cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14122049
title: Update on the multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs: auditory, sensory and high-frequency sensory evoked potentials

description: Building upon the previously shared data set, here we expand from a spontaneous to an evoked responses data set containing brain electrical activities in the form of electrocorticogram (ECOG) and electrothalamogram (EThG). This evoked responses data set includes auditory (AEP) and sensory (SEP) stimulation paradigms. This permits derivation of electroencephalogram (EEG) biomarkers of corticothalamic communication under normal, sedation, and hypoxic/ischemic conditions with ensuing recovery. The data set is presented in full band sampled at 2000 Hz. A unique feature is the additional measurement of the high-frequency oscillations in response to sensory stimulation (HFO SEPs). We provide technical validation of the evoked responses for the composite states of sedation, ischemia and recovery, as before. This extended data set now permits mutual inferences between spontaneous and evoked activities across the recorded modalities. Future studies on the dataset may contribute to the development of new brain monitoring technologies, which will facilitate the prevention of neurological injuries.
DOI: 10.6084/m9.figshare.14122049.v2
title: Update on the multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs: auditory, sensory and high-frequency sensory evoked potentials

description: Building upon the previously shared data set, here we expand from a spontaneous to an evoked responses data set containing brain electrical activities in the form of electrocorticogram (ECOG) and electrothalamogram (EThG). This evoked responses data set includes auditory (AEP) and sensory (SEP) stimulation paradigms. This permits derivation of electroencephalogram (EEG) biomarkers of corticothalamic communication under normal, sedation, and hypoxic/ischemic conditions with ensuing recovery. The data set is presented in full band sampled at 2000 Hz. A unique feature is the additional measurement of the high-frequency oscillations in response to sensory stimulation (HFO SEPs). We provide technical validation of the evoked responses for the composite states of sedation, ischemia and recovery, as before. This extended data set now permits mutual inferences between spontaneous and evoked activities across the recorded modalities. Future studies on the dataset may contribute to the development of new brain monitoring technologies, which will facilitate the prevention of neurological injuries.
DOI: 10.6084/m9.figshare.16671211
title: Rhizosphere interactions under diverse canola genotypes: a key component in seed nitrogen use efficiency

description: Belowground dynamics between soil-plant-microbial interactions impact crop nitrogen use efficiency (NUE), but current research focuses on aboveground crop management and breeding, leaving belowground dynamics scarcely studied. Canola (Brassica napus L.) is an agriculturally relevant crop in Canada, with relatively high N requirement and largely unknown soil-plant-microbial impact. We explored canola genotypic and temporal changes in soil N concentrations, root morphology, and rhizosphere and root microbiomes to identify belowground traits important to canola NUE. Sixteen canola genotypes were grown on a Dark Brown Chernozem in Saskatchewan, Canada, in a randomized complete block design with three blocks. Soil and plant were sampled five times over the growing season from 32- 81 days after sowing (DAS), and seeds sampled at 81 DAS. Soil moisture and NO3--N were negatively correlated with canola NUE, with genotype specific changes possibly related to genetically inherited traits that controlled soil moisture and N cycling. Root length and surface area were highest under seed ripening (67 DAS) and root surface area was negatively correlated with soil NO3--N concentrations. This suggests that root morphology changed to facilitate greater soil mineral N absorption, with genetically driven changing controlled by plant inherited traits. Rhizosphere microbial diversity and community structure were largely predicted by soil NH4+-N and pH respectively; and root microbial diversity and community structure predicted by soil moisture and pH, and soil NO3--N respectively. We determined canola genotypes had a significant influence on rhizosphere and root microbial assemblages, and plant-microbial interactions likely shaped these microbiomes, making them distinct between genotypes. This research helps us understand belowground predictors on canola seed NUE that can benefit agronomic practices for greater canola productivity and NUE metrics.
DOI: 10.6084/m9.figshare.16671211.v1
title: Rhizosphere interactions under diverse canola genotypes: a key component in seed nitrogen use efficiency

description: Belowground dynamics between soil-plant-microbial interactions impact crop nitrogen use efficiency (NUE), but current research focuses on aboveground crop management and breeding, leaving belowground dynamics scarcely studied. Canola (Brassica napus L.) is an agriculturally relevant crop in Canada, with relatively high N requirement and largely unknown soil-plant-microbial impact. We explored canola genotypic and temporal changes in soil N concentrations, root morphology, and rhizosphere and root microbiomes to identify belowground traits important to canola NUE. Sixteen canola genotypes were grown on a Dark Brown Chernozem in Saskatchewan, Canada, in a randomized complete block design with three blocks. Soil and plant were sampled five times over the growing season from 32- 81 days after sowing (DAS), and seeds sampled at 81 DAS. Soil moisture and NO3--N were negatively correlated with canola NUE, with genotype specific changes possibly related to genetically inherited traits that controlled soil moisture and N cycling. Root length and surface area were highest under seed ripening (67 DAS) and root surface area was negatively correlated with soil NO3--N concentrations. This suggests that root morphology changed to facilitate greater soil mineral N absorption, with genetically driven changing controlled by plant inherited traits. Rhizosphere microbial diversity and community structure were largely predicted by soil NH4+-N and pH respectively; and root microbial diversity and community structure predicted by soil moisture and pH, and soil NO3--N respectively. We determined canola genotypes had a significant influence on rhizosphere and root microbial assemblages, and plant-microbial interactions likely shaped these microbiomes, making them distinct between genotypes. This research helps us understand belowground predictors on canola seed NUE that can benefit agronomic practices for greater canola productivity and NUE metrics.
DOI: 10.25380/iastate.14887854
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2020

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2020 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.14887854.v1
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2020

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2020 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.5281/zenodo.5524813
title: Datasets for HLU7 of the CROSSBOW project.

description: Datasets for HLU7 of the CROSSBOW project.
DOI: 10.25380/iastate.14885825
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2020

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2020 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.14885825.v1
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2020

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2020 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.5281/zenodo.5524488
title: Real Operatiοn Data from PV, WT, Battery (measurements from pilot site)

description: Real Operatiοn Data from PV, WT, Battery (measurements from pilot site)
DOI: 10.5281/zenodo.5524487
title: Real Operatiοn Data from PV, WT, Battery (measurements from pilot site)

description: Real Operatiοn Data from PV, WT, Battery (measurements from pilot site)
DOI: 10.5281/zenodo.5524460
title: Datasets with weather forecasts (Temperature, Wind Direction, Humidity, Pressure, Wind Speed, GHI)

description: Datasets with weather forecasts for HLU7 (Temperature, Wind Direction, Humidity, Pressure, Wind Speed, GHI) of the CROSSBOW project.
description: Weather forecast provider: SKIRON (National and Kapodistrian University of Athens) The file includes weather forecasts for a specific geolocation in Greece, exclusively for the purposes of the CROSSBOW project. Any use of this data outside the CROSSBOW consortium for a commercial application without the permission from the weather forecast provider (SKIRON) is prohibited.
DOI: 10.5281/zenodo.5524459
title: Datasets with weather forecasts (Temperature, Wind Direction, Humidity, Pressure, Wind Speed, GHI)

description: Datasets with weather forecasts for HLU7 (Temperature, Wind Direction, Humidity, Pressure, Wind Speed, GHI) of the CROSSBOW project.
description: Weather forecast provider: SKIRON (National and Kapodistrian University of Athens) The file includes weather forecasts for a specific geolocation in Greece, exclusively for the purposes of the CROSSBOW project. Any use of this data outside the CROSSBOW consortium for a commercial application without the permission from the weather forecast provider (SKIRON) is prohibited.
DOI: 10.25380/iastate.12646255
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2019

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2019 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645919
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2019

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2019 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645919.v1
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2019

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2019 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.48577/jpl.k37v-y751
title: US Counties Atmospheric Optical Depth Climatology from MODIS-TERRA

description: Software for processing this is available at: https://doi.org/10.48577/jpl.j0m6-wz55
DOI: 10.25380/iastate.12645805
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2018

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2018 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645741
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2017

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2017 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.48577/jpl.ws86-1q81
title:  US Counties Relative Humidity Climatology from AIRS

description: Software for processing this is available at: https://doi.org/10.48577/jpl.j0m6-wz55
DOI: 10.25380/iastate.12645741.v2
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2017

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2017 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645741.v1
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2017

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2017 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645692
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2017

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2017 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645692.v2
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2017

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2017 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.3886/e121561
title: Data and Code for: MPC Heterogeneity and Household Balance Sheets

description: We use sizable lottery prizes in Norwegian administrative panel data to explorehow transitory income shocks are spent and saved over time, and how households’marginal propensities to consume (MPCs) vary with household characteristics andshock size. We find that spending peaks in the year of winning and gradually revertsto normal within five years. Controlling for all items on households’ balancesheets and characteristics such as education and income, it is the amount won, age,and liquid assets that vary systematically with MPCs. Low-liquidity winners of thesmallest prizes (around USD 1,500) are estimated to spend all within the year of winning.The corresponding estimate for high-liquidity winners of large prizes (USD8,300-150,000) is slightly below one half. While conventional models will struggle toaccount for such high MPC levels, we show that a two-asset life-cycle model with arealistic earnings profile and a luxury bequest motive can account for both the timeprofile of consumption responses and their systematic co-variation with observables.
description: Households in Norway.
DOI: 10.25380/iastate.12645692.v1
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2017

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2017 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.3886/e121561v1
title: Data and Code for: MPC Heterogeneity and Household Balance Sheets

description: We use sizable lottery prizes in Norwegian administrative panel data to explorehow transitory income shocks are spent and saved over time, and how households’marginal propensities to consume (MPCs) vary with household characteristics andshock size. We find that spending peaks in the year of winning and gradually revertsto normal within five years. Controlling for all items on households’ balancesheets and characteristics such as education and income, it is the amount won, age,and liquid assets that vary systematically with MPCs. Low-liquidity winners of thesmallest prizes (around USD 1,500) are estimated to spend all within the year of winning.The corresponding estimate for high-liquidity winners of large prizes (USD8,300-150,000) is slightly below one half. While conventional models will struggle toaccount for such high MPC levels, we show that a two-asset life-cycle model with arealistic earnings profile and a luxury bequest motive can account for both the timeprofile of consumption responses and their systematic co-variation with observables.
description: Households in Norway.
DOI: 10.25380/iastate.12645600
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2016

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2016 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645569
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2016

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2016 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645528
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2015

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2015 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645482
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2015

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2015 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645452
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2014

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2014 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645399
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2014

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2014 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645380
title: A seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2013

description: This seamless 1 km resolution global nighttime (1:30 AM) land surface temperature dataset in 2013 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.25380/iastate.12645365
title: A seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2013

description: This seamless 1 km resolution global daytime (1:30 PM) land surface temperature dataset in 2013 was generated from Moderate-resolution Imaging Spectroradiometer (MODIS) LST products (MOD11A1 and MYD11A1), using a spatiotemporal gap-filling algorithm. The seamless LST dataset is of great use in global studies of urban, climate, and ecosystems.
DOI: 10.48331/scielo.kdpo6m/5hr1fk
title: 1982-2170-bcg-27-spe-e2021020-gf4.jpg

description: :unav
DOI: 10.48331/scielo.kdpo6m/dodfdi
title: 1982-2170-bcg-27-spe-e2021020.pdf

description: :unav
DOI: 10.48331/scielo.kdpo6m/bf0osb
title: 1982-2170-bcg-27-spe-e2021020-gf8.jpg

description: :unav
DOI: 10.48331/scielo.kdpo6m/hg0qoq
title: 1982-2170-bcg-27-spe-e2021020-gf1.jpg

description: :unav
DOI: 10.48331/scielo.kdpo6m/uohqkr
title: 1982-2170-bcg-27-spe-e2021020-gf5.jpg

description: :unav
DOI: 10.48331/scielo.kdpo6m/hthl5h
title: 1982-2170-bcg-27-spe-e2021020-gf9.jpg

description: :unav
DOI: 10.48331/scielo.kdpo6m/6gk2ar
title: 1982-2170-bcg-27-spe-e2021020-gf7.png

description: :unav
DOI: 10.48331/scielo.kdpo6m/rvuda3
title: 1982-2170-bcg-27-spe-e2021020-gf3.jpg

description: :unav
DOI: 10.48331/scielo.kdpo6m/68pzqn
title: 1982-2170-bcg-27-spe-e2021020-gf10.jpg

description: :unav
DOI: 10.48331/scielo.kdpo6m/7rkf5u
title: 1982-2170-bcg-27-spe-e2021020-gf6.jpg

description: :unav
DOI: 10.48331/scielo.kdpo6m/w2ohxl
title: 1982-2170-bcg-27-spe-e2021020.xml

description: :unav
DOI: 10.48331/scielo.kdpo6m/6pxa6j
title: 1982-2170-bcg-27-spe-e2021020-gf2.png

description: :unav
DOI: 10.48331/scielo.kdpo6m/beyeqt
title: 1982-2170-bcg-27-spe-e2021020-gf11.jpg

description: :unav
DOI: 10.48331/scielo.kdpo6m/k0exyv
title: 1982-2170-bcg-27-spe-e2021020.xml

description: :unav
DOI: 10.48331/scielo.kdpo6m
title: THE INFLUENCE OF THE DEFLECTION OF THE VERTICAL ON GEODETIC SURVEYS IN BRAZIL

description: A influência da deflexão da vertical nas pesquisas geodéticas no Brasil