cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7519682
title: EMERGE 2016 Autochamber Sites NMR

description: METHODS:To follow bio-available metabolites, we used NMR on the water extracted supernatant samples. Supernatant samples (180 µL) were combined with 2,2-dimethyl-2-silapentane-5-sulfonate-d6 (DSS-d6) in D2O (20 µL, 5 mM) and thoroughly mixed prior to transfer to 3 mm NMR tubes. NMR spectra were acquired on a Bruker Neo spectrometer operating at 18.8T (1H ν0 of 800.30 MHz) equipped with a 5mm Bruker TCI/CP HCN (inverse) cryoprobe with Z-gradient.at a regulated temperature of 298.0 K. The 90° 1H pulse was calibrated prior to the measurement of each sample. The one-dimensional 1H spectra were acquired using a nuclear Overhauser effect spectroscopy (noesypr1d) pulse sequence with a spectral width of 20.1 ppm and 2048 transients. The NOESY mixing time was 100ms and the acquisition time was 4s followed by a relaxation delay of 1.5 s during which presaturation of the water signal was applied. The 1D 1H spectra were manually processed, assigned metabolite identifications and quantified using Chenomx NMR Suite 9.0. Time domain free induction decays (65536 total points) were zero filled to 131072 total points prior to Fourier transform, followed by exponential multiplication (0.3 Hz line-broadening), and semi-automatic multipoint smooth segments baseline correction. Chemical shifts were referenced to the 1H methyl signal in DSS-d6 at 0 ppm. Metabolite identification was based on matching the chemical shift, J-coupling and intensity of experimental signals to compound signals in the Chenomx, HMDB and custom in-house databases (Supplementary Data X). Quantification was based on fitted metabolite signals relative to the internal standard (DSS-d6). Signal to noise ratios (S/N) were checked using MestReNova 14.1 with the limit of quantification equal to a S/N of 10 and the limit of detection equal to a S/N of 3.FUNDING:This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070.We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164.This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0010580 and DE-SC0016440. A portion of this research was performed under the Facilities Integrating Collaborations for User Science (FICUS) exploratory effort and used resources at the Environmental Molecular Sciences Laboratory (proposal ID 51858), which are DOE Office of Science User Facilities. A portion of the research has been performed using EMSL (grid.436923.9), a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research.
DOI: 10.5281/zenodo.7519683
title: EMERGE 2016 Autochamber Sites NMR

description: METHODS:To follow bio-available metabolites, we used NMR on the water extracted supernatant samples. Supernatant samples (180 µL) were combined with 2,2-dimethyl-2-silapentane-5-sulfonate-d6 (DSS-d6) in D2O (20 µL, 5 mM) and thoroughly mixed prior to transfer to 3 mm NMR tubes. NMR spectra were acquired on a Bruker Neo spectrometer operating at 18.8T (1H ν0 of 800.30 MHz) equipped with a 5mm Bruker TCI/CP HCN (inverse) cryoprobe with Z-gradient.at a regulated temperature of 298.0 K. The 90° 1H pulse was calibrated prior to the measurement of each sample. The one-dimensional 1H spectra were acquired using a nuclear Overhauser effect spectroscopy (noesypr1d) pulse sequence with a spectral width of 20.1 ppm and 2048 transients. The NOESY mixing time was 100ms and the acquisition time was 4s followed by a relaxation delay of 1.5 s during which presaturation of the water signal was applied. The 1D 1H spectra were manually processed, assigned metabolite identifications and quantified using Chenomx NMR Suite 9.0. Time domain free induction decays (65536 total points) were zero filled to 131072 total points prior to Fourier transform, followed by exponential multiplication (0.3 Hz line-broadening), and semi-automatic multipoint smooth segments baseline correction. Chemical shifts were referenced to the 1H methyl signal in DSS-d6 at 0 ppm. Metabolite identification was based on matching the chemical shift, J-coupling and intensity of experimental signals to compound signals in the Chenomx, HMDB and custom in-house databases (Supplementary Data X). Quantification was based on fitted metabolite signals relative to the internal standard (DSS-d6). Signal to noise ratios (S/N) were checked using MestReNova 14.1 with the limit of quantification equal to a S/N of 10 and the limit of detection equal to a S/N of 3.FUNDING:This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070.We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164.This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0010580 and DE-SC0016440. A portion of this research was performed under the Facilities Integrating Collaborations for User Science (FICUS) exploratory effort and used resources at the Environmental Molecular Sciences Laboratory (proposal ID 51858), which are DOE Office of Science User Facilities. A portion of the research has been performed using EMSL (grid.436923.9), a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research.
DOI: 10.18739/a2z31nq6f
title: Multispectral Orthomosaic Image for the South Fork Serpentine River Beaver Dams and Ponds, Seward Peninsula, Alaska, 15 August 2022

description: Emergence of beavers as ecosystem engineers in the New Arctic project focuses on establishing field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost. Drones are being used to collect baseline data and track beaver dam building and pond evolution over time. This dataset consists of a multispectral orthomosaic derived from drone surveys on 15 August 2022 at the South Fork Serpentine River site on the Seward Peninsula, Alaska. 3,654 digital images from five spectral bands were acquired from a DJI Phantom 4 Real-Time Kinematic (DJI P4RTK) quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 86 hectares (ha). The drone system was flown at 120 meters (m) above ground level (agl) and images were captured using the hover and capture at point mode. The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.7.5) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the multispectral orthophoto mosaic at a spatial resolution of 10 centimeters (cm). Images of a MicaSense calibrated reflectance panel were used for radiometric processing and calibration of each spectral band in the Index Calculator in Pix4D. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 3 North.
DOI: 10.18739/a2tb0xx29
title: Orthomosaic Image and Digital Surface Model for the South Fork Serpentine River Beaver Dams and Ponds, Seward Peninsula, Alaska, 31 March 2023

description: Emergence of beavers as ecosystem engineers in the New Arctic project focuses on establishing field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost. Drones are being used to collect baseline data and track beaver dam building and pond evolution over time. This dataset consists of an orthomosaic and digital surface model (DSM) derived from drone surveys on 31 March 2023 at the South Fork Serpentine River site on the Seward Peninsula, Alaska. 1,387 digital images were acquired from a DJI Phantom 4 Real-Time Kinematic (DJI P4RTK) quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 200 hectares (ha). The drone system was flown at 120 meters (m) above ground level (agl) and flight speeds varied from 8-9 meters/second (m/s). The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.8.4) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the orthophoto mosaic and digital surface model at spatial resolutions of 5 and 10 centimeters (cm), respectively. Elevation information derived over waterbodies is noisy and does not represent the surface elevation of the feature. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 3 North in Ellipsoid Heights (meters).
DOI: 10.18739/a2pk0737v
title: Multispectral Orthomosaic Image for the Glacier Creek Road Beaver Dams and Ponds, Seward Peninsula, Alaska, 14 August 2022

description: Emergence of beavers as ecosystem engineers in the New Arctic project focuses on establishing field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost. Drones are being used to collect baseline data and track beaver dam building and pond evolution over time. This dataset consists of a multispectral orthomosaic derived from drone surveys on 14 August 2022 at the Glacier Creek Road site on the Seward Peninsula, Alaska. 4,146 digital images from five spectral bands were acquired from a DJI Phantom 4 Real-Time Kinematic (DJI P4RTK) quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 50 hectares (ha). The drone system was flown at 120 meters (m) above ground level (agl) and images were captured using the hover and capture at point mode. The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.7.5) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the multispectral orthophoto mosaic at a spatial resolution of 10 centimeters (cm). Images of a MicaSense calibrated reflectance panel were used for radiometric processing and calibration of each spectral band in the Index Calculator in Pix4D. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 3 North.
DOI: 10.18739/a2js9h935
title: Multispectral Orthomosaic Image for the Glacier Creek Road Beaver Dams and Ponds, Seward Peninsula, Alaska, 09 August 2021

description: Emergence of beavers as ecosystem engineers in the New Arctic project focuses on establishing field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost. Drones are being used to collect baseline data and track beaver dam building and pond evolution over time. This dataset consists of a multispectral orthomosaic derived from drone surveys on 09 August 2021 at the Glacier Creek Road site on the Seward Peninsula, Alaska. 3,648 digital images from five spectral bands were acquired from a DJI Phantom 4 Real-Time Kinematic (DJI P4RTK) quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 45 hectares (ha). The drone system was flown at 120 meters (m) above ground level (agl) and images were captured using the hover and capture at point mode. The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.8.4) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the multispectral orthophoto mosaic at a spatial resolution of 10 centimeters (cm). Images of a MicaSense calibrated reflectance panel were used for radiometric processing and calibration of each spectral band in the Index Calculator in Pix4D. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 3 North.
DOI: 10.18739/a2f18sg9q
title: Multispectral Orthomosaic Image for the Glacier Creek Road Beaver Dams and Ponds, Seward Peninsula, Alaska, 04 August 2023

description: Emergence of beavers as ecosystem engineers in the New Arctic project focuses on establishing field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost. Drones are being used to collect baseline data and track beaver dam building and pond evolution over time. This dataset consists of a multispectral orthomosaic derived from drone surveys on 04 August 2023 at the Glacier Creek Road site on the Seward Peninsula, Alaska. 4,272 digital images from five spectral bands were acquired from a DJI Phantom 4 Real-Time Kinematic (DJI P4RTK) quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 45 hectares (ha). The drone system was flown at 120 meters (m()above ground level (agl) and images were captured using the hover and capture at point mode. The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.8.4) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the multispectral orthophoto mosaic at a spatial resolution of 10 centimeters (cm). Images of a MicaSense calibrated reflectance panel were used for radiometric processing and calibration of each spectral band in the Index Calculator in Pix4D. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 3 North.
DOI: 10.18739/a29882p6f
title: Orthomosaic Image and Digital Surface Model for the Glacier Creek Road Beaver Dams and Ponds, Seward Peninsula, Alaska, 09 August 2021

description: Emergence of beavers as ecosystem engineers in the New Arctic project focuses on establishing field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost. Drones are being used to collect baseline data and track beaver dam building and pond evolution over time. This dataset consists of an orthomosaic and digital surface model (DSM) derived from drone surveys on 09 August 2021 at the Glacier Creek Road site on the Seward Peninsula, Alaska. 258 digital images were acquired from a DJI P4RTK quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 45 hectares (ha). The drone system was flown at 120 meters (m) above ground level (agl) and flight speeds varied from 8-9 meters/second (m/s). The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.8.4) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the orthophoto mosaic and digital surface model at spatial resolutions of 5 and 10 centimeters (cm), respectively. Elevation information derived over waterbodies is noisy and does not represent the surface elevation of the feature. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 3 North in Ellipsoid Heights (meters).
DOI: 10.18739/a25m6284j
title: Orthomosaic Image and Digital Surface Model for the Swan Lake Drained Lake Basin (MP64) Beaver Dams, Seward Peninsula, Alaska, 27 March 2022

description: Emergence of beavers as ecosystem engineers in the New Arctic project focuses on establishing field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost. Drones are being used to collect baseline data and track beaver dam building and pond evolution over time. This dataset consists of an orthomosaic and digital surface model (DSM) derived from drone surveys on 27 March 2022 at the Swan Lake Drained Lake Basin, MP64, site on the Seward Peninsula, Alaska. 577 digital images were acquired from a DJI Phantom 4 Real-Time Kinematic (DJI P4RTK) quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 90 hectares (ha). The drone system was flown at 120 meters (m) above ground level (agl) and flight speeds varied from 8-9 meters/second (m/s). The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.8.4) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the orthophoto mosaic and digital surface model at spatial resolutions of 5 and 10 centimeters (cm), respectively. Elevation information derived over waterbodies is noisy and does not represent the surface elevation of the feature. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 3 North in Ellipsoid Heights (meters).
DOI: 10.18739/a21v5bg0d
title: Bugeye Lakes Complex Water Level Sensor Data, Arctic Coastal Plain of northern Alaska, 2021-2022

description: Taken together, lakes and drained lake basins may cover up to 80% of the lowland landscapes in permafrost regions of the Arctic. Lake formation, growth, and drainage in lowland permafrost regions create a terrestrial and aquatic landscape mosaic of importance to geomorphic and hydrologic processes, tundra vegetation communities, permafrost and ground-ice characteristics, biogeochemical cycling, wildlife habitat, and human land-use activities. Our project focuses on quantifying the role of thermokarst lake expansion, drainage, and drained lake basin evolution in the Arctic System. We did this through a combination of field studies, environmental sensor networks, remote sensing, and modeling.
 This dataset consists of environmental sensor records that record temperature and water level at three lakes in the Bugeye Lakes Complex in 2021 and 2022. Onset HOBO water level loggers (U2OL-04) were deployed in Bugeye Lakes 1, 2, and 4 in 2021 and 2022 to record temperature and pressure changes at 30-minute intervals. Water level was determined in Onset Hoboware Pro v. 3.7.23 using the barometric compensation assistant based on pressure transducer measurements below the water and from nearby atmospheric pressure measurements from a local pressure transducer mounted to pole on the tundra. The sensor data capture the partial drainage of Bugeye Lakes 2 and 4 into Bugeye Lake 1. Bugeye Lakes 1 and 2 also measure snow dam outburst flooding associated with the recently drained lake basins.
DOI: 10.18739/a2x34mt5q
title: Orthomosaic Image and Digital Surface Model for the Bugeye Lakes Complex, Arctic Coastal Plain of northern Alaska, July 2022

description: Taken together, lakes and drained lake basins may cover up to 80% of the lowland landscapes in permafrost regions of the Arctic. Lake formation, growth, and drainage in lowland permafrost regions create a terrestrial and aquatic landscape mosaic of importance to geomorphic and hydrologic processes, tundra vegetation communities, permafrost and ground-ice characteristics, biogeochemical cycling, wildlife habitat, and human land-use activities. Our project focuses on quantifying the role of thermokarst lake expansion, drainage, and drained lake basin evolution in the Arctic System. We did this through a combination of field studies, environmental sensor networks, remote sensing, and modeling.
 This dataset consists of an orthomosaic and digital surface model (DSM) derived from drone surveys on 19 and 20 July 2022 at the Bugeye Lakes Complex on the Arctic Coastal Plain of northern Alaska. 5,968 digital images were acquired from a DJI Phantom 4 Real-Time Kinematic (DJI P4RTK) quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 320 hectares (ha). The drone system was flown at 120 meters (m) above ground level (agl) and flight speeds varied from 7–8 meters/second (m/s). The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.8.4) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the orthophoto mosaic and digital surface model at spatial resolutions of 5 and 10 centimeters (cm), respectively. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 5 North in Ellipsoid Heights (meters). Elevation information derived over waterbodies is noisy and does not represent the surface elevation of the feature.
DOI: 10.6084/m9.figshare.24668871
title: Source data for "Multi-modality integrated microresonators using the Moire speedup effect"

description: Source data for "Multi-modality integrated microresonators using the Moire speedup effect"
DOI: 10.6084/m9.figshare.24668871.v1
title: Source data for "Multi-modality integrated microresonators using the Moire speedup effect"

description: Source data for "Multi-modality integrated microresonators using the Moire speedup effect"
DOI: 10.18739/a2sb3x110
title: Ethnographic study of teaching and learning in Fairbanks Alaska Native song and dance, 2022

description: This data set comes from an ethnography of the teaching and learning practices of Alaska Native song and dance groups. Included are interviews with Yupik and Iñupiaq Alaska Native Elders and dance community members. These interviews took place at the 2022 World Eskimo-Indian Olympics in Fairbanks, Alaska. The goal of this data is to provide insight into the how Alaska Native dance is taught and learned, what that process speaks to about the pedagogical structures of Alaska Native communities, and what is taught and learned through Alaska Native dance including practical skills and values/norms.
DOI: 10.6084/m9.figshare.24845412.v1
title: の 嫌悪感が日本の製造現場におけるLMXと紛争解決戦略に及ぼす影響

description: This is a study conducted at a Japanese manufacturing site that investigated how the subordinates' aversive traits toward their superiors affects LMX and conflict resolution.The results showed that when subordinates perceive their superiors as “arrogance”“egocentrism”,and “difference” it has a negative impact on LMX. They also found that if a subordinate is arrogant, that is, a boss who does not accept his subordinates, when there is a conflict with that superior, the subordinate is less likely to take the initiative to resolve the problem amicably.
DOI: 10.5281/zenodo.10418001
title: A Digital Fragmentation Method More Applicable to Artificial Intelligence Drug Design
DOI: 10.5281/zenodo.10418000
title: Row_data
DOI: 10.5281/zenodo.10426489
title: Row_data
DOI: 10.34740/kaggle/dsv/7263827
title: WallStreetBets 2022