ice break-up. DateFreezeUp: day of year (with 1 corresponding to January 1) of sea-ice freeze-up. Values superior to 365 (or 366) indicate that freeze-up occured in the following year. <br> <strong>AO_data</strong>: contains the Arctic Oscillation-related metrics <br> winter_AO: three-month (Jan, Feb, Mar) average of the AO index for year t prior_winter_AO: three-month (Jan, Feb, Mar) average of the AO index for year t-1 prior_spring_AO: three-month (Apr, May, Jun) average of the AO index for year t-1 <br>
DOI: 10.6084/m9.figshare.20748847.v2
title: Data_logistic regressions_Reproductive Senescence in Polar Bears in a Variable Environment

description: Thise csv files contain the capture data and the environmental data used in the logistic regression of litter production and the logistic regression of litter size. <br> <strong>CR_f_lone_or_w_coys.csv</strong>: includes all females captured alone or with cubs-of-the-year between 2000 and 2022. <br> unique_ID: unique ID of the capture (ID of the bear and date of capture) date: date of capture year: year of capture day_number: day of year of capture (with 1 corresponding to January 1) ID_NR: ID of the bear lat: latitude (decimal degrees) lon: longitude (decimal degrees) age: age at capture s_length: straight line body length cub_status: reproductive status at capture, "n" = no cubs, "c" = with cubs of the year cub_number: number of cubs accompanying the female at capture <br> <br> <strong>CR_f_w_coys.csv</strong>: includes all females captured with cubs-of-the-year between 1992 and 2022 <br> unique_ID: unique ID of the capture (ID of the bear and date of capture) date: date of capture year: year of capture day_number: day of year of capture (with 1 corresponding to January 1) ID_NR: ID of the bear lat: latitude (decimal degrees) lon: longitude (decimal degrees) age: age at capture s_length: straight line body length cub_status: reproductive status at capture, "n" = no cubs, "c" = with cubs of the year cub_number: number of cubs accompanying the female at capture sea <br> <strong>sea_ice_data</strong>: contains the sea ice-related metrics <br> DateBreakUp: day of year (with 1 corresponding to January 1) of sea-ice break-up. DateFreezeUp: day of year (with 1 corresponding to January 1) of sea-ice freeze-up. Values superior to 365 (or 366) indicate that freeze-up occured in the following year. <br> <strong>AO_data</strong>: contains the Arctic Oscillation-related metrics <br> winter_AO: three-month (Jan, Feb, Mar) average of the AO index for year t prior_winter_AO: three-month (Jan, Feb, Mar) average of the AO index for year t-1 prior_spring_AO: three-month (Apr, May, Jun) average of the AO index for year t-1 <br>
DOI: 10.6084/m9.figshare.20748847.v1
title: Data_logistic regressions_Reproductive Senescence in Polar Bears in a Variable Environment

description: Thise csv files contain the capture data and the environmental data used in the logistic regression of litter production and the logistic regression of litter size. <br> <strong>CR_f_lone_or_w_coys.csv</strong>: includes all females captured alone or with cubs-of-the-year between 2000 and 2022. <br> unique_ID: unique ID of the capture (ID of the bear and date of capture) date: date of capture year: year of capture day_number: day of year of capture (with 1 corresponding to January 1) ID_NR: ID of the bear lat: latitude (decimal degrees) lon: longitude (decimal degrees) age: age at capture s_length: straight line body length cub_status: reproductive status at capture, "n" = no cubs, "c" = with cubs of the year cub_number: number of cubs accompanying the female at capture <br> <br> <strong>CR_f_w_coys.csv</strong>: includes all females captured with cubs-of-the-year between 1992 and 2022 <br> unique_ID: unique ID of the capture (ID of the bear and date of capture) date: date of capture year: year of capture day_number: day of year of capture (with 1 corresponding to January 1) ID_NR: ID of the bear lat: latitude (decimal degrees) lon: longitude (decimal degrees) age: age at capture s_length: straight line body length cub_status: reproductive status at capture, "n" = no cubs, "c" = with cubs of the year cub_number: number of cubs accompanying the female at capture sea <br> <strong>sea_ice_data</strong>: contains the sea ice-related metrics <br> DateBreakUp: day of year (with 1 corresponding to January 1) of sea-ice break-up. DateFreezeUp: day of year (with 1 corresponding to January 1) of sea-ice freeze-up. Values superior to 365 (or 366) indicate that freeze-up occured in the following year. <br> <strong>AO_data</strong>: contains the Arctic Oscillation-related metrics <br> winter_AO: three-month (Jan, Feb, Mar) average of the AO index for year t prior_winter_AO: three-month (Jan, Feb, Mar) average of the AO index for year t-1 prior_spring_AO: three-month (Apr, May, Jun) average of the AO index for year t-1 <br>
DOI: 10.5281/zenodo.5988170
title: Responsive Environmental Assessment Commercially Hosted (REACH)

description: This is the historical REACH data release. These are the “v3” files produced at The Aerospace Corporation, spanning March 2017 until December 2019. It is accompanied by a README (PDF), which includes a brief mission description, describes the features of the collection of dosimeters, discusses data availability throughout the dataset, describes data quality flags, and concludes with a data dictionary.
description: {"references": ["https://ui.adsabs.harvard.edu/#abs/2020AGUFMSM0030016G/abstract", "https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/212711"]}
DOI: 10.5281/zenodo.5988171
title: Responsive Environmental Assessment Commercially Hosted (REACH)

description: This is the historical REACH data release. These are the “v3” files produced at The Aerospace Corporation, spanning March 2017 until December 2019. It is accompanied by a README (PDF), which includes a brief mission description, describes the features of the collection of dosimeters, discusses data availability throughout the dataset, describes data quality flags, and concludes with a data dictionary.
description: {"references": ["https://ui.adsabs.harvard.edu/#abs/2020AGUFMSM0030016G/abstract", "https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/212711"]}
DOI: 10.5281/zenodo.6423507
title: Responsive Environmental Assessment Commercially Hosted (REACH)

description: This is the historical REACH data release. These are the “v3” files produced at The Aerospace Corporation, spanning March 2017 until December 2019. It is accompanied by a README (PDF), which includes a brief mission description, describes the features of the collection of dosimeters, discusses data availability throughout the dataset, describes data quality flags, and concludes with a data dictionary.
description: {"references": ["https://ui.adsabs.harvard.edu/#abs/2020AGUFMSM0030016G/abstract", "https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/212711"]}
DOI: 10.5281/zenodo.7038285
title: Responsive Environmental Assessment Commercially Hosted (REACH)

description: This is the historical REACH data release. These are the “v3” files produced at The Aerospace Corporation, spanning March 2017 until December 2019. It is accompanied by a README (PDF), which includes a brief mission description, describes the features of the collection of dosimeters, discusses data availability throughout the dataset, describes data quality flags, and concludes with a data dictionary.
description: {"references": ["https://ui.adsabs.harvard.edu/#abs/2020AGUFMSM0030016G/abstract", "https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/212711"]}
DOI: 10.6084/m9.figshare.20526876
title: Social Media Study EJIS

description: Data for Submission
DOI: 10.6084/m9.figshare.20526876.v4
title: Social Media Study EJIS

description: Data for Submission
DOI: 10.5281/zenodo.7038304
title: Data belonging to the article "Syllabification in Language Contact between French and Vietnamese"

description: This dataset belongs to an article which will appear in the ICAAL 8 conference proceedings and which is dedicated to the syllabification in two language contact settings between Vietnamese and French. The paper discusses gemination and related phenomena. First, it contributes to the theoretical discussion on borrowing processes in loanwords and presents a model that includes all extant views and also accounts for other language contact situations. In our data analysis, we compare loan data to experimental data, and find similar processes in both scenarios. Syllable boundaries are shifted, consonants are geminated and consonant slots are doubled in certain syllabic environments. The emergence of gemination is especially noteworthy as it is only a marginal phenomenon in French and has not been found to exist in Vietnamese. Results provide evidence for our hypothesis that optimal Vietnamese syllables are closed, as these syllables have the highest frequency in the native lexicon. This goes beyond, but also corresponds to the idea that Vietnamese has a dimoraic minimum, and this paper provides more evidence for it.
DOI: 10.5281/zenodo.7038303
title: Data belonging to the article "Syllabification in Language Contact between French and Vietnamese"

description: This dataset belongs to an article which will appear in the ICAAL 8 conference proceedings and which is dedicated to the syllabification in two language contact settings between Vietnamese and French. The paper discusses gemination and related phenomena. First, it contributes to the theoretical discussion on borrowing processes in loanwords and presents a model that includes all extant views and also accounts for other language contact situations. In our data analysis, we compare loan data to experimental data, and find similar processes in both scenarios. Syllable boundaries are shifted, consonants are geminated and consonant slots are doubled in certain syllabic environments. The emergence of gemination is especially noteworthy as it is only a marginal phenomenon in French and has not been found to exist in Vietnamese. Results provide evidence for our hypothesis that optimal Vietnamese syllables are closed, as these syllables have the highest frequency in the native lexicon. This goes beyond, but also corresponds to the idea that Vietnamese has a dimoraic minimum, and this paper provides more evidence for it.
DOI: 10.6084/m9.figshare.20751238
title: POINT_CLOUD_1.pcd

description: Three Point clouds surveyed onto a water tank.
DOI: 10.6084/m9.figshare.20751238.v1
title: POINT_CLOUD_1.pcd

description: Three Point clouds surveyed onto a water tank.
DOI: 10.25574/53751
title: Chandra X-ray Observatory ObsId 53751
DOI: 10.25574/53757
title: Chandra X-ray Observatory ObsId 53757
DOI: 10.25574/53765
title: Chandra X-ray Observatory ObsId 53765
DOI: 10.25574/53771
title: Chandra X-ray Observatory ObsId 53771
DOI: 10.25574/53774
title: Chandra X-ray Observatory ObsId 53774
DOI: 10.25574/53779
title: Chandra X-ray Observatory ObsId 53779
DOI: 10.25574/53786
title: Chandra X-ray Observatory ObsId 53786
DOI: 10.25574/53792
title: Chandra X-ray Observatory ObsId 53792
DOI: 10.25574/53808
title: Chandra X-ray Observatory ObsId 53808
DOI: 10.25574/53814
title: Chandra X-ray Observatory ObsId 53814
DOI: 10.25574/53820
title: Chandra X-ray Observatory ObsId 53820
DOI: 10.25574/53836
title: Chandra X-ray Observatory ObsId 53836
DOI: 10.25574/53844
title: Chandra X-ray Observatory ObsId 53844
DOI: 10.25574/53846
title: Chandra X-ray Observatory ObsId 53846
DOI: 10.25574/53852
title: Chandra X-ray Observatory ObsId 53852
DOI: 10.25574/53861
title: Chandra X-ray Observatory ObsId 53861
DOI: 10.25574/53876
title: Chandra X-ray Observatory ObsId 53876
DOI: 10.25574/53878
title: Chandra X-ray Observatory ObsId 53878
DOI: 10.25574/53883
title: Chandra X-ray Observatory ObsId 53883
DOI: 10.25574/53898
title: Chandra X-ray Observatory ObsId 53898
DOI: 10.25574/53906
title: Chandra X-ray Observatory ObsId 53906
DOI: 10.25574/53909
title: Chandra X-ray Observatory ObsId 53909
DOI: 10.25574/53915
title: Chandra X-ray Observatory ObsId 53915
DOI: 10.25574/53923
title: Chandra X-ray Observatory ObsId 53923
DOI: 10.25574/53931
title: Chandra X-ray Observatory ObsId 53931
DOI: 10.25574/53939
title: Chandra X-ray Observatory ObsId 53939
DOI: 10.25574/53946
title: Chandra X-ray Observatory ObsId 53946