cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8010916
title: IODP Expedition 369 Interstitial water composite report

description: This composite report includes data from numerous interstitial water (IW) analyses (e.g., ICP-LIQUIDS and IONCHROM) in a variable set of columns. Each row combines the data from several tests (groups of measurements made on the same sample at the same time) for a particular IW sample. If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate analysis (ALKALINITY, ICP-LIQUIDS, IONCHROM, SALINITY, SPEC, TITRATOR, and potentially others). Major and minor elements were determined by inductively coupled plasma-atomic emission spectrocsopy (ICP-LIQUIDS). Cations and anions were measured by ion chromatography (IONCHROM). Complex ions were measured by colorimetric measurements using a UV-VIS spectrometer (SPEC). Alkalinity and chloride was measured by titration (ALKALINITY and TITRATOR). Dissolved carbon (DC), dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC) were measured by combustion in a total organic carbon (TOC) analyzer. Salinity was measured by refractometer (SALINITY). pH was measured by ion-selective electrode as part of the alkalinity procedure and is reported in the ALKALINITY analysis.
DOI: 10.5281/zenodo.8010915
title: IODP Expedition 369 Interstitial water composite report

description: This composite report includes data from numerous interstitial water (IW) analyses (e.g., ICP-LIQUIDS and IONCHROM) in a variable set of columns. Each row combines the data from several tests (groups of measurements made on the same sample at the same time) for a particular IW sample. If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate analysis (ALKALINITY, ICP-LIQUIDS, IONCHROM, SALINITY, SPEC, TITRATOR, and potentially others). Major and minor elements were determined by inductively coupled plasma-atomic emission spectrocsopy (ICP-LIQUIDS). Cations and anions were measured by ion chromatography (IONCHROM). Complex ions were measured by colorimetric measurements using a UV-VIS spectrometer (SPEC). Alkalinity and chloride was measured by titration (ALKALINITY and TITRATOR). Dissolved carbon (DC), dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC) were measured by combustion in a total organic carbon (TOC) analyzer. Salinity was measured by refractometer (SALINITY). pH was measured by ion-selective electrode as part of the alkalinity procedure and is reported in the ALKALINITY analysis.
DOI: 10.5281/zenodo.8011318
title: Does V1 response suppression initiate binocular rivalry?

description: <strong>Using this dataset</strong> As Cell Press authors, we share all of the data and original code we report in our paper with the research community. This dataset contains stimulus-locked multi-units responses for each recording session analyzed and reported in the associated manuscript at iScience. Please download and extract eventTriggeredData.zip into a file on your MATLAB path. For generating the figures reported in the manuscript, please use our custom MATLAB repository published on GitHub at: https://github.com/BrockMCarlson/BMC_AdaptdcosFigures. Download the GitHub repository, follow the setup instructions in the ReadMe, and run the Controller_iScienceSubmission.mlx live script. IDX_iScienceSubmission.mat, JASP_sustained.csv, & JASP_transient.csv are files created by Controller_iScienceSubmission.mlx. You do not need to download them, but they are included in this Zenodo directory for your reference. <em><strong>Does V1 response suppression initiate binocular rivalry?</strong></em> <strong>HIGHLIGHTS</strong> The role of primary visual cortex (V1) for binocular rivalry (BR) is unclear. V1 population spiking is reduced at the onset of BR, providing a potential trigger. However, this broad spiking suppression in does not occur for a variant of BR. The BR variant reduces subpopulation responses, a potential alternate trigger. <strong>SUMMARY</strong> In binocular rivalry (BR) only one’s view is perceived. The neural underpinnings of BR are debated. Recent studies suggest that primary visual cortex (V1) initiates BR. One such trigger might be response-suppression across most V1 neurons at the onset of BR. Here we utilize a variant of BR called binocular rivalry flash suppression (BRFS) to test this hypothesis. BRFS is identical to binocular rivalry, except stimuli are shown with a ~1s delay. If V1 response suppression was required to initiate BR, it should occur during BRFS as well. To test this hypothesis, we compared V1 spiking in two macaques observing BRFS. We found that BRFS resulted in response-facilitation rather than response-suppression across V1 neurons. However, BRFS still reduces responses in a subset of V1 neurons due to the adaptive effects of asynchronous stimulus presentation. We argue that this selective response suppression could serve as an alternate initiator of BR.
description: https://github.com/BrockMCarlson/BMC_AdaptdcosFigures
DOI: 10.5281/zenodo.7949494
title: Does V1 response suppression initiate binocular rivalry?

description: <strong>Using this dataset</strong> As Cell Press authors, we share all of the data and original code we report in our paper with the research community. This dataset contains stimulus-locked multi-units responses for each recording session analyzed and reported in the associated manuscript at iScience. Please download and extract eventTriggeredData.zip into a file on your MATLAB path. For generating the figures reported in the manuscript, please use our custom MATLAB repository published on GitHub at: https://github.com/BrockMCarlson/BMC_AdaptdcosFigures. Download the GitHub repository, follow the setup instructions in the ReadMe, and run the Controller_iScienceSubmission.mlx live script. IDX_iScienceSubmission.mat, JASP_sustained.csv, & JASP_transient.csv are files created by Controller_iScienceSubmission.mlx. You do not need to download them, but they are included in this Zenodo directory for your reference. <em><strong>Does V1 response suppression initiate binocular rivalry?</strong></em> <strong>HIGHLIGHTS</strong> The role of primary visual cortex (V1) for binocular rivalry (BR) is unclear. V1 population spiking is reduced at the onset of BR, providing a potential trigger. However, this broad spiking suppression in does not occur for a variant of BR. The BR variant reduces subpopulation responses, a potential alternate trigger. <strong>SUMMARY</strong> In binocular rivalry (BR) only one’s view is perceived. The neural underpinnings of BR are debated. Recent studies suggest that primary visual cortex (V1) initiates BR. One such trigger might be response-suppression across most V1 neurons at the onset of BR. Here we utilize a variant of BR called binocular rivalry flash suppression (BRFS) to test this hypothesis. BRFS is identical to binocular rivalry, except stimuli are shown with a ~1s delay. If V1 response suppression was required to initiate BR, it should occur during BRFS as well. To test this hypothesis, we compared V1 spiking in two macaques observing BRFS. We found that BRFS resulted in response-facilitation rather than response-suppression across V1 neurons. However, BRFS still reduces responses in a subset of V1 neurons due to the adaptive effects of asynchronous stimulus presentation. We argue that this selective response suppression could serve as an alternate initiator of BR.
description: https://github.com/BrockMCarlson/BMC_AdaptdcosFigures
DOI: 10.5281/zenodo.8011410
title: Does V1 response suppression initiate binocular rivalry?

description: <strong>Using this dataset</strong> As Cell Press authors, we share all of the data and original code we report in our paper with the research community. This dataset contains stimulus-locked multi-units responses for each recording session analyzed and reported in the associated manuscript at iScience. Please download and extract eventTriggeredData.zip into a file on your MATLAB path. For generating the figures reported in the manuscript, please use our custom MATLAB repository published on GitHub at: https://github.com/BrockMCarlson/BMC_AdaptdcosFigures. Download the GitHub repository, follow the setup instructions in the ReadMe, and run the Controller_iScienceSubmission.mlx live script. IDX_iScienceSubmission.mat, JASP_sustained.csv, & JASP_transient.csv are files created by Controller_iScienceSubmission.mlx. You do not need to download them, but they are included in this Zenodo directory for your reference. <em><strong>Does V1 response suppression initiate binocular rivalry?</strong></em> <strong>HIGHLIGHTS</strong> The role of primary visual cortex (V1) for binocular rivalry (BR) is unclear. V1 population spiking is reduced at the onset of BR, providing a potential trigger. However, this broad spiking suppression in does not occur for a variant of BR. The BR variant reduces subpopulation responses, a potential alternate trigger. <strong>SUMMARY</strong> In binocular rivalry (BR) only one’s view is perceived. The neural underpinnings of BR are debated. Recent studies suggest that primary visual cortex (V1) initiates BR. One such trigger might be response-suppression across most V1 neurons at the onset of BR. Here we utilize a variant of BR called binocular rivalry flash suppression (BRFS) to test this hypothesis. BRFS is identical to binocular rivalry, except stimuli are shown with a ~1s delay. If V1 response suppression was required to initiate BR, it should occur during BRFS as well. To test this hypothesis, we compared V1 spiking in two macaques observing BRFS. We found that BRFS resulted in response-facilitation rather than response-suppression across V1 neurons. However, BRFS still reduces responses in a subset of V1 neurons due to the adaptive effects of asynchronous stimulus presentation. We argue that this selective response suppression could serve as an alternate initiator of BR.
description: https://github.com/BrockMCarlson/BMC_AdaptdcosFigures
DOI: 10.5281/zenodo.8010908
title: IODP Expedition 369 ICP-AES elemental analysis (interstitial water)

description: Elemental concentration in interstitial water samples was measured by inductively coupled plasma - atomic emission spectroscopy (ICP-AES). Data are presented by element-wavelength pair (e.g., more than one calcium line may be reported). Elemental lines for which data do not exist for a particular expedition will not appear.
DOI: 10.5281/zenodo.8010907
title: IODP Expedition 369 ICP-AES elemental analysis (interstitial water)

description: Elemental concentration in interstitial water samples was measured by inductively coupled plasma - atomic emission spectroscopy (ICP-AES). Data are presented by element-wavelength pair (e.g., more than one calcium line may be reported). Elemental lines for which data do not exist for a particular expedition will not appear.
DOI: 10.5281/zenodo.8011453
title: Raw Data on Marshall properties of asphalt mixtures containing recycled concrete aggregate.

description: these raw data about the feasibility of using recycled concrete aggregate for the surface layer of asphalt pavement. these will be useful data for transportation Engineers, environmentalists, and researchers for further development
DOI: 10.5281/zenodo.8011452
title: Raw Data on Marshall properties of asphalt mixtures containing recycled concrete aggregate.

description: these raw data about the feasibility of using recycled concrete aggregate for the surface layer of asphalt pavement. these will be useful data for transportation Engineers, environmentalists, and researchers for further development
DOI: 10.5281/zenodo.8010914
title: IODP Expedition 369 Ion chromatography

description: Cation and anion concentration in interstitial water samples was measured by ion chromatography using a conductivity detector. Cation analytes include calcium, magnesium, potassium, and sodium. Anion analytes include chloride, sulfate, and bromide.
DOI: 10.5281/zenodo.8010913
title: IODP Expedition 369 Ion chromatography

description: Cation and anion concentration in interstitial water samples was measured by ion chromatography using a conductivity detector. Cation analytes include calcium, magnesium, potassium, and sodium. Anion analytes include chloride, sulfate, and bromide.
DOI: 10.5281/zenodo.8011478
title: SimuComp Bus Study Data Set

description: Raw data set and calculations of the study for the paper "Simulink bus usage in practice: an empirical study" accepted at the 19th European Conference on Modelling Foundations and Applications (ECMFA 2023)
DOI: 10.5281/zenodo.8010783
title: Conjunto de dados sobre o perfil das escolas similares da Microrregião de Salvador - Bahia (Nota técnica 2014 - INEP)

description: O conjunto de dados são resultados parciais da tese de doutorado <strong>MODELAGEM DE DADOS ABERTOS GOVERNAMENTAIS DA EDUCAÇÃO BASEADO EM REDES: PROJETO ESCOLAS SIMILARES </strong>, desenvolvida no ambito do programa de Pósgraduação em Difusão do Conhecimento da Universidade Federal da Bahia Autora: Eneida Santana de Ávila Goulart Orientador: Roberto Monteiro
DOI: 10.5281/zenodo.8011477
title: SimuComp Bus Study Data Set

description: Raw data set and calculations of the study for the paper "Simulink bus usage in practice: an empirical study" accepted at the 19th European Conference on Modelling Foundations and Applications (ECMFA 2023)
DOI: 10.5281/zenodo.8010782
title: Conjunto de dados sobre o perfil das escolas similares da Microrregião de Salvador - Bahia (Nota técnica 2014 - INEP)

description: O conjunto de dados são resultados parciais da tese de doutorado <strong>MODELAGEM DE DADOS ABERTOS GOVERNAMENTAIS DA EDUCAÇÃO BASEADO EM REDES: PROJETO ESCOLAS SIMILARES </strong>, desenvolvida no ambito do programa de Pósgraduação em Difusão do Conhecimento da Universidade Federal da Bahia Autora: Eneida Santana de Ávila Goulart Orientador: Roberto Monteiro
DOI: 10.5281/zenodo.6469694
title: Indian Rainfall Erosivity Dataset (IRED)

description: Soil erosion induced by water has been identified as one of the major environmental problems worldwide. The erosive force of rainfall, also known as rainfall erosivity (R-factor), is the potential of rain to cause soil degradation and one of the factors in the widely adopted RUSLE (Revised Universal Soil Loss Equation) empirical soil erosion estimation model. About 68.4% of total eroded soil in India is eroded due to erosion by water, and rainfall erosivity is one of the major factors. The past assessments of rainfall erosivity in India were however largely based on rain-gauge recordings and surveys which hinders its understanding and estimation over large areas. Growing availability of gridded precipitation datasets presents an unprecedented opportunity to study long-term rainfall erosivity over varied terrains and address some of the limitations of point data-based studies. IRED (Indian Rainfall Erosivity Dataset) is the first such national-scale assessment of rainfall erosivity over India using gridded precipitation datasets, which will be helpful for agricultural experts, watershed managers, agronomists, and soil-conservational experts in order to understand and mitigate rainfall-induced erosion. In this dataset, long term yearly average R-factor, Fourier Index (FI), and Modified Fourier Index (MFI) maps have been included with a distributional analysis over IMD (India Metrological Department) defined regions, states and districts of India.
DOI: 10.5281/zenodo.6470233
title: Indian Rainfall Erosivity Dataset (IRED)

description: Soil erosion induced by water has been identified as one of the major environmental problems worldwide. The erosive force of rainfall, also known as rainfall erosivity (R-factor), is the potential of rain to cause soil degradation and one of the factors in the widely adopted RUSLE (Revised Universal Soil Loss Equation) empirical soil erosion estimation model. About 68.4% of total eroded soil in India is eroded due to erosion by water, and rainfall erosivity is one of the major factors. The past assessments of rainfall erosivity in India were however largely based on rain-gauge recordings and surveys which hinders its understanding and estimation over large areas. Growing availability of gridded precipitation datasets presents an unprecedented opportunity to study long-term rainfall erosivity over varied terrains and address some of the limitations of point data-based studies. IRED (Indian Rainfall Erosivity Dataset) is the first such national-scale assessment of rainfall erosivity over India using gridded precipitation datasets, which will be helpful for agricultural experts, watershed managers, agronomists, and soil-conservational experts in order to understand and mitigate rainfall-induced erosion. In this dataset, long term yearly average R-factor, Fourier Index (FI), and Modified Fourier Index (MFI) maps have been included with a distributional analysis over IMD (India Metrological Department) defined regions, states and districts of India.
DOI: 10.5281/zenodo.6469693
title: Indian Rainfall Erosivity Dataset (IRED)

description: Soil erosion induced by water has been identified as one of the major environmental problems worldwide. The erosive force of rainfall, also known as rainfall erosivity (R-factor), is the potential of rain to cause soil degradation and one of the factors in the widely adopted RUSLE (Revised Universal Soil Loss Equation) empirical soil erosion estimation model. About 68.4% of total eroded soil in India is eroded due to erosion by water, and rainfall erosivity is one of the major factors. The past assessments of rainfall erosivity in India were however largely based on rain-gauge recordings and surveys which hinders its understanding and estimation over large areas. Growing availability of gridded precipitation datasets presents an unprecedented opportunity to study long-term rainfall erosivity over varied terrains and address some of the limitations of point data-based studies. IRED (Indian Rainfall Erosivity Dataset) is the first such national-scale assessment of rainfall erosivity over India using gridded precipitation datasets, which will be helpful for agricultural experts, watershed managers, agronomists, and soil-conservational experts in order to understand and mitigate rainfall-induced erosion. In this dataset, long term yearly average R-factor, Fourier Index (FI), and Modified Fourier Index (MFI) maps have been included with a distributional analysis over IMD (India Metrological Department) defined regions, states and districts of India.
DOI: 10.5281/zenodo.6505510
title: Indian Rainfall Erosivity Dataset (IRED)

description: Soil erosion induced by water has been identified as one of the major environmental problems worldwide. The erosive force of rainfall, also known as rainfall erosivity (R-factor), is the potential of rain to cause soil degradation and one of the factors in the widely adopted RUSLE (Revised Universal Soil Loss Equation) empirical soil erosion estimation model. About 68.4% of total eroded soil in India is eroded due to erosion by water, and rainfall erosivity is one of the major factors. The past assessments of rainfall erosivity in India were however largely based on rain-gauge recordings and surveys which hinders its understanding and estimation over large areas. Growing availability of gridded precipitation datasets presents an unprecedented opportunity to study long-term rainfall erosivity over varied terrains and address some of the limitations of point data-based studies. IRED (Indian Rainfall Erosivity Dataset) is the first such national-scale assessment of rainfall erosivity over India using gridded precipitation datasets, which will be helpful for agricultural experts, watershed managers, agronomists, and soil-conservational experts in order to understand and mitigate rainfall-induced erosion. In this dataset, long term yearly average R-factor, Fourier Index (FI), and Modified Fourier Index (MFI) maps have been included with a distributional analysis over IMD (India Metrological Department) defined regions, states and districts of India.
DOI: 10.5281/zenodo.6505315
title: Indian Soil Erodibility Dataset (ISED)

description: Soil erosion has been spotted as one of the major global problems, and soil erodibility is the property of soil which refers to the erosive nature of the soil. India is also struggling with the erosion problem in most parts of the country. A national-scale soil erosion study is needed to assess such types of problems. ISED (Indian Soil Erodibility Dataset) is a step toward building datasets in mapping soil erosion at a national scale after IRED (Indian Rainfall Erosivity Dataset). This dataset consists of K-factor (t-ha-h/ha/MJ/mm), soil erodibility indices like CR (Clay Ratio), Modified Clay Ratio (MCR), and CLOM (Critical Level of Organic Matter) map over India at high resolution (250 m). Distribution maps of soil erodibility corresponding to the districts and soil types of India are also added to this dataset. This dataset is an additional dataset at a national scale for soil erosion modeling which will be handy data for experts and researchers.
DOI: 10.5281/zenodo.6505314
title: Indian Soil Erodibility Dataset (ISED)

description: Soil erosion has been spotted as one of the major global problems, and soil erodibility is the property of soil which refers to the erosive nature of the soil. India is also struggling with the erosion problem in most parts of the country. A national-scale soil erosion study is needed to assess such types of problems. ISED (Indian Soil Erodibility Dataset) is a step toward building datasets in mapping soil erosion at a national scale after IRED (Indian Rainfall Erosivity Dataset). This dataset consists of K-factor (t-ha-h/ha/MJ/mm), soil erodibility indices like CR (Clay Ratio), Modified Clay Ratio (MCR), and CLOM (Critical Level of Organic Matter) map over India at high resolution (250 m). It also includes a Susceptibility to Erosion map of India due to Organic Matter availability. Distribution maps of soil erodibility corresponding to the districts and soil types of India are also added to this dataset. This dataset is an additional dataset at a national scale for soil erosion modeling which will be handy data for experts and researchers.
DOI: 10.5281/zenodo.6505511
title: Indian Soil Erodibility Dataset (ISED)

description: Soil erosion has been spotted as one of the major global problems, and soil erodibility is the property of soil which refers to the erosive nature of the soil. India is also struggling with the erosion problem in most parts of the country. A national-scale soil erosion study is needed to assess such types of problems. ISED (Indian Soil Erodibility Dataset) is a step toward building datasets in mapping soil erosion at a national scale after IRED (Indian Rainfall Erosivity Dataset). This dataset consists of K-factor (t-ha-h/ha/MJ/mm), soil erodibility indices like CR (Clay Ratio), Modified Clay Ratio (MCR), and CLOM (Critical Level of Organic Matter) map over India at high resolution (250 m). Distribution maps of soil erodibility corresponding to the districts and soil types of India are also added to this dataset. This dataset is an additional dataset at a national scale for soil erosion modeling which will be handy data for experts and researchers.