cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5815878
title: R Script of analysis of megafauna-dispersed fruit species

description: This data supports the analysis of the publication: van Zonneveld M, Larranaga N, Blonder B, Coradin L, Hormaza JI, Hunter D. Human diets drive range expansion of megafauna-dispersed fruit species (2018) PNAS. 10.1073/pnas.1718045115. The R script and the data can be used to recalculate the analysis of this paper. The analysis consists of geographic and environmental ranges of 130 fruit species from three diet groups: · 30 fruit-producing species that were part of megafauna diets but that did <i>not</i> became part of human diets. These are fruit species reported to have been consumed by and dispersed by giant sloths and other extinct megafauna in Central and South America. · 61 wild fruit-producing species that have been part of both human and megafauna diets in Central and South America. · 39 cultivated fruit-producing species that have been part of both human and megafauna diets in Central and South America.
DOI: 10.6084/m9.figshare.5815878.v2
title: R Script of analysis of megafauna-dispersed fruit species

description: This data supports the analysis of the publication: van Zonneveld M, Larranaga N, Blonder B, Coradin L, Hormaza JI, Hunter D. Human diets drive range expansion of megafauna-dispersed fruit species (2018) PNAS. 10.1073/pnas.1718045115. The R script and the data can be used to recalculate the analysis of this paper. The analysis consists of geographic and environmental ranges of 130 fruit species from three diet groups: · 30 fruit-producing species that were part of megafauna diets but that did <i>not</i> became part of human diets. These are fruit species reported to have been consumed by and dispersed by giant sloths and other extinct megafauna in Central and South America. · 61 wild fruit-producing species that have been part of both human and megafauna diets in Central and South America. · 39 cultivated fruit-producing species that have been part of both human and megafauna diets in Central and South America.
DOI: 10.6084/m9.figshare.5815809
title: Sacroiliac Stretching Improves Glenohumeral Internal Rotational Deficit of the Opposite Shoulder in Baseball Players in a Randomized Control Trial

description: Glenohumeral Internal Rotational Deficit (GIRD) is a well-documented finding in throwing athletes. The purpose of this study is to investigate if stretching the contralateral sacroiliac (SI) joint improves GIRD in baseball players. Additionally, we aimed to compare our SI joint stretching regiment with a classically described sleeper stretch routine. In this study of asymptomatic minor league baseball players, we found that over 50% had decreased internal rotation compared to the non-throwing shoulder. Our results demonstrate greater improvement in shoulder range of motion after stretching of the contralateral SI joint compared to a sleeper’s stretch.
DOI: 10.6084/m9.figshare.5815809.v1
title: Sacroiliac Stretching Improves Glenohumeral Internal Rotational Deficit of the Opposite Shoulder in Baseball Players in a Randomized Control Trial

description: Glenohumeral Internal Rotational Deficit (GIRD) is a well-documented finding in throwing athletes. The purpose of this study is to investigate if stretching the contralateral sacroiliac (SI) joint improves GIRD in baseball players. Additionally, we aimed to compare our SI joint stretching regiment with a classically described sleeper stretch routine. In this study of asymptomatic minor league baseball players, we found that over 50% had decreased internal rotation compared to the non-throwing shoulder. Our results demonstrate greater improvement in shoulder range of motion after stretching of the contralateral SI joint compared to a sleeper’s stretch.
DOI: 10.6084/m9.figshare.5815800
title: Aureococcus mitochondrial genome.txt

description: The draft mitochondrial genome of Aureococcus anophagefferens - a pelagophyte algae.
DOI: 10.6084/m9.figshare.5815800.v1
title: Aureococcus mitochondrial genome.txt

description: The draft mitochondrial genome of Aureococcus anophagefferens - a pelagophyte algae.
DOI: 10.6084/m9.figshare.5815437
title: Electrodermal data

description: Electrodermal activity recorded from subjects' left and right wrists during the entirety of an overground balance beam walking task.
DOI: 10.6084/m9.figshare.5815431
title: EEG data

description: EEG data from 19 subjects (includes .fdt and .set files for loading into EEGLAB)<br>
DOI: 10.6084/m9.figshare.5813934
title: Path-Dependent Institutions Drive Alternative Stable States in Conservation: Data and Code

description: Dataset and Matlab code demonstrating path-dependent harvest rates in global marine fisheries.<br>Files:- Tekwa Data and Code.zip: Matlab files for analyses. See RAManalysis_README inside for detail.
DOI: 10.6084/m9.figshare.5813934.v1
title: Global Harvesting Patterns are Path-Dependent due to Social-Ecological Feedbacks: Data and Code

description: Dataset and Matlab code demonstrating path-dependent harvest rates in global marine fisheries.<br>Files:- RAManalysis data.xlsx: Excel datasheets containing ecological and economic data for analyses.- Code.zip: Matlab files for analyses. See RAManalysis_README inside for details.
DOI: 10.6084/m9.figshare.5813934.v2
title: Global Harvesting Patterns are Path-Dependent due to Social-Ecological Feedbacks: Data and Code

description: Dataset and Matlab code demonstrating path-dependent harvest rates in global marine fisheries.<br>Files:- RAManalysis data.xlsx: Excel datasheets containing ecological and economic data for analyses.- Code.zip: Matlab files for analyses. See RAManalysis_README inside for details.- RAManalysis model fit data and fish labels: plot of mean harvest rates, with one-year lag from initial years, with labels of fishery names.
DOI: 10.6084/m9.figshare.5813934.v3
title: Conservation is Path-Dependent: Data and Code

description: Dataset and Matlab code demonstrating path-dependent harvest rates in global marine fisheries.<br>Files:- RAManalysis data.xlsx: Excel datasheets containing ecological and economic data for analyses.- Code.zip: Matlab files for analyses. See RAManalysis_README inside for details.- RAManalysis model fit data and fish labels: plot of mean harvest rates, with one-year lag from initial years, with labels of fishery names.
DOI: 10.6084/m9.figshare.5813934.v4
title: Path-Dependence in Conservation: Data and Code

description: Dataset and Matlab code demonstrating path-dependent harvest rates in global marine fisheries.<br>Files:- RAManalysis data.xlsx: Excel datasheets containing ecological and economic data for analyses.- Code.zip: Matlab files for analyses. See RAManalysis_README inside for details.- RAManalysis model fit data and fish labels: plot of mean harvest rates, with one-year lag from initial years, with labels of fishery names.
DOI: 10.6084/m9.figshare.5813934.v5
title: Path-Dependence in Conservation: Data and Code

description: Dataset and Matlab code demonstrating path-dependent harvest rates in global marine fisheries.<br>Files:- RAManalysis data.xlsx: Excel datasheets containing ecological and economic data for analyses.- Code.zip: Matlab files for analyses. See RAManalysis_README inside for details.- RAManalysis model fit data and fish labels: plot of mean harvest rates, with one-year lag from initial years, with labels of fishery names.
DOI: 10.6084/m9.figshare.5813934.v6
title: Path-Dependent Institutions Drive Alternative Stable States in Conservation: Data and Code

description: Dataset and Matlab code demonstrating path-dependent harvest rates in global marine fisheries.<br>Files:- RAManalysis data.xlsx: Excel datasheets containing ecological and economic data for analyses.- Code.zip: Matlab files for analyses. See RAManalysis_README inside for details.
DOI: 10.6084/m9.figshare.5813934.v7
title: Path-Dependent Institutions Drive Alternative Stable States in Conservation: Data and Code

description: Dataset and Matlab code demonstrating path-dependent harvest rates in global marine fisheries.<br>Files:- Tekwa Data and Code.zip: Matlab files for analyses. See RAManalysis_README inside for detail.
DOI: 10.6084/m9.figshare.5813934.v8
title: Path-Dependent Institutions Drive Alternative Stable States in Conservation: Data and Code

description: Dataset and Matlab code demonstrating path-dependent harvest rates in global marine fisheries.<br>Files:- Tekwa Data and Code.zip: Matlab files for analyses. See RAManalysis_README inside for detail.
DOI: 10.6084/m9.figshare.5813928
title: Polynomial Accelerated Solutions to a Large Gaussian Model for Imaging Biofilms: In Theory and Finite Precision

description: Three-dimensional confocal scanning laser microscope images offer dramatic visualizations of living biofilms before and after interventions. Here, we use confocal microscopy to study the effect of a treatment over time that causes a biofilm to swell and contract due to osmotic pressure changes. From these data (the video is provided in the supplementary materials), our goal is to reconstruct biofilm surfaces, to estimate the effect of the treatment on the biofilm’s volume, and to quantify the related uncertainties. We formulate the associated massive linear Bayesian inverse problem and then solve it using iterative samplers from large multivariate Gaussians that exploit well-established polynomial acceleration techniques from numerical linear algebra. Because of a general equivalence with linear solvers, these polynomial accelerated iterative samplers have known convergence rates, stopping criteria, and perform well in finite precision. An explicit algorithm is provided, for the first time, for an iterative sampler that is accelerated by the synergistic implementation of preconditioned conjugate gradient and Chebyshev polynomials. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.5813928.v1
title: Polynomial accelerated solutions to a LARGE Gaussian model for imaging biofilms: in theory and finite precision

description: Three dimensional confocal scanning laser microscope images offer dramatic visualizations of the action of living biofilms before and after interventions. Here we use confocal microscopy to study the effect of a treatment over time that causes a biofilm to swell and contract due to osmotic pressure changes. From these data, our goal is to reconstruct biofilm surfaces, to estimate the effect of the treatment on the biofilm's volume, and to quantify the related uncertainties. We formulate the associated massive linear Bayesian inverse problem and then solve it using iterative samplers from large multivariate Gaussians that exploit well-established polynomial acceleration techniques from numerical linear algebra. Because of a general equivalence with linear solvers, these polynomial accelerated iterative samplers have known convergence rates, stopping criteria, and perform well in finite precision. An explicit algorithm is provided, for the first time, for an iterative sampler that is accelerated by the synergistic implementation of preconditioned conjugate gradient and Chebyshev polynomials.
DOI: 10.6084/m9.figshare.5813928.v3
title: Polynomial Accelerated Solutions to a Large Gaussian Model for Imaging Biofilms: In Theory and Finite Precision

description: Three-dimensional confocal scanning laser microscope images offer dramatic visualizations of living biofilms before and after interventions. Here, we use confocal microscopy to study the effect of a treatment over time that causes a biofilm to swell and contract due to osmotic pressure changes. From these data (the video is provided in the supplementary materials), our goal is to reconstruct biofilm surfaces, to estimate the effect of the treatment on the biofilm’s volume, and to quantify the related uncertainties. We formulate the associated massive linear Bayesian inverse problem and then solve it using iterative samplers from large multivariate Gaussians that exploit well-established polynomial acceleration techniques from numerical linear algebra. Because of a general equivalence with linear solvers, these polynomial accelerated iterative samplers have known convergence rates, stopping criteria, and perform well in finite precision. An explicit algorithm is provided, for the first time, for an iterative sampler that is accelerated by the synergistic implementation of preconditioned conjugate gradient and Chebyshev polynomials. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.5813928.v2
title: Polynomial Accelerated Solutions to a Large Gaussian Model for Imaging Biofilms: In Theory and Finite Precision

description: Three-dimensional confocal scanning laser microscope images offer dramatic visualizations of living biofilms before and after interventions. Here, we use confocal microscopy to study the effect of a treatment over time that causes a biofilm to swell and contract due to osmotic pressure changes. From these data (the video is provided in the supplementary materials), our goal is to reconstruct biofilm surfaces, to estimate the effect of the treatment on the biofilm’s volume, and to quantify the related uncertainties. We formulate the associated massive linear Bayesian inverse problem and then solve it using iterative samplers from large multivariate Gaussians that exploit well-established polynomial acceleration techniques from numerical linear algebra. Because of a general equivalence with linear solvers, these polynomial accelerated iterative samplers have known convergence rates, stopping criteria, and perform well in finite precision. An explicit algorithm is provided, for the first time, for an iterative sampler that is accelerated by the synergistic implementation of preconditioned conjugate gradient and Chebyshev polynomials. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.5813904
title: Amici et al. 2008 Current biology_monkey data.xlsx

description: Individual level data from of an inhibitory control test battery with capuchin monkeys, spider monkeys, and long-tailed macaques (see Amici et al. 2008, Current Biology, Table 2).<br>
DOI: 10.6084/m9.figshare.5813877.v1
title: Carbocupration of heterosubstituted alkynes

description: Inputs and outputs
DOI: 10.6084/m9.figshare.5813859
title: Using First Name Information to Improve Race and Ethnicity Classification

description: This article uses a recent first name list to develop an improvement to an existing Bayesian classifier, namely the Bayesian Improved Surname Geocoding (BISG) method, which combines surname and geography information to impute missing race/ethnicity. The new Bayesian Improved First Name Surname Geocoding (BIFSG) method is validated using a large sample of mortgage applicants who self-report their race/ethnicity. BIFSG outperforms BISG, in terms of accuracy and coverage, for all major racial/ethnic categories. Although the overall magnitude of improvement is somewhat small, the largest improvements occur for non-Hispanic Blacks, a group for which the BISG performance is weakest. When estimating the race/ethnicity effects on mortgage pricing and underwriting decisions with regression models, estimation biases from both BIFSG and BISG are very small, with BIFSG generally having smaller biases, and the maximum a posteriori classifier resulting in smaller biases than through use of estimated probabilities. Robustness checks using voter registration data confirm BIFSG's improved performance vis-a-vis BISG and illustrate BIFSG's applicability to areas other than mortgage lending. Finally, I demonstrate an application of the BIFSG to the imputation of missing race/ethnicity in the Home Mortgage Disclosure Act data, and in the process, offer novel evidence that the incidence of missing race/ethnicity information is correlated with race/ethnicity.
DOI: 10.6084/m9.figshare.5813859.v2
title: Using First Name Information to Improve Race and Ethnicity Classification

description: This article uses a recent first name list to develop an improvement to an existing Bayesian classifier, namely the Bayesian Improved Surname Geocoding (BISG) method, which combines surname and geography information to impute missing race/ethnicity. The new Bayesian Improved First Name Surname Geocoding (BIFSG) method is validated using a large sample of mortgage applicants who self-report their race/ethnicity. BIFSG outperforms BISG, in terms of accuracy and coverage, for all major racial/ethnic categories. Although the overall magnitude of improvement is somewhat small, the largest improvements occur for non-Hispanic Blacks, a group for which the BISG performance is weakest. When estimating the race/ethnicity effects on mortgage pricing and underwriting decisions with regression models, estimation biases from both BIFSG and BISG are very small, with BIFSG generally having smaller biases, and the maximum a posteriori classifier resulting in smaller biases than through use of estimated probabilities. Robustness checks using voter registration data confirm BIFSG's improved performance vis-a-vis BISG and illustrate BIFSG's applicability to areas other than mortgage lending. Finally, I demonstrate an application of the BIFSG to the imputation of missing race/ethnicity in the Home Mortgage Disclosure Act data, and in the process, offer novel evidence that the incidence of missing race/ethnicity information is correlated with race/ethnicity.
DOI: 10.6084/m9.figshare.5813859.v1
title: Using First Name Information to Improve Race and Ethnicity Classification

description: This paper uses a recent first name list to develop an improvement to an existing Bayesian classifier, namely the Bayesian Improved Surname Geocoding (BISG) method, which combines surname and geography information to impute missing race/ethnicity. The new Bayesian Improved First Name Surname Geocoding (BIFSG) method is validated using a large sample of mortgage applicants who self-report their race/ethnicity. BIFSG outperforms BISG, in terms of accuracy and coverage, for all major racial/ethnic categories. Although the overall magnitude of improvement is somewhat small, the largest improvements occur for non-Hispanic Blacks, a group for which the BISG performance is weakest. When estimating the race/ethnicity effects on mortgage pricing and underwriting decisions with regression models, estimation biases from both BIFSG and BISG are very small, with BIFSG generally having smaller biases, and the maximum a posteriori classifier resulting in smaller biases than probabilities. Robustness checks using voter registration data confirm BIFSG's improved performance vis-a-vis BISG and illustrate BIFSG's applicability to areas other than mortgage lending. Finally, I demonstrate an application of the BIFSG to the imputation of missing race/ethnicity in the Home Mortgage Disclosure Act data, and in the process, offer novel evidence that the incidence of missing race/ethnicity information is correlated with race/ethnicity.
DOI: 10.6084/m9.figshare.5813793.v1
title: Shape constrained kernel-weighted least squares: Estimating production functions for Chilean manufacturing industries

description: In this paper we examine a novel way of imposing shape constraints on a local polynomial kernel estimator. The proposed approach is referred to as Shape Constrained Kernel-weighted Least Squares (SCKLS). We prove uniform consistency of the SCKLS estimator with monotonicity and convexity/concavity constraints and establish its convergence rate. In addition, we propose a test to validate whether shape constraints are correctly specified. The competitiveness of SCKLS is shown in a comprehensive simulation study. Finally, we analyze Chilean manufacturing data using the SCKLS estimator and quantify production in the plastics and wood industries. The results show that exporting firms have significantly higher productivity.
DOI: 10.6084/m9.figshare.5813760
title: A Boundary Bluring Graduate Program

description: Description of the University of Idaho Bioinformatics and Computational Biology graduate program at the University of Idaho. The design principles were to explicitly train students to be able to cross boundaries/disciplines between math, computation, and biology.
DOI: 10.6084/m9.figshare.5813760.v1
title: A Boundary Bluring Graduate Program

description: Description of the University of Idaho Bioinformatics and Computational Biology graduate program at the University of Idaho. The design principles were to explicitly train students to be able to cross boundaries/disciplines between math, computation, and biology.
DOI: 10.6084/m9.figshare.5813604
title: A New Species of Tanaecium (Bignonieae, Bignoniaceae) from the Brazilian Amazon and its Phylogenetic Placement

description: If you have any question about the methodology, please write me. See details in Plants Systematic and Evolution 2018 issues.
DOI: 10.6084/m9.figshare.5813604.v1
title: A New Species of Tanaecium (Bignonieae, Bignoniaceae) from the Brazilian Amazon and its Phylogenetic Placement

description: If you have any question about the methodology, please write me. See details in Plants Systematic and Evolution 2018 issues.
DOI: 10.6084/m9.figshare.5813529
title: A role for endothelial cells in radiation-induced inflammation

description: <b>Purpose:</b> To unravel the role of the vasculature in radiation-induced brain tissue damage. <b>Materials and methods:</b> Postnatal day 14 mice received a single dose of 10 Gy cranial irradiation and were sacrificed 6 h, 24 h or 7 days post-irradiation. Endothelial cells were isolated from the hippocampus and cerebellum using fluorescence-activated cell sorting, followed by cell cycle analysis and gene expression profiling. <b>Results:</b> Flow cytometric analysis revealed that irradiation increased the percentage of endothelial cells, relative to the whole cell population in both the hippocampus and the cerebellum. This change in cell distribution indicates that other cell types are more susceptible to irradiation-induced cell death, compared to endothelial cells. This was supported by data showing that genes involved in endothelial cell-specific apoptosis (e.g. <i>Smpd1</i>) were not induced at any time point investigated but that genes involved in cell-cycle arrest (e.g. <i>Cdkn1a</i>) were upregulated at all investigated time points, indicating endothelial cell repair. Inflammation-related genes, on the other hand, were strongly induced, such as <i>Ccl2</i>, <i>Ccl11</i> and <i>Il6</i>. <b>Conclusions:</b> We conclude that endothelial cells are relatively resistant to ionizing radiation but that they play an active, hitherto unknown, role in the inflammatory response after irradiation. In the current study, this was shown in both the hippocampus, where neurogenesis and extensive cell death after irradiation occurs, and in the cerebellum, where neurogenesis no longer occurs at this developmental age.