cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7284/104750
title: Speedlog data collected during research cruise CH0111 using a Furuno DS-80 instrument system onboard the platform RV Cape Hatteras

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/107837
title: Anemometer data collected during research cruise CH0112 using a RM Young 05103 instrument system onboard the platform RV Cape Hatteras

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/107838
title: Anemometer data collected during research cruise CH0112 using a RM Young 05103 instrument system onboard the platform RV Cape Hatteras

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/107840
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise CH0112 using a Sea-Bird SBE-911+ instrument system onboard the platform RV Cape Hatteras

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7660286
title: Temperaure.csv

description: Vitesse d'un cours d'eau
DOI: 10.6084/m9.figshare.7660286.v1
title: Temperaure.csv

description: Vitesse d'un cours d'eau
DOI: 10.7284/107832
title: Fluorometer data collected during research cruise CH0112 using a Turner 10-AU instrument system onboard the platform RV Cape Hatteras

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7660274
title: Supplementary Material for: Endogenous Erythropoietin and Hepatic Dysfunction in Acute Kidney Injury Requiring Renal Replacement Therapy

description: <b><i>Backgrounds/Objectives:</i></b> Elevated erythropoietin (EPO) is observed in human acute kidney injury (AKI). Whether blood EPO level is associated with mortality or other organ dysfunction in critically ill patients is unknown. <b><i>Methods:</i></b> A prospective observational cohort study of 162 AKI patients requiring renal replacement therapy (RRT) was conducted in our intensive care unit (ICU) during October 2013 through October 2016. We evaluated the relation with plasma EPO at RRT initiation and 90-day mortality, hemoglobin, urine output, and sequential organ failure assessment (SOFA) score until day 7 or discharge from the ICU. <b><i>Results:</i></b> The analysis revealed that EPO was significantly associated with 90-day mortality with an adjusted hazard ratio of 2.13 (95% CI 1.11–5.78). Hemoglobin levels, RRT dependence, and daily urine output on days 1 through 7 did not differ between the high EPO group (≥56.2 mIU/mL) and low EPO groups (&lt; 56.2 mIU/mL). As for organ dysfunction, hyperbilirubinemia patients (≥2.0 mg/dL; hepatic SOFA ≥2) were more frequent in the high EPO group (62.1 vs. 37.9%; <i>p</i> &lt; 0.05), while other SOFA scores did not differ between both groups. Exacerbation of hepatic dysfunction was observed more frequently in the high EPO than the low EPO group (49.3 vs. 27.2%; <i>p</i> &lt; 0.05). <b><i>Conclusion:</i></b> Elevated EPO was not associated with anemia or RRT dependence. However, higher rates of mortality and hepatic dysfunction were observed in high EPO patients than in low EPO patients.
DOI: 10.7284/107839
title: GNSS (Global Navigation Satellite System) data collected during research cruise CH0112 using a Northstar 952X instrument system onboard the platform RV Cape Hatteras

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7660268
title: Supplementary Material for: End-Stage Kidney Diseases in Immigrant Groups: A Nationwide Cohort Study in Sweden

description: <b><i>Background:</i></b> Our aim was to study the association between the country of birth and incident end-stage kidney disease (ESKD) in several immigrant groups in Sweden, using individuals born in Sweden or with Swedish-born parents as referents. <b><i>Methods:</i></b> A cohort study of first- and second-generation immigrants residing in Sweden between January 1, 1998 and December 31, 2012 was performed. Outcomes were defined as having at least one registered diagnosis of ESKD in the National Patient Register. The incidence of ESKD in different immigrant groups was used in the Cox regression models to estimate hazard ratios (HRs) and 95% CIs. All models were stratified by sex and adjusted for age, geographical residence, educational level, marital status, and neighbourhood socioeconomic status. <b><i>Results:</i></b> Compared to their referents, higher incidence rates and HRs of ESKD (HR; 95% CI) were observed in general among foreign-born men (1.10; 1.04–1.16) and women (1.12; 1.04–1.21) but not among second-generation immigrants (persons born in Sweden with foreign-born parents). A particularly high ­incidence was noted among men and women from ­East-European countries, as well as from non-European regions. A lower incidence of ESKD was noted among men from Finland. <b><i>Conclusions:</i></b> We observed substantial differences in incidence of ESKD between immigrant groups and the Swedish-born population, which may be clinically relevant when monitoring preventive measures in patient subgroups with a higher risk of deteriorating kidney disease, and suggest higher attention to hypertension and diabetes control in immigrants. Mechanisms attributable to the migration process or ethnic differences may lead to an increased risk of ESKD.
DOI: 10.6084/m9.figshare.7660274.v1
title: Supplementary Material for: Endogenous Erythropoietin and Hepatic Dysfunction in Acute Kidney Injury Requiring Renal Replacement Therapy

description: <b><i>Backgrounds/Objectives:</i></b> Elevated erythropoietin (EPO) is observed in human acute kidney injury (AKI). Whether blood EPO level is associated with mortality or other organ dysfunction in critically ill patients is unknown. <b><i>Methods:</i></b> A prospective observational cohort study of 162 AKI patients requiring renal replacement therapy (RRT) was conducted in our intensive care unit (ICU) during October 2013 through October 2016. We evaluated the relation with plasma EPO at RRT initiation and 90-day mortality, hemoglobin, urine output, and sequential organ failure assessment (SOFA) score until day 7 or discharge from the ICU. <b><i>Results:</i></b> The analysis revealed that EPO was significantly associated with 90-day mortality with an adjusted hazard ratio of 2.13 (95% CI 1.11–5.78). Hemoglobin levels, RRT dependence, and daily urine output on days 1 through 7 did not differ between the high EPO group (≥56.2 mIU/mL) and low EPO groups (&lt; 56.2 mIU/mL). As for organ dysfunction, hyperbilirubinemia patients (≥2.0 mg/dL; hepatic SOFA ≥2) were more frequent in the high EPO group (62.1 vs. 37.9%; <i>p</i> &lt; 0.05), while other SOFA scores did not differ between both groups. Exacerbation of hepatic dysfunction was observed more frequently in the high EPO than the low EPO group (49.3 vs. 27.2%; <i>p</i> &lt; 0.05). <b><i>Conclusion:</i></b> Elevated EPO was not associated with anemia or RRT dependence. However, higher rates of mortality and hepatic dysfunction were observed in high EPO patients than in low EPO patients.
DOI: 10.7284/107836
title: Gyrocompass data collected during research cruise CH0112 using a Sperry MK-37 instrument system onboard the platform RV Cape Hatteras

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7660265
title: Supplementary Material for: Reported Outcomes in Perinatal Iron Deficiency Anemia Trials: A Systematic Review

description: <b><i>Background/Aims:</i></b> Iron deficiency (ID) and iron deficiency anemia (IDA) are global health concerns associated with adverse perinatal effects. Despite efforts taken at the international level, there is no consensus on unified prevention/treatment strategies, largely stemming from inconsistencies of outcome reporting. Our objective was to comprehensively assess outcome reporting perinatal iron intervention trials as Phase 1 of core outcome set (COS) development to inform future research. <b><i>Methods:</i></b> Systematic search in MEDLINE, EMBASE, Cochrane Databases, and CINAHL (January 2000 – April 2016), with inclusion of trials involving pregnant or postpartum women with ID/IDA confirmed before recruitment. Articles were independently screened and selected by 2 reviewers; data were extracted in duplicate. Quality was assessed using published scoring systems. Outcome definitions and measurement methods were tabulated. <b><i>Results:</i></b> Of 7,046 citations, 33 randomized controlled trials were included. Sixty-nine reported outcomes were categorized into 8 domains. High methodological quality characterized 25 (76%) studies. Reporting quality was low in 16 (49%), moderate in 13 (39%), and high in 4 (12%) studies. Variation was greatest for outcome definition, timing of assessment and measurement methods. <b><i>Conclusion:</i></b> This review identifies a comprehensive long-list of outcomes reported of perinatal iron interventions for ID/IDA. Beyond highlighting existing variation in outcome reporting, it provides a foundation for development of a COS for future trials.
DOI: 10.7284/107833
title: Meteorological Station data collected during research cruise CH0112 using a RM Young 26700 instrument system onboard the platform RV Cape Hatteras

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7660265.v1
title: Supplementary Material for: Reported Outcomes in Perinatal Iron Deficiency Anemia Trials: A Systematic Review

description: <b><i>Background/Aims:</i></b> Iron deficiency (ID) and iron deficiency anemia (IDA) are global health concerns associated with adverse perinatal effects. Despite efforts taken at the international level, there is no consensus on unified prevention/treatment strategies, largely stemming from inconsistencies of outcome reporting. Our objective was to comprehensively assess outcome reporting perinatal iron intervention trials as Phase 1 of core outcome set (COS) development to inform future research. <b><i>Methods:</i></b> Systematic search in MEDLINE, EMBASE, Cochrane Databases, and CINAHL (January 2000 – April 2016), with inclusion of trials involving pregnant or postpartum women with ID/IDA confirmed before recruitment. Articles were independently screened and selected by 2 reviewers; data were extracted in duplicate. Quality was assessed using published scoring systems. Outcome definitions and measurement methods were tabulated. <b><i>Results:</i></b> Of 7,046 citations, 33 randomized controlled trials were included. Sixty-nine reported outcomes were categorized into 8 domains. High methodological quality characterized 25 (76%) studies. Reporting quality was low in 16 (49%), moderate in 13 (39%), and high in 4 (12%) studies. Variation was greatest for outcome definition, timing of assessment and measurement methods. <b><i>Conclusion:</i></b> This review identifies a comprehensive long-list of outcomes reported of perinatal iron interventions for ID/IDA. Beyond highlighting existing variation in outcome reporting, it provides a foundation for development of a COS for future trials.
DOI: 10.5281/zenodo.7686404
title: Relative Phase Data to 'Experimental observation of curved light-cones in a quantum field simulator', arXiv:2209.09132

description: <strong>Relative phase profiles and averaged density profiles for the results shown in arXiv:2209.09132</strong> Each file "phase_and_mean_density_scan_X.mat" contains data for a measurement presented in the manuscript, where "X" is the corresponding scan number.<br> The following table shows the relevant scan number to measurement descriptions mentioned in the manuscript (see Table S1 in the SI Appendix). Measurement description Scan number Homogeneous (main text) 9185 Inhomogeneous with sharp edges 10419 Inhomogeneous with smoothed edges 8935 Homogeneous 2 (SI Appendix) 10455 <strong>File Contents</strong> Each file contains the following variables: "phase": A MATLAB cell containing all the phase profiles for every time step. Thus, "phase{t_ind}" is a matrix where rows represent experimental realizations and columns the spatial grid points. For example, "phase{5}(1,:)" would be a one-dimensional phase profile, representing the first realization of the fifth time step. To learn more about the extraction of phase profiles, read Section 2 and see Fig. S5 in SI Appendix. "z_grid_phase_si": Vector. Grid points for phase profiles in SI units (m). "averaged_density_si": Vector. Averaged initial linear density in SI units (m^-1). See Fig. 1(a). "z_grid_density_si": Vector. Grid points for averaged density in SI units (m). "times_si": Vector. Time points in SI units (s). <strong>Matlab script calculating the velocity field</strong> In addition to the data, a MATLAB script (velocity_field_calculation.m) loads a data file and calculates the velocity field and its correlations following the equations in the manuscript: "u": MATLAB cell. Velocity field for every time step. "u_u_corr": MATLAB cell. Second-order correlations of the velocity field for every time step. "std_u_u_corr": MATLAB cell. Standard deviation of second-order correlations of the velocity field for every time-step. Finally, the script plots "u_u_corr" for all the time steps and plots the averaged linear density.
DOI: 10.5281/zenodo.7686403
title: Relative Phase Data to 'Experimental observation of curved light-cones in a quantum field simulator', arXiv:2209.09132

description: <strong>Relative phase profiles and averaged density profiles for the results shown in arXiv:2209.09132</strong> Each file "phase_and_mean_density_scan_X.mat" contains data for a measurement presented in the manuscript, where "X" is the corresponding scan number.<br> The following table shows the relevant scan number to measurement descriptions mentioned in the manuscript (see Table S1 in the SI Appendix). Measurement description Scan number Homogeneous (main text) 9185 Inhomogeneous with sharp edges 10419 Inhomogeneous with smoothed edges 8935 Homogeneous 2 (SI Appendix) 10455 <strong>File Contents</strong> Each file contains the following variables: "phase": A MATLAB cell containing all the phase profiles for every time step. Thus, "phase{t_ind}" is a matrix where rows represent experimental realizations and columns the spatial grid points. For example, "phase{5}(1,:)" would be a one-dimensional phase profile, representing the first realization of the fifth time step. To learn more about the extraction of phase profiles, read Section 2 and see Fig. S5 in SI Appendix. "z_grid_phase_si": Vector. Grid points for phase profiles in SI units (m). "averaged_density_si": Vector. Averaged initial linear density in SI units (m^-1). See Fig. 1(a). "z_grid_density_si": Vector. Grid points for averaged density in SI units (m). "times_si": Vector. Time points in SI units (s). <strong>Matlab script calculating the velocity field</strong> In addition to the data, a MATLAB script (velocity_field_calculation.m) loads a data file and calculates the velocity field and its correlations following the equations in the manuscript: "u": MATLAB cell. Velocity field for every time step. "u_u_corr": MATLAB cell. Second-order correlations of the velocity field for every time step. "std_u_u_corr": MATLAB cell. Standard deviation of second-order correlations of the velocity field for every time-step. Finally, the script plots "u_u_corr" for all the time steps and plots the averaged linear density.
DOI: 10.6084/m9.figshare.19317638
title: Occlusion and coupling effects with different earmold designs – all a matter of opening the ear canal?

description: Ear canal occlusion by a hearing aid leads to an unnatural sound of the own voice due to a level increase of bone-conducted low-frequency components of the ear canal. Opening the ear through vents or domes reduces this so-called occlusion effect, however at the cost of reduced hearing aid performance. For individual earmolds, several other design options to reduce the occlusion effect have been proposed but not reliably evaluated. The occlusion effect and coupling parameters were assessed through subjective ratings and real-ear measurements. Six individual earmold designs, each with different venting options, were tested in 10 subjects. In line with previous studies, our data show that the opening of the ear as described by the acoustic mass of the vent is the prime parameter that predicts both the occlusion effect and coupling parameters. However, the design of the earmold, most importantly the location where sealing of the ear canal is achieved, is another important factor for occlusion and coupling effects. Although no reduction of the occlusion effect seems possible without additional opening of the ear canal, some earmold modifications seem to aggravate the occlusion effect as compared to a standard earmold with equivalent vent.
DOI: 10.6084/m9.figshare.19317638.v1
title: Occlusion and coupling effects with different earmold designs – all a matter of opening the ear canal?

description: Ear canal occlusion by a hearing aid leads to an unnatural sound of the own voice due to a level increase of bone-conducted low-frequency components of the ear canal. Opening the ear through vents or domes reduces this so-called occlusion effect, however at the cost of reduced hearing aid performance. For individual earmolds, several other design options to reduce the occlusion effect have been proposed but not reliably evaluated. The occlusion effect and coupling parameters were assessed through subjective ratings and real-ear measurements. Six individual earmold designs, each with different venting options, were tested in 10 subjects. In line with previous studies, our data show that the opening of the ear as described by the acoustic mass of the vent is the prime parameter that predicts both the occlusion effect and coupling parameters. However, the design of the earmold, most importantly the location where sealing of the ear canal is achieved, is another important factor for occlusion and coupling effects. Although no reduction of the occlusion effect seems possible without additional opening of the ear canal, some earmold modifications seem to aggravate the occlusion effect as compared to a standard earmold with equivalent vent.
DOI: 10.6084/m9.figshare.21647450.v1
title: 1079773: A Bioartificial and Vasculomorphic Bone Matrix -based Organoid for Studying Microtopography of Bone Immunomodulation_MS Proteomics data

description: Rat tail collagene was extracted following standard methods and analyzed in its molecular components.
DOI: 10.6084/m9.figshare.21647450
title: 1079773: A Bioartificial and Vasculomorphic Bone Matrix -based Organoid for Studying Microtopography of Bone Immunomodulation_MS Proteomics data

description: Rat tail collagene was extracted following standard methods and analyzed in its molecular components.
DOI: 10.26179/1pb8-4g29
title: Orthomosaic and digital surface model of Casey station, 8th February 2023.
DOI: 10.5281/zenodo.7604077
title: Doodleverse/Segmentation Zoo Res-UNet models for Aerial/nadir/2-class (water, nowater) segmentation of RGB 1024x768 high-res. images

description: <em><strong>Doodleverse/Segmentation Zoo Res-UNet models for Aerial/nadir/2-class (water, nowater) segmentation of RGB 1024x768 high-res. images</strong></em> These Residual-UNet models have been created using Segmentation Gym* using the following dataset**: Image size used by model: 1024 x 768 x 3 pixels classes: water other <br> <strong>File descriptions</strong> For each model, there are 5 files with the same root name: 1. '.json' config file: this is the file that was used by Segmentation Gym* to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse. 2. '.h5' weights file: this is the file that was created by the Segmentation Gym* function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym* function `seg_images_in_folder.py`. Models may be ensembled. 3. '_modelcard.json' model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model 4. '_model_history.npz' model training history file: this numpy archive file contains numpy arrays describing the training and validation losses and metrics. It is created by the Segmentation Gym function `train_model.py` 5. '.png' model training loss and mean IoU plot: this png file contains plots of training and validation losses and mean IoU scores during model training. A subset of data inside the .npz file. It is created by the Segmentation Gym function `train_model.py` Additionally, BEST_MODEL.txt contains the name of the model with the best validation loss and mean IoU <strong>References</strong> <br> *Segmentation Gym: Buscombe, D., & Goldstein, E. B. (2022). A reproducible and reusable pipeline for segmentation of geoscientific imagery. Earth and Space Science, 9, e2022EA002332. https://doi.org/10.1029/2022EA002332 See: https://github.com/Doodleverse/segmentation_gym **
DOI: 10.5281/zenodo.7604076
title: Doodleverse/Segmentation Zoo Res-UNet models for Aerial/nadir/2-class (water, nowater) segmentation of RGB 1024x768 high-res. images

description: <em><strong>Doodleverse/Segmentation Zoo Res-UNet models for Aerial/nadir/2-class (water, nowater) segmentation of RGB 1024x768 high-res. images</strong></em> These Residual-UNet models have been created using Segmentation Gym* using the following dataset**: Image size used by model: 1024 x 768 x 3 pixels classes: water other <br> <strong>File descriptions</strong> For each model, there are 5 files with the same root name: 1. '.json' config file: this is the file that was used by Segmentation Gym* to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse. 2. '.h5' weights file: this is the file that was created by the Segmentation Gym* function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym* function `seg_images_in_folder.py`. Models may be ensembled. 3. '_modelcard.json' model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model 4. '_model_history.npz' model training history file: this numpy archive file contains numpy arrays describing the training and validation losses and metrics. It is created by the Segmentation Gym function `train_model.py` 5. '.png' model training loss and mean IoU plot: this png file contains plots of training and validation losses and mean IoU scores during model training. A subset of data inside the .npz file. It is created by the Segmentation Gym function `train_model.py` Additionally, BEST_MODEL.txt contains the name of the model with the best validation loss and mean IoU <strong>References</strong> <br> *Segmentation Gym: Buscombe, D., & Goldstein, E. B. (2022). A reproducible and reusable pipeline for segmentation of geoscientific imagery. Earth and Space Science, 9, e2022EA002332. https://doi.org/10.1029/2022EA002332 See: https://github.com/Doodleverse/segmentation_gym **