cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4529115
title: Data set from Mazzaccaro D, Berti F, Antonini L, Pennati G, Petrini L, Migliavacca F, Nano G. Biomechanical interpretation of observed fatigue fractures of peripheral Nitinol stents in the superficial femoral arteries through in silico modelling. Med Hypotheses. 2020 Sep;142:109771. doi: 10.1016/j.mehy.2020.109771. Epub 2020 May 4. PMID: 32408069.

description: Data set from the article Mazzaccaro D, Berti F, Antonini L, Pennati G, Petrini L, Migliavacca F, Nano G. Biomechanical interpretation of observed fatigue fractures of peripheral Nitinol stents in the superficial femoral arteries through in silico modelling. Med Hypotheses. 2020 Sep;142:109771. doi: 10.1016/j.mehy.2020.109771. Epub 2020 May 4. PMID: 32408069. <strong>Abstract </strong> <strong>Purpose: </strong>To suggest an in silico modelling approach to estimate the fatigue failure on peripheral Nitinol stents implanted in the superficial femoral artery (SFA) and interpret the clinically observed stent fractures of a retrospective series of patients. <strong>Materials and methods: </strong>Preoperative data of 27 patients who underwent SFA Nitinol stenting were retrospectively analyzed. Data about preoperative features of the SFA and the lesion were collected. Follow-up data were also collected about the occurrence of restenosis/occlusion and stent fracture. <strong>Results: </strong>After a lengthening of the entire vessel, the occluded region was slightly stretched due to its high stiffness, whereas the healthy regions accommodated the artery length variation. The stent fatigue was predicted to be higher in the regions of low stiffness and higher shortening. In 7 out of 27 patients a stent fracture was clinically recorded. The model resulted to be accurate in 90% of the cases. <strong>Conclusions: </strong>The clinical outcomes in terms of biomechanical fatigue behavior of peripheral Nitinol stents of the SFA could be interpreted by our new approach.
DOI: 10.5281/zenodo.4529135
title: Idealized GCM datasets for 'Reduced High-Latitude Land Seasonality in Climates with Very High Carbon Dioxide' by Henry and Vallis (2021)

description: Isca GCM datasets used to reproduce figures from 'Reduced High-Latitude Land Seasonality in Climates with Very High Carbon Dioxide' by Henry and Vallis (2021) Find code at https://github.com/matthewjhenry/simple-seasonality-arctic
DOI: 10.5281/zenodo.4529134
title: Idealized GCM datasets for 'Reduced High-Latitude Land Seasonality in Climates with Very High Carbon Dioxide' by Henry and Vallis (2021)

description: Isca GCM datasets used to reproduce figures from 'Reduced High-Latitude Land Seasonality in Climates with Very High Carbon Dioxide' by Henry and Vallis (2021) Find code at https://github.com/matthewjhenry/simple-seasonality-arctic
DOI: 10.5281/zenodo.3830966
title: Passive Morphological Adaptation for Obstacle Avoidance in a Self-Growing Robot Produced by Additive Manufacturing

description: Dataset acquired for the obstacle negotiation experiments. The dataset collects the forces obtained by the growing robot when facing obstacles at different inclinations. You an find the related publication on https://doi.org/10.1089/soro.2019.0025
DOI: 10.5281/zenodo.3830965
title: Passive Morphological Adaptation for Obstacle Avoidance in a Self-Growing Robot Produced by Additive Manufacturing

description: Dataset acquired for the obstacle negotiation experiments. The dataset collects the forces obtained by the growing robot when facing obstacles at different inclinations. You an find the related publication on https://doi.org/10.1089/soro.2019.0025
DOI: 10.6084/m9.figshare.13199687
title: Supplementary Datasets of Association of Gut Microbiota during Early Pregnancy with Risk of Incident Gestational Diabetes Mellitus

description: Supplemantary Datasets-Sheet1. Prevalence and relative abundance of gut microbiota at genus level of the cases and controls in the studySupplemantary Datasets-Sheet2. The a diversity metrics of the cases and controls in the study. (mean± SD)<br>Supplemantary Datasets-Sheet3. The 84 genera in Random forest analysis<br>Supplemantary Datasets-Sheet4. The 157 changing genera in Association network analysis<br>Supplemantary Datasets-Sheet5. The features in Association network analysis (274 genera)<br>
DOI: 10.6084/m9.figshare.13199687.v2
title: Supplementary Datasets of Association of Gut Microbiota during Early Pregnancy with Risk of Incident Gestational Diabetes Mellitus

description: Supplemantary Datasets-Sheet1. Prevalence and relative abundance of gut microbiota at genus level of the cases and controls in the studySupplemantary Datasets-Sheet2. The a diversity metrics of the cases and controls in the study. (mean± SD)<br>Supplemantary Datasets-Sheet3. The 84 genera in Random forest analysis<br>Supplemantary Datasets-Sheet4. The 157 changing genera in Association network analysis<br>Supplemantary Datasets-Sheet5. The features in Association network analysis (274 genera)<br>
DOI: 10.6084/m9.figshare.13199687.v1
title: Supplementary Datasets of Association of Gut Microbiota during Early Pregnancy with Risk of Incident Gestational Diabetes Mellitus

description: Supplemantary Datasets-Sheet1. Prevalence and relative abundance of gut microbiota at genus level of the cases and controls in the study.Supplemantary Datasets-Sheet2. The 84 genera in Random forest analysis<br>Supplemantary Datasets-Sheet3. The 157 changing genera in Association network analysis<br>Supplemantary Datasets-Sheet4. The features in Association network analysis (274 genera)<br>Supplemantary Datasets-Sheet5. The 177 genera in Correlation analysis<br>Supplemantary Datasets-Sheet6. The 27 genera in Association network analysis<br>Supplemantary Datasets-Sheet7. The features in Association network analysis (27 genera)<br>Supplemantary Datasets-Sheet8. The significant pathway with PICRUSt2 analysis<br>
DOI: 10.5281/zenodo.3951927
title: Phonon calculations for "Uncovering design principles for amorphous-like heat conduction using two-channel lattice dynamics"

description: These are the phonon calculations for R. Hanus, <strong>J. George</strong>, M. Wood, <strong>A. Bonkowski</strong>, Y. Cheng, D. L. Abernathy, M. E. Manley, G. Hautier, G. J. Snyder, R. P. Hermann, “Uncovering design principles for amorphous-like heat conduction using two-channel lattice dynamics”, <em>Materials Today Physics</em>, <strong>2021</strong>, In Press, https://doi.org/10.1016/j.mtphys.2021.100344
DOI: 10.5281/zenodo.3736005
title: Phonon calculations for "Uncovering design principles for amorphous-like heat conduction using two-channel lattice dynamics"

description: These are the phonon calculations for R. Hanus, <strong>J. George</strong>, M. Wood, <strong>A. Bonkowski</strong>, Y. Cheng, D. L. Abernathy, M. E. Manley, G. Hautier, G. J. Snyder, R. P. Hermann, “Uncovering design principles for amorphous-like heat conduction using two-channel lattice dynamics”, <em>Materials Today Physics</em>, <strong>2021</strong>, In Press, https://doi.org/10.1016/j.mtphys.2021.100344
DOI: 10.6084/m9.figshare.13851263
title: Supplementary Material for: Fibroblast Growth Factor 21 Predicts and Promotes Vascular Calcification in Haemodialysis Patients

description: <b><i>Background:</i></b> Cardiovascular disease (CVD) is the leading cause of death in haemodialysis (HD) patients. Vascular calcification (VC) is dramatically accelerated and is strongly associated with CVD events and mortality in HD patients. VC coexists with osteoporosis in many studies. Fibroblast growth factor 21 (FGF21) which is known as an adipocytokine is a new hypoglycemic strategy and is inversely related to bone mineral density. <b><i>Methods:</i></b> To evaluate the contribution of FGF21 to VC in HD patients, we detected circulating FGF21 levels and measured the whole thoracic aorta calcification scores (TACS) and calcification scores of the 3 segments of thoracic aorta, including ascending thoracic aorta (ATACS), aortic arch (AoACS), and descending thoracic aorta (DTACS) of our HD patients in this cross-sectional study. In addition, we pre-incubated human aortic endothelial cells (HAECs) with FGF21 in the presence or absence of parathyroid hormone (PTH) in vitro. <b><i>Results:</i></b> The median serum FGF21 level in HD patients was 11-fold higher than that in healthy controls. Ln(FGF21) was positively correlated with Ln(TACS+1), Ln(ATACS+1), Ln(AoACS+1), and Ln(DTACS+1), respectively, in HD patients. Serum FGF21 was independently associated with TACS and ATACS, AoACS, and DTACS. FGF21 which was combined with age, calcium, and intact PTH demonstrated a high area under the curve of 0.84 with optimal sensitivity (84%) and specificity (71%) for the prediction of VC in HD patients. Our vitro results showed that FGF21 enhanced the calcification effect of PTH on HAECs by increasing calcium deposition and endothelial-to-mesenchymal transition. <b><i>Conclusions:</i></b> Circulating FGF21 was notably higher and was a potential predictor and promoter of VC in HD patients.
DOI: 10.5281/zenodo.3924402
title: GAP model parameter files for "Combining phonon accuracy with high transferability in Gaussian approximation potential models"

description: GAP model parameter files to accompany the publication "Combining phonon accuracy with high transferability in Gaussian approximation potential models" by Janine George, Geoffroy Hautier, Albert P. Bartók, Gábor Csányi, and Volker L. Deringer All models are defined by the main parameter file "gp_iter6C.xml" and the associated file "gp_iter6C.xml.sparseX.GAP_00001", where "GAP_0000" is a placeholder for the unique identifier of the potential (also given in the XML header), and the trailing "1" indicates that only one set of descriptor (here, SOAP) parameters is given. The directories in this dataset follow the figures in the publication for which the respective potentials have been first used. Fig_2/only_random/M_1000<br> Fig_2/only_random/M_3000<br> Fig_2/only_random/M_5000<br> Fig_2/only_random/M_7000<br> Fig_2/only_random/M_9000 Fig_2/only_individual/M_1000<br> Fig_2/only_individual/M_3000<br> Fig_2/only_individual/M_5000<br> Fig_2/only_individual/M_7000<br> Fig_2/only_individual/M_9000 Fig_2/combined/M_1000<br> Fig_2/combined/M_3000<br> Fig_2/combined/M_5000<br> Fig_2/combined/M_7000<br> Fig_2/combined/M_9000 Fig_4/only_individual/f_0.1000<br> Fig_4/only_individual/f_0.0100<br> Fig_4/only_individual/f_0.0010<br> Fig_4/only_individual/f_0.0001 Fig_4/combined/f_0.1000<br> Fig_4/combined/f_0.0100<br> Fig_4/combined/f_0.0010<br> Fig_4/combined/f_0.0001 Fig_5/GAP-18_plus_SCs_f0.01 <br> Fig_5/GAP-18_plus_SCs_f0.001
DOI: 10.5281/zenodo.3924401
title: GAP model parameter files for "Combining phonon accuracy with high transferability in Gaussian approximation potential models"

description: GAP model parameter files to accompany the publication "Combining phonon accuracy with high transferability in Gaussian approximation potential models" by Janine George, Geoffroy Hautier, Albert P. Bartók, Gábor Csányi, and Volker L. Deringer All models are defined by the main parameter file "gp_iter6C.xml" and the associated file "gp_iter6C.xml.sparseX.GAP_00001", where "GAP_0000" is a placeholder for the unique identifier of the potential (also given in the XML header), and the trailing "1" indicates that only one set of descriptor (here, SOAP) parameters is given. The directories in this dataset follow the figures in the publication for which the respective potentials have been first used. Fig_2/only_random/M_1000<br> Fig_2/only_random/M_3000<br> Fig_2/only_random/M_5000<br> Fig_2/only_random/M_7000<br> Fig_2/only_random/M_9000 Fig_2/only_individual/M_1000<br> Fig_2/only_individual/M_3000<br> Fig_2/only_individual/M_5000<br> Fig_2/only_individual/M_7000<br> Fig_2/only_individual/M_9000 Fig_2/combined/M_1000<br> Fig_2/combined/M_3000<br> Fig_2/combined/M_5000<br> Fig_2/combined/M_7000<br> Fig_2/combined/M_9000 Fig_4/only_individual/f_0.1000<br> Fig_4/only_individual/f_0.0100<br> Fig_4/only_individual/f_0.0010<br> Fig_4/only_individual/f_0.0001 Fig_4/combined/f_0.1000<br> Fig_4/combined/f_0.0100<br> Fig_4/combined/f_0.0010<br> Fig_4/combined/f_0.0001 Fig_5/GAP-18_plus_SCs_f0.01 <br> Fig_5/GAP-18_plus_SCs_f0.001
DOI: 10.5519/qd.frkph7jt
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1349969 records)
DOI: 10.25625/usvvhj/mlzxe4
title: Randimbiharinirina et al. PaN - raw data.tab

description: :unav
DOI: 10.25625/usvvhj/0nvmkg
title: Supplementary Table S1.tab

description: :unav
DOI: 10.25625/usvvhj
title: Raw interview data

description: Raw interview data and supplementary table S1
DOI: 10.5281/zenodo.4529203
title: GMRT radiometric data of Venus observation campaign conducted during 2004

description: The folder contains all the data of the radiometric observation campaign of Venus using the GMRT carried out during 2004. The data have been used in the publication of the paper, "Radio observation of Venus at meter wavelengths using the GMRT, by Mohan et al (2017)". The data can also be obtained from the GMRT data archive (https://naps.ncra.tifr.res.in/goa/data/search) with proposal code 05BBA01.
DOI: 10.5281/zenodo.4450031
title: GMRT radiometric data of Venus observation campaign conducted during 2004

description: The folder contains all the data of the radiometric observation campaign of Venus using the GMRT carried out during 2004. The data have been used in the publication of the paper, "Radio observation of Venus at meter wavelengths using the GMRT, by Mohan et al (2017)". The data can also be obtained from the GMRT data archive (https://naps.ncra.tifr.res.in/goa/data/search) with proposal code 05BBA01.
DOI: 10.17632/6hjwh5fhpx.1
title: Numerical Model for Haze Detection (Multiple Scattering Theory Approach)

description: Sample code to conduct numerical assessment of haze detection model. These codes are written using Python programming language and follow the numerical scheme described in Section 3.2 of the paper. 
LIDAR parameters used in this sample code: laser wavelength: 808 nm, RFOV: 10 mrad. 

Sequence of operation and description:
1. data_generator.py - generates data for given LIDAR parameters and exports data as separate .csv files
2. data_analysis.py    - extracts data from .csv files for analysis according to numerical model scheme
DOI: 10.17632/6hjwh5fhpx.2
title: Multiple Scattering Theory Approach - Numerical Model for Haze Detection

description: Sample code to conduct numerical assessment of haze detection model. These codes are written using Python programming language and follow the numerical scheme described in Section 3.2 of the paper. 
LIDAR parameters used in this sample code: laser wavelength: 808 nm, RFOV: 10 mrad. 

Sequence of operation and description:
1. data_generator.py - generates data for given LIDAR parameters and exports data as separate .csv files
2. data_analysis.py    - extracts data from .csv files for analysis according to numerical model scheme
DOI: 10.17632/nznpkg9h9j.1
title: Multi-wave modeling for Covid-19 in Brazil: estimating epidemiological parameters across four waves

description: The dataset used in "Multi-wave modeling for Covid-19 in Brazil: estimating epidemiological parameters across four waves" that is under review in the International Journal of Infectious Diseases (IJID).
DOI: 10.5255/ukda-sn-856271
title: Counseling People With Dementia: Qualitative Research Interviews With Participants Living With Dementia and Other Key Practitioners, 2023

description: The data sought to capture the views of people living with dementia before and after their experience of therapeutic counselling to assess their experience of the therapeutic process. Therapist, supervisor and managerial perspectives on therapy provision were also gathered following the counselling intervention. The data comprises transcripts of pre and post-qualitative interviews with counselling participants (n=4); post-intervention qualitative interviews with the therapists who delivered the counselling intervention (n=2) and with their counselling supervisor (n=1); post-intervention qualitative interview with the care home manager of the residential care home where three of the counselling interventions took place. Also included are reflective diaries (n=36) written by the therapists following each counselling session.
DOI: 10.17632/ydf3m7pd4j.1
title: Data for: Developing a phenology- and pixel-based algorithm for mapping rapeseed at 10m spatial resolution using multi-source data
DOI: 10.17632/ydf3m7pd4j.2
title: Data for: Developing a phenology- and pixel-based algorithm for mapping rapeseed at 10m spatial resolution using multi-source data

description: The data file is in “.tif" format Temporal Resolution: Yearly Pixel size: 10 m XY Coordinate System: GCS_WGS_1984 Year: Values from 2017 to 2019
DOI: 10.17632/ydf3m7pd4j.3
title: Data for: Developing a phenology- and pixel-based algorithm for mapping rapeseed at 10m spatial resolution using multi-source data

description: The data file is in “.tif" format Temporal Resolution: Yearly Pixel size: 10 m XY Coordinate System: GCS_WGS_1984 Year: Values from 2017 to 2019
DOI: 10.17632/ydf3m7pd4j.4
title: The RapeseedMap10 database: annual maps of rapeseed at a spatial resolution of 10 m based on multi-source data

description:  The data file is in “.tif" format

Temporal Resolution: Yearly

Pixel size: 10 m

XY Coordinate System: GCS_WGS_1984

Year: Values from 2017 to 2019
DOI: 10.17632/b2y882mzg3.1
title: PREVELANCE OF FOREARM AND WRIST PAIN DUE TO PROLONGED BIKE RIDING

description: Forearm and wrist pain due to prolonged bike riding is a common issue among motorcyclists. The prevalence of this condition varies across studies, but it is clear that it is a significant problem that can lead to discomfort and injury. The position of the handlebars, the type of handlebars, and the size and shape of the handlebars are all factors that can contribute to forearm and wrist pain in Bikers.
DOI: 10.15151/esrf-es-1112062234
title: Probing the leaching of carbene-functionalized Ni nanoparticles using a combined HERDF-XAS and DFT-level molecular dynamics approach

description: Traditionally, Ni-carbene catalysts are regarded as either heterogeneous (functionalized nanoparticles) or homogeneous (complexes). However, in the past decade, seminal work by Ananikov and co-workers has established that Pd- and Pt-based carbene-functionalized nanoparticles, clusters and complexes co-exist in a dynamic equilibrium. High-resolution X-ray absorption measurements (HERFD-XAS) have proven useful for the resolution of complex reaction mixtures. The interpretation of XAS is facilitated using cross-reading based on computational models. Since solvent effects are crucial for these systems, molecular dynamics simulations at the DFT level (DFT-MD) of fully solvated Ni nanoparticles in a solvent cell are expected to provide an appropriate model for these complex systems. We will use a combined HERFD-XAS and DFT-MD approach to probe ligand effects on the behavior of carbene-ligated Ni nanoparticles, focusing on the leaching to clusters and molecular complexes in solution.
DOI: 10.6084/m9.figshare.17012473
title: Test size calculation by comparing three binomial proportions

description: For non-inferiority tests in three-arm comparisons, we establish a theorem affirming that if the rejection region is a three-dimensional Barnard convex set, then the test size is the maximum of the power function over the boundary of the null space. To illustrate this, we present two examples using the likelihood ratio test for two margin functions.
DOI: 10.6084/m9.figshare.17012473.v1
title: Test size calculation by comparing three binomial proportions

description: For non-inferiority tests in three-arm comparisons, we establish a theorem affirming that if the rejection region is a three-dimensional Barnard convex set, then the test size is the maximum of the power function over the boundary of the null space. To illustrate this, we present two examples using the likelihood ratio test for two margin functions.
DOI: 10.5281/zenodo.7910330
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 1km SIN Grid in 2014

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 1 km spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2014. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2013</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2015</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2014 Spatial Resolution: 1 km Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7910329
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 1km SIN Grid in 2014

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 1 km spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2014. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2013</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2015</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2014 Spatial Resolution: 1 km Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).