cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2fvt48
title: CCDC 2260090: Experimental Crystal Structure Determination

description: Related Article: Xiaoting Liu, Jingliang Cui, Qun Zeng, Liwen Fang, Peng-Yu Liang, Pan-Pan Zhou, Sean Parkin, Tonglei Li, Shigang Ruan, Sihui Long|2023|RSC Advances|13|21021|doi:10.1039/D3RA04102F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.17894/ucph.74c9271c-1346-4a57-9c8e-fb854dbb3500
title: Data for Agronomic performance of novel biobased fertilizers Results from field trials at five European sites
DOI: 10.6084/m9.figshare.23704185
title: Supplementary Material for: A case of mesangial proliferative nephritis caused by slow cryoglobulin

description: The patient was a woman in her 60s. She was found to have proteinuria on a health checkup. She did not have any particular subjective symptoms, and no definitive diagnosis was made, despite serological findings indicative of immune abnormalities. A renal biopsy was performed. Light microscopy of renal tissue section revealed mesangial proliferative nephritis. Electron microscopic findings included electron dense deposits (EDD) and fibrillar/tubular structures with a diameter of 20 to 30 nm. These findings suggested the presence of cryoglobulin (CG), but CG was not detected in qualitative or quantitative hematologic tests. Thus, the serum samples were stored at 37℃ for a long period of time and then cooled to 4℃. When the obtained precipitates were examined, CG was successfully detected. CG that precipitates only after a long period of time is referred to as slow cryoglobulin (sCG), and sCG is extremely rare. The present case is the first documented case, to our knowledge, of renal disorders caused by sCG. It should be noted that there are some cases in which it takes much time for CG to precipitate. Thus, when CG cannot be detected, it is necessary to spend much time to determine whether CG precipitates.
DOI: 10.6084/m9.figshare.23704185.v1
title: Supplementary Material for: A case of mesangial proliferative nephritis caused by slow cryoglobulin

description: The patient was a woman in her 60s. She was found to have proteinuria on a health checkup. She did not have any particular subjective symptoms, and no definitive diagnosis was made, despite serological findings indicative of immune abnormalities. A renal biopsy was performed. Light microscopy of renal tissue section revealed mesangial proliferative nephritis. Electron microscopic findings included electron dense deposits (EDD) and fibrillar/tubular structures with a diameter of 20 to 30 nm. These findings suggested the presence of cryoglobulin (CG), but CG was not detected in qualitative or quantitative hematologic tests. Thus, the serum samples were stored at 37℃ for a long period of time and then cooled to 4℃. When the obtained precipitates were examined, CG was successfully detected. CG that precipitates only after a long period of time is referred to as slow cryoglobulin (sCG), and sCG is extremely rare. The present case is the first documented case, to our knowledge, of renal disorders caused by sCG. It should be noted that there are some cases in which it takes much time for CG to precipitate. Thus, when CG cannot be detected, it is necessary to spend much time to determine whether CG precipitates.
DOI: 10.5255/ukda-sn-856620
title: Waterproofing Data Project: Participatory Flooding Maps for Flood-Prone Neighbourhoods, 2020-2021

description: The Waterproofing Data project explored how to build communities’ resilience to flooding, by engaging them in the process of generating the data used to predict when floods will occur. The project team developed a functional citizen-science mobile app prototype and a model school curriculum, which has been successfully co-produced and trialled with more than 300 students from over 20 schools and civil protection agencies of five Brazilian states (Acre, Mato Grosso, Pernambuco, Santa Catarina and Sao Paulo). The app and curriculum enabled the communities involved to democratise flood data, raise awareness of flood risks, and co-design new initiatives to reduce disaster risks to communities. The project invited participants to co-create a dataset that continuously describes the areas in which flooding impacted their territory. Through this process, the team sought to enhance knowledge about floods among those engaged with the project. This dataset showcases collaborative maps of two flood-prone neighbourhoods in Brazil. The maps were co-created and evaluated with the help of community members and school students living in underserved areas. Data was generated using the SketchMap tool https://sketch-map-tool.heigit.org. The tool supported i) printing paper maps of the neighbourhoods, ii) participants' drawings with the areas they perceived flooding risks, and iii) digitising those areas in a format suitable for cartography. The purpose of this process was to gather input from locals and identify areas that are prone to flooding in the two neighbourhoods. Labels and legends are written in Portuguese. This dataset is complementary data for our publication “Dialogic data innovations for sustainability transformations and flood resilience: The case for waterproofing data” available here https://doi.org/10.1016/j.gloenvcha.2023.102730
DOI: 10.5255/ukda-sn-856619
title: Waterproofing Data Project: Evaluation Survey Results With School Students and Community Resident Volunteers, 2020-2021

description: The Waterproofing Data project explored how to build communities’ resilience to flooding, by engaging them in the process of generating the data used to predict when floods will occur. The project team developed a functional citizen-science mobile app prototype and a model school curriculum, which has been successfully co-produced and trialled with more than 300 students from over 20 schools and civil protection agencies of five Brazilian states (Acre, Mato Grosso, Pernambuco, Santa Catarina and Sao Paulo). The app and curriculum enabled the communities involved to democratise flood data, raise awareness of flood risks, and co-design new initiatives to reduce disaster risks to communities. Aiming to understand better the impact of our project, we gathered further quantitative evidence of improvement of knowledge about floods through an evaluation survey with school students and community resident volunteers after our data generation activities using the mobile app. This data set compiles the answers to an evaluation survey aiming at evaluating the knowledge improvement about floods derived from the Waterproofing Data Project. The data groups questions in 8 groups that cover flooding aspects related to housing, neighbourhoods, communication, and flooding features. Our analysis indicates the positive impact of data generation activities on the flood risk knowledge of participants. We analysed the group of users before (baseline, n=292) and after they participated in data generation activities (treatment, n=216). The percentage of participants who declared to have “sufficient”, “good” or “very good” flood risk knowledge after our pedagogical intervention (48%) was higher than before their participation (32%) and this difference was statistically significant (Wilcoxon Signed Ranks Test, p &lt; 0.0005, effect size, r = 0.324). No significant change has been observed in a control group of non-participants. The questionnaire and answers are written in Portuguese. This dataset is complementary data for our publication “Dialogic data innovations for sustainability transformations and flood resilience: The case for waterproofing data” available here https://doi.org/10.1016/j.gloenvcha.2023.102730
DOI: 10.6084/m9.figshare.23944218
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.23944218.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.23944236
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.23944236.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: 10.5281/zenodo.8163573
title: Global SGD and CO2 data

description: This dataset is a global compilation of 40 coastal ecosystems across 12 countries. It consists of continuous time series for carbon dioxide and radon. Other parameters included are latitude, longitude, depth, temperature, salinity, and dissolved oxygen. Timestamps of each measurement correspond to the local time zone. Carbon dioxide and radon were measured using Licor and RAD7, respectively. Depth, temperature, salinity, and dissolved oxygen were measured using probes. This dataset was used to interpret the impact of SGD on CO2 dynamics in globally distributed coastal ecosystems. Data sources are mentioned in the sheet References. Column names in the "Raw Data" sheet: Location: Name of the location of measurement Location ID: ID of the location Country: Country of location Ecosystem Type: categorical ecosystem type Latitude: Latitudinal coordinate of the location (DD) Longitude: Longitudinal coordinate of the location (DD) Date (DD/MM/YYYY): Date when the measurement was taken (DD/MM/YYYY) Time since start (Days): Duration of the continuous measurement since the first measurement was started (days) Periods of Day: Part of the diurnal cycle when the measurement was taken (Day/Night) Tide: Part of the Tidal cycle when the measurement was taken (High/Ebb/Low/Flood) Depth (m): Depth at which the measurement was taken (m) Temperature (°C): Temperature at the point of radon/carbon dioxide measurement Salinity: Salinity of water at the point of radon/carbon dioxide measurement DO (%): Dissolved oxygen in the water at the point where radon measurement was taken (%) Radon (dpm/L): Radon measurement in water (dpm/L). Measured using Durridge RAD7 CO2 (µatm) at sst: measurement of Carbon Dioxide dissolved in water at sea surface temperature (µatm). Measured using LiCor.
DOI: 10.5281/zenodo.8163572
title: Global SGD and CO2 data

description: This dataset is a global compilation of 40 coastal ecosystems across 12 countries. It consists of continuous time series for carbon dioxide and radon. Other parameters included are latitude, longitude, depth, temperature, salinity, and dissolved oxygen. Timestamps of each measurement correspond to the local time zone. Carbon dioxide and radon were measured using Licor and RAD7, respectively. Depth, temperature, salinity, and dissolved oxygen were measured using probes. This dataset was used to interpret the impact of SGD on CO2 dynamics in globally distributed coastal ecosystems. Data sources are mentioned in the sheet References. Column names in the "Raw Data" sheet: Location: Name of the location of measurement Location ID: ID of the location Country: Country of location Ecosystem Type: categorical ecosystem type Latitude: Latitudinal coordinate of the location (DD) Longitude: Longitudinal coordinate of the location (DD) Date (DD/MM/YYYY): Date when the measurement was taken (DD/MM/YYYY) Time since start (Days): Duration of the continuous measurement since the first measurement was started (days) Periods of Day: Part of the diurnal cycle when the measurement was taken (Day/Night) Tide: Part of the Tidal cycle when the measurement was taken (High/Ebb/Low/Flood) Depth (m): Depth at which the measurement was taken (m) Temperature (°C): Temperature at the point of radon/carbon dioxide measurement Salinity: Salinity of water at the point of radon/carbon dioxide measurement DO (%): Dissolved oxygen in the water at the point where radon measurement was taken (%) Radon (dpm/L): Radon measurement in water (dpm/L). Measured using Durridge RAD7 CO2 (µatm) at sst: measurement of Carbon Dioxide dissolved in water at sea surface temperature (µatm). Measured using LiCor.