cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12843235.v1
title: All_Data_Cat TA from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: These four Excel files contain the values for Z (Normalized Center of Mass Position), P (Period), A (Amplitude), and D (Distance) in each cycle of a recording for four different cats. The cat names are encoded: MO, NO, TA, and WE, labeled in the Cat column. Recordings include the 04:04 m/s condition, the 04:06 m/s condition, the 04:08 m/s condition, and the 08:04 m/s condition, labeled in the Left : Right Speed Ratio column. Recordings with no anesthesia have a 0 and recordings with anesthesia have a 1 in the Anesthesia column. The cycles in this file are all of the cycles in the recording before removal of outliers and the cycles at the beginning and end of the recording, by the description in the manuscript.
DOI: 10.6084/m9.figshare.12843226.v1
title: SPSS OUTPUT from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: This file contains the Mixed ANOVA test output by the SPSS program after processing the data in the file All_conditions_all cats.xlsx
DOI: 10.6084/m9.figshare.12843235
title: All_Data_Cat TA from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: These four Excel files contain the values for Z (Normalized Center of Mass Position), P (Period), A (Amplitude), and D (Distance) in each cycle of a recording for four different cats. The cat names are encoded: MO, NO, TA, and WE, labeled in the Cat column. Recordings include the 04:04 m/s condition, the 04:06 m/s condition, the 04:08 m/s condition, and the 08:04 m/s condition, labeled in the Left : Right Speed Ratio column. Recordings with no anesthesia have a 0 and recordings with anesthesia have a 1 in the Anesthesia column. The cycles in this file are all of the cycles in the recording before removal of outliers and the cycles at the beginning and end of the recording, by the description in the manuscript.
DOI: 10.6084/m9.figshare.12843241
title: All conditions all cats from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: This file contains the cat names, speed, and anesthesia encodings in the “Index” tab. This file contains the values for Z (Normalized Center of Mass Position), P (Period), A (Amplitude), and D (Distance) in cycles of each condition after removal of outliers and beginning and end cycles for four different cats in the “Data” tab.
DOI: 10.6084/m9.figshare.12843229.v1
title: All_Data_Cat MO from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: These four Excel files contain the values for Z (Normalized Center of Mass Position), P (Period), A (Amplitude), and D (Distance) in each cycle of a recording for four different cats. The cat names are encoded: MO, NO, TA, and WE, labeled in the Cat column. Recordings include the 04:04 m/s condition, the 04:06 m/s condition, the 04:08 m/s condition, and the 08:04 m/s condition, labeled in the Left : Right Speed Ratio column. Recordings with no anesthesia have a 0 and recordings with anesthesia have a 1 in the Anesthesia column. The cycles in this file are all of the cycles in the recording before removal of outliers and the cycles at the beginning and end of the recording, by the description in the manuscript.
DOI: 10.6084/m9.figshare.12843238
title: All Data Cat ‘CatName’ from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: These four Excel files contain the values for Z (Normalized Center of Mass Position), P (Period), A (Amplitude), and D (Distance) in each cycle of a recording for four different cats. The cat names are encoded: MO, NO, TA, and WE, labeled in the Cat column. Recordings include the 04:04 m/s condition, the 04:06 m/s condition, the 04:08 m/s condition, and the 08:04 m/s condition, labeled in the Left : Right Speed Ratio column. Recordings with no anesthesia have a 0 and recordings with anesthesia have a 1 in the Anesthesia column. The cycles in this file are all of the cycles in the recording before removal of outliers and the cycles at the beginning and end of the recording, by the description in the manuscript.
DOI: 10.6084/m9.figshare.12843226
title: SPSS OUTPUT from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: This file contains the Mixed ANOVA test output by the SPSS program after processing the data in the file All_conditions_all cats.xlsx
DOI: 10.6084/m9.figshare.12843238.v1
title: All Data Cat ‘CatName’ from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: These four Excel files contain the values for Z (Normalized Center of Mass Position), P (Period), A (Amplitude), and D (Distance) in each cycle of a recording for four different cats. The cat names are encoded: MO, NO, TA, and WE, labeled in the Cat column. Recordings include the 04:04 m/s condition, the 04:06 m/s condition, the 04:08 m/s condition, and the 08:04 m/s condition, labeled in the Left : Right Speed Ratio column. Recordings with no anesthesia have a 0 and recordings with anesthesia have a 1 in the Anesthesia column. The cycles in this file are all of the cycles in the recording before removal of outliers and the cycles at the beginning and end of the recording, by the description in the manuscript.
DOI: 10.6084/m9.figshare.12843241.v1
title: All conditions all cats from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: This file contains the cat names, speed, and anesthesia encodings in the “Index” tab. This file contains the values for Z (Normalized Center of Mass Position), P (Period), A (Amplitude), and D (Distance) in cycles of each condition after removal of outliers and beginning and end cycles for four different cats in the “Data” tab.
DOI: 10.6084/m9.figshare.12843244.v1
title: All Data Cat WE from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: These four Excel files contain the values for Z (Normalized Center of Mass Position), P (Period), A (Amplitude), and D (Distance) in each cycle of a recording for four different cats. The cat names are encoded: MO, NO, TA, and WE, labeled in the Cat column. Recordings include the 04:04 m/s condition, the 04:06 m/s condition, the 04:08 m/s condition, and the 08:04 m/s condition, labeled in the Left : Right Speed Ratio column. Recordings with no anesthesia have a 0 and recordings with anesthesia have a 1 in the Anesthesia column. The cycles in this file are all of the cycles in the recording before removal of outliers and the cycles at the beginning and end of the recording, by the description in the manuscript.
DOI: 10.6084/m9.figshare.12843244
title: All Data Cat WE from Frontal plane dynamics of the centre of mass during quadrupedal locomotion on a split-belt treadmill

description: These four Excel files contain the values for Z (Normalized Center of Mass Position), P (Period), A (Amplitude), and D (Distance) in each cycle of a recording for four different cats. The cat names are encoded: MO, NO, TA, and WE, labeled in the Cat column. Recordings include the 04:04 m/s condition, the 04:06 m/s condition, the 04:08 m/s condition, and the 08:04 m/s condition, labeled in the Left : Right Speed Ratio column. Recordings with no anesthesia have a 0 and recordings with anesthesia have a 1 in the Anesthesia column. The cycles in this file are all of the cycles in the recording before removal of outliers and the cycles at the beginning and end of the recording, by the description in the manuscript.
DOI: 10.6084/m9.figshare.12844098.v1
title: ExperimentDataComb from Observing the Mpemba effect with minimal bias and the value of the Mpemba effect to scientific outreach and engagement

description: Data from all cooling experiments
DOI: 10.6084/m9.figshare.12844098
title: ExperimentDataComb from Observing the Mpemba effect with minimal bias and the value of the Mpemba effect to scientific outreach and engagement

description: Data from all cooling experiments
DOI: 10.6084/m9.figshare.12844282
title: Magic State Distillation with the Ternary Golay Code (Mathematica file) from Magic state distillation with the ternary Golay code

description: This is the Wolfram Mathematica notebook used to obtain the main results of this paper.
DOI: 10.6084/m9.figshare.12844282.v1
title: Magic State Distillation with the Ternary Golay Code (Mathematica file) from Magic state distillation with the ternary Golay code

description: This is the Wolfram Mathematica notebook used to obtain the main results of this paper.
DOI: 10.6084/m9.figshare.12844287
title: Wald's martingale and the conditional distributions of absorption time in the Moran process.ipynb

description: Jupyter notebook that reproduces all simulations and figures
DOI: 10.6084/m9.figshare.12844287.v1
title: Wald's martingale and the conditional distributions of absorption time in the Moran process.ipynb

description: Jupyter notebook that reproduces all simulations and figures
DOI: 10.6084/m9.figshare.12844294
title: Simulation Code (f90) from Corrugation of unpaved road surface under vehicle weight

description: Numerical simulation code for time evolution calculation written by Fortran 90.
DOI: 10.6084/m9.figshare.12844291
title: Experimental Data (csv) from Corrugation of unpaved road surface under vehicle weight

description: Experimental data of soil consolidation test required to create Figure 3.
DOI: 10.6084/m9.figshare.12844291.v1
title: Experimental Data (csv) from Corrugation of unpaved road surface under vehicle weight

description: Experimental data of soil consolidation test required to create Figure 3.
DOI: 10.6084/m9.figshare.12844294.v1
title: Simulation Code (f90) from Corrugation of unpaved road surface under vehicle weight

description: Numerical simulation code for time evolution calculation written by Fortran 90.
DOI: 10.6084/m9.figshare.12844296
title: Numeric Data from Figures 3–9 from Force reversal and energy dissipation in composite tubes through nonlinear viscoelasticity of component materials

description: CSV files containing numeric results displayed in paper figures.
DOI: 10.6084/m9.figshare.12844296.v1
title: Numeric Data from Figures 3–9 from Force reversal and energy dissipation in composite tubes through nonlinear viscoelasticity of component materials

description: CSV files containing numeric results displayed in paper figures.
DOI: 10.5281/zenodo.3966472
title: Mating-type locus rearrangements and shifts in thallism states in Citrus-associated Phyllosticta species

description: Files related to the manuscript published in to Fungal Genetics and Biology (https://doi.org/10.1016/j.fgb.2020.103444), with preprint available in bioRxiv (https://doi.org/10.1101/2020.04.14.040725). Contains: - 03 genome assemblies: Phyllosticta capitalensis LGMF01, Phyllosticta citribraziliensis LGMF08 and Phyllosticta citricarpa LGMF06; - 14 protein-coding gene annotation based in 14 Phyllosticta genomes; - Mating-type locus annotation from the 14 Phyllosticta strains in GBK format, and related FASTA sequences;
DOI: 10.5281/zenodo.3750350
title: Mating-type locus rearrangements and shifts in thallism states in Citrus-associated Phyllosticta species

description: Files related to the manuscript published in to Fungal Genetics and Biology (https://doi.org/10.1016/j.fgb.2020.103444), with preprint available in bioRxiv (https://doi.org/10.1101/2020.04.14.040725). Contains: - 03 genome assemblies: Phyllosticta capitalensis LGMF01, Phyllosticta citribraziliensis LGMF08 and Phyllosticta citricarpa LGMF06; - 14 protein-coding gene annotation based in 14 Phyllosticta genomes; - Mating-type locus annotation from the 14 Phyllosticta strains in GBK format, and related FASTA sequences;
DOI: 10.5517/ccdc.csd.cc24stzr
title: CCDC 1990075: Experimental Crystal Structure Determination

description: Related Article: Alireza Aliabadi, Mohammad Hakimi, Fatemeh Hosseinabadi, Elham Motieiyan, Vitor Hugo Nunes Rodrigues, Mohammad Ghadermazi, Domenica Marabello, Sara Abdolmaleki|2021|J.Mol.Struct.|1223|129005|doi:10.1016/j.molstruc.2020.129005
DOI: 10.5517/ccdc.csd.cc24sv0t
title: CCDC 1990076: Experimental Crystal Structure Determination

description: Related Article: Alireza Aliabadi, Mohammad Hakimi, Fatemeh Hosseinabadi, Elham Motieiyan, Vitor Hugo Nunes Rodrigues, Mohammad Ghadermazi, Domenica Marabello, Sara Abdolmaleki|2021|J.Mol.Struct.|1223|129005|doi:10.1016/j.molstruc.2020.129005
DOI: 10.5066/p9ltu2qm
title: National Land Cover Database (NLCD) 2016 Shrubland Fractional Components for the Western U.S. (ver. 2.0, October 2019)

description: This data release has been superseded by version 3.0, available here: https://doi.org/10.5066/P9MJVQSQ Quantifying Western U.S. shrublands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. The USGS NLCD team in collaboration with the BLM has produced the most comprehensive remote sensing-based quantification of Western U.S. shrublands to date. Nine shrubland ecosystem components, including percent shrub, sagebrush (Artemisia spp.), big sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, along with sagebrush and shrub heights, were quantified at 30-m resolution by mapping region. Each region required extensive ground measurement for model training and validation, two scales of remote sensing data from commercial high-resolution satellites and Landsat 8, and regression tree modeling to create component predictions. In the mapped portion (1,946,100 km�) of the total study area (2,557,556 km�), bare ground averaged 46.8%, shrub 14.4%, sagebrush 4.4%, big sagebrush 3.1%, herbaceous 22.8%, annual herbaceous 4.3% and litter 15.6%. Shrub height averaged 39.8 cm and sagebrush height 10.5 cm. Component accuracies using independent validation averaged R� values of 0.46, RMSE of 10.37 and nRMSE of 0.12, and cross validation averaged R� values of 0.72, RMSE of 5.09 and nRMSE of 0.062. Component composition strongly diverges by level III ecoregions, where 13 of 22 ecoregions are bare ground dominant, 8 are herbaceous dominant, and one is shrub dominant. Sagebrush physically covers 86,219 km�, or 4.4%, of our study area, but it is present in 835,507 km�, or 42.9%, of the non-masked area of our study area, underscoring its widespread distribution. This version contains some confusion between pinyon-juniper tree cover and shrubs. In a subsequent version, we have applied a more aggressive masking of tree canopy cover to each rangeland component. Specifically, we lowered the tree canopy cover threshold for exclusion from 40 to 25%. For pixels with 1-25% tree canopy cover we ensured that our primary components (shrub, herbaceous, litter, and bare ground) cover summed to 100% when added with the tree canopy. And, for the secondary components (sagebrush, big sagebrush, sagebrush height and shrub height) we reconciled to the primary component (shrub), excluding any pinyon-juniper woodlands. For the updated version with these changes applied, see https://doi.org/10.5066/P9MJVQSQ. This version of data were used as training for the Back-in-Time (BIT) fractional cover time series available at https://doi.org/10.5066/P9C9O66W. Component products can also be downloaded from www.mrlc.gov. First posted - May 15, 2019 (available from author) Revised - October 21, 2019 (version 2.0)
DOI: 10.15468/xetku5
title: Rocky-intertidal cheilostome bryozoans from the vicinity of the Sesoko Biological Station, west-central Okinawa, Japan

description: This dataset contains the digitized treatments in Plazi based on the original journal article Dick, Matthew H., Grischenko, Andrei V. (2016): Rocky-intertidal cheilostome bryozoans from the vicinity of the Sesoko Biological Station, west-central Okinawa, Japan. Journal of Natural History 51: 141-266, DOI: 10.1080/00222933.2016.1253797, URL: http://dx.doi.org/10.1080/00222933.2016.1253797
DOI: 10.15468/dnmeve
title: An unusual new species of Trechona (Araneae: Mygalomorphae: Dipluridae), from quartzitic caves of the Diamantina Plateau, Minas Gerais, Brazil, with a key to the known species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Guadanucci, José Paulo L., Fonseca-Ferreira, Rafael, Baptista, Renner Luiz Cerqueira, Pedroso, Denis Rafael (2016): An unusual new species of Trechona (Araneae: Mygalomorphae: Dipluridae), from quartzitic caves of the Diamantina Plateau, Minas Gerais, Brazil, with a key to the known species. Journal of Natural History 50: 2487-2497, DOI: 10.1080/00222933.2016.1193652, URL: http://dx.doi.org/10.1080/00222933.2016.1193652
DOI: 10.6084/m9.figshare.12840980
title: R0187_20170927a_videos

description: Rat 0187, skilled reaching data collected on 9/27/2017 in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.12840980.v1
title: R0187_20170927a_videos

description: Rat 0187, skilled reaching data collected on 9/27/2017 in Leventhal laboratory by Alexandra Bova
DOI: 10.5281/zenodo.3976952
title: CM2Mc Simulation Library

description: CM2Mc is a coarse-resolution (3-degree) version of the GFDL coupled model. It is similar to CM2.1 and ESM2M, with larger biases. It includes the BLING biogeochemical module (both the published version, v0, and a developmental version with more functionality). The basic model is described by Galbraith et al., 2011. The code used here has been updated from the original publication (to the GFDL Siena release) and there are some small modifications to the runtime parameters as described in Galbraith and de Lavergne, 2018. Simulation output is provided here, with no strings attached, in the hope that it might be useful for other investigators. Output can be used in publication, please just cite the description papers. If you have a burning question about anything, feel free to contact Eric. Otherwise, analyze away! The GFDL Earth system model CM2Mc was run to quasi-equilibrium under a broad range of external forcings, as described by Galbraith and deLavergne (2018). The purpose of these simulations was to map out the expectations of a modern climate model – of the sort used for conducting future climate change scenarios – under conditions that have occurred in the geologically-recent past. These simulations were described by Galbraith and de Lavergne (Climate Dynamics, 2018). Changes in ocean carbon storage among the simulations were also explored by Eggleston and Galbraith (Biogeosciences). However, these descriptions only scratch the surface – the output could be used to explore general mechanisms within the climate system, as well as their interactions with global biogeochemistry. The results could also be tested against new paleoclimate observations, to identify aspects of the simulations that are consistent, as well as to identify model biases and shortcomings when confronted with reality. For more please see: https://earthsystemdynamics.org/models/cm2mc-simulation-library/equilibrium-simulations/
DOI: 10.5281/zenodo.3976951
title: CM2Mc Simulation Library

description: CM2Mc is a coarse-resolution (3-degree) version of the GFDL coupled model. It is similar to CM2.1 and ESM2M, with larger biases. It includes the BLING biogeochemical module (both the published version, v0, and a developmental version with more functionality). The basic model is described by Galbraith et al., 2011. The code used here has been updated from the original publication (to the GFDL Siena release) and there are some small modifications to the runtime parameters as described in Galbraith and de Lavergne, 2018. Simulation output is provided here, with no strings attached, in the hope that it might be useful for other investigators. Output can be used in publication, please just cite the description papers. If you have a burning question about anything, feel free to contact Eric. Otherwise, analyze away! The GFDL Earth system model CM2Mc was run to quasi-equilibrium under a broad range of external forcings, as described by Galbraith and deLavergne (2018). The purpose of these simulations was to map out the expectations of a modern climate model – of the sort used for conducting future climate change scenarios – under conditions that have occurred in the geologically-recent past. These simulations were described by Galbraith and de Lavergne (Climate Dynamics, 2018). Changes in ocean carbon storage among the simulations were also explored by Eggleston and Galbraith (Biogeosciences). However, these descriptions only scratch the surface – the output could be used to explore general mechanisms within the climate system, as well as their interactions with global biogeochemistry. The results could also be tested against new paleoclimate observations, to identify aspects of the simulations that are consistent, as well as to identify model biases and shortcomings when confronted with reality. For more please see: https://earthsystemdynamics.org/models/cm2mc-simulation-library/equilibrium-simulations/
DOI: 10.6084/m9.figshare.12844438
title: Investigating the impact of filters on long-term particle concentration measurements in residences (RP-1649)

description: Filters in heating, ventilation, and air-conditioning (HVAC) systems are the most prevalent air cleaning method in residential environments in North America. This study evaluated the long-term impact of residential filtration systems on indoor particle concentrations by examining concentration measurements from low-cost monitors over one year in twenty homes in Toronto, Ontario, Canada. These concentration results suggested that in general, indoor concentration had a similar seasonal trend as the ambient concentration, and indoor activities (e.g., cooking) elevated indoor particle levels for 40-50% of the time. Further, the impacts of electret filters were examined using a non-electret filter with a minimum efficiency reporting value (MERV) of 8 as the reference point at each home. The mean effectiveness of the filters (MERV 8E = −4.19%, MERV 11E = −0.51%, and MERV 14E = 14.5%) were lower than values found in the literature, most likely due to lower HVAC system runtime in our sample of homes (median = 9.6%). Overall, this filter effectiveness analysis reveals that the real-life filter performance was strongly influenced by system and house characteristics (e.g., system runtime, in-situ efficiency, air change rate, and particle source strength), and thus can be different from modeling and laboratory test results.