cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8340381
title: TUdi-Vinedivers_Vineyard_Soil_Data_Austria

description: Dataset of soil properties from the TUdi/Vinedivers vineyard management experiments in Austria
DOI: 10.5281/zenodo.8340371
title: Phantom measurement data for 'Pure balanced steady-state free precession imaging (pure bSSFP)'

description: This dataset contains the phantom bSSFP phase-cycled measurement data used in the published article: Schäper et al. 'Pure balanced steady-state free precession imaging (pure bSSFP)', Magn Reson Med. 2022;87:1886-1893 (doi: 10.1002/mrm.29086).<br> The acquisitions were made with a 3 T MRI system (Magnetom Prisma; Siemens Healthcare, Erlangen, Germany) using a 20 channel head coil. The data contains four datasets for different TR values (1.5 ms, 3 ms, 5 ms and 8 ms), each was measured with eight phase cycles (0°, 45°, 90°, 135°, 180°, 225°, 270° and 315°). For further measurement details, please refer to the mentioned original article.
DOI: 10.5281/zenodo.8340370
title: Phantom measurement data for 'Pure balanced steady-state free precession imaging (pure bSSFP)'

description: This dataset contains the phantom bSSFP phase-cycled measurement data used in the published article: Schäper et al. 'Pure balanced steady-state free precession imaging (pure bSSFP)', Magn Reson Med. 2022;87:1886-1893 (doi: 10.1002/mrm.29086).<br> The acquisitions were made with a 3 T MRI system (Magnetom Prisma; Siemens Healthcare, Erlangen, Germany) using a 20 channel head coil. The data contains four datasets for different TR values (1.5 ms, 3 ms, 5 ms and 8 ms), each was measured with eight phase cycles (0°, 45°, 90°, 135°, 180°, 225°, 270° and 315°). For further measurement details, please refer to the mentioned original article.
DOI: 10.6084/m9.figshare.24131760
title: Supplementary Material for: Plasma MicroRNAs related to metabolic syndrome in Mexican women

description: Introduction: The metabolic syndrome (MetS) is a cluster of abnormalities related to cardiovascular disease (CVD). Circulating miRNAs (c-miRNAs) are non-coding RNAs associated with different phenotypes, some of them integrating the MetS. The aim of the study is to compare the c-miRNAs profile in plasma between women with MetS and controls, and explore their possible association with dysregulation of metabolic pathways. Methods: The study was conducted in two phases. At the screening phase, miRNA composition in fasting plasma was compared between 8 participants with MetS and 10 healthy controls, using microarray technology. The validation phase included the analysis by qRT-PCR of 10 selected c-miRNAs in an independent sample (n=29). Results: We found 21 c-miRNAs differentially expressed between cases and controls. The concentration in plasma of the c-miRNAs hsa-miR-1260a, hsa-miR-4514 and hsa-miR-4687-5p were also correlated with risk factors for CVD. Differences of hsa-miR-1260a between cases and controls were validated using qRT-PCR. (Fold-change= 7.0; P= 0.00289). Conclusion: The signature of plasma c-miRNA differed between women with MetS and controls. The identified miRNAs regulate pathways related to the MetS such as insulin resistance and adipokine activity. The role of c-miR-1260a in the MetS remains to be elucidated.
DOI: 10.5281/zenodo.8340272
title: BikeDNA BIG: Denmark analysis

description: All code, data and results from running BikeDNA BIG with bicycle infrastructure data from Denmark: https://github.com/anerv/BikeDNA_BIG/ Data from © OpenStreetMap contributors and © SDFI
DOI: 10.34740/kaggle/dsv/6463495
title: Egypt Gold Prices | Daily Updated
DOI: 10.5281/zenodo.8340303
title: Science, Technology & Society Eurobarometers 1993 - 2021: Trend Data Collection

description: These files contain structured collections of Eurobarometer (EB) survey data from 1993 to 2021, focusing on European citizen’s views on science and technology (S&T). The primary aim of these data collections is to facilitate research on trends over time regarding people’s knowledge, perception and attitudes towards S&T. The European Union has collected extensive survey data from the general public over the past 50 years through its official polling instrument, the Eurobarometer. Its general goal is monitoring the state of public opinion on diverse subjects and issues throughout Europe, one of which is S&T. The data collection files, provided in the folder ‘EB_data_csv’, include data from seven different Eurobarometer surveys. These surveys were selected because their raw datasets were openly accessible through Open EU Datasets. To ensure sufficient data points for plotting specific trends over time, we included only survey questions that appeared in at least three different EB surveys.
DOI: 10.5281/zenodo.8340302
title: Science, Technology & Society Eurobarometers 1993 - 2021: Trend Data Collection

description: These files contain structured collections of Eurobarometer (EB) survey data from 1993 to 2021, focusing on European citizen’s views on science and technology (S&T). The primary aim of these data collections is to facilitate research on trends over time regarding people’s knowledge, perception and attitudes towards S&T. The European Union has collected extensive survey data from the general public over the past 50 years through its official polling instrument, the Eurobarometer. Its general goal is monitoring the state of public opinion on diverse subjects and issues throughout Europe, one of which is S&T. The data collection files, provided in the folder ‘EB_data_csv’, include data from seven different Eurobarometer surveys. These surveys were selected because their raw datasets were openly accessible through Open EU Datasets. To ensure sufficient data points for plotting specific trends over time, we included only survey questions that appeared in at least three different EB surveys.
DOI: 10.6084/m9.figshare.24131754
title: IDENT tree trait database

description: Soon...
DOI: 10.6084/m9.figshare.24131775
title: Supplementary Material for: Clinicoradiological Factors Predicting Lymph Node Metastasis in Patients with Nonfunctioning Pancreatic Neuroendocrine Neoplasms: A Systematic Review and Meta-Analysis

description: Introduction: Lymph node metastasis of nonfunctioning pancreatic neuroendocrine neoplasms (pNENs) potentially leads to poor survival. Given the contradictory results in the literature regarding factors associated with lymph node metastasis of nonfunctioning pNENs, we conducted a systematic review and meta-analysis to determine the preoperative predictors of lymph node metastasis. Methods: Original studies reporting factors associated with lymph node metastasis in patients with nonfunctioning pNENs were identified in PubMed, EMBASE, and Cochrane Library databases, and data from eligible studies were analyzed using random-effects meta-analysis to obtain pooled estimates of odds ratios (OR) and their 95% confidence intervals (CI). Results: Eleven studies were included. Tumor size (&gt;2 cm or &gt;2.5 cm; OR, 5.80 [95% CI, 4.07–8.25]) and pancreatic head location (OR, 1.75 [95% CI, 1.05–2.94]) were significant preoperative predictors of lymph node metastasis. Age (OR, 1.07 [95% CI, 0.68–1.68]) and male sex (OR, 1.12 [95% CI, 0.74–1.70]) were not significantly associated with lymph node metastasis. Conclusions: A large tumor size and pancreatic head location can be useful for planning optimal treatment in patients with nonfunctioning pNENs.
DOI: 10.5281/zenodo.8340387
title: Phantom measurement data for 'Myelin water imaging at 0.55 T using a multi-gradient-echo sequence'

description: This dataset contains the phantom mGRE measurement data used in the submitted article Schäper et al. 'Myelin water imaging at 0.55 T using a multi-gradient-echo sequence'.<br> The acquisitions were done with a 0.55 T MRI system (Magnetom Free.Max; Siemens Healthcare, Erlangen, Germany) using a 12 channel head coil and a 3 T MRI system (Magnetom Prisma; Siemens Healthcare, Erlangen, Germany) using a 20 channel head coil. For further measurement details, please refer to the mentioned original article.
DOI: 10.5281/zenodo.8340386
title: Phantom measurement data for 'Myelin water imaging at 0.55 T using a multi-gradient-echo sequence'

description: This dataset contains the phantom mGRE measurement data used in the submitted article Schäper et al. 'Myelin water imaging at 0.55 T using a multi-gradient-echo sequence'.<br> The acquisitions were done with a 0.55 T MRI system (Magnetom Free.Max; Siemens Healthcare, Erlangen, Germany) using a 12 channel head coil and a 3 T MRI system (Magnetom Prisma; Siemens Healthcare, Erlangen, Germany) using a 20 channel head coil. For further measurement details, please refer to the mentioned original article.
DOI: 10.5281/zenodo.1238215
title: Yerrida Basin Geophysical Modeling - Input data and inverted models.

description: This companion datasets relates to the manuscript "<strong>Integration of geological uncertainty into geophysical inversion by means of local gradient regularization</strong>", by J. Giraud, M. Lindsay, V. Ogarko, M. Jessell, R. Martin and E. Pakyuz-Charrier, submitted to Solid Earth. The archive contains the input and output geophysical data, starting and inverted models, probabilistic geological model and conditioning volume derived from the calculation of Shannon's entropy.
DOI: 10.6084/m9.figshare.24131787
title: Supplementary Material for: Clinicoradiological Factors Predicting Lymph Node Metastasis in Patients with Nonfunctioning Pancreatic Neuroendocrine Neoplasms: A Systematic Review and Meta-Analysis

description: Introduction: Lymph node metastasis of nonfunctioning pancreatic neuroendocrine neoplasms (pNENs) potentially leads to poor survival. Given the contradictory results in the literature regarding factors associated with lymph node metastasis of nonfunctioning pNENs, we conducted a systematic review and meta-analysis to determine the preoperative predictors of lymph node metastasis. Methods: Original studies reporting factors associated with lymph node metastasis in patients with nonfunctioning pNENs were identified in PubMed, EMBASE, and Cochrane Library databases, and data from eligible studies were analyzed using random-effects meta-analysis to obtain pooled estimates of odds ratios (OR) and their 95% confidence intervals (CI). Results: Eleven studies were included. Tumor size (&gt;2 cm or &gt;2.5 cm; OR, 5.80 [95% CI, 4.07–8.25]) and pancreatic head location (OR, 1.75 [95% CI, 1.05–2.94]) were significant preoperative predictors of lymph node metastasis. Age (OR, 1.07 [95% CI, 0.68–1.68]) and male sex (OR, 1.12 [95% CI, 0.74–1.70]) were not significantly associated with lymph node metastasis. Conclusions: A large tumor size and pancreatic head location can be useful for planning optimal treatment in patients with nonfunctioning pNENs.
DOI: 10.6084/m9.figshare.24131787.v1
title: Supplementary Material for: Clinicoradiological Factors Predicting Lymph Node Metastasis in Patients with Nonfunctioning Pancreatic Neuroendocrine Neoplasms: A Systematic Review and Meta-Analysis

description: Introduction: Lymph node metastasis of nonfunctioning pancreatic neuroendocrine neoplasms (pNENs) potentially leads to poor survival. Given the contradictory results in the literature regarding factors associated with lymph node metastasis of nonfunctioning pNENs, we conducted a systematic review and meta-analysis to determine the preoperative predictors of lymph node metastasis. Methods: Original studies reporting factors associated with lymph node metastasis in patients with nonfunctioning pNENs were identified in PubMed, EMBASE, and Cochrane Library databases, and data from eligible studies were analyzed using random-effects meta-analysis to obtain pooled estimates of odds ratios (OR) and their 95% confidence intervals (CI). Results: Eleven studies were included. Tumor size (&gt;2 cm or &gt;2.5 cm; OR, 5.80 [95% CI, 4.07–8.25]) and pancreatic head location (OR, 1.75 [95% CI, 1.05–2.94]) were significant preoperative predictors of lymph node metastasis. Age (OR, 1.07 [95% CI, 0.68–1.68]) and male sex (OR, 1.12 [95% CI, 0.74–1.70]) were not significantly associated with lymph node metastasis. Conclusions: A large tumor size and pancreatic head location can be useful for planning optimal treatment in patients with nonfunctioning pNENs.
DOI: 10.6084/m9.figshare.24131793
title: Supplementary Material for: Clinicoradiological Factors Predicting Lymph Node Metastasis in Patients with Nonfunctioning Pancreatic Neuroendocrine Neoplasms: A Systematic Review and Meta-Analysis

description: Introduction: Lymph node metastasis of nonfunctioning pancreatic neuroendocrine neoplasms (pNENs) potentially leads to poor survival. Given the contradictory results in the literature regarding factors associated with lymph node metastasis of nonfunctioning pNENs, we conducted a systematic review and meta-analysis to determine the preoperative predictors of lymph node metastasis. Methods: Original studies reporting factors associated with lymph node metastasis in patients with nonfunctioning pNENs were identified in PubMed, EMBASE, and Cochrane Library databases, and data from eligible studies were analyzed using random-effects meta-analysis to obtain pooled estimates of odds ratios (OR) and their 95% confidence intervals (CI). Results: Eleven studies were included. Tumor size (&gt;2 cm or &gt;2.5 cm; OR, 5.80 [95% CI, 4.07–8.25]) and pancreatic head location (OR, 1.75 [95% CI, 1.05–2.94]) were significant preoperative predictors of lymph node metastasis. Age (OR, 1.07 [95% CI, 0.68–1.68]) and male sex (OR, 1.12 [95% CI, 0.74–1.70]) were not significantly associated with lymph node metastasis. Conclusions: A large tumor size and pancreatic head location can be useful for planning optimal treatment in patients with nonfunctioning pNENs.
DOI: 10.6084/m9.figshare.24131793.v1
title: Supplementary Material for: Clinicoradiological Factors Predicting Lymph Node Metastasis in Patients with Nonfunctioning Pancreatic Neuroendocrine Neoplasms: A Systematic Review and Meta-Analysis

description: Introduction: Lymph node metastasis of nonfunctioning pancreatic neuroendocrine neoplasms (pNENs) potentially leads to poor survival. Given the contradictory results in the literature regarding factors associated with lymph node metastasis of nonfunctioning pNENs, we conducted a systematic review and meta-analysis to determine the preoperative predictors of lymph node metastasis. Methods: Original studies reporting factors associated with lymph node metastasis in patients with nonfunctioning pNENs were identified in PubMed, EMBASE, and Cochrane Library databases, and data from eligible studies were analyzed using random-effects meta-analysis to obtain pooled estimates of odds ratios (OR) and their 95% confidence intervals (CI). Results: Eleven studies were included. Tumor size (&gt;2 cm or &gt;2.5 cm; OR, 5.80 [95% CI, 4.07–8.25]) and pancreatic head location (OR, 1.75 [95% CI, 1.05–2.94]) were significant preoperative predictors of lymph node metastasis. Age (OR, 1.07 [95% CI, 0.68–1.68]) and male sex (OR, 1.12 [95% CI, 0.74–1.70]) were not significantly associated with lymph node metastasis. Conclusions: A large tumor size and pancreatic head location can be useful for planning optimal treatment in patients with nonfunctioning pNENs.
DOI: 10.34943/0a003926-76a7-441c-a8ea-05dd12875b03
title: Barkley Canyon Hydrates Multibeam Rotary Sonar Deployed 2023-09-11

description: The Imagenex Delta-T 837B Sonar 5756 was deployed on 2023-09-11 at Barkley Canyon Hydrates. Barkley Canyon Hydrates denotes a gas hydrate field within Barkley Canyon. This device is a Multibeam Rotary Sonar. Multibeam Rotary Sonars (MRS) are devices used in underwater imaging. The use of wide beam and high speed, allows the display of an image from a wide field of view in a video-like fashion. Mounted on a platform, a multibeam transducer rotates at fixed increments and intervals to survey up to 360 degrees. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.5281/zenodo.8340379
title: ASSIST-IoT Multimodal Fall Detection Dataset

description: Multimodal dataset for fall detection. Includes acceleration data collected from a tag and two smartwatches, and location reported by the tag. More details about the data collection procedure can be found in <code>notes.md</code>. <strong>Contents</strong> The repository contains: <code>data/location_data.csv</code> and <code>data/full_acceleration</code> – preprocessed acceleration and location data from 10 participants and mannequin simulated falls with target variable identified <code>data/subsampled_acceleration_data.csv</code> – subsampled acceleration dataset used for training the AI model <code>notes.md</code> – description of activities performed and notes from data collection <code>videos</code> – reference videos for performed activities <strong>Authors</strong> Piotr Sowiński – research methodology, data collection and processing Monika Kobus – research methodology, data collection Anna Dąbrowska – research methodology, methodological supervision Kajetan Rachwał – data collection Karolina Bogacka – research methodology Krzysztof Baszczyński – research methodology, data collection Anastasiya Danilenka – research methodology, data collection and processing <strong>Acknowledgements</strong> This work is part of the ASSIST-IoT project that has received funding from the EU’s Horizon 2020 research and innovation programme under grant agreement No 957258. The Central Institute for Labour Protection – National Research Institute provided facilities and equipment for data collection. <strong>License</strong> The dataset is licensed under the Creative Commons Attribution 4.0 International License.
DOI: 10.5281/zenodo.8340378
title: ASSIST-IoT Multimodal Fall Detection Dataset

description: Multimodal dataset for fall detection. Includes acceleration data collected from a tag and two smartwatches, and location reported by the tag. More details about the data collection procedure can be found in <code>notes.md</code>. <strong>Contents</strong> The repository contains: <code>data/location_data.csv</code> and <code>data/full_acceleration</code> – preprocessed acceleration and location data from 10 participants and mannequin simulated falls with target variable identified <code>data/subsampled_acceleration_data.csv</code> – subsampled acceleration dataset used for training the AI model <code>notes.md</code> – description of activities performed and notes from data collection <code>videos</code> – reference videos for performed activities <strong>Authors</strong> Piotr Sowiński – research methodology, data collection and processing Monika Kobus – research methodology, data collection Anna Dąbrowska – research methodology, methodological supervision Kajetan Rachwał – data collection Karolina Bogacka – research methodology Krzysztof Baszczyński – research methodology, data collection Anastasiya Danilenka – research methodology, data collection and processing <strong>Acknowledgements</strong> This work is part of the ASSIST-IoT project that has received funding from the EU’s Horizon 2020 research and innovation programme under grant agreement No 957258. The Central Institute for Labour Protection – National Research Institute provided facilities and equipment for data collection. <strong>License</strong> The dataset is licensed under the Creative Commons Attribution 4.0 International License.
DOI: 10.5281/zenodo.8340428
title: ASSIST-IoT Multimodal Fall Detection Dataset

description: Multimodal dataset for fall detection. Includes acceleration data collected from a tag and two smartwatches, and location reported by the tag. More details about the data collection procedure can be found in <code>notes.md</code>. <strong>Contents</strong> The repository contains: <code>data/location_data.csv</code> and <code>data/full_acceleration</code> – preprocessed acceleration and location data from 10 participants and mannequin simulated falls with target variable identified <code>data/subsampled_acceleration_data.csv</code> – subsampled acceleration dataset used for training the AI model <code>notes.md</code> – description of activities performed and notes from data collection <code>videos</code> – reference videos for performed activities <strong>Authors</strong> Piotr Sowiński – research methodology, data collection and processing Monika Kobus – research methodology, data collection Anna Dąbrowska – research methodology, methodological supervision Kajetan Rachwał – data collection Karolina Bogacka – research methodology Krzysztof Baszczyński – research methodology, data collection Anastasiya Danilenka – research methodology, data collection and processing <strong>Acknowledgements</strong> This work is part of the ASSIST-IoT project that has received funding from the EU’s Horizon 2020 research and innovation programme under grant agreement No 957258. The Central Institute for Labour Protection – National Research Institute provided facilities and equipment for data collection. <strong>License</strong> The dataset is licensed under the Creative Commons Attribution 4.0 International License.
DOI: 10.18746/bmth.data.00000320
title: VR Clinical Training Simulation Usability Scores
DOI: 10.5255/ukda-sn-856672
title: Central Bank Independence in 21 OECD Countries: Panel Dataset, 2010-2020

description: In the literature, the consensus about the importance of the independence of the central banks towards stable economic growth has been proven (e.g. Barro and Gordon 1983). The empirical papers studying this problem follow Cukierman, Webb, and Neyapti (1992) central bank independence index which does not include some important factors such as rule of law in the given country and defines the components of independence too generally. In this project, we aim to build an alternative index that will measure the central bank independence in more detail which will account for the rule of law and other relevant aspects that indirectly affect the true independence of the central bank. Obtaining the index, we will study whether the independence of the central bank has a positive effect on maintaining the given central bank's primary target. Furthermore, in this research, we aim to test whether our results differ from the previous findings in the empirical literature on the central bank independence and its effect on stable prices. Based on the obtained results, an optimal legislature of the central bank's independence shall be suggested. This panel dataset provides an assessment of the independence of central banks in 21 OECD countries (excluding the Eurozone), focusing on their monetary policy autonomy as determined by legislation in 2010, 2015, and 2020. Our data collection adopts a novel approach, building upon theinnovating methodology proposed by Cukierman et al. (1992), while incorporating revised components of the index that place greater emphasis on current standards of central bank independence. Additionally, we introduce new criteria to evaluate budgetary independence, an important aspect of central bank autonomy (Swinburne and Castello-Branco, 1991). The dataset serves as a valuable resource for empirical studies seeking to analyze the impact of monetary policy independence on economic performance. Furthermore, policymakers can draw insights from this index to enhance legislative frameworks and promote stronger performance in central bank independence.