cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.2951263.v225
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.6084/m9.figshare.2375476.v1
title: Cross-Sectional Study of Road Accidents and Related Law Enforcement Efficiency for Ten Countries: A Gap Coherence Analysis

description: <i>Objective</i>: Road crashes are considered as the eighth leading causes of death. There is a wide disparity in crash severity and law enforcement efficiency among low, medium and high-income countries. It would be helpful to review the crash severity trends in these countries, identify the vulnerable road users and understand the law enforcement effectiveness for coming up with efficient road safety improvement strategies. <i>Method</i>: The crash severity, fatality rate among various age groups and law enforcement strategies of ten countries representing low-income (i.e. India and Morocco), medium-income (i.e. Argentina, South Korea and Greece) and high-income (i.e. Australia, Canada, France, UK and USA) are studied and compared for a period of five years (i.e. 2008 to 2012). The critical parameters affecting road safety are identified and correlated with education, culture and basic compliance to traffic safety laws. In the process, possible road safety improvement strategies are identified for low-income countries. <i>Result</i>: The number of registered vehicles shows an increasing trend for low-income countries and so does the crash rate and crash severity. Compliance related to seatbelt and helmet law is high in high-income countries. Also, recent seatbelt and helmet related safety programs in middle-income countries helped to curb fatalities. Whereas, the safety law incompliance among low-income countries is attributed to education, culture and inefficient law enforcement. <i>Conclusion</i>: Efficient law enforcement and effective safety education without discounting cultural diversity are the key aspects to reduce traffic related injuries and fatalities in low-income countries like India.
DOI: 10.6084/m9.figshare.2375344
title: Development of cycling skills in 7- to 12-year-old children

description: <b>Objective</b>: Cycling is a complex skill consisting of motor skills such as pedalling, braking, and steering. Because the ability to perform cycling skills is based on the age-related development of the child, experience and age-related reference values are of interest in light of customized testing and training. <b>Methods</b>: One hundred thirty-eight children from the second (7–8 years), fourth (9–10 years), and sixth (11–12 years) grades performed a practical bicycle test consisting of 13 test items with specific points of interest. Moreover, age at onset of cycling, cycling to and from school, independent mobility, and minutes cycling per week were estimated using a parental questionnaire. <b>Results:</b> It is found that cycling skills are strongly related to age with 11- to 12-year-old children outperforming 7- to 8-year-old children for 11 test items and 9- to 10-year-old children for 8 test items. <b>Conclusions</b>: Next to age, age at onset of cycling also contributed to cycling skills. Therefore, our results suggest that cycling skills are associated with physical and mental maturation. Subsequently, age-related reference values are provided to customize testing and training.
DOI: 10.6084/m9.figshare.2885308.v218
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.6084/m9.figshare.2375344.v2
title: Development of cycling skills in 7- to 12-year-old children

description: <b>Objective</b>: Cycling is a complex skill consisting of motor skills such as pedalling, braking, and steering. Because the ability to perform cycling skills is based on the age-related development of the child, experience and age-related reference values are of interest in light of customized testing and training. <b>Methods</b>: One hundred thirty-eight children from the second (7–8 years), fourth (9–10 years), and sixth (11–12 years) grades performed a practical bicycle test consisting of 13 test items with specific points of interest. Moreover, age at onset of cycling, cycling to and from school, independent mobility, and minutes cycling per week were estimated using a parental questionnaire. <b>Results:</b> It is found that cycling skills are strongly related to age with 11- to 12-year-old children outperforming 7- to 8-year-old children for 11 test items and 9- to 10-year-old children for 8 test items. <b>Conclusions</b>: Next to age, age at onset of cycling also contributed to cycling skills. Therefore, our results suggest that cycling skills are associated with physical and mental maturation. Subsequently, age-related reference values are provided to customize testing and training.
DOI: 10.6084/m9.figshare.2951263.v226
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.6084/m9.figshare.2375344.v1
title: Development of cycling skills in 7 to 12-year-old children

description: OBJECTIVE: Cycling is a complex skill consisting of motor skills such as pedalling, braking and steering. As the ability to perform cycling skills is based on the age-related development of the child, experience and age related reference values are of interest in light of customized testing and training. METHODS: 138 children from the 2<sup>nd</sup> (7–8 year), 4<sup>th</sup> (9–10 year) and 6<sup>th</sup> (11–12 year) grade performed a practical bicycle test consisting of thirteen test items with specific points of interest. Moreover, age at onset of cycling, cycling to and from school, independent mobility and minutes cycling per week were estimated using a parental questionnaire. RESULTS: It is found that cycling skills are strongly related to age with 11–12 year old children outperforming 7–8 year old children for 11 test items and 9–10 year old children for 8 test items. CONCLUSIONS: Next to age, age at onset of cycling also contributed to cycling skills. Therefore our results suggest cycling skills to be associated with physical and mental maturation. Subsequently age related reference values are provided to customize testing and training.
DOI: 10.6084/m9.figshare.2885308.v219
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.6084/m9.figshare.2951263.v227
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.6084/m9.figshare.2885308.v220
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.6084/m9.figshare.2375302
title: A data-driven allocation tool for in-kind resources distributed by a state health department

description: <b>Objective</b>: The objective of this study was to leverage a state health department's operational data to allocate in-kind resources (children's car seats) to counties, with the proposition that need-based allocation could ultimately improve public health outcomes. <b>Methods</b>: This study used a retrospective analysis of administrative data on car seats distributed to counties statewide by the Georgia Department of Public Health and development of a need-based allocation tool (presented as interactive supplemental digital content, adaptable to other types of in-kind public health resources) that relies on current county-level injury and sociodemographic data. <b>Results</b>: Car seat allocation using public health data and a need-based formula resulted in substantially different recommended allocations to individual counties compared to historic distribution. <b>Conclusions</b>: Results indicate that making an in-kind public health resource like car seats universally available results in a less equitable distribution of that resource compared to deliberate allocation according to public health need. Public health agencies can use local data to allocate in-kind resources consistent with health objectives; that is, in a manner offering the greatest potential health impact. Future analysis can determine whether the change to a more equitable allocation of resources is also more efficient, resulting in measurably improved public health outcomes.
DOI: 10.6084/m9.figshare.2375302.v2
title: A data-driven allocation tool for in-kind resources distributed by a state health department

description: <b>Objective</b>: The objective of this study was to leverage a state health department's operational data to allocate in-kind resources (children's car seats) to counties, with the proposition that need-based allocation could ultimately improve public health outcomes. <b>Methods</b>: This study used a retrospective analysis of administrative data on car seats distributed to counties statewide by the Georgia Department of Public Health and development of a need-based allocation tool (presented as interactive supplemental digital content, adaptable to other types of in-kind public health resources) that relies on current county-level injury and sociodemographic data. <b>Results</b>: Car seat allocation using public health data and a need-based formula resulted in substantially different recommended allocations to individual counties compared to historic distribution. <b>Conclusions</b>: Results indicate that making an in-kind public health resource like car seats universally available results in a less equitable distribution of that resource compared to deliberate allocation according to public health need. Public health agencies can use local data to allocate in-kind resources consistent with health objectives; that is, in a manner offering the greatest potential health impact. Future analysis can determine whether the change to a more equitable allocation of resources is also more efficient, resulting in measurably improved public health outcomes.
DOI: 10.6084/m9.figshare.2951263.v228
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.6084/m9.figshare.2375302.v1
title: A data-driven allocation tool for in-kind resources distributed by a state health department

description: <b>Objective</b>: The objective of this study was to leverage a state health department's operational data to allocate in-kind resources (children's car seats) to counties, with the proposition that need-based allocation could ultimately improve public health outcomes. <b>Methods</b>: This study used a retrospective analysis of administrative data on car seats distributed to counties statewide by the Georgia Department of Public Health and development of a need-based allocation tool (presented as interactive supplemental digital content, adaptable to other types of in-kind public health resources) that relies on current county-level injury and sociodemographic data. <b>Results</b>: Car seat allocation using public health data and a need-based formula resulted in substantially different recommended allocations to individual counties compared to historic distribution. <b>Conclusions</b>: Results indicate that making an in-kind public health resource like car seats universally available results in a less equitable distribution of that resource compared to deliberate allocation according to public health need. Public health agencies can use local data to allocate in-kind resources consistent with health objectives; that is, in a manner offering the greatest potential health impact. Future analysis can determine whether the change to a more equitable allocation of resources is also more efficient, resulting in measurably improved public health outcomes.
DOI: 10.6084/m9.figshare.2885308.v221
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.7910/dvn/xjlzin/1bktyi
title: dfp_covid_tracking_poll.tab

description: Data file. Includes all waves of tracking poll.
DOI: 10.6084/m9.figshare.2951263.v229
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.6084/m9.figshare.2885308.v222
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.7910/dvn/xjlzin/2rswkq
title: Questionnaire.pdf

description: Questionnaire for the poll.
DOI: 10.6084/m9.figshare.2951263.v230
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.7910/dvn/xjlzin/kjwddf
title: dfp_covid_tracking_poll.tab

description: :unav
DOI: 10.6084/m9.figshare.2885308.v223
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.7910/dvn/xjlzin/yy87a9
title: Survey Questionnaire.pdf

description: Questionnaire for the tracking poll. (Updated on May 19, 2020)
DOI: 10.6084/m9.figshare.2951263.v231
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.7910/dvn/xjlzin/waw6rj
title: dfp_covid_tracking_poll.tab

description: Dataset for the tracking poll. (Included interviews conducted through May 19, 2020).
DOI: 10.7910/dvn/xjlzin/mptfie
title: dfp_covid_tracking_poll.tab

description: Dataset for the tracking poll. (Included interviews conducted through June 9, 2020).
DOI: 10.6084/m9.figshare.2374054.v1
title: Long-term wheel-running and acute 6-h advances alter glucose tolerance and insulin levels in TALLYHO/JngJ mice

description: Studies have shown a relationship between circadian rhythm disruptions and type-2 diabetes. This investigation examined the effects of circadian disruption (6-h phase advances) on the progression of diabetes in a type-2 diabetic mouse model –TALLYHO/JngJ – and whether wheel-running can alleviate the effects of the phase advances. 6-h advances alter fasting glucose, glucose tolerance and insulin production. Wheel-running reduced body mass, improved glucose tolerance and reduced insulin in TALLYHO/JngJ and alleviated some of the changes in diabetic symptoms due to 6-h advances. These results indicate that individuals with type-2 diabetes can benefit from physical activity and exercise can be a countermeasure to offset the effects of an acute phase advance.
DOI: 10.7910/dvn/xjlzin/pwyvaz
title: Survey questionnaire.pdf

description: Questionnaire for the tracking poll (updated on July 7, 2020).
DOI: 10.6084/m9.figshare.2374687.v1
title: <i>MYC</i> and <i>PVT1</i> synergize to regulate RSPO1 levels in breast cancer

description: Copy number gain of the 8q24 region including the v-myc avian myelocytomatosis viral oncogene homolog (<i>MYC)</i> oncogene has been observed in many different cancers and is associated with poor outcomes. While the role of <i>MYC</i> in tumor formation has been clearly delineated, we have recently shown that co-operation between adjacent long non-coding RNA plasmacytoma variant transcription 1 (<i>PVT1)</i> and <i>MYC</i> is necessary for tumor promotion. Chromosome engineered mice containing an increased copy of <i>Myc-Pvt1</i> (Gain <i>Myc-Pvt1</i>) accelerates mammary tumors in <i>MMTV-Neu</i> mice, while single copy increase of each is not sufficient. In addition, mammary epithelium from the Gain <i>Myc-Pvt1</i> mouse show precancerous phenotypes, notably increased DNA replication, elevated -<i>H2AX</i> phosphorylation and increased ductal branching. In an attempt to capture the molecular signatures in pre-cancerous cells we utilized RNA sequencing to identify potential targets of supernumerary <i>Myc-Pvt1</i> cooperation in mammary epithelial cells. In this extra view we show that an extra copy of both <i>Myc</i> and <i>Pvt1</i> leads to increased levels of <i>Rspo1</i>, a crucial regulator of canonical β-catenin signaling required for female development. Human breast cancer tumors with high levels of <i>MYC</i> transcript have significantly more <i>PVT1</i> transcript and <i>RSPO1</i> transcript than tumors with low levels of MYC showing that the murine results are relevant to a subset of human tumors. Thus, this work identifies a key mechanism in precancerous and cancerous tissue by which a main player in female differentiation is transcriptionally activated by supernumerary <i>MYC</i> and <i>PVT1</i>, leading to increased premalignant features, and ultimately to tumor formation.
DOI: 10.6084/m9.figshare.2885308.v224
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.6084/m9.figshare.2951263.v232
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.7910/dvn/xjlzin/hjq7zh
title: dfp_covid_tracking_poll.tab

description: Dataset for the tracking poll (includes interviews conducted through July 7, 2020).
DOI: 10.6084/m9.figshare.2372716
title: pone-d-15-41735data.tar.bz2

description: This file contains raw data and processed data for the Plos One paper entitled: "Preconditioning 2D Integer Data fro Fast Convex Hull Computations" 10.1371/journal.pone.0149860
DOI: 10.6084/m9.figshare.2372716.v1
title: pone-d-15-41735data.tar.bz2

description: This file contains raw data and processed data for the Plos One paper entitled: "Preconditioning 2D Integer Data fro Fast Convex Hull Computations" 10.1371/journal.pone.0149860
DOI: 10.6084/m9.figshare.2885308.v225
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.6084/m9.figshare.2951263.v233
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.7910/dvn/xjlzin/gwukta
title: dfp_covid_tracking_poll.tab

description: Dataset for the tracking poll (includes interviews conducted through July 28, 2020).
DOI: 10.7910/dvn/xjlzin/ohwzvb
title: Survey questionnaire.pdf

description: Questionnaire for the tracking poll (updated on July 28, 2020).
DOI: 10.6084/m9.figshare.2885308.v226
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.6084/m9.figshare.2951263.v234
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.7910/dvn/xjlzin/ntmeqn
title: dfp_covid_tracking_poll.tab

description: Dataset for the tracking poll (includes interviews conducted through September 1, 2020).
DOI: 10.6084/m9.figshare.2885308.v227
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.6084/m9.figshare.2951263.v235
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.
DOI: 10.6084/m9.figshare.2885308.v228
title: UNH-RVAT 3-D SST RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions using the k-omega SST RANS model in OpenFOAM 2.3.x. See the link below for case files and download instructions.
DOI: 10.6084/m9.figshare.2951263.v236
title: UNH-RVAT 3-D Spalart--Allmaras RANS simulation results

description: Results from simulating the UNH-RVAT cross-flow turbine in three dimensions with the Spalart--Allmaras RANS model in OpenFOAM 2.3.x (590d57f32fed). See link below for case files (note: use the `SpalartAllmaras` branch), which include a script for downloading and extracting, as well as scripts for post-processing.