cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23944308
title: Supplementary Material for: Medication status and related factors in essential tremor patients: a cross-sectional study in China

description: Abstract Introduction: Essential Tremor (ET) is one of the most common movement disorders. Oral drugs play a crucial role in treating ET, with various available options such as propranolol, primidone and topiramate. However, the medication status and related factors among Chinese ET patients are unknown yet. Methods: This study used the baseline data from the National Survey of Essential Tremor Plus in China cohort. ET patients with information related to medication intake were included. Medication patients was defined as patients who were taking medication at the time of the survey. We further defined recommended medication users according to Chinese guideline recommendations and clinical knowledge. We used mean and standard deviation (SD), median and interquartile range (IQR), or frequencies and percentages when appropriate for descriptive analysis. We used multivariate logistic regression analyses to explore factors related to medication intake in all ET patients, and in recommended medication users respectively. Results: Of 1153 included ET participants, 207 (18.0%) took medication. Arotinolol (115, 55.6%) and propranolol (63, 30.4%) were the top 2 used medicines. Patients with middle school education (odds ratio 0.57, 95% confidence interval 0.39 to 0.83), college or higher level education (0.46, 0.28 to 0.76) and late onset ET (LO-ET) (0.38, 0.23 to 0.63) were less likely to take medication. Patients with intention tremor (1.90, 1.38 to 2.62), every 10-unit increase in age (1.10, 1.00 to 1.21), Tremor Research Group Essential Tremor Rating Assessment Scale (TETRAS) Part 1 (1.63, 1.37 to 1.93), and TETRAS Part 2 (1.81, 1.48 to 2.22) were more likely to take medication. Among 332 recommended medication users, only 104 (31.3%) took medicine. The associations of LO-ET (0.36, 0.17 to 0.75), intention tremor (2.27, 1.35 to 3.81), TETRAS Part1 (1.52, 1.09 to 2.13) and TETRAS Part 2 (1.59, 1.15 to 2.20) with medication were similar to all ET patients. Conclusion: The proportion of medication intake is low among both all ET patients and recommended medication users. The top two commonly used medications among all ET patients are arotinolol and propranolol. Influencing factors of medication intake are different between all ET patients and recommended medication users. Clinicians are suggested to provide counseling and education on ET medication to promote medication intake.
DOI: 10.6084/m9.figshare.23944308.v1
title: Supplementary Material for: Medication status and related factors in essential tremor patients: a cross-sectional study in China

description: Abstract Introduction: Essential Tremor (ET) is one of the most common movement disorders. Oral drugs play a crucial role in treating ET, with various available options such as propranolol, primidone and topiramate. However, the medication status and related factors among Chinese ET patients are unknown yet. Methods: This study used the baseline data from the National Survey of Essential Tremor Plus in China cohort. ET patients with information related to medication intake were included. Medication patients was defined as patients who were taking medication at the time of the survey. We further defined recommended medication users according to Chinese guideline recommendations and clinical knowledge. We used mean and standard deviation (SD), median and interquartile range (IQR), or frequencies and percentages when appropriate for descriptive analysis. We used multivariate logistic regression analyses to explore factors related to medication intake in all ET patients, and in recommended medication users respectively. Results: Of 1153 included ET participants, 207 (18.0%) took medication. Arotinolol (115, 55.6%) and propranolol (63, 30.4%) were the top 2 used medicines. Patients with middle school education (odds ratio 0.57, 95% confidence interval 0.39 to 0.83), college or higher level education (0.46, 0.28 to 0.76) and late onset ET (LO-ET) (0.38, 0.23 to 0.63) were less likely to take medication. Patients with intention tremor (1.90, 1.38 to 2.62), every 10-unit increase in age (1.10, 1.00 to 1.21), Tremor Research Group Essential Tremor Rating Assessment Scale (TETRAS) Part 1 (1.63, 1.37 to 1.93), and TETRAS Part 2 (1.81, 1.48 to 2.22) were more likely to take medication. Among 332 recommended medication users, only 104 (31.3%) took medicine. The associations of LO-ET (0.36, 0.17 to 0.75), intention tremor (2.27, 1.35 to 3.81), TETRAS Part1 (1.52, 1.09 to 2.13) and TETRAS Part 2 (1.59, 1.15 to 2.20) with medication were similar to all ET patients. Conclusion: The proportion of medication intake is low among both all ET patients and recommended medication users. The top two commonly used medications among all ET patients are arotinolol and propranolol. Influencing factors of medication intake are different between all ET patients and recommended medication users. Clinicians are suggested to provide counseling and education on ET medication to promote medication intake.
DOI: 10.6084/m9.figshare.23944314
title: Supplementary Material for: Medication status and related factors in essential tremor patients: a cross-sectional study in China

description: Abstract Introduction: Essential Tremor (ET) is one of the most common movement disorders. Oral drugs play a crucial role in treating ET, with various available options such as propranolol, primidone and topiramate. However, the medication status and related factors among Chinese ET patients are unknown yet. Methods: This study used the baseline data from the National Survey of Essential Tremor Plus in China cohort. ET patients with information related to medication intake were included. Medication patients was defined as patients who were taking medication at the time of the survey. We further defined recommended medication users according to Chinese guideline recommendations and clinical knowledge. We used mean and standard deviation (SD), median and interquartile range (IQR), or frequencies and percentages when appropriate for descriptive analysis. We used multivariate logistic regression analyses to explore factors related to medication intake in all ET patients, and in recommended medication users respectively. Results: Of 1153 included ET participants, 207 (18.0%) took medication. Arotinolol (115, 55.6%) and propranolol (63, 30.4%) were the top 2 used medicines. Patients with middle school education (odds ratio 0.57, 95% confidence interval 0.39 to 0.83), college or higher level education (0.46, 0.28 to 0.76) and late onset ET (LO-ET) (0.38, 0.23 to 0.63) were less likely to take medication. Patients with intention tremor (1.90, 1.38 to 2.62), every 10-unit increase in age (1.10, 1.00 to 1.21), Tremor Research Group Essential Tremor Rating Assessment Scale (TETRAS) Part 1 (1.63, 1.37 to 1.93), and TETRAS Part 2 (1.81, 1.48 to 2.22) were more likely to take medication. Among 332 recommended medication users, only 104 (31.3%) took medicine. The associations of LO-ET (0.36, 0.17 to 0.75), intention tremor (2.27, 1.35 to 3.81), TETRAS Part1 (1.52, 1.09 to 2.13) and TETRAS Part 2 (1.59, 1.15 to 2.20) with medication were similar to all ET patients. Conclusion: The proportion of medication intake is low among both all ET patients and recommended medication users. The top two commonly used medications among all ET patients are arotinolol and propranolol. Influencing factors of medication intake are different between all ET patients and recommended medication users. Clinicians are suggested to provide counseling and education on ET medication to promote medication intake.
DOI: 10.6084/m9.figshare.23944314.v1
title: Supplementary Material for: Medication status and related factors in essential tremor patients: a cross-sectional study in China

description: Abstract Introduction: Essential Tremor (ET) is one of the most common movement disorders. Oral drugs play a crucial role in treating ET, with various available options such as propranolol, primidone and topiramate. However, the medication status and related factors among Chinese ET patients are unknown yet. Methods: This study used the baseline data from the National Survey of Essential Tremor Plus in China cohort. ET patients with information related to medication intake were included. Medication patients was defined as patients who were taking medication at the time of the survey. We further defined recommended medication users according to Chinese guideline recommendations and clinical knowledge. We used mean and standard deviation (SD), median and interquartile range (IQR), or frequencies and percentages when appropriate for descriptive analysis. We used multivariate logistic regression analyses to explore factors related to medication intake in all ET patients, and in recommended medication users respectively. Results: Of 1153 included ET participants, 207 (18.0%) took medication. Arotinolol (115, 55.6%) and propranolol (63, 30.4%) were the top 2 used medicines. Patients with middle school education (odds ratio 0.57, 95% confidence interval 0.39 to 0.83), college or higher level education (0.46, 0.28 to 0.76) and late onset ET (LO-ET) (0.38, 0.23 to 0.63) were less likely to take medication. Patients with intention tremor (1.90, 1.38 to 2.62), every 10-unit increase in age (1.10, 1.00 to 1.21), Tremor Research Group Essential Tremor Rating Assessment Scale (TETRAS) Part 1 (1.63, 1.37 to 1.93), and TETRAS Part 2 (1.81, 1.48 to 2.22) were more likely to take medication. Among 332 recommended medication users, only 104 (31.3%) took medicine. The associations of LO-ET (0.36, 0.17 to 0.75), intention tremor (2.27, 1.35 to 3.81), TETRAS Part1 (1.52, 1.09 to 2.13) and TETRAS Part 2 (1.59, 1.15 to 2.20) with medication were similar to all ET patients. Conclusion: The proportion of medication intake is low among both all ET patients and recommended medication users. The top two commonly used medications among all ET patients are arotinolol and propranolol. Influencing factors of medication intake are different between all ET patients and recommended medication users. Clinicians are suggested to provide counseling and education on ET medication to promote medication intake.
DOI: 10.17617/4.dm
title: High-Performance Humidity Sensing in π-Conjugated Molecular Assemblies through the Engineering of Electron/Proton Transport and Device Interfaces

description: Turetta, N., Stoeckel, M.-A., de Oliveira, R. F., Devaux, F., Greco, A., Cendra, C., et al. (2022). High-Performance Humidity Sensing in π-Conjugated Molecular Assemblies through the Engineering of Electron/Proton Transport and Device Interfaces. Journal of the American Chemical Society, 144(6), 2546-2555. doi:10.1021/jacs.1c10119.
DOI: 10.5281/zenodo.8246394
title: Results files for Land-free Bioenergy From Circular Agroecology -- A Diverse Option Space and Trade-offs

description: This is the open data repository to support and reproduce results in the paper "<em>Land-free Bioenergy From Circular Agroecology -- A Diverse Option Space and Trade-offs</em>." There are <strong>three types </strong>of files here: <strong>1. Ready-to-use final results files of all strategies and scenarios referred to in the paper. </strong>They can be downloaded and used directly without running any codes. They all have the same naming format for strategies/scenarios: `Org` = organic share, `ConcRed` = concentrate feeding reduction share, `WasteRed` = waste reduction share, and numbers refer to the share. E.g., `Org0_ConcRed50_WasteRed75` is a strategy with 0% organic share, 50% concentrate feeding reduction, and 75% waste reduction. `NationalAncillaryBioenergyPotential_EJ.csv`: The national potential of ancillary bioenergy in 2050 from all scenarios. (Units: EJ). Same in both pathways. `GlobalPotentialEnvironmentalImpacts_NutrientFirst.csv`: Environmental impacts of all scenarios from the pathway `<em>NutrientFirst</em>.` The first three rows refer to the combination of agroecological practices in places, which allow you to explore environmental impacts grouped by, e.g., different organic shares. `GlobalPotentialEnvironmentalImpacts_NegFirst.csv`: Same structure as the file above, but from another pathway, `<em>NegativeFirst</em>`. <strong>2. `SOLmOutputs` contains all original output files from our model SOLmV6. </strong> <strong>3. `DataCleaningKit` has the Python codes and additional dataset of heat values to process 2. `SOLmOutputs` and spit 1. </strong>(Tip: One should adjust the `input_path` and `output_path` before running `DataCleaning.py.`) Fei Wu (fei.wu@usys.ethz.ch) Delft, August, 2023
DOI: 10.5281/zenodo.8246393
title: Results files for Land-free Bioenergy From Circular Agroecology -- A Diverse Option Space and Trade-offs

description: This is the open data repository to support and reproduce results in the paper "<em>Land-free Bioenergy From Circular Agroecology -- A Diverse Option Space and Trade-offs</em>." There are <strong>three types </strong>of files here: <strong>1. Ready-to-use final results files of all strategies and scenarios referred to in the paper. </strong>They can be downloaded and used directly without running any codes. They all have the same naming format for strategies/scenarios: `Org` = organic share, `ConcRed` = concentrate feeding reduction share, `WasteRed` = waste reduction share, and numbers refer to the share. E.g., `Org0_ConcRed50_WasteRed75` is a strategy with 0% organic share, 50% concentrate feeding reduction, and 75% waste reduction. `NationalAncillaryBioenergyPotential_EJ.csv`: The national potential of ancillary bioenergy in 2050 from all scenarios. (Units: EJ). Same in both pathways. `GlobalPotentialEnvironmentalImpacts_NutrientFirst.csv`: Environmental impacts of all scenarios from the pathway `<em>NutrientFirst</em>.` The first three rows refer to the combination of agroecological practices in places, which allow you to explore environmental impacts grouped by, e.g., different organic shares. `GlobalPotentialEnvironmentalImpacts_NegFirst.csv`: Same structure as the file above, but from another pathway, `<em>NegativeFirst</em>`. <strong>2. `SOLmOutputs` contains all original output files from our model SOLmV6. </strong> <strong>3. `DataCleaningKit` has the Python codes and additional dataset of heat values to process 2. `SOLmOutputs` and spit 1. </strong>(Tip: One should adjust the `input_path` and `output_path` before running `DataCleaning.py.`) Fei Wu (fei.wu@usys.ethz.ch) Delft, August, 2023
DOI: 10.34740/kaggle/dsv/6301403
title: 2021 World Population (updated daily)
DOI: 10.25444/nhlbi.23818215
title: Data on phase separation of Sup35p protein in Vivo

description: When yeast are energy depleted, Sup35 prion protein phase separates into condensates with very different properties than the phase separated Sup35 liquid droplets that form in vitro at low pH characterized by the Alberti laboratory (Franzmann et al. Science 2018). In contrast to Sup35 liquid droplets, which is driven by the prion domain of Sup35 and does not require the C-terminal domain, a Sup35 fragment consisting of only the N-terminal prion domain and the M-domain does not phase separate in vivo. Phase separation of Sup35 in vivo requires the C-terminal domain, which binds to Sup45 to form the translation termination complex. The phase separated Sup35 not only colocalizes <i>in vivo</i> with Sup45 but also with Pub1, a stress granule marker protein. In addition, like stress granules, phase separation of Sup35 appears to require mRNA since treating the yeast with cycloheximide, which inhibits mRNA release from ribosomes, prevents phase separation of Sup35. Finally, the liquid droplets of Sup35 that form in vivo do not reversibly disassemble when the intracellular pH is increased unlike the purified Sup35 in vitro. Taken together, these results suggest that, in energy-depleted cells, Sup35 is incorporated into supramolecular assemblies whose properties differ from those of Sup35 liquid droplets that form <i>in vitro</i>.
DOI: 10.25444/nhlbi.23818215.v1
title: Data on phase separation of Sup35p protein in Vivo

description: When yeast are energy depleted, Sup35 prion protein phase separates into condensates with very different properties than the phase separated Sup35 liquid droplets that form in vitro at low pH characterized by the Alberti laboratory (Franzmann et al. Science 2018). In contrast to Sup35 liquid droplets, which is driven by the prion domain of Sup35 and does not require the C-terminal domain, a Sup35 fragment consisting of only the N-terminal prion domain and the M-domain does not phase separate in vivo. Phase separation of Sup35 in vivo requires the C-terminal domain, which binds to Sup45 to form the translation termination complex. The phase separated Sup35 not only colocalizes <i>in vivo</i> with Sup45 but also with Pub1, a stress granule marker protein. In addition, like stress granules, phase separation of Sup35 appears to require mRNA since treating the yeast with cycloheximide, which inhibits mRNA release from ribosomes, prevents phase separation of Sup35. Finally, the liquid droplets of Sup35 that form in vivo do not reversibly disassemble when the intracellular pH is increased unlike the purified Sup35 in vitro. Taken together, these results suggest that, in energy-depleted cells, Sup35 is incorporated into supramolecular assemblies whose properties differ from those of Sup35 liquid droplets that form <i>in vitro</i>.
DOI: 10.34740/kaggle/dsv/6301407
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.23944203
title: Data file. Causes of death for 1530 consecutive patients diagnosed with uveal melanoma.

description: Data set (anonymized, with patient ages at diagnosis and death rounded to nearest decade) for a comprehensive study on the causes of death, for patients diagnosed with uveal melanoma. All patients were deceased at the time of data collection.
DOI: 10.6084/m9.figshare.23944203.v1
title: Data file. Causes of death for 1530 consecutive patients diagnosed with uveal melanoma.

description: Data set (anonymized, with patient ages at diagnosis and death rounded to nearest decade) for a comprehensive study on the causes of death, for patients diagnosed with uveal melanoma. All patients were deceased at the time of data collection.
DOI: 10.5281/zenodo.6371582
title: A Longitudinal Analysis of Bug Handling Across Eclipse Releases

description: This repository contains the data used in the paper accepted at ICSME 2019 entitled ["A Longitudinal Analysis of Bug Handling Across Eclipse Releases"] # Structure The repository contains : 1. `raw_data`: a repository containing all the raw data of our study before processing.<br> 2. `data_processing`: a repository containing all the raw data of our study during processing.<br> 3. `data`: a repository containing all the data of our study after all processing steps.<br> 4. `figs`: The generated figures from the notebooks for the paper.<br> 5. The various Jupyter notebooks containing all the scripts used to gather the data and answer each research question.<br>
DOI: 10.5063/f12b8wgk
title: Multi-year dataset of flower visitors and reproductive output of Big Pine partridge pea.

description: Arthropod species were observed at flowers of Big Pine partridge pea (Chamaecrista lineata var. keyensis; Fabaceae), a federally endangered perennial herb, extant only on pine rockland in Big Pine Key, FL. We compared the composition of flower visitors before (2001) after (2015-2019) orchid bees (Euglossa dilemma; Apidae) to the island. Similarly, reproductive output in partridge pea was compared before and after invasion for the same series of years. "Before invasion" data were originally collected and published in (Liu and Koptur, 2003; DOI: 10.3732/ajb.90.8.1180). Sites were distributed across urban and forested sites on pine rockland in Big Pine Key, FL. Hurricane Irma, a category four hurricane, crossed the island after our seasonal sampling was completed in 2017.
DOI: 10.5281/zenodo.6371591
title: A Longitudinal Analysis of Bug Handling Across Eclipse Releases

description: This repository contains the data used in the paper accepted at ICSME 2019 entitled ["A Longitudinal Analysis of Bug Handling Across Eclipse Releases"] # Structure The repository contains : 1. `raw_data`: a repository containing all the raw data of our study before processing.<br> 2. `data_processing`: a repository containing all the raw data of our study during processing.<br> 3. `data`: a repository containing all the data of our study after all processing steps.<br> 4. `figs`: The generated figures from the notebooks for the paper.<br> 5. The various Jupyter notebooks containing all the scripts used to gather the data and answer each research question.<br>
DOI: 10.5281/zenodo.3246947
title: A Longitudinal Analysis of Bug Handling Across Eclipse Releases

description: This repository contains the data used in the paper accepted at ICSME 2019 entitled ["A Longitudinal Analysis of Bug Handling Across Eclipse Releases"] # Structure The repository contains : 1. `raw_data`: a repository containing all the raw data of our study before processing.<br> 2. `data_processing`: a repository containing all the raw data of our study during processing.<br> 3. `data`: a repository containing all the data of our study after all processing steps.<br> 4. `figs`: The generated figures from the notebooks for the paper.<br> 5. The various Jupyter notebooks containing all the scripts used to gather the data and answer each research question.<br>
DOI: 10.5281/zenodo.6371455
title: Proyectos de investigación estudiantil en Udelar

description: La Comisión Sectorial de Investigación Científica (CSIC) es un servicio de la Universidad de la República, principal institución educativa de alto nivel en Uruguay concentrando el 90% de la población universitaria. Dentro de los cometidos de la CSIC está la administración, estudio y financiación de programas de investigación, cuyos proyectos abarcan todas las disciplinas en todas las áreas. Uno de estos programas es el Programa de Apoyo a la Investigación Estudiantil (PAIE), que permite a los estudiantes universitarios de grado tener una primer experiencia participando en sus propios proyectos de investigación, orientados en todo momento por profesores responsables y expertos en las áreas en las que estos se desarrollan. Este instrumento es el dispositivo de salida, en muchos casos, de motivación y de <em>hook</em>, para ampliar la capacidad de investigación y de fomentar el interés por la carrera como investigador. Si bien el monto total financiado es demasiado bajo para una investigación de alto impacto, no se busca que estos proyectos tengan una trascendencia internacional, sino alcanzar una rigurosidad en términos de metodología y razonamiento. El título para este DataSet será entonces “PAIES - <em>Proyectos de investigación de estudiantes de grado en UdelaR</em>”, y el nombre del fichero “paies.csv”. La información se toma desde la web del programa, accediendo a cada página que contiene la información del listado de proyectos por año del llamado, de ahí se guardan las URLs de cada proyecto en cuestión y luego se toman los datos de esa segunda instancia. El total de registros asciende a 823 filas y 6 columnas, fichero que se adjunta a este documento, abarcando los años desde el 2008 al 2019 inclusive. Los datos están publicados en la web https://estudiantes.csic.edu.uy siendo estos de dominio público.