cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25452/figshare.plus.23564517.v2
title: <b><i>Glo3DHydroClimEventSet(v1.0)</i></b>: A global-scale event set of hydroclimatic extremes from 3D perspective (1951—2022)

description: The <b><i>Glo3DHydroClimEventSet(v1.0)</i></b> is a 1950-2022 comprehensive and unified event-based set of multi-scale and multi-threshold heatwaves, cold surges, droughts, and extreme precipitation, generated with a 3D DBSCAN-based model by Dr. Zhenchen Liu and Prof. Wen Zhou @Fudan University, China. The event set consists of three parts as follows:<br>i) event sets are stored in four kinds of <i>zip-format</i> files prefixed with "<i>ExtremePreci_</i>", "<i>Cold_</i>", "<i>Heat_</i>", and "<i>Drought_</i>";<br>ii) Typical Examples for valications are provided as "<i>TechValidation_Example_Animations_Table5.zip</i>" and "<i>TechValidation_Example_Files_Table5.zip</i>";<br>iii) Codes for selection of events located within target areas during the target periods are also provided, entitled as "Codes_SciData_LiuZhou2023.zip"<br>In addition, the decompressed sizes of all the zip-format files of event sets are as follows:(1/9): Global-scale SA-based cold surge event set. The total size of decompressed files are 282GB.(2/9): Global-scale percentile-based cold surge event set. The total size of decompressed files is 96GB.(3/9): Global-scale SA-based extreme precipitation event set based on five-day-accumulated precipitation. The total size of decompressed files is 1.01TB.(4/9): Global-scale SA-based extreme precipitation event set based on daily total precipitation. The total size of decompressed files is 301GB.(5/9): Global-scale percentile-based extreme precipitation event set based on daily total precipitation. The total size of decompressed files is 72GB.(6/9): Global-scale percentile-based extreme precipitation event set based on five-day-accumulated total precipitation. The total size of decompressed files is 284GB.(7/9): Global-scale SA-based heatwave event set on daily scale. The total size of decompressed files is 205GB.(8/9): Global-scale percentile-based heatwave event set. The total size of decompressed files is 34.7GB.(9/9): Global-scale SA-based meteorological drought event set. The total size of decompressed files are 147GB.<br>
DOI: 10.6084/m9.figshare.24562414
title: Cross-Comparison of Observations with the Predictions of Global Hybrid Simulations for Multiple IMF Discontinuities Impacting the Bow shock and Magnetosheath

description: We use the three-dimensional (3-D) global hybrid code ANGIE3D to simulate the interaction of four solar wind tangential discontinuities (TDs) observed by ARTEMIS P1 from 0740 UT to 0800 UT on 28 December 2019 with the bow shock, magnetosheath, and magnetosphere. We demonstrate how the four discontinuities produce foreshock transients, a magnetosheath cavity-like structure, and a brief magnetopause crossing observed by THEMIS and MMS spacecraft from 0800 UT to 0830 UT.
DOI: 10.6084/m9.figshare.24562414.v1
title: Cross-Comparison of Observations with the Predictions of Global Hybrid Simulations for Multiple IMF Discontinuities Impacting the Bow shock and Magnetosheath

description: We use the three-dimensional (3-D) global hybrid code ANGIE3D to simulate the interaction of four solar wind tangential discontinuities (TDs) observed by ARTEMIS P1 from 0740 UT to 0800 UT on 28 December 2019 with the bow shock, magnetosheath, and magnetosphere. We demonstrate how the four discontinuities produce foreshock transients, a magnetosheath cavity-like structure, and a brief magnetopause crossing observed by THEMIS and MMS spacecraft from 0800 UT to 0830 UT.
DOI: 10.6084/m9.figshare.24201318
title: A Regression-Based Approach to Robust Estimation and Inference for Genetic Covariance

description: Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits, and some variants are shown to be associated with multiple complex traits. Genetic covariance between two traits is defined as the underlying covariance of genetic effects and can be used to measure the shared genetic architecture. The data used to estimate such a genetic covariance can be from the same group or different groups of individuals, and the traits can be of different types or collected based on different study designs. This article proposes a unified regression-based approach to robust estimation and inference for genetic covariance of general traits that may be associated with genetic variants nonlinearly. The asymptotic properties of the proposed estimator are provided and are shown to be robust under certain model misspecification. Our method under linear working models provides a robust inference for the narrow-sense genetic covariance, even when both linear models are mis-specified. Numerical experiments are performed to support the theoretical results. Our method is applied to an outbred mice GWAS dataset to study the overlapping genetic effects between the behavioral and physiological phenotypes. The real data results reveal interesting genetic covariance among different mice developmental traits. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24201318.v2
title: A Regression-Based Approach to Robust Estimation and Inference for Genetic Covariance

description: Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits, and some variants are shown to be associated with multiple complex traits. Genetic covariance between two traits is defined as the underlying covariance of genetic effects and can be used to measure the shared genetic architecture. The data used to estimate such a genetic covariance can be from the same group or different groups of individuals, and the traits can be of different types or collected based on different study designs. This article proposes a unified regression-based approach to robust estimation and inference for genetic covariance of general traits that may be associated with genetic variants nonlinearly. The asymptotic properties of the proposed estimator are provided and are shown to be robust under certain model misspecification. Our method under linear working models provides a robust inference for the narrow-sense genetic covariance, even when both linear models are mis-specified. Numerical experiments are performed to support the theoretical results. Our method is applied to an outbred mice GWAS dataset to study the overlapping genetic effects between the behavioral and physiological phenotypes. The real data results reveal interesting genetic covariance among different mice developmental traits. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24201318.v1
title: A Regression-based Approach to Robust Estimation and Inference for Genetic Covariance

description: Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits, and some variants are shown to be associated with multiple complex traits. Genetic covariance between two traits is defined as the underlying covariance of genetic effects and can be used to measure the shared genetic architecture. The data used to estimate such a genetic covariance can be from the same group or different groups of individuals, and the traits can be of different types or collected based on different study designs. This paper proposes a unified regression-based approach to robust estimation and inference for genetic covariance of general traits that may be associated with genetic variants nonlinearly. The asymptotic properties of the proposed estimator are provided and are shown to be robust under certain model mis-specification. Our method under linear working models provides a robust inference for the narrow-sense genetic covariance, even when both linear models are mis-specified. Numerical experiments are performed to support the theoretical results. Our method is applied to an outbred mice GWAS data set to study the overlapping genetic effects between the behavioral and physiological phenotypes. The real data results reveal interesting genetic covariance among different mice developmental traits.
DOI: 10.34740/kaggle/dsv/6968691
title: Gun Deaths in America
DOI: 10.5066/p9fx3nn9
title: Geologic map of the Rumker Quadrangle of the Moon

description: The Rumker quadrangle, in the northwest quadrant of the Moon, is adjacent to the western rim of the multi-ring Imbrium basin and to Sinus Iridum, a large (220 km diameter) mare-filled crater. Both of these great depressions were probably formed by impact, as indicated here and elsewhere on the Moon by the characteristic form, distribution, and texture of surrounding materials and structures. The Imbrium basin and Iridum crater were filled by mare materials during the Imbrain and Eratosthenian Periods. In this quadrangle, the widespread ejecta blanket of the Imbrium basin, as well as the basin’s concentric ridges and mountain rings, has largely been buried by terra materials of mixed origin and by ejecta from Iridum and numerous smaller impact craters. These materials, together with some terra units of probable volcanic origin, make up the highland terrain. Mare materials of Oceanus Procellarum cover part of this westward-sloping highland shelf that separate it from the Rumker Hills, an isolated plateau surrounded by the mare. No visible discontinuity distinguishes mare material of Oceanus Procellarum from those in the Imbrium basin, both of which contain several units having similar albedo and color. Parts of the mare are very dark and smooth and appear relatively young, and parts of the terra contain many diverse landforms of Imbrian and younger age that appear to be volcanic. This region may therefore have been more active internally during late stages of lunar history than many others on the near side.
DOI: 10.48432/ktq70a
title: LiDAR survey on 334.97 hectares in Jamari, Rondônia, Brasil in 2014.

description: The LiDAR data Floresta Nacional do Jamari (JAM_A05_2014_LiDAR) refers to the survey carried out in Jamari National Forest, Rondonia state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/pqnfaa
title: LiDAR survey on 399.98 hectares in Jamari, Rondônia, Brasil in 2014.

description: The LiDAR data Floresta Nacional do Jamari (JAM_A06_2014_LiDAR) refers to the survey carried out in Jamari National Forest, Rondonia state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.5066/p9bfjrq0
title: Geologic map of the Purbach Quadrangle of the Moon

description: The Purbach quadrangle is in the south central part of the lunar near side and includes the following four distinct topographic geologic provinces: 1) rugged and densely cratered highlands extending north south through the central part of the area locally dissected by large troughs (sculpture) of Imbrium age (Gilbert, 1893; Hartmann, 1963) 2) subdued terrain in the east where both isolated and interconnected topographic lows are partly filled with plains material 3) terra and plains materials of low relief in the southwest which obscure the large ancient crater Deslandres; 4) basalt flows of Mare Numbium which embay and overlap the adjacent terrae along the west central and northwestern parts of the quadrangle.
DOI: 10.48432/so0sib
title: LiDAR survey on 224.99 hectares in Jamari, Rondônia, Brasil in 2015

description: The LiDAR data Floresta Nacional do Jamari (JAM_A06_2015_LiDAR) refers to the survey carried out in Jamari National Forest, Rondônia state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/v0pofn
title: LiDAR survey on 249.9 hectares in Jamari, Rondônia, Brasil in 2015

description: The LiDAR data Floresta Nacional do Jamari (JAM_A07_2015_LiDAR) refers to the survey carried out in Jamari National Forest, Rondônia state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.5281/zenodo.10126148
title: Data for Development and Evaluation of a North America Ensemble Wildfire Air Quality Forecast: Initial Application to the 2020 Western United States "Gigafire"
DOI: 10.5281/zenodo.10126149
title: Data for Development and Evaluation of a North America Ensemble Wildfire Air Quality Forecast: Initial Application to the 2020 Western United States "Gigafire"
DOI: 10.48432/z4jstn
title: LiDAR survey on 224.99 hectares in Jamari, Rondônia, Brasil in 2015

description: The LiDAR data Floresta Nacional do Jamari (JAM_A08_2015_LiDAR) refers to the survey carried out in Jamari National Forest, Rondonia state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/stkpkv
title: LiDAR survey on 302.09 hectares in Jacundá, Rondônia, Brasil in 2015.

description: The LiDAR data Floresta Nacional de Jacundá (JAC_A01_2015_LiDAR) refers to the survey carried out in Jacundá National Forest, Rondônia State, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.5281/zenodo.8021180
title: Comparison of wind tunnel and bLS measurement of ammona volatilization from field-applied slurry

description: Data and analysis on wind tunnel and bLS measurement of ammonia volatilization from field-applied slurry
DOI: 10.6084/m9.figshare.24548443
title: Mouse_ovaries_highres_images

description: Zip folder containing images (TIFF files) of Hematoxylin & Eosin stained tissue sections from untreated and hormone treated ovaries of immature mice. These images represent tissues that were used for high-resolution spatial transcriptomics experiment using Curio Seeker technology.
DOI: 10.48432/92vjbe
title: LiDAR survey on 235.7 hectares in Jacundá, Rondônia, Brasil in 2015.

description: The LiDAR data Floresta Nacional de Jacundá (JAC_A02_2015_LiDAR) refers to the survey carried out in Jacundá National Forest, Rondônia State, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/aht6ox
title: LiDAR survey on 217.93 hectares in Jacundá, Rondônia, Brasil in 2015.

description: The LiDAR data Floresta Nacional de Jacundá (JAC_A03_2015_LiDAR) refers to the survey carried out in Jacundá National Forest, Rondônia State, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/hxto2n
title: LiDAR survey on 349.99 hectares in Jacundá, Rondônia, Brasil in 2015.

description: The LiDAR data Floresta Nacional de Jacundá (JAC_A04_2015_LiDAR) refers to the survey carried out in Jacundá National Forest, Rondônia State, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/iywxpn
title: LiDAR survey on 349.99 hectares in Jacundá, Rondônia, Brasil in 2015

description: The LiDAR data Floresta Nacional de Jacundá (JAC_A05_2015_LiDAR) refers to the survey carried out in Jacundá National Forest, Rondônia State, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa)has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/8po8gk
title: LiDAR survey on 1214 hectares in Cauaxi, Paragomina, Pará, Brasil in 2012.

description: The LiDAR data Fazenda Cauaxi (CAU_A01_2012_LiDAR) refers to the survey carried out in Paragominas municipality, Pará state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/jofwhr
title: LiDAR survey on 1216 hectares in Cauaxi, Paragomina, Pará, Brasil in 2014.

description: The LiDAR data Fazenda Cauaxi (CAU_A01_2014_LiDAR) refers to the survey carried out in Paragominas municipality, Pará state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."