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375 results for “compactness”
A Compact Immersion Grating Spectrometer with Quantum Capacitance Detectors for Space-Borne Far-IR Spectroscopy Project
<p>SPECTROMETER:&nbsp; The grating spectrometer uses a curved grating fabricated on a high resistivity silicon wafer. Light will be coupled in via a silicon immersion lens and coupling waveguide. The wafer profile, including the grating facets are defined by photolithography and deep reactive etching (DRIE) and the wafer is metallized on both sides for better light confinement (except in the regions below where the detector antennas will be placed).&nbsp; The grating both focuses and diffracts the light in the plane of the wafer to a focal arc, where the detectors are positioned. QCD DETECTOR ARRAY: The Quantum Capacitance Detector is a mesoscopic superconducting device that exploits its extreme susceptibility to the presence of quasiparticle excitations arising from pair-breaking radiation to enable background limited detection.&nbsp; QCDs have demonstrated photon noise limited performance&nbsp; at 1.5THz for optical loadings 10-20 to 10-17W.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The detector die will be placed directly on top of the spectrometer wafer and will have an array of QCDs with antennas positioned at the focusing spots of each wavelength.&nbsp; Each detector will be coupled to a superconducting resonator with a different resonant frequency to allow for frequency multiplexing with a single feedline coupling the RF signal to all resonators.&nbsp; A&nbsp; prototype with 32 spectral channels will be demonstrated</p>
DISCOVER-AQ Colorado Deployment B-200 Aircraft Remotely Sensed Airborne Compact Atmospheric Mapper Data
DISCOVERAQ_Colorado_AircraftRemoteSensing_B200_ACAM_Data contains remotely sensed data collected by the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's B-200 aircraft during the Colorado (Denver) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Denver deployment and data collection is complete.Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality.DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS).The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.
Development of Immersion Gratings to Enable a Compact Architecture for High Spectral and Spatial Resolution Imaging Project
<p> Fabricate Si immersed gratings for IR (1150 &ndash; 6500 nm) spectroscopy to support ground-based, airborne, and space-based infrared spectrometers.<br /> These devices offer substantial advantages in compactness, formatting, and efficiency over other dispersive devices and have 3.44 times the resolving power of a conventional front-surface device for a grating of a given size.<br /> &nbsp;</p>
Ground-Based Global Navigation Satellite System (GNSS) Hatanaka-compressed Observation Data (1-second sampling, sub-hourly files) from NASA CDDIS
This dataset consists of ground-based Global Navigation Satellite System (GNSS) Observation Data (1-second sampling, sub-hourly files) from the NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. GNSS data sets from ground receivers at the CDDIS consist primarily of the data from the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS). Since 2011, the CDDIS GNSS archive includes data from other GNSS (Europe’s Galileo, China’s Beidou, Japan’s Quasi-Zenith Satellite System/QZSS, the Indian Regional Navigation Satellite System/IRNSS, and worldwide Satellite Based Augmentation Systems/SBASs), which are similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. The sub-hourly GNSS observation files (compact) contain 15 minutes of GPS or multi-GNSS observation (1-second sampling) data in RINEX format from a global permanent network of ground-based receivers, one file per 15 minutes per site. More information about these data is available on the CDDIS website at https://cddis.nasa.gov/Data_and_Derived_Products/GNSS/high-rate_data.html.
DISCOVER-AQ Maryland Deployment UC-12 Aircraft Remotely Sensed Airborne Compact Atmospheric Mapper Data
DISCOVERAQ_Maryland_AircraftRemoteSensing_UC12_ACAM_Data contains remotely sensed data collected by the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's UC-12 aircraft during the Maryland deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Maryland deployment and data collection is complete.Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality.DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS).The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.
Free Form Mirrors for Ultra Compact High Speed Optical Systems Project
<p>This task is to collaboratively design and fabricate the free-form WIRIS telescope primary mirror with our partner Zygo as a technology demonstration. Fabricating the primary is challenging as it has 865 um of aspheric departure and is not rotationally symmetric.</p>
Ground-Based Global Navigation Satellite System (GNSS) Hatanaka-compressed Observation Data (30-second sampling, hourly files) from NASA CDDIS
This dataset consists of ground-based Global Navigation Satellite System (GNSS) Observation Data (30-second sampling, hourly files) from the NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. GNSS data sets from ground receivers at the CDDIS consist primarily of the data from the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS). Since 2011, the CDDIS GNSS archive includes data from other GNSS (Europe’s Galileo, China’s Beidou, Japan’s Quasi-Zenith Satellite System/QZSS, the Indian Regional Navigation Satellite System/IRNSS, and worldwide Satellite Based Augmentation Systems/SBASs), which are similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. The hourly GNSS observation files (compact) contain one hour of GPS or multi-GNSS observation (30-second sampling) data in RINEX format from a global permanent network of ground-based receivers, one file per hour per site. More information about these data is available on the CDDIS website at https://cddis.nasa.gov/Data_and_Derived_Products/GNSS/hourly_30second_data.html.
DISCOVER-AQ Texas Deployment B-200 Aircraft Remotely Sensed Airborne Compact Atmospheric Mapper Data
DISCOVERAQ_Texas_AircraftRemoteSensing_B200_ACAM_Data contains remotely sensed data collected by the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's B-200 aircraft during the Texas (Houston) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Texas deployment and data collection is complete.Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality.DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS).The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.
DISCOVER-AQ California Deployment B-200 Aircraft Remotely Sensed Airborne Compact Atmospheric Mapper Data
DISCOVERAQ_California_AircraftRemoteSensing_B200_ACAM_Data contains remotely sensed data collected by the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's B-200 aircraft during the California (San Joaquin Valley) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the California deployment and data collection is complete.Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality.DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS).The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.
Compact Fiber Optic Strain Sensors (cFOSS) Element
<p>Armstrong researchers are reducing the Fiber Optic Sensing Sysme (FOSS) technology&rsquo;s size, power requirement, weight, and cost to effectively extend opportunities for broader fields of application. Unlike current commercially available systems, which are limited by the number of fibers that are interrogated simultaneously, Armstrong&rsquo;s cFOSS technology maintains its multi-fiber capability (four or eight fibers) while providing a smaller overall form factor. FOSS is the size of a shoebox and weighs 28.5 pounds; cFOSS will be the size of a 6-inch cube and weigh less than 10 pounds. Each component within the system has been custom-designed specifically for miniaturization, thus reducing capital costs. As industries strive for ever smaller profiles, this miniaturization will be an important benefit for multiple markets. For example, small aviation UAVs would benefit significantly from this smaller, more compact, and lightweight package.&nbsp;</p><p><strong>Work to date: </strong>In partnership with the AERO Institute, researchers have flown the cFOSS v1.0 system, a convection-cooled 5-lb version, on a small UAV, interrogating four fibers simultaneously.&nbsp;</p><p><strong>Looking ahead: </strong>By the end of December 2015, cFOSS v2.0, with conduction cooling, will fly on an Antares rocket.&nbsp;</p><p><strong>Benefits</strong></p><ul><li><strong>Cost-efficient:</strong> Each component within the&nbsp;system has been custom designed specifically&nbsp;for miniaturization, thus reducing capital costs</li><li><strong>Compact:</strong> The miniaturized size requires less&nbsp;associated hardware than existing systems</li><li><strong>Reliable:&nbsp;</strong>Components are customized for aggressive environments yet maintain a compact form factor</li></ul><p><strong>Applications</strong></p><ul><li>Aeronautics and launch vehicles</li><li>Medical procedures</li><li>Drilling</li><li>Wind energy</li><li>Automotive testing</li><li>Industrial processes</li></ul>
H4K16 acetylation marks active genes and enhancers of embryonic stem cells, but does not alter chromatin compaction [NimbleGen array]
GEO Series GSE47762. Mus musculus. 2 samples. Type: Genome binding/occupancy profiling by genome tiling array.
H1 linker histones regulate the balance of repressive and active chromatin domains via localized genomic compaction [CUT&Tag]
GEO Series GSE153543. Mus musculus. 18 samples. Type: Other.
H1 linker histones regulate the balance of repressive and active chromatin domains via localized genomic compaction
GEO Series GSE141187. Mus musculus. 62 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Other.
Polycomb-mediated axial patterning requires nucleosome compaction [ChIP-seq]
GEO Series GSE86084. Mus musculus. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Single-cell RNA-seq of Kitaake rice roots grown in gel, and non-compacted soil conditions
GEO Series GSE251706. Oryza sativa. 18 samples. Type: Expression profiling by high throughput sequencing.
MORC proteins regulate transcription factor binding through mediating chromatin compaction at active chromatin regions
GEO Series GSE212801. Arabidopsis thaliana. 39 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
H4K16 acetylation marks active genes and enhancers of embryonic stem cells, but does not alter chromatin compaction (I) [ChIP-Seq]
GEO Series GSE43102. Mus musculus. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Polycomb-mediated axial patterning requires nucleosome compaction
GEO Series GSE86085. Mus musculus. 31 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Heterochromatin rewiring and domain disruption-mediated chromatin compaction during erythropoiesis [CUT&RUN]
GEO Series GSE183989. Homo sapiens. 28 samples. Type: Other.
Cohesin-dependent compaction of mitotic chromosomes in budding yeast
GEO Series GSE87311. Saccharomyces cerevisiae. 10 samples. Type: Other.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.