cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e135321
title: Data and Code for: Family Heterogeneity, Human Capital Investment, and College Attainment

description: From 1995 to 2015, the aggregate college completion rate in the US increased almost 50%. Yet, completion trends differed markedly for individuals from different family backgrounds. This paper considers the extent to which trends in college preparedness contributed to the growth in aggregate completion, as well as the variation in completion trends across family backgrounds. We first document parallel empirical patterns in pre-college investments, college preparedness, and college completion. We then evaluate the quantitative importance of pre-college investments and preparedness for completion trends in a structural model of intergenerational human capital investment with heterogeneous families. Within our model, the human capital investment channel generates half of the empirical increase in college completion, while the changing composition of family types generates about one-fourth of the increase. In policy experiments, we find that subsidizing pre-college investment for low resource families has a larger impact on college completion and lifetime earnings compared to alternative interventions like tuition subsidies or cash transfers.
DOI: 10.3886/e135321v1
title: Data and Code for: Family Heterogeneity, Human Capital Investment, and College Attainment

description: From 1995 to 2015, the aggregate college completion rate in the US increased almost 50%. Yet, completion trends differed markedly for individuals from different family backgrounds. This paper considers the extent to which trends in college preparedness contributed to the growth in aggregate completion, as well as the variation in completion trends across family backgrounds. We first document parallel empirical patterns in pre-college investments, college preparedness, and college completion. We then evaluate the quantitative importance of pre-college investments and preparedness for completion trends in a structural model of intergenerational human capital investment with heterogeneous families. Within our model, the human capital investment channel generates half of the empirical increase in college completion, while the changing composition of family types generates about one-fourth of the increase. In policy experiments, we find that subsidizing pre-college investment for low resource families has a larger impact on college completion and lifetime earnings compared to alternative interventions like tuition subsidies or cash transfers.
DOI: 10.6073/pasta/9554230a00a81382c898a64b45c13251
title: Arbuscular mycorrhizal fungal response to fire and urbanization in the Great Smoky Mountains National Park

description: Wildfires are increasing in frequency and intensity as drier and warmer climates increase plant detrital fuel loads. At the same time, increases in urbanization position 9% of fire-prone land within the US at the wildland-urban interface. While rarely studied, the compounded effects of urbanization and wildfires may have unknown synergistically negative effects on ecosystems. Previous studies at the wildland-urban interface often focus on aboveground plant communities, but belowground ecosystems may also be affected by this double disturbance. In particular, it is unclear how much fire and urbanization independently or interactively affect nutritional symbioses such as those between arbuscular mycorrhizal (AM) fungi and the majority of terrestrial plants. In November 2016, extreme drought conditions and long-term fire suppression combined to create a wildfire within the Great Smoky Mountains National Park (GSMNP) and the neighboring exurban city of Gatlinburg, TN. To understand how the double disturbance of urbanization and fire affected AM fungal communities, we collected fine roots from the five dominant understory species in September 2018 at each of 18 sites spanning three burn severities in both exurban and natural sites. Despite large variation in burn severity, plant species identity had the largest influence on AM fungi. AM fungal colonization, richness, and composition all varied most among plant species. Fire and urbanization did influence some AM fungal metrics; colonization was lower in burned sites and composition was more variable among exurban locations. There were no interactions among burn severity and urbanization on AM fungi. Our results point to the large influence of plant species identity structuring this obligate nutritional symbiosis regardless of disturbance regime. Therefore, the majority of AM fungal taxa may be buffered from fire-induced ecosystem changes if plant community composition largely remains intact, plant species life history traits allow for AM fungal persistence after fire disturbance, and/or nearby undisturbed habitat can act as an inoculum source for recolonization following fires. Thus, it is critical to maintain natural, undisturbed habitats interspersed within the wildland-urban interface.
DOI: 10.5281/zenodo.5577180
title: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X

description: This dataset contains a recording of X-band telemetry downlink from the Lucy spacecraft done on 2021-10-17,about 24 hours after launch. The recording was done at Allen Telescope Array using antenna 2e in dual XY (linear) polarization. The hardware configuration was as follows: antenna 2e was connected to RFCB LO d, which was tuned to a frequency of 8445.6 MHz and used an output IF of 512 MHz. A USRP N321 was connected to the IF output of the RFCB and digitized both polarizations. The USRP used external 10 MHz reference and PPS coming from the observatory distribution system. The IQ sample rate of the USRP was 1.92 Msps and a GNU Radio flowgraph was used to record IQ data to disk. The GNU Radio flowgraph stored the IQ data for each channel as 16-bin integers in the GNU Radio metatata file format, with detached headers. The complete recording was split in two parts to keep the file size below 50 GB. After this, the data was converted to SigMF format. This dataset contains part 1, polarization X. These are the datasets in this collection: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y
DOI: 10.5281/zenodo.5579165
title: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y

description: This dataset contains a recording of X-band telemetry downlink from the Lucy spacecraft done on 2021-10-17,about 24 hours after launch. The recording was done at Allen Telescope Array using antenna 2e in dual XY (linear) polarization. The hardware configuration was as follows: antenna 2e was connected to RFCB LO d, which was tuned to a frequency of 8445.6 MHz and used an output IF of 512 MHz. A USRP N321 was connected to the IF output of the RFCB and digitized both polarizations. The USRP used external 10 MHz reference and PPS coming from the observatory distribution system. The IQ sample rate of the USRP was 1.92 Msps and a GNU Radio flowgraph was used to record IQ data to disk. The GNU Radio flowgraph stored the IQ data for each channel as 16-bin integers in the GNU Radio metatata file format, with detached headers. The complete recording was split in two parts to keep the file size below 50 GB. After this, the data was converted to SigMF format. This dataset contains part 1, polarization X. These are the datasets in this collection: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y
DOI: 10.5281/zenodo.5577179
title: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X

description: This dataset contains a recording of X-band telemetry downlink from the Lucy spacecraft done on 2021-10-17,about 24 hours after launch. The recording was done at Allen Telescope Array using antenna 2e in dual XY (linear) polarization. The hardware configuration was as follows: antenna 2e was connected to RFCB LO d, which was tuned to a frequency of 8445.6 MHz and used an output IF of 512 MHz. A USRP N321 was connected to the IF output of the RFCB and digitized both polarizations. The USRP used external 10 MHz reference and PPS coming from the observatory distribution system. The IQ sample rate of the USRP was 1.92 Msps and a GNU Radio flowgraph was used to record IQ data to disk. The GNU Radio flowgraph stored the IQ data for each channel as 16-bin integers in the GNU Radio metatata file format, with detached headers. The complete recording was split in two parts to keep the file size below 50 GB. After this, the data was converted to SigMF format. This dataset contains part 1, polarization X. These are the datasets in this collection: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y
DOI: 10.5281/zenodo.5579164
title: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y

description: This dataset contains a recording of X-band telemetry downlink from the Lucy spacecraft done on 2021-10-17,about 24 hours after launch. The recording was done at Allen Telescope Array using antenna 2e in dual XY (linear) polarization. The hardware configuration was as follows: antenna 2e was connected to RFCB LO d, which was tuned to a frequency of 8445.6 MHz and used an output IF of 512 MHz. A USRP N321 was connected to the IF output of the RFCB and digitized both polarizations. The USRP used external 10 MHz reference and PPS coming from the observatory distribution system. The IQ sample rate of the USRP was 1.92 Msps and a GNU Radio flowgraph was used to record IQ data to disk. The GNU Radio flowgraph stored the IQ data for each channel as 16-bin integers in the GNU Radio metatata file format, with detached headers. The complete recording was split in two parts to keep the file size below 50 GB. After this, the data was converted to SigMF format. This dataset contains part 1, polarization X. These are the datasets in this collection: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y
DOI: 10.5281/zenodo.5582218
title: Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X

description: This dataset contains a recording of X-band telemetry downlink from the Lucy spacecraft done on 2021-10-17,about 24 hours after launch. The recording was done at Allen Telescope Array using antenna 2e in dual XY (linear) polarization. The hardware configuration was as follows: antenna 2e was connected to RFCB LO d, which was tuned to a frequency of 8445.6 MHz and used an output IF of 512 MHz. A USRP N321 was connected to the IF output of the RFCB and digitized both polarizations. The USRP used external 10 MHz reference and PPS coming from the observatory distribution system. The IQ sample rate of the USRP was 1.92 Msps and a GNU Radio flowgraph was used to record IQ data to disk. The GNU Radio flowgraph stored the IQ data for each channel as 16-bin integers in the GNU Radio metatata file format, with detached headers. The complete recording was split in two parts to keep the file size below 50 GB. After this, the data was converted to SigMF format. This dataset contains part 1, polarization X. These are the datasets in this collection: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y
DOI: 10.5281/zenodo.5585389
title: Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y

description: This dataset contains a recording of X-band telemetry downlink from the Lucy spacecraft done on 2021-10-17,about 24 hours after launch. The recording was done at Allen Telescope Array using antenna 2e in dual XY (linear) polarization. The hardware configuration was as follows: antenna 2e was connected to RFCB LO d, which was tuned to a frequency of 8445.6 MHz and used an output IF of 512 MHz. A USRP N321 was connected to the IF output of the RFCB and digitized both polarizations. The USRP used external 10 MHz reference and PPS coming from the observatory distribution system. The IQ sample rate of the USRP was 1.92 Msps and a GNU Radio flowgraph was used to record IQ data to disk. The GNU Radio flowgraph stored the IQ data for each channel as 16-bin integers in the GNU Radio metatata file format, with detached headers. The complete recording was split in two parts to keep the file size below 50 GB. After this, the data was converted to SigMF format. This dataset contains part 1, polarization X. These are the datasets in this collection: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y
DOI: 10.5281/zenodo.5582217
title: Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X

description: This dataset contains a recording of X-band telemetry downlink from the Lucy spacecraft done on 2021-10-17,about 24 hours after launch. The recording was done at Allen Telescope Array using antenna 2e in dual XY (linear) polarization. The hardware configuration was as follows: antenna 2e was connected to RFCB LO d, which was tuned to a frequency of 8445.6 MHz and used an output IF of 512 MHz. A USRP N321 was connected to the IF output of the RFCB and digitized both polarizations. The USRP used external 10 MHz reference and PPS coming from the observatory distribution system. The IQ sample rate of the USRP was 1.92 Msps and a GNU Radio flowgraph was used to record IQ data to disk. The GNU Radio flowgraph stored the IQ data for each channel as 16-bin integers in the GNU Radio metatata file format, with detached headers. The complete recording was split in two parts to keep the file size below 50 GB. After this, the data was converted to SigMF format. This dataset contains part 1, polarization X. These are the datasets in this collection: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y
DOI: 10.5281/zenodo.5585388
title: Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y

description: This dataset contains a recording of X-band telemetry downlink from the Lucy spacecraft done on 2021-10-17,about 24 hours after launch. The recording was done at Allen Telescope Array using antenna 2e in dual XY (linear) polarization. The hardware configuration was as follows: antenna 2e was connected to RFCB LO d, which was tuned to a frequency of 8445.6 MHz and used an output IF of 512 MHz. A USRP N321 was connected to the IF output of the RFCB and digitized both polarizations. The USRP used external 10 MHz reference and PPS coming from the observatory distribution system. The IQ sample rate of the USRP was 1.92 Msps and a GNU Radio flowgraph was used to record IQ data to disk. The GNU Radio flowgraph stored the IQ data for each channel as 16-bin integers in the GNU Radio metatata file format, with detached headers. The complete recording was split in two parts to keep the file size below 50 GB. After this, the data was converted to SigMF format. This dataset contains part 1, polarization X. These are the datasets in this collection: Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 1/2, polarization Y Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization X Lucy recording with Allen Telescope Array on 2021-10-17: part 2/2, polarization Y
DOI: 10.5281/zenodo.5582576
title: Dry matter databases derived by crossing burned areas databases with above ground estimations from SMOS sensor

description: Estimates of the the fuel consumed during a fire (dry-matter, DM) is derived by combining burned areas (from two different fire inventories) with above ground biomass (derived from SMOS L Band Vegetation Optical Depth). Six new datasets are provided on a 25 km grid for the years 2010-2017. The portion of vegetation that is consumed during biomass burning is expressed as:<br> <strong>\(DM= AGB * BA*\beta\)</strong> where BA is the burned area; AGB is the fuel load, the amount of biomass or organic matter an ecosystem contains per unit area; \(\beta\) is the combustion completeness or burning efficiency, which is the fraction of fuel actually consumed during the fire. Monthly maps of AGB are converted from SMOS L-band vegetation optical depth (VOD) through an algorithm described in [1] and obtained looking at the relationship between three static AGB benchmark maps from the works of [2],[3] and [4]. Each static map provide three L-VOD to AGB conversion curves fitting the 5th, 50th and 95th percentiles of the data using a logistic regression([1]) In the following, the three different databases are named AGB-BA (Baccini), AGB-SA (Saatchi) and AGB-AV (Avitabile) Monthly total of burned areas are available from two sources. The first one, called hereinafter BA-GFED, is available though GEFD4.1s [5] and is based on MODIS MCD64A1 product. It has a 500m pixel resolution and is also available on a regular grid of 0.25 deg. The second BA product, named hereinafter BA-CCI, is a multi-sensors product provided by the European Space Agency Climate Change Initiative (ESA-CCI) [6] We use version FireCCI5.1 which is calculated using a two-phase algorithm, where MODIS active fire locations are used to identify seed pixels corresponding to high confidence burned areas. These areas are then grown using Medium Resolution Imaging Spectrometer (MERIS) vegetation input data. Combustion completeness, is a taken from table 4 of [7]. By selectively combining any AGB estimations with the two available BA datasets, a total of 6 products are generated. <strong>References </strong> [1] https://doi.org/10.5194/bg-15-4627-2018 [2] DOI: 10.1126/science.aam5962 [3]https://cce.nasa.gov/veg3dbiomass/saatchi_tgrs07.pdf [4] https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.13139 [5] https://daac.ornl.gov/VEGETATION/guides/fire_emissions_v4_R1.html [6] https://geogra.uah.es/fire_cci/firecci51.php [7] https://acp.copernicus.org/articles/6/3423/2006/acp-6-3423-2006.pdf
description: A full description of the dataset an an exemple of application can be found in DiGiuseppe et al A global bottom-up approach to estimate fuel consumed by fires using above ground biomass observations, GRL, 2020
DOI: 10.5281/zenodo.5582575
title: Dry matter databases derived by crossing burned areas databases with above ground estimations from SMOS sensor

description: Estimates of the the fuel consumed during a fire (dry-matter, DM) is derived by combining burned areas (from two different fire inventories) with above ground biomass (derived from SMOS L Band Vegetation Optical Depth). Six new datasets are provided on a 25 km grid for the years 2010-2017. The portion of vegetation that is consumed during biomass burning is expressed as:<br> <strong>\(DM= AGB * BA*\beta\)</strong> where BA is the burned area; AGB is the fuel load, the amount of biomass or organic matter an ecosystem contains per unit area; \(\beta\) is the combustion completeness or burning efficiency, which is the fraction of fuel actually consumed during the fire. Monthly maps of AGB are converted from SMOS L-band vegetation optical depth (VOD) through an algorithm described in [1] and obtained looking at the relationship between three static AGB benchmark maps from the works of [2],[3] and [4]. Each static map provide three L-VOD to AGB conversion curves fitting the 5th, 50th and 95th percentiles of the data using a logistic regression([1]) In the following, the three different databases are named AGB-BA (Baccini), AGB-SA (Saatchi) and AGB-AV (Avitabile) Monthly total of burned areas are available from two sources. The first one, called hereinafter BA-GFED, is available though GEFD4.1s [5] and is based on MODIS MCD64A1 product. It has a 500m pixel resolution and is also available on a regular grid of 0.25 deg. The second BA product, named hereinafter BA-CCI, is a multi-sensors product provided by the European Space Agency Climate Change Initiative (ESA-CCI) [6] We use version FireCCI5.1 which is calculated using a two-phase algorithm, where MODIS active fire locations are used to identify seed pixels corresponding to high confidence burned areas. These areas are then grown using Medium Resolution Imaging Spectrometer (MERIS) vegetation input data. Combustion completeness, is a taken from table 4 of [7]. By selectively combining any AGB estimations with the two available BA datasets, a total of 6 products are generated. <strong>References </strong> [1] https://doi.org/10.5194/bg-15-4627-2018 [2] DOI: 10.1126/science.aam5962 [3]https://cce.nasa.gov/veg3dbiomass/saatchi_tgrs07.pdf [4] https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.13139 [5] https://daac.ornl.gov/VEGETATION/guides/fire_emissions_v4_R1.html [6] https://geogra.uah.es/fire_cci/firecci51.php [7] https://acp.copernicus.org/articles/6/3423/2006/acp-6-3423-2006.pdf
description: A full description of the dataset an an exemple of application can be found in DiGiuseppe et al A global bottom-up approach to estimate fuel consumed by fires using above ground biomass observations, GRL, 2020
DOI: 10.6084/m9.figshare.16840240.v1
title: Dataset PRT paper

description: This data set was used for the paper entitled "Effect of speed on the proportional reading time: Re-analyzing subtitle reading data with mixed effects models."
DOI: 10.6084/m9.figshare.16840240
title: Dataset PRT paper

description: This data set was used for the paper entitled "Effect of speed on the proportional reading time: Re-analyzing subtitle reading data with mixed effects models."
DOI: 10.5281/zenodo.5585986
title: Cardiovascular contributions and energetic costs of thermoregulation in ectothermic vertebrates

description: Unfiltered data used in the manuscript with file descriptions. Includes R script and example datasets for reproducing figure 1, as well as animating figure 1 for the box turtle and painted turtle (body temperature - black solid line, ambient temperature - black dotted line, and heart rate - red solid line).
DOI: 10.5281/zenodo.4579861
title: Cardiovascular contributions and energetic costs of thermoregulation in ectothermic vertebrates

description: Unfiltered data used in the manuscript with file descriptions. Includes R script and example datasets for reproducing figure 1, as well as animating figure 1 for the box turtle and painted turtle (body temperature - black solid line, ambient temperature - black dotted line, and heart rate - red solid line).