cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14714697
title: timeseries gene list - diastema vs molar

description: Time series analysis result sorted by expression patternFastQ data are available at NCBI SRA (SRP308455).
DOI: 10.6084/m9.figshare.14714697.v1
title: timeseries gene list - diastema vs molar

description: Time series analysis result sorted by expression patternFastQ data are available at NCBI SRA (SRP308455).
DOI: 10.6084/m9.figshare.14714688
title: TS Molar GO enrichment

description: Time series analysis of molar region FastQ data are available at NCBI SRA (SRP308455).<br>
DOI: 10.6084/m9.figshare.14714700
title: Sequencing Statistics Result

description: Sequencing Statistics Result (metadata)FastQ data are available at NCBI SRA (SRP308455).<br>
DOI: 10.6084/m9.figshare.14714703
title: biosample attributes table

description: biosample attributes table (metadata)<br>Sequencing raw data deposited at SRA of NCBI (SRP308455)
DOI: 10.6084/m9.figshare.14714688.v1
title: TS Molar GO enrichment

description: Time series analysis of molar region FastQ data are available at NCBI SRA (SRP308455).<br>
DOI: 10.6084/m9.figshare.14714700.v1
title: Sequencing Statistics Result

description: Sequencing Statistics Result (metadata)FastQ data are available at NCBI SRA (SRP308455).<br>
DOI: 10.6084/m9.figshare.14714706
title: biosample metadata

description: biosample metadataFastQ raw data are available at NCBI SRA (SRP308455).<br>
DOI: 10.6084/m9.figshare.14714709
title: TS E12.5 GO enrichment

description: Time series analysis of E12.5 stageFastQ data are available at NCBI SRA (SRP308455).
DOI: 10.6084/m9.figshare.14714703.v1
title: biosample attributes table

description: biosample attributes table (metadata)<br>Sequencing raw data deposited at SRA of NCBI (SRP308455)
DOI: 10.6084/m9.figshare.14714706.v1
title: biosample metadata

description: biosample metadataFastQ raw data are available at NCBI SRA (SRP308455).<br>
DOI: 10.6084/m9.figshare.14714712
title: time series - GO list

description: Time series analysis result - GO term FastQ data are available at NCBI SRA (SRP308455).<br>
DOI: 10.6084/m9.figshare.14714712.v1
title: time series - GO list

description: Time series analysis result - GO term FastQ data are available at NCBI SRA (SRP308455).<br>
DOI: 10.6084/m9.figshare.14714709.v1
title: TS E12.5 GO enrichment

description: Time series analysis of E12.5 stageFastQ data are available at NCBI SRA (SRP308455).
DOI: 10.14457/cmu.the.2006.745
title: การประเมินผลการปฏิบัติงาน ด้านสุขภาพจิตชุมชนของอาสาสมัครสาธารณสุข ประจำหมู่บ้าน อำเภอเชียงแสน จังหวัดเชียงราย
DOI: 10.14457/cmu.the.2005.426
title: การรับรู้และการปฏิบัติการให้ความรู้ ด้านสร้างเสริมสุขภาพ ของพยาบาลวิชาชีพกลุ่มงานผู้ป่วยนอก โรงพยาบาลพิจิตร
DOI: 10.14457/cmu.the.2006.746
title: การทดสอบความสัมพันธ์ ระหว่างเงินเฟ้อของประเทศไทยกับอัตราการเจริญเติบโตทางเศรษฐกิจ
DOI: 10.14457/cmu.the.2005.428
title: ความต้องการพัฒนา ของบุคลากรสำนักงานวัฒนธรรมจังหวัดลำปาง ลำพูน เชียงใหม่ และเชียงราย
DOI: 10.14457/cmu.the.2005.429
title: การใช้หลักสูตรการศึกษาขั้นพื้นฐาน พุทธศักราช 2544 ในโรงเรียนประถมศึกษา อำเภอทุ่งหัวช้าง จังหวัดลำพูน
DOI: 10.14457/cmu.the.2006.747
title: การประเมินศักยภาพธุรกิจชุมชน ในโครงการหนึ่งตำบล หนึ่งผลิตภัณฑ์ : ของตำบลมะขุนหวาน อำเภอสันป่าตอง จังหวัดเชียงใหม่
DOI: 10.14457/cmu.the.2005.430
title: ปัญหาในการปฏิบัติหน้าที่ของตำรวจอาสาสมัครประจำหมู่บ้าน ในตำบลสุเทพ อำเภอเมืองเชียงใหม่ จังหวัดเชียงใหม่
DOI: 10.14457/cmu.the.2005.431
title: การพัฒนาเว็บไซต์ของสมาคมผู้ผลิต และผู้ส่งออกสินค้าหัตถกรรมภาคเหนือ
DOI: 10.14457/cmu.the.2005.432
title: อุปสรรคของพยาบาลในการใช้ระบบสนับสนุนและให้ความรู้ เกี่ยวกับการดูแลตนเองแก่ผู้ที่เป็นโรคเบาหวาน
DOI: 10.14457/cmu.the.2005.433
title: ผลการใช้กิจกรรมการตั้งคำถาม ที่มีต่อทักษะการคิดวิเคราะห์ ของนักเรียนที่มีความสามารถทางการเรียนแตกต่างกัน
DOI: 10.14457/cmu.the.2005.427
title: ผลกระทบของการเปิดเขตการค้าเสรี ระหว่างไทยกับจีนต่อผู้ประกอบการเขตภาคเหนือ ในการลดภาษีสินค้าผักและผลไม้
DOI: 10.48512/xcv8459539
title: Becoming Hopi pit structure data set

description: Data on pit structures published in Becoming Hopi: A History
DOI: 10.5281/zenodo.4915870
title: Dataset of "Habitable Zones for Land Planets"

description: This dataset contains results to create figures in the paper "Habitable Zones for Land Planets" by T. Kodama et al. It contains data from our GCM calculations to create figures. We used Gtool3-dcl5 which is developed by the GFD-DENNOU Club for analysis (https://www.gfd-dennou.org).
DOI: 10.5281/zenodo.4915869
title: Dataset of "Habitable Zones for Land Planets"

description: This dataset contains results to create figures in the paper "Habitable Zones for Land Planets" by T. Kodama et al. It contains data from our GCM calculations to create figures. We used Gtool3-dcl5 which is developed by the GFD-DENNOU Club for analysis (https://www.gfd-dennou.org).
DOI: 10.5281/zenodo.4915889
title: synthetic dataset covid-19 PER

description: Synthetic dataset for outbreaks col-per 2021
DOI: 10.5281/zenodo.4915646
title: IR spectra of COVID-2019 virus (SARS-CoV-2) protein.

description: The source of the MD simulation trajectories and structures we use to simulate the IR spectra of SARS-CoV-2 virus were obtained from Komatsu and co-workers (MD simulation trajectories of SARS-CoV-2) and D. E. Shaw research (MD simulation trajectories of SARS-CoV-1-ACE2, SARS-CoV-2-ACE2 and trimeric SARS-CoV-2 spike glycoprotein, receptor-binding domain of the SARS-CoV-2 spike and the human ACE2 receptor), respectively. The criteria of the snapshots chosen and the time steps of the obtained snapshots were stated as below:<br> (1) For the snapshots of SARS-CoV-1 were chosen from 2 ns MD simulation, in total 1000 configurations were extracted with a 2 ps time step interval for calculating the IR spectra.<br> (2) For the snapshots of SARS-CoV-2 were chosen from 10 us MD simulation, in total 10000 configurations were extracted with a 1 ns time step interval for calculating the IR spectra. <br> (3) For the snapshots of SARS-CoV-1-ACE2 were chosen from 10 us MD simulation, in total 8334 configurations were extracted with a 1.2 ns time step interval from start time 1200ps – 10us for calculating the IR spectra. <br> (4) For the snapshots of SARS-CoV-2-ACE2 were chosen from 10 us MD simulation, in total 8334 configurations were extracted with a 1.2 ns time step interval from start time 1200ps – 10us for calculating the IR spectra.<br> (5) For the snapshots of Trimeric SARS-CoV-2 spike glycoprotein (closed state) were chosen from 10 us MD simulation, a total of 8334 configurations were extracted with an 1.2 ns interval from start time 1200ps – 10us (contains 9 trajectories, 1000 snapshots for No.1-8 trajectories, 334 snapshots for No.9 trajectory). We chose the first 800 snapshots in each of No.1-8 trajectories (6400 in total) to calculate the IR spectra.<br> (6) For the snapshots of Trimeric SARS-CoV-2 spike glycoprotein (opened state) were chosen from 10 us MD simulation, a total of 8334 configurations were extracted with a 1.2 ns interval from start time 1200ps – 10us(contains 9 trajectories,1000 snapshots for No.1-8 trajectories, 334 snapshots for No.9 trajectory). We chose the first 800 snapshots in each of No.1-8 trajectories (6400 in total) to calculate the IR spectra. <br>
DOI: 10.5281/zenodo.4915645
title: IR spectra of COVID-2019 virus (SARS-CoV-2) protein.

description: The source of the MD simulation trajectories and structures we use to simulate the IR spectra of SARS-CoV-2 virus were obtained from Komatsu and co-workers (MD simulation trajectories of SARS-CoV-2) and D. E. Shaw research (MD simulation trajectories of SARS-CoV-1-ACE2, SARS-CoV-2-ACE2 and trimeric SARS-CoV-2 spike glycoprotein, receptor-binding domain of the SARS-CoV-2 spike and the human ACE2 receptor), respectively. The criteria of the snapshots chosen and the time steps of the obtained snapshots were stated as below:<br> (1) For the snapshots of SARS-CoV-1 were chosen from 2 ns MD simulation, in total 1000 configurations were extracted with a 2 ps time step interval for calculating the IR spectra.<br> (2) For the snapshots of SARS-CoV-2 were chosen from 10 us MD simulation, in total 10000 configurations were extracted with a 1 ns time step interval for calculating the IR spectra. <br> (3) For the snapshots of SARS-CoV-1-ACE2 were chosen from 10 us MD simulation, in total 8334 configurations were extracted with a 1.2 ns time step interval from start time 1200ps – 10us for calculating the IR spectra. <br> (4) For the snapshots of SARS-CoV-2-ACE2 were chosen from 10 us MD simulation, in total 8334 configurations were extracted with a 1.2 ns time step interval from start time 1200ps – 10us for calculating the IR spectra.<br> (5) For the snapshots of Trimeric SARS-CoV-2 spike glycoprotein (closed state) were chosen from 10 us MD simulation, a total of 8334 configurations were extracted with an 1.2 ns interval from start time 1200ps – 10us (contains 9 trajectories, 1000 snapshots for No.1-8 trajectories, 334 snapshots for No.9 trajectory). We chose the first 800 snapshots in each of No.1-8 trajectories (6400 in total) to calculate the IR spectra.<br> (6) For the snapshots of Trimeric SARS-CoV-2 spike glycoprotein (opened state) were chosen from 10 us MD simulation, a total of 8334 configurations were extracted with a 1.2 ns interval from start time 1200ps – 10us(contains 9 trajectories,1000 snapshots for No.1-8 trajectories, 334 snapshots for No.9 trajectory). We chose the first 800 snapshots in each of No.1-8 trajectories (6400 in total) to calculate the IR spectra. <br>
DOI: 10.6084/m9.figshare.14753565
title: Effects of weather parameters on endurance running performance

description: The aim of the analysis was to evaluate how single or combinations of weather parameters (temperature, humidity, wind speed, solar load) affect peak performance during endurance running events and identify which events are most vulnerable to varying weather conditions. Results for the marathon, 50 km race-walk, 20 km race-walk, 10,000 m, 5,000 m and 3,000 m-steeplechase were obtained from the official websites of the largest competitions in the world. Finish times for all races were collected from the first year of each competition for which data were available online until the end of 2019. The collection of these data was completed between February 2016 and September 2020 We obtained the date, time, and location for each race from its official website while the relevant longitude and latitude were obtained from www.locationiq.com. Weather data (air temperature, dew point, wind speed, and cloud coverage) corresponding to the time at half-way in each race were obtained from the closest meteorological station using the official dataset of the National Oceanic and Atmospheric Administration (www.ncei.noaa.gov/data/global-hourly). In cases where these data were not available, we retrieved the information from widely-used meteorology websites (www.wunderground.com and www.weatherspark.com). Wind speed was adjusted for height above the ground and air friction coefficient (i.e., large city with tall buildings). Dew point data were converted to relative humidity. For cases where cloud coverage was not available in the National Oceanic and Atmospheric Administration datasets, the cloud coverage (in okta) was computed using relative humidity data based on previous methodology and applying coefficients of 0.25 for low and high as well as 0.5 for middle clouds, as previously suggested. Solar radiation was calculated using the date, time, and coordinates of each race, while accounting for cloud coverage. Thereafter, the Heat Index, Simplified WBGT and WBGT, were calculated using previous methodology. <br>
DOI: 10.5281/zenodo.4915997
title: Effects of atmospheric attenuation on lightning spectrum

description: Spectrum carries important information reflecting atomic and molecular processes inside light source. Accurate spectral diagnosis is of vital significance in revealing microscopic physical mechanism of lightning discharge process. Aimed at the problems of atmospheric attenuation in long-distance lightning spectrum observations, considering the influence of atmospheric attenuation, grating efficiency and camera response on the observed spectrum, the spectral correction is carried out in this work. Based on the restored spectrum, the temperature of core current-carrying channel and the mean temperature of the luminous channel were calculated respectively. The result showed that the corrected temperature of core current-carrying channel at initial stage of return stroke could reach up to 40000 K, which was about 10000 K higher than the value directly obtained from observed spectrum. In addition, there is a steep temperature gradient between the core current-carrying channel and its peripheral hot channel. This work provided the attenuation ratio of the characteristic lines in lightning spectra with distance which is could be used for more precisely quantitative investigation on physical characteristic of lightning process, and it also has application value for improving the spectral diagnostic techniques on celestial body and other natural luminous process.
DOI: 10.5281/zenodo.4915996
title: Effects of atmospheric attenuation on lightning spectrum

description: Spectrum carries important information reflecting atomic and molecular processes inside light source. Accurate spectral diagnosis is of vital significance in revealing microscopic physical mechanism of lightning discharge process. Aimed at the problems of atmospheric attenuation in long-distance lightning spectrum observations, considering the influence of atmospheric attenuation, grating efficiency and camera response on the observed spectrum, the spectral correction is carried out in this work. Based on the restored spectrum, the temperature of core current-carrying channel and the mean temperature of the luminous channel were calculated respectively. The result showed that the corrected temperature of core current-carrying channel at initial stage of return stroke could reach up to 40000 K, which was about 10000 K higher than the value directly obtained from observed spectrum. In addition, there is a steep temperature gradient between the core current-carrying channel and its peripheral hot channel. This work provided the attenuation ratio of the characteristic lines in lightning spectra with distance which is could be used for more precisely quantitative investigation on physical characteristic of lightning process, and it also has application value for improving the spectral diagnostic techniques on celestial body and other natural luminous process.
DOI: 10.5281/zenodo.4915919
title: Power Sharing at the Local Level: Evidence on Opting‑in for Non‑citizen Voting Rights

description: Datasets and corresponding codebooks underlying the publication: Stutzer, A., & Slotwinski, M. (2021). Power Sharing at the Local Level: Evidence on Opting-in for Non-citizen Voting Rights. <em>Constitutional Political Economy</em>, <em>32</em>(1), 1-30.
DOI: 10.5281/zenodo.4915918
title: Power Sharing at the Local Level: Evidence on Opting‑in for Non‑citizen Voting Rights

description: Datasets and corresponding codebooks underlying the publication: Stutzer, A., & Slotwinski, M. (2021). Power Sharing at the Local Level: Evidence on Opting-in for Non-citizen Voting Rights. <em>Constitutional Political Economy</em>, <em>32</em>(1), 1-30.
DOI: 10.6084/m9.figshare.14753634
title: dataset.xlsx

description: data
DOI: 10.6084/m9.figshare.14753634.v2
title: dataset.xlsx

description: data
DOI: 10.6084/m9.figshare.14753634.v1
title: dataset.xlsx

description: data
DOI: 10.5281/zenodo.4916017
title: Thicket State Soil Temperature and Humidity Dataset: Thicket Soil Microbiome Project

description: This dataset is part of a larger project exploring the soil microbiomes across three thicket states: intact thicket, degraded (by domestic herbivore overbrowsing), and restored (14-year old <em>Portulacaria afra</em> cuttings).
DOI: 10.5281/zenodo.4916016
title: Thicket State Soil Temperature and Humidity Dataset: Thicket Soil Microbiome Project

description: This dataset is part of a larger project exploring the soil microbiomes across three thicket states: intact thicket, degraded (by domestic herbivore overbrowsing), and restored (14-year old <em>Portulacaria afra</em> cuttings).
DOI: 10.6084/m9.figshare.14753616
title: Supplementary Material for: Factors and Outcomes of Intensive Care Unit Readmission in Elderly Patients

description: <b><i>Introduction:</i></b> An increase in age has been observed among patients admitted to the intensive care unit (ICU). Age is a well-known risk factor for ICU readmission and mortality. However, clinical characteristics and risk factors of ICU readmission of elderly patients (≥65 years) have not been studied. <b><i>Methods:</i></b> This retrospective single-center cohort study was conducted in a total of 122-bed ICU of a tertiary care hospital in Seoul, Korea. A total of 85,413 patients were enrolled in this hospital between January 1, 2007, and December 31, 2017. The odds ratio of readmission and in-hospital mortality was calculated by logistic regression analysis. <b><i>Results:</i></b> Totally, 29,503 patients were included in the study group, of which 2,711 (9.2%) had ICU readmissions. Of the 2,711 readmitted patients, 472 patients were readmitted more than once (readmitted 2 or more times to the ICU, 17.4%). In the readmitted patient group, there were more males, higher sequential organ failure assessment (SOFA) scores, and hospitalized for medical reasons. Length of stay (LOS) in ICU and in-hospital were longer, and 28-day and in-hospital mortality was higher in readmitted patients than in nonreadmitted patients. Risk factors of ICU readmission included the ICU admission due to medical reason, SOFA score, presence of chronic heart disease, diabetes mellitus, chronic kidney disease, transplantation, use of mechanical ventilation, and initial ICU LOS. ICU readmission and age (over 85 years) were independent predictors of in-hospital mortality on multivariable analysis. The delayed ICU readmission group (&gt;72 h) had higher in-hospital mortality than the early readmission group (≤72 h) (20.6 vs. 16.2%, <i>p</i> = 0.005). <b><i>Conclusions:</i></b> ICU readmissions occurred in 9.2% of elderly patients and were associated with poor prognosis and higher mortality.
DOI: 10.6084/m9.figshare.14753616.v1
title: Supplementary Material for: Factors and Outcomes of Intensive Care Unit Readmission in Elderly Patients

description: <b><i>Introduction:</i></b> An increase in age has been observed among patients admitted to the intensive care unit (ICU). Age is a well-known risk factor for ICU readmission and mortality. However, clinical characteristics and risk factors of ICU readmission of elderly patients (≥65 years) have not been studied. <b><i>Methods:</i></b> This retrospective single-center cohort study was conducted in a total of 122-bed ICU of a tertiary care hospital in Seoul, Korea. A total of 85,413 patients were enrolled in this hospital between January 1, 2007, and December 31, 2017. The odds ratio of readmission and in-hospital mortality was calculated by logistic regression analysis. <b><i>Results:</i></b> Totally, 29,503 patients were included in the study group, of which 2,711 (9.2%) had ICU readmissions. Of the 2,711 readmitted patients, 472 patients were readmitted more than once (readmitted 2 or more times to the ICU, 17.4%). In the readmitted patient group, there were more males, higher sequential organ failure assessment (SOFA) scores, and hospitalized for medical reasons. Length of stay (LOS) in ICU and in-hospital were longer, and 28-day and in-hospital mortality was higher in readmitted patients than in nonreadmitted patients. Risk factors of ICU readmission included the ICU admission due to medical reason, SOFA score, presence of chronic heart disease, diabetes mellitus, chronic kidney disease, transplantation, use of mechanical ventilation, and initial ICU LOS. ICU readmission and age (over 85 years) were independent predictors of in-hospital mortality on multivariable analysis. The delayed ICU readmission group (&gt;72 h) had higher in-hospital mortality than the early readmission group (≤72 h) (20.6 vs. 16.2%, <i>p</i> = 0.005). <b><i>Conclusions:</i></b> ICU readmissions occurred in 9.2% of elderly patients and were associated with poor prognosis and higher mortality.
DOI: 10.6084/m9.figshare.14464305
title: Supplementary Material for: Risk Factors for Non-Ampullary Duodenal Adenocarcinoma: A Systematic Review

description: Medicine
DOI: 10.6084/m9.figshare.14464305.v1
title: Supplementary Material for: Risk Factors for Non-Ampullary Duodenal Adenocarcinoma: A Systematic Review

description: Medicine
DOI: 10.6084/m9.figshare.14753553
title: Supplementary Material for: Results of a Gene Panel Approach in a Cohort of Patients with Incomplete Distal Renal Tubular Acidosis and Nephrolithiasis

description: <b><i>Background:</i></b> Distal renal tubular acidosis (dRTA) is characterized by an impairment of urinary acidification resulting in metabolic acidosis, hypokalemia, and inappropriately elevated urine pH. If not treated, this chronic condition eventually leads to nephrocalcinosis, nephrolithiasis, impaired renal function, and bone demineralization. dRTA is a well-defined entity that can be diagnosed by genetic testing of 5 genes known to be disease-causative. Incomplete dRTA (idRTA) is defined as impaired urinary acidification that does not lead to overt metabolic acidosis and therefore can be diagnosed if patients fail to adequately acidify urine after an ammonium chloride (NH<sub>4</sub>Cl) challenge or furosemide and fludrocortisone test. It is still uncertain whether idRTA represents a distinct entity or is part of the dRTA spectrum and whether it is caused by mutations in the same genes of overt dRTA. <b><i>Methods:</i></b> In this cross-sectional study, we investigated a group of 22 stone formers whose clinical features were suspicious of idRTA. They underwent an NH<sub>4</sub>Cl challenge and were found to have impaired urinary acidification ability. These patients were then analyzed by genetic testing with sequencing of 5 genes: <i>SLC4A1</i>, <i>ATP6V1B1</i>, <i>ATP6V0A4</i>, <i>FOXI1</i>, and <i>WDR72</i>. <b><i>Results:</i></b> Two unrelated individuals were found to have two different variants in <i>SLC4A1</i> that had never been described before. <b><i>Conclusions:</i></b> Our results suggest the involvement of other genes or nongenetic tubular dysfunction in the pathogenesis of idRTA in stone formers. However, genetic testing may represent a cost-effective tool to recognize, treat, and prevent complications in these patients.
DOI: 10.15159/eds.dt.21.02
title: Combined Acute Ozone and Water Stress Alters the Quantitative Relationships between O₃ Uptake, Photosynthetic Characteristics and Volatile Emissions in Brassica nigra

description: Ozone and water stress effects on Brassica nigra volatile organic compounds emission (VOC) and photosynthetic characteristics. VOCs were collected on adsorbent cartridges and analyzed with GC-MS. Ozone exposures were 250 ppb O₃ for well-watered and 550 ppb O₃ for well-watered and water-stressed B. nigra plants.
DOI: 10.5281/zenodo.4916000
title: Herseninstituut/FYD_Datasets: Changed naming of folders and files

description: File system image of a dataset, with http links associated with each file.
DOI: 10.5281/zenodo.4716653
title: Herseninstituut/FYD_Datasets: Changed naming of folders and files

description: File system image of a dataset, with http links associated with each file.
DOI: 10.17188/1748326
title: Materials Data on Li2Fe3P5O18 by Materials Project

description: Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations