cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6082922
title: Pre-trained cui2vec embeddings

description: Pre-trained embeddings for 108,477 medical concepts
DOI: 10.6084/m9.figshare.6082865
title: Figure scripts and data to accompany "Variable-threshold behavior in rivers arising from hillslope-derived blocks"

description: This fileset contains the data and scripts to reproduce the figures from "Variable-threshold behavior in rivers arising from hillslope-derived blocks" (Shobe et al., JGR-Earth Surface). The data is contained in CSV files, and the scripts are written in Python 2.7 with dependencies on Numpy, Scipy, and Matplotlib.<br>Figures 1-9 were generated using the BRaKE (Blocky River and Knickpoint Evolution) model of Shobe et al (2016; <i>Geophysical Research Letters</i>), which is freely available from the Community Surface Dynamics Modeling System model repository.<br>Figure 2 used the DAKOTA sensitivity analysis software package distributed by Sandia National Laboratories.<br>Figure 10 used the channel evolution model of Lague et al (2005; Journal of Geophysical Research).
DOI: 10.6084/m9.figshare.6082865.v1
title: Figure scripts and data to accompany "Variable-threshold behavior in rivers arising from hillslope-derived blocks"

description: This fileset contains the data and scripts to reproduce the figures from "Variable-threshold behavior in rivers arising from hillslope-derived blocks" (Shobe et al., JGR-Earth Surface). The data is contained in CSV files, and the scripts are written in Python 2.7 with dependencies on Numpy, Scipy, and Matplotlib.<br>Figures 1-9 were generated using the BRaKE (Blocky River and Knickpoint Evolution) model of Shobe et al (2016; <i>Geophysical Research Letters</i>), which is freely available from the Community Surface Dynamics Modeling System model repository.<br>Figure 2 used the DAKOTA sensitivity analysis software package distributed by Sandia National Laboratories.<br>Figure 10 used the channel evolution model of Lague et al (2005; Journal of Geophysical Research).
DOI: 10.6084/m9.figshare.6081329
title: Time wears on: assessing how bone wears using 3D surface texture analysis (dataset)

description: An experiment was undertaken with the intention of understanding the basics of use-wear formation over time by taking incremental impressions of bone specimens subjected to a controlled, mechanical experiment. This study assessed how bone wears during extended use on three materials (processed leather, fresh skin, or dry bark), from three initial surface modification states (unmodified, scraped with flint, or ground with sandstone). Data obtained from a confocal disc-scanning microscope was then applied to 3D surface texture analysis using ISO 25178 parameters: surface roughness [Sa], peak curvature [Spc], autocorrelation length [Sal], and upper material ratio [Smr1]. Additional 3D surface texture parameters from the experimental specimens are also recorded here. Other data is recorded here including specimen ID, amount of time used, location of scan, sample type, whether the sample is the terminus of the experiment and if a surface mold was taken at the end of the experiment, whether the sample was rescanned after one year, material type used, manufacturing type at start of experiment, which lot of the bone specimens were acquired in, state of bone, and sampling method.<br>The dataset is attached here.
DOI: 10.6084/m9.figshare.6081329.v2
title: Time wears on: assessing how bone wears using 3D surface texture analysis (dataset)

description: An experiment was undertaken with the intention of understanding the basics of use-wear formation over time by taking incremental impressions of bone specimens subjected to a controlled, mechanical experiment. This study assessed how bone wears during extended use on three materials (processed leather, fresh skin, or dry bark), from three initial surface modification states (unmodified, scraped with flint, or ground with sandstone). Data obtained from a confocal disc-scanning microscope was then applied to 3D surface texture analysis using ISO 25178 parameters: surface roughness [Sa], peak curvature [Spc], autocorrelation length [Sal], and upper material ratio [Smr1]. Additional 3D surface texture parameters from the experimental specimens are also recorded here. Other data is recorded here including specimen ID, amount of time used, location of scan, sample type, whether the sample is the terminus of the experiment and if a surface mold was taken at the end of the experiment, whether the sample was rescanned after one year, material type used, manufacturing type at start of experiment, which lot of the bone specimens were acquired in, state of bone, and sampling method.<br>The dataset is attached here.
DOI: 10.6084/m9.figshare.6081329.v1
title: Time wears on: understanding how bone wears using 3D surface texture analysis

description: An experiment was undertaken with the intention of understanding the basics of use-wear formation over time by taking incremental impressions of bone specimens subjected to a controlled, mechanical experiment. This study assessed how bone wears during extended use on three materials (processed leather, fresh skin, or dry bark), from three initial surface modification states (unmodified, scraped with flint, or ground with sandstone). Data obtained from a confocal disc-scanning microscope was then applied to 3D surface texture analysis using ISO 25178 parameters: surface roughness [Sa], peak curvature [Spc], autocorrelation length [Sal], and upper material ratio [Smr1]. Additional 3D surface texture parameters from the experimental specimens are also recorded here. Other data is recorded here including specimen ID, amount of time used, location of scan, sample type, whether the sample is the terminus of the experiment and if a surface mold was taken at the end of the experiment, whether the sample was rescanned after one year, material type used, manufacturing type at start of experiment, which lot of the bone specimens were acquired in, state of bone, and sampling method.
DOI: 10.6084/m9.figshare.6081272
title: Data for: Systematic review and meta-analysis of tick-borne disease risk factors in residential yards, neighborhoods, and beyond

description: Information on methods and citations for each source are available in the accompanying article.
DOI: 10.6084/m9.figshare.6081143
title: for_c_output.csv

description: Mesocosm experiment in Santa Fe County, NM, USA with transplanted Bouteloua gracilis and biocrust. Manipulated partner removal (clip B. gracilis to root crown; autoclave and replace biocrust), precipitation addition regime (400ml 1x per month or 100ml 4x per month), and belowground connection (0.45um mesh or none). Measured plant aboveground biomass (g) and biocrust chlorophyll content (ug per g soil).<br>
DOI: 10.6084/m9.figshare.6081143.v1
title: for_c_output.csv

description: Mesocosm experiment in Santa Fe County, NM, USA with transplanted Bouteloua gracilis and biocrust. Manipulated partner removal (clip B. gracilis to root crown; autoclave and replace biocrust), precipitation addition regime (400ml 1x per month or 100ml 4x per month), and belowground connection (0.45um mesh or none). Measured plant aboveground biomass (g) and biocrust chlorophyll content (ug per g soil).<br>
DOI: 10.6084/m9.figshare.6081086
title: PIMM LSP treatments report

description: PIMM LSP report about treatments realized in february.<br>
DOI: 10.6084/m9.figshare.6081086.v1
title: PIMM LSP treatments report

description: PIMM LSP report about treatments realized in february.<br>
DOI: 10.6084/m9.figshare.6081050
title: Exact and Approximate Power and Sample Size Calculations for Analysis of Covariance in Randomized Clinical Trials With or Without Stratification

description: Analysis of covariance (ANCOVA) is commonly used in the analysis of randomized clinical trials to adjust for baseline covariates and improve the precision of the treatment effect estimate. We derive the exact power formulas for testing a homogeneous treatment effect in superiority, noninferiority, and equivalence trials under both unstratified and stratified randomizations, and for testing the overall treatment effect and treatment × stratum interaction in the presence of heterogeneous treatment effects when the covariates excluding the intercept, treatment, and prestratification factors are normally distributed. These formulas also work very well for nonnormal covariates. The sample size methods based on the normal approximation or the asymptotic variance generally underestimate the required size. We adapt the recently developed noniterative and two-step sample size procedures to the above tests. Both methods take into account the nonnormality of the <i>t</i> statistic, and the lower order variance term commonly ignored in the sample size estimation. Numerical examples demonstrate the excellent performance of the proposed methods particularly in small samples. We revisit the topic on the prestratification versus post-stratification by comparing their relative efficiency and power. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.6081050.v2
title: Exact and Approximate Power and Sample Size Calculations for Analysis of Covariance in Randomized Clinical Trials With or Without Stratification

description: Analysis of covariance (ANCOVA) is commonly used in the analysis of randomized clinical trials to adjust for baseline covariates and improve the precision of the treatment effect estimate. We derive the exact power formulas for testing a homogeneous treatment effect in superiority, noninferiority, and equivalence trials under both unstratified and stratified randomizations, and for testing the overall treatment effect and treatment × stratum interaction in the presence of heterogeneous treatment effects when the covariates excluding the intercept, treatment, and prestratification factors are normally distributed. These formulas also work very well for nonnormal covariates. The sample size methods based on the normal approximation or the asymptotic variance generally underestimate the required size. We adapt the recently developed noniterative and two-step sample size procedures to the above tests. Both methods take into account the nonnormality of the <i>t</i> statistic, and the lower order variance term commonly ignored in the sample size estimation. Numerical examples demonstrate the excellent performance of the proposed methods particularly in small samples. We revisit the topic on the prestratification versus post-stratification by comparing their relative efficiency and power. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.6081050.v1
title: Exact and approximate power and sample size calculations for analysis of covariance in randomized clinical trials with or without stratification

description: Analysis of covariance (ANCOVA) is commonly used in the analysis of randomized clinical trials to adjust for baseline covariates and improve the precision of the treatment effect estimate. We derive the exact power formulae for testing a homogeneous treatment effect in superiority, noninferiority and equivalence trials under both unstratified and stratified randomizations, and for testing the overall treatment effect and treatment × stratum interaction in the presence of heterogeneous treatment effects when the covariates excluding the intercept, treatment and pre-stratification factors are normally distributed. These formulae also work very well for nonnormal covariates. The sample size methods based on the normal approximation or the asymptotic variance generally underestimate the required size. We adapt the recently developed noniterative and two-step sample size procedures to the above tests. Both methods take into account of the nonnormality of the t statistic, and the lower order variance term commonly ignored in the sample size estimation. Numerical examples demonstrate the excellent performance of the proposed methods particularly in small samples. We revisit the topic on the pre-stratification versus post-stratification by comparing their relative efficiency and power.
DOI: 10.6084/m9.figshare.6081044
title: Appendix 1.docx

description: List of tree species in seven remnants in the São João river basin, Rio de Janeiro, Brazil.
DOI: 10.6084/m9.figshare.6081044.v2
title: Appendix 1.docx

description: List of tree species in seven remnants in the São João river basin, Rio de Janeiro, Brazil.
DOI: 10.6084/m9.figshare.6081044.v1
title: Appendix 2.docx

description: List of tree species in seven remnants in the São João river basin, Rio de Janeiro, Brazil.
DOI: 10.6084/m9.figshare.6080831
title: An Empirical Comparison of Parametric and Permutation Tests for Regression Analysis of Randomized Experiments

description: Hypothesis tests based on linear models are widely accepted by organizations that regulate clinical trials. These tests are derived using strong assumptions about the data-generating process so that the resulting inference can be based on parametric distributions. Because these methods are well understood and robust, they are sometimes applied to data that depart from assumptions, such as ordinal integer scores. Permutation tests are a nonparametric alternative that require minimal assumptions which are often guaranteed by the randomization that was conducted. We compare analysis of covariance (ANCOVA), a special case of linear regression that incorporates stratification, to several permutation tests based on linear models that control for pretreatment covariates. In simulations of randomized experiments using models which violate some of the parametric regression assumptions, the permutation tests maintain power comparable to ANCOVA. We illustrate the use of these permutation tests alongside ANCOVA using data from a clinical trial comparing the effectiveness of two treatments for gastroesophageal reflux disease. Given the considerable costs and scientific importance of clinical trials, an additional nonparametric method, such as a linear model permutation test, may serve as a robustness check on the statistical inference for the main study endpoints. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.6080831.v1
title: An Empirical Comparison of Parametric and Permutation Tests for Regression Analysis of Randomized Experiments

description: Hypothesis tests based on linear models are widely accepted by organizations that regulate clinical trials. These tests are derived using strong assumptions about the data-generating process so that the resulting inference can be based on parametric distributions. Because these methods are well understood and robust, they are sometimes applied to data that depart from assumptions, such as ordinal integer scores. Permutation tests are a nonparametric alternative that require minimal assumptions which are often guaranteed by the randomization that was conducted. We compare analysis of covariance (ANCOVA), a special case of linear regression that incorporates stratification, to several permutation tests based on linear models that control for pretreatment covariates. In simulations of randomized experiments using models which violate some of the parametric regression assumptions, the permutation tests maintain power comparable to ANCOVA. We illustrate the use of these permutation tests alongside ANCOVA using data from a clinical trial comparing the effectiveness of two treatments for gastroesophageal reflux disease. Given the considerable costs and scientific importance of clinical trials, an additional nonparametric method, such as a linear model permutation test, may serve as a robustness check on the statistical inference for the main study endpoints. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.6080801
title: Supplementary Material for: Effect of Fluid Intake on Hydration Status and Skin Barrier Characteristics in Geriatric Patients: An Explorative Study

description: <b><i>Background/Aim:</i></b> Inadequate fluid intake is assumed to be a trigger of water-loss dehydration, which is a major health risk in aged and geriatric populations. Thus, there is a need to search for easy to use diagnostic tests to identify dehydration. Our overall aim was to investigate whether skin barrier parameters could be used for predicting fluid intake and/or hydration status in geriatric patients. <b><i>Methods:</i></b> An explorative observational comparative study was conducted in a geriatric hospital including patients aged 65 years and older. We measured 3-day fluid intake, skin barrier parameters, Overall Dry Skin Score, serum osmolality, cognitive and functional health, and medications. <b><i>Results:</i></b> Forty patients were included (mean age 78.45 years and 65% women) with a mean fluid intake of 1,747 mL/day. 20% of the patients were dehydrated and 22.5% had an impending dehydration according to serum osmolality. Multivariate analysis suggested that skin surface pH and epidermal hydration at the face were associated with fluid intake. Serum osmolality was associated with epidermal hydration at the leg and skin surface pH at the face. Fluid intake was not correlated with serum osmolality. Diuretics were associated with high serum osmolality. <b><i>Conclusions:</i></b> Approximately half of the patients were diagnosed as being dehydrated according to osmolality, which is the current reference standard. However, there was no association with fluid intake, questioning the clinical relevance of this measure. Results indicate that single skin barrier parameters are poor markers for fluid intake or osmolality. Epidermal hydration might play a role but most probably in combination with other tests.
DOI: 10.6084/m9.figshare.6080801.v1
title: Supplementary Material for: Effect of Fluid Intake on Hydration Status and Skin Barrier Characteristics in Geriatric Patients: An Explorative Study

description: <b><i>Background/Aim:</i></b> Inadequate fluid intake is assumed to be a trigger of water-loss dehydration, which is a major health risk in aged and geriatric populations. Thus, there is a need to search for easy to use diagnostic tests to identify dehydration. Our overall aim was to investigate whether skin barrier parameters could be used for predicting fluid intake and/or hydration status in geriatric patients. <b><i>Methods:</i></b> An explorative observational comparative study was conducted in a geriatric hospital including patients aged 65 years and older. We measured 3-day fluid intake, skin barrier parameters, Overall Dry Skin Score, serum osmolality, cognitive and functional health, and medications. <b><i>Results:</i></b> Forty patients were included (mean age 78.45 years and 65% women) with a mean fluid intake of 1,747 mL/day. 20% of the patients were dehydrated and 22.5% had an impending dehydration according to serum osmolality. Multivariate analysis suggested that skin surface pH and epidermal hydration at the face were associated with fluid intake. Serum osmolality was associated with epidermal hydration at the leg and skin surface pH at the face. Fluid intake was not correlated with serum osmolality. Diuretics were associated with high serum osmolality. <b><i>Conclusions:</i></b> Approximately half of the patients were diagnosed as being dehydrated according to osmolality, which is the current reference standard. However, there was no association with fluid intake, questioning the clinical relevance of this measure. Results indicate that single skin barrier parameters are poor markers for fluid intake or osmolality. Epidermal hydration might play a role but most probably in combination with other tests.
DOI: 10.6084/m9.figshare.6080699
title: Examining physiotherapist use of structured aerobic exercise testing to decrease barriers to aerobic exercise

description: <b>Objective</b>: To determine the frequency of physiotherapist-administered aerobic exercise testing/training, the proportion of physiotherapists who administer this testing/training, and the barriers that currently exist across different practice environments. A secondary objective is to identify the learning needs of physiotherapists for the development of an education curriculum in aerobic exercise testing and training with electrocardiograph (ECG) administration and interpretation. <b>Design</b>: National, cross-sectional survey. <b>Participants</b>: Registered physiotherapists practicing in Canada. <b>Results</b>: Out of 137 participants, most (75%) physiotherapists prescribed aerobic exercise on a regular basis (weekly); however, 65% had never conducted an aerobic exercise test. There were no significant differences in frequency of aerobic exercise testing across different practice environments or across years of physiotherapy experience. Physiotherapists perceived the main barriers to aerobic exercise testing as being a lack of equipment/space (78%), time (65%), and knowledge (56%). Although most (82%) were uncomfortable administering 12-lead ECG-monitored aerobic exercise tests, 60% stated they would be interested in learning more about ECG interpretation. <b>Conclusion</b>: This study found that physiotherapists are regularly implementing aerobic exercise. This exercise was infrequently guided by formal aerobic exercise testing, which could increase access to safe and effective exercise within the optimal aerobic training zone. As well, this could facilitate training in patients with cardiovascular diagnoses that require additional testing for medical clearance. Increased ECG training and access to equipment for physiotherapists may augment pre-screening aerobic exercise testing. This training should include learning the key arrhythmias for aerobic exercise test termination as defined by the American College of Sports Medicine.
DOI: 10.6084/m9.figshare.6080699.v2
title: Examining physiotherapist use of structured aerobic exercise testing to decrease barriers to aerobic exercise

description: <b>Objective</b>: To determine the frequency of physiotherapist-administered aerobic exercise testing/training, the proportion of physiotherapists who administer this testing/training, and the barriers that currently exist across different practice environments. A secondary objective is to identify the learning needs of physiotherapists for the development of an education curriculum in aerobic exercise testing and training with electrocardiograph (ECG) administration and interpretation. <b>Design</b>: National, cross-sectional survey. <b>Participants</b>: Registered physiotherapists practicing in Canada. <b>Results</b>: Out of 137 participants, most (75%) physiotherapists prescribed aerobic exercise on a regular basis (weekly); however, 65% had never conducted an aerobic exercise test. There were no significant differences in frequency of aerobic exercise testing across different practice environments or across years of physiotherapy experience. Physiotherapists perceived the main barriers to aerobic exercise testing as being a lack of equipment/space (78%), time (65%), and knowledge (56%). Although most (82%) were uncomfortable administering 12-lead ECG-monitored aerobic exercise tests, 60% stated they would be interested in learning more about ECG interpretation. <b>Conclusion</b>: This study found that physiotherapists are regularly implementing aerobic exercise. This exercise was infrequently guided by formal aerobic exercise testing, which could increase access to safe and effective exercise within the optimal aerobic training zone. As well, this could facilitate training in patients with cardiovascular diagnoses that require additional testing for medical clearance. Increased ECG training and access to equipment for physiotherapists may augment pre-screening aerobic exercise testing. This training should include learning the key arrhythmias for aerobic exercise test termination as defined by the American College of Sports Medicine.