cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1066070.v10
title: Supporting files for "Climate change may have limited effect on global risk of potato late blight"

description: Supporting files for "Climate change may have limited effect on global risk of potato late blight" (Sparks et al. 2014). Code is freely available on GitHub, http://adamhsparks.github.io/Global-Late-Blight-Modelling/. <strong>A2 Files</strong> The A2 climate files files are <em>ensemble models</em> (averages) of the following three models: BCCR BCM2.0 (Bjerknes Centre for Climate Research Bergen Climate Model Version 2.0 Commonwealth Scientific and Industrial Research Organization GCM mark 3), CSIRO mk3.0 (Commonwealth Scientific and Industrial Research Organization GCM mark 3) and INMCM3.0 (Institute for Numerical Mathematics Version 3.0 Model). The original A2 emission scenario files were obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP Working Group on Coupled Modelling (WGCM) and downscaled using the delta method to 10 arcminute resolution. Data include maximum temperature, minimum temperature, mean temperature, relative humidity and precipitation. Three time-slices are represented: 2000-2019, 2040-2059 and 2080-2099. <strong> Daily and Monthly Files</strong> These tables contain blight units as calculated by the SimCast model, using HUSWO (Hourly US Weather Observations; NOAA) for resistant and susceptible potato cultivars. These files are used for the creation of the SimCastMeta GAM (Sparks et al. 2011). Daily files are the original blight unit output from the SimCast model (Grünwald et al. 2002) and corresponding temperature and relative humidity values. Monthly files are monthly averages of blight units and corresponding temperature and relative humidity values. <strong>SimCastMeta Look Up Files</strong> These tables contain the blight unit output of the SimCastMeta model along with corresponding temperature and relative humidity values which generate the blight units. Can be used in other applications as a look-up table rather than recreating the whole model in R.
DOI: 10.6084/m9.figshare.1066070.v11
title: Supporting files for "Climate change may have limited effect on global risk of potato late blight"

description: Supporting files for "Climate change may have limited effect on global risk of potato late blight" (Sparks et al. 2014). Code is freely available on GitHub, http://adamhsparks.github.io/Global-Late-Blight-Modelling/. <strong>A2 Files</strong> The A2 climate files files are <em>ensemble models</em> (averages) of the following three models: BCCR BCM2.0 (Bjerknes Centre for Climate Research Bergen Climate Model Version 2.0 Commonwealth Scientific and Industrial Research Organization GCM mark 3), CSIRO mk3.0 (Commonwealth Scientific and Industrial Research Organization GCM mark 3) and INMCM3.0 (Institute for Numerical Mathematics Version 3.0 Model). The original A2 emission scenario files were obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP Working Group on Coupled Modelling (WGCM) and downscaled using the delta method to 10 arcminute resolution. Data include maximum temperature, minimum temperature, mean temperature, relative humidity and precipitation. Three time-slices are represented: 2000-2019, 2040-2059 and 2080-2099. <strong> Daily and Monthly Files</strong> These tables contain blight units as calculated by the SimCast model, using HUSWO (Hourly US Weather Observations; NOAA) for resistant and susceptible potato cultivars. These files are used for the creation of the SimCastMeta GAM (Sparks et al. 2011). Daily files are the original blight unit output from the SimCast model (Grünwald et al. 2002) and corresponding temperature and relative humidity values. Monthly files are monthly averages of blight units and corresponding temperature and relative humidity values. <strong>SimCastMeta Look Up Files</strong> These tables contain the blight unit output of the SimCastMeta model along with corresponding temperature and relative humidity values which generate the blight units. Can be used in other applications as a look-up table rather than recreating the whole model in R.
DOI: 10.6084/m9.figshare.1064408.v1
title: The walking environment in Lima, Peru and pedestrian-motor vehicle collisions: An exploratory analysis

description: ABSTRACT<b>Objective:</b> Pedestrians comprise 78% of the road fatalities in Peru. The objective of this study was to explore the relationship between the walking environment and pedestrian-motor vehicle collisions.<b>Methods:</b> A matched case-control study was used to detect the odds of a pedestrian-motor vehicle collision at a pedestrian crossing location. Data were collected within eleven sampled police commissaries in Lima, Peru.<b>Results:</b> In a multivariable model adjusting for vehicle and pedestrian flow, pedestrian collisions were less likely in the presence of a curb and sidewalk on both roadway sides (Odds Ratio [OR] 0.19, 95% Confidence Interval [CI] 0.11-0.33) or a pedestrian barricade (OR 0.11, 95% CI 0.01-0.81). There was a greater risk of collisions for each street vendor present (OR 2.82, 95% CI 1.59-5.00) or if any parked vehicles (OR 3.67, 95% CI 1.18-11.4) were present.<b>Conclusions:</b> Improving or addressing these potentially modifiable features of the walking environment could improve pedestrian safety in Lima and in similar urban settings in low and middle-income countries.
DOI: 10.6084/m9.figshare.1064368
title: From Swab to Publication Sample Data (Tatumella)

description: Raw fastq reads (contaminated with yeast) Sanger 16s .ab1 RAST 16s fasta RDP alignment Cleaned up alignment FastTree phylogenetic tree FastTree rerooted phylogenetic tree
DOI: 10.6084/m9.figshare.1066070.v12
title: Supporting files for "Climate change may have limited effect on global risk of potato late blight"

description: Supporting files for "Climate change may have limited effect on global risk of potato late blight" (Sparks et al. 2014). Code is freely available on GitHub, http://adamhsparks.github.io/Global-Late-Blight-Modelling/. <strong>A2 Files</strong> The A2 climate files files are <em>ensemble models</em> (averages) of the following three models: BCCR BCM2.0 (Bjerknes Centre for Climate Research Bergen Climate Model Version 2.0 Commonwealth Scientific and Industrial Research Organization GCM mark 3), CSIRO mk3.0 (Commonwealth Scientific and Industrial Research Organization GCM mark 3) and INMCM3.0 (Institute for Numerical Mathematics Version 3.0 Model). The original A2 emission scenario files were obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP Working Group on Coupled Modelling (WGCM) and downscaled using the delta method to 10 arcminute resolution. Data include maximum temperature, minimum temperature, mean temperature, relative humidity and precipitation. Three time-slices are represented: 2000-2019, 2040-2059 and 2080-2099. <strong> Daily and Monthly Files</strong> These tables contain blight units as calculated by the SimCast model, using HUSWO (Hourly US Weather Observations; NOAA) for resistant and susceptible potato cultivars. These files are used for the creation of the SimCastMeta GAM (Sparks et al. 2011). Daily files are the original blight unit output from the SimCast model (Grünwald et al. 2002) and corresponding temperature and relative humidity values. Monthly files are monthly averages of blight units and corresponding temperature and relative humidity values. <strong>SimCastMeta Look Up Files</strong> These tables contain the blight unit output of the SimCastMeta model along with corresponding temperature and relative humidity values which generate the blight units. Can be used in other applications as a look-up table rather than recreating the whole model in R.
DOI: 10.6084/m9.figshare.1064408
title: The Walking Environment in Lima, Peru and Pedestrian–Motor Vehicle Collisions: An Exploratory Analysis

description: <b>Objective:</b> Pedestrians comprise 78% of the road fatalities in Peru. The objective of this study was to explore the relationship between the walking environment and pedestrian–motor vehicle collisions. <b>Methods:</b> A matched case-control study was used to detect the odds of a pedestrian–motor vehicle collision at a pedestrian crossing location. Data were collected from 11 sampled police commissaries in Lima, Peru. <b>Results:</b> In a multivariable model adjusting for vehicle and pedestrian flow, pedestrian collisions were less likely in the presence of a curb and sidewalk on both roadway sides (odds ratio [OR] = 0.19, 95% confidence interval [CI], 0.11–0.33) or a pedestrian barricade (OR = 0.11, 95% CI, 0.01–0.81). There was a greater risk of collisions for each street vendor present (OR = 2.82, 95% CI, 1.59–5.00) or whether any parked vehicles (OR = 3.67, 95% CI, 1.18–11.4) were present. <b>Conclusions:</b> Improving or addressing these potentially modifiable features of the walking environment could improve pedestrian safety in Lima and in similar urban settings in low- and middle-income countries.
DOI: 10.6084/m9.figshare.1064408.v2
title: The Walking Environment in Lima, Peru and Pedestrian–Motor Vehicle Collisions: An Exploratory Analysis

description: <b>Objective:</b> Pedestrians comprise 78% of the road fatalities in Peru. The objective of this study was to explore the relationship between the walking environment and pedestrian–motor vehicle collisions.<b>Methods:</b> A matched case-control study was used to detect the odds of a pedestrian–motor vehicle collision at a pedestrian crossing location. Data were collected from 11 sampled police commissaries in Lima, Peru.<b>Results:</b> In a multivariable model adjusting for vehicle and pedestrian flow, pedestrian collisions were less likely in the presence of a curb and sidewalk on both roadway sides (odds ratio [OR] = 0.19, 95% confidence interval [CI], 0.11–0.33) or a pedestrian barricade (OR = 0.11, 95% CI, 0.01–0.81). There was a greater risk of collisions for each street vendor present (OR = 2.82, 95% CI, 1.59–5.00) or whether any parked vehicles (OR = 3.67, 95% CI, 1.18–11.4) were present.<b>Conclusions:</b> Improving or addressing these potentially modifiable features of the walking environment could improve pedestrian safety in Lima and in similar urban settings in low- and middle-income countries.
DOI: 10.6084/m9.figshare.1064408.v4
title: The Walking Environment in Lima, Peru and Pedestrian–Motor Vehicle Collisions: An Exploratory Analysis

description: <b>Objective:</b> Pedestrians comprise 78% of the road fatalities in Peru. The objective of this study was to explore the relationship between the walking environment and pedestrian–motor vehicle collisions. <b>Methods:</b> A matched case-control study was used to detect the odds of a pedestrian–motor vehicle collision at a pedestrian crossing location. Data were collected from 11 sampled police commissaries in Lima, Peru. <b>Results:</b> In a multivariable model adjusting for vehicle and pedestrian flow, pedestrian collisions were less likely in the presence of a curb and sidewalk on both roadway sides (odds ratio [OR] = 0.19, 95% confidence interval [CI], 0.11–0.33) or a pedestrian barricade (OR = 0.11, 95% CI, 0.01–0.81). There was a greater risk of collisions for each street vendor present (OR = 2.82, 95% CI, 1.59–5.00) or whether any parked vehicles (OR = 3.67, 95% CI, 1.18–11.4) were present. <b>Conclusions:</b> Improving or addressing these potentially modifiable features of the walking environment could improve pedestrian safety in Lima and in similar urban settings in low- and middle-income countries.
DOI: 10.6084/m9.figshare.1064408.v3
title: The Walking Environment in Lima, Peru and Pedestrian–Motor Vehicle Collisions: An Exploratory Analysis

description: <b>Objective:</b> Pedestrians comprise 78% of the road fatalities in Peru. The objective of this study was to explore the relationship between the walking environment and pedestrian–motor vehicle collisions.<b>Methods:</b> A matched case-control study was used to detect the odds of a pedestrian–motor vehicle collision at a pedestrian crossing location. Data were collected from 11 sampled police commissaries in Lima, Peru.<b>Results:</b> In a multivariable model adjusting for vehicle and pedestrian flow, pedestrian collisions were less likely in the presence of a curb and sidewalk on both roadway sides (odds ratio [OR] = 0.19, 95% confidence interval [CI], 0.11–0.33) or a pedestrian barricade (OR = 0.11, 95% CI, 0.01–0.81). There was a greater risk of collisions for each street vendor present (OR = 2.82, 95% CI, 1.59–5.00) or whether any parked vehicles (OR = 3.67, 95% CI, 1.18–11.4) were present.<b>Conclusions:</b> Improving or addressing these potentially modifiable features of the walking environment could improve pedestrian safety in Lima and in similar urban settings in low- and middle-income countries.
DOI: 10.6084/m9.figshare.1066070.v13
title: Supporting files for "Climate change may have limited effect on global risk of potato late blight"

description: Supporting files for "Climate change may have limited effect on global risk of potato late blight" (Sparks et al. 2014). Code is freely available on GitHub, http://adamhsparks.github.io/Global-Late-Blight-Modelling/. <strong>A2 Files</strong> The A2 climate files files are <em>ensemble models</em> (averages) of the following three models: BCCR BCM2.0 (Bjerknes Centre for Climate Research Bergen Climate Model Version 2.0 Commonwealth Scientific and Industrial Research Organization GCM mark 3), CSIRO mk3.0 (Commonwealth Scientific and Industrial Research Organization GCM mark 3) and INMCM3.0 (Institute for Numerical Mathematics Version 3.0 Model). The original A2 emission scenario files were obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP Working Group on Coupled Modelling (WGCM) and downscaled using the delta method to 10 arcminute resolution. Data include maximum temperature, minimum temperature, mean temperature, relative humidity and precipitation. Three time-slices are represented: 2000-2019, 2040-2059 and 2080-2099. <strong> Daily and Monthly Files</strong> These tables contain blight units as calculated by the SimCast model, using HUSWO (Hourly US Weather Observations; NOAA) for resistant and susceptible potato cultivars. These files are used for the creation of the SimCastMeta GAM (Sparks et al. 2011). Daily files are the original blight unit output from the SimCast model (Grünwald et al. 2002) and corresponding temperature and relative humidity values. Monthly files are monthly averages of blight units and corresponding temperature and relative humidity values. <strong>SimCastMeta Look Up Files</strong> These tables contain the blight unit output of the SimCastMeta model along with corresponding temperature and relative humidity values which generate the blight units. Can be used in other applications as a look-up table rather than recreating the whole model in R.
DOI: 10.6084/m9.figshare.1064342
title: Quantifying the impact of bottom trawling on soft-bottom megafauna communities using video and scanning-sonar data on the continental slope off Vancouver Island, British Columbia.

description: Megafauna found along transect R1074 grouped by 250m with habitat attributes.
DOI: 10.6084/m9.figshare.1066070.v14
title: Supporting files for "Climate change may have limited effect on global risk of potato late blight"

description: Supporting files for "Climate change may have limited effect on global risk of potato late blight" (Sparks et al. 2014). Code is freely available on GitHub, http://adamhsparks.github.io/Global-Late-Blight-Modelling/. <strong>A2 Files</strong> The A2 climate files files are <em>ensemble models</em> (averages) of the following three models: BCCR BCM2.0 (Bjerknes Centre for Climate Research Bergen Climate Model Version 2.0 Commonwealth Scientific and Industrial Research Organization GCM mark 3), CSIRO mk3.0 (Commonwealth Scientific and Industrial Research Organization GCM mark 3) and INMCM3.0 (Institute for Numerical Mathematics Version 3.0 Model). The original A2 emission scenario files were obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP Working Group on Coupled Modelling (WGCM) and downscaled using the delta method to 10 arcminute resolution. Data include maximum temperature, minimum temperature, mean temperature, relative humidity and precipitation. Three time-slices are represented: 2000-2019, 2040-2059 and 2080-2099. <strong> Daily and Monthly Files</strong> These tables contain blight units as calculated by the SimCast model, using HUSWO (Hourly US Weather Observations; NOAA) for resistant and susceptible potato cultivars. These files are used for the creation of the SimCastMeta GAM (Sparks et al. 2011). Daily files are the original blight unit output from the SimCast model (Grünwald et al. 2002) and corresponding temperature and relative humidity values. Monthly files are monthly averages of blight units and corresponding temperature and relative humidity values. <strong>SimCastMeta Look Up Files</strong> These tables contain the blight unit output of the SimCastMeta model along with corresponding temperature and relative humidity values which generate the blight units. Can be used in other applications as a look-up table rather than recreating the whole model in R.
DOI: 10.6084/m9.figshare.1064360
title: Monte Carlo Algorithms for Identifying Densely Connected Subgraphs

description: The problem of finding densely connected subgraphs in a network has attracted a lot of recent interest. Such subgraphs are sometimes referred to as communities in social networks or molecular modules in protein networks. In this article, we propose two Monte Carlo optimization algorithms for identifying the densest subgraphs with a fixed size or with size in a given range. The new algorithms combine the idea of simulated annealing and efficient moves for the Markov chain, and both algorithms are shown to converge to the set of optimal states (densest subgraphs) with probability 1. When applied to a yeast protein interaction network and a stock market graph, the algorithms identify interesting new densely connected subgraphs. Supplementary materials for the article are available online.
DOI: 10.6084/m9.figshare.1064360.v2
title: Monte Carlo Algorithms for Identifying Densely Connected Subgraphs

description: The problem of finding densely connected subgraphs in a network has attracted a lot of recent interest. Such subgraphs are sometimes referred to as communities in social networks or molecular modules in protein networks. In this article, we propose two Monte Carlo optimization algorithms for identifying the densest subgraphs with a fixed size or with size in a given range. The new algorithms combine the idea of simulated annealing and efficient moves for the Markov chain, and both algorithms are shown to converge to the set of optimal states (densest subgraphs) with probability 1. When applied to a yeast protein interaction network and a stock market graph, the algorithms identify interesting new densely connected subgraphs. Supplementary materials for the article are available online.
DOI: 10.6084/m9.figshare.1064342.v1
title: Quantifying the impact of bottom trawling on soft-bottom megafauna communities using video and scanning-sonar data on the continental slope off Vancouver Island, British Columbia.

description: Megafauna found along transect R1074 grouped by 250m with habitat attributes.
DOI: 10.6084/m9.figshare.1064360.v1
title: Monte Carlo Algorithms for Identifying Densely Connected Subgraphs

description: The problem of finding densely connected subgraphs in a network has attracted a lot of recent interest. Such subgraphs are sometimes referred to as communities in social networks or molecular modules in protein networks. In this article, we propose two Monte Carlo optimization algorithms for identifying the densest subgraphs with a fixed size or with size in a given range. The new algorithms combine the idea of simulated annealing and efficient moves for the Markov chain, and both algorithms are shown to converge to the set of optimal states (densest subgraphs) with probability one. When applied to a yeast protein interaction network and a stock market graph, the algorithms identify interesting new densely connected subgraphs. Supplemental materials for the article are available online.
DOI: 10.6084/m9.figshare.1066070.v15
title: Supporting files for "Climate change may have limited effect on global risk of potato late blight"

description: Supporting files for "Climate change may have limited effect on global risk of potato late blight" (Sparks et al. 2014). Code is freely available on GitHub, http://adamhsparks.github.io/Global-Late-Blight-Modelling/. <strong>A2 Files</strong> The A2 climate files files are <em>ensemble models</em> (averages) of the following three models: BCCR BCM2.0 (Bjerknes Centre for Climate Research Bergen Climate Model Version 2.0 Commonwealth Scientific and Industrial Research Organization GCM mark 3), CSIRO mk3.0 (Commonwealth Scientific and Industrial Research Organization GCM mark 3) and INMCM3.0 (Institute for Numerical Mathematics Version 3.0 Model). The original A2 emission scenario files were obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP Working Group on Coupled Modelling (WGCM) and downscaled using the delta method to 10 arcminute resolution. Data include maximum temperature, minimum temperature, mean temperature, relative humidity and precipitation. Three time-slices are represented: 2000-2019, 2040-2059 and 2080-2099. <strong> Daily and Monthly Files</strong> These tables contain blight units as calculated by the SimCast model, using HUSWO (Hourly US Weather Observations; NOAA) for resistant and susceptible potato cultivars. These files are used for the creation of the SimCastMeta GAM (Sparks et al. 2011). Daily files are the original blight unit output from the SimCast model (Grünwald et al. 2002) and corresponding temperature and relative humidity values. Monthly files are monthly averages of blight units and corresponding temperature and relative humidity values. <strong>SimCastMeta Look Up Files</strong> These tables contain the blight unit output of the SimCastMeta model along with corresponding temperature and relative humidity values which generate the blight units. Can be used in other applications as a look-up table rather than recreating the whole model in R.
DOI: 10.6084/m9.figshare.1064339
title: Integrating NEON data with existing models: An example with the Community Land Model

description: The manuscript and accompanying talk for the International Congress on Environmental Modeling and Software on building informatics infrastructure to support the integration of models and data. Please cite as: "Hart, E.M., Fox, A., Berukoff, S., Hoar, T., 2014 Integrating NEON data with existing models: An example with the Community Land Model In: Ames, D.P., Quinn, N.W.T., Rizzoli, A.E. (Eds.), Proceedings of the 7th International Congress on Environmental Modelling and Software, June 15-19, San Diego, California, USA. http://www.iemss.org/society/index.php/iemss-2014-proceedings"
DOI: 10.6084/m9.figshare.1064341
title: Quantifying the impact of bottom trawling on soft-bottom megafauna communities using video and scanning-sonar data on the continental slope off Vancouver Island, British Columbia

description: Megafauna found along transect R1075 grouped by 250m with habitat attributes
DOI: 10.6084/m9.figshare.1064341.v1
title: Quantifying the impact of bottom trawling on soft-bottom megafauna communities using video and scanning-sonar data on the continental slope off Vancouver Island, British Columbia

description: Megafauna found along transect R1075 grouped by 250m with habitat attributes