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At least 1,405 records · Page 78

Linking NASA Environmental Data with a National Public Health Cohort Study and a CDC On-Line System to Enhance Public Health Decision Making

The overall goal of this study is to address issues of environmental health and enhance public health decision making by utilizing NASA remotely-sensed data and products. This study is a collaboration between NASA Marshall Space Flight Center, Universities Space Research Association (USRA), the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) National Center for Public Health Informatics. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the linked data sets and associated analyses to local, state and federal end-user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental datasets were linked with public health data from the UAB REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental national datasets will also be made available to public health professionals, researchers and the general public via the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system, where they can be aggregated to the county, state or regional level as per users need and downloaded in tabular, graphical, and map formats. The linkage of these data provides a useful addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in this online system. It also substantially expands public access to NASA data, making their use by a wide range of decision makers feasible.

Al-Hamdan, Mohammad↗

Public Health Applications of Remotely-sensed Environmental Datasets for the Conterminous United States

NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) National Center for Public Health Informatics to address issues of environmental health and enhance public health decision-making using NASA remotely-sensed data and products. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the linked data sets and associated analyses to local, state and federal end-user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid using the US Environmental Protection Agency (EPA) ground observations and NASA's MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Incoming Solar Radiation (Insolation) and heat-related products using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets were linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline, stroke and other health outcomes. These environmental datasets and the results of the public health linkage analyses will be disseminated to end-users for decision-making through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system and through peer-reviewed publications respectively. The linkage of these data with the CDC WONDER system substantially expands public access to NASA data, making their use by a wide range of decision makers feasible. By successful completion of this research, decision-making activities, including policy-making and clinical decision-making, can be positively affected through utilization of the data products and analyses provided on the CDC WONDER system.

Al-Hamdan, Mohammad↗

Temporal covariation of island arc Sr isotopes and seawater chemistry over the past 2 billion years

The chemical compositions of island arc basalts (IAB) reflect contributions from the mantle as well as fluids and melts from the subducting slab. Addition of radiogenic seawater Sr to oceanic crust through hydrothermal alteration and subsequent subduction is often invoked to explain elevated 87 Sr/ 86 Sr signatures in modern IAB. However, changes in the 87 Sr/ 86 Sr of island arc magmatic rocks through time has not been investigated, limiting our understanding of the factors influencing the Sr budgets of arcs throughout Earth’s history. To address this, we compiled 87 Sr/ 86 Sr values from island arc magmatic rocks ranging in age from modern to Paleoproterozoic, only including data from island arc localities that best preserve initial magmatic 87 Sr/ 86 Sr. Median initial 87 Sr/ 86 Sr values are consistently elevated compared to depleted mantle 87 Sr/ 86 Sr over this period, indicating persistent enrichment in radiogenic Sr in island arcs. Moreover, the elevation in island arc 87 Sr/ 86 Sr relative to the depleted mantle is variable. A notable rise in island arc 87 Sr/ 86 Sr during the late Neoproterozoic coincides with a steep increase in seawater 87 Sr/ 86 Sr and Sr concentration. To investigate this potential connectivity, we modeled the 87 Sr/ 86 Sr of island arc magmas between 0 and 830 Ma with inputs of depleted mantle 87 Sr/ 86 Sr, seawater 87 Sr/ 86 Sr, and seawater Sr concentration. The model reproduces the overall trajectory of the compiled data. We interpret the observed temporal variation in island arc 87 Sr/ 86 Sr values and its close association with fluctuations in seawater chemistry as evidence that changes in marine geochemistry have strongly influenced the Sr isotopic record of island arc magmas over time.

Science & Technology - Other Topics↗

Appalachian Basin Play Fairway Analysis Thermal Risk Factor and Quality Analyses

*This submission revises the analysis and products for Thermal Quality Analysis for the northern half of the Appalachian Basin (https://gdr.openei.org/submissions/638)* This submission is one of five major parts of a Low Temperature Geothermal Play Fairway Analysis. Phase 1 of the project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylvania, West Virginia and New York. This submission includes a subset of the necessary shapefiles, rasters, datasets, code, and references to code repositories that were used to create the thermal resource and risk factor maps as part of the project. This subset is those contents that were improved upon during calendar year 2016. Figures are provided as examples of some shapefiles and rasters. See also: Final Report: Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (https://gdr.openei.org/submissions/899). The 2015 data submission should be visited to obtain: 1) the regional standardized 1 square km grid used in the project as points (cell centers), polygons, and as a raster, 2) the raw well data for the state well temperature databases, 3) the COSUNA section shapefile and formation thermal conductivities by state as *.xlsx files, 4) the sediment thickness map and 30 m Digital Elevation Model for the Appalachian Basin as GeoTIFF raster files, 5) the BHT correction sections shapefile and drilling fluid databases as *.csv files, 6) the unbuffered interpolation regions as shapefiles, 7) several 50 km buffered interpolation regions as shapefiles, 8) several gridded interpolation regions as raster files, 9) an R script for organizing the thermal data and running the local spatial outlier analysis, 10) shapefiles and rasters for the prediction, uncertainty, and cross validation of the temperature at 1.5 km, 2.5 km, and 3.5 km depth, 11) shapefiles and rasters for the prediction, uncertainty, and cross validation depth to 100 degrees C, 12) an ArcGIS toolbox for thermal risk factor models, 13) an ArcGIS model for extracting results specific to each county of interest, 14) thermal resource cross section plots, 15) the geothermal Play Fairways.

15 GEOTHERMAL ENERGY↗

Development and Testing of Nuclear Data Libraries for Improved Energy Deposition Modeling - Paper 144

Accurate calculations of local energy deposition rates require the presence of gamma production data (GPD) in the nuclear data library used by radiation transport codes such as MCNP5, MONACO, or Denovo. The lack of GPD in the underlying nuclear data library can cause significant over-prediction of local heat generation rates with a corresponding under-prediction of heat generation rates away from a region of interest. To address this concern, continuous energy (CE) and multigroup (MG) cross section libraries with additional GPD have been created. Both ACE- and AMPX-formatted CE libraries, as well as ANISN- and AMPX-formatted MG libraries, have been created and are undergoing verification and validation (V and V) testing. A hybrid data set consisting of cross-section evaluations from five different nuclear data repositories has been developed. This hybrid data set, referred to as GPD-Rev0, is intended to support enhanced energy deposition calculations. Code-specific libraries in CE ACE, CE AMPX, MG AMPX, and MG ANISN formats have been created from the GPD-Rev0 data set. V and V testing has demonstrated that these various code-specific libraries are performing well for the intended applications. Localized over- and under-predictions of HFIR heating rates have been addressed without adversely affecting the prediction of other key operating parameters. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

VHF radar and rocket observations of equatorial spread F on Kwajalein

VHF radar data from the Summer 1990 Equatorial Spread F campaign on Kwajalein are presented. The Cornell 50 MHz portable radar interferometer (CUPRI) operated concurrently with the Altair UHF incoherent scatter radar throughout July and August and supported two sounding rocket flights on July 30 and August 2. This experiment provided the first opportunity to simultaneously diagnose equatorial spread F using the three prime experimental techniques: VHF/UHF coherent scatter, incoherent scatter, and in situ probe measurements of electric field and density fluctuations. The intensity of the coherent echoes observed was consistent with typical Jicamarca spread F observations, but chains of periodic, large-scale plasma upwellings were observed more often and for much longer durations on Kwajalein than have been seen over Peru. CUPRI also measured Doppler frequencies in one upwelling corresponding to 1200-m/s plasma drift velocities. This measurement agrees with recent observations of supersonic drift rates at the magnetic equator by spacecraft. Near the most active localized plasma upwellings, interferometer data reveal that the zonal drift rate of plasma irregularities can vary sharply in space, as one would expect for two-dimensional incompressible flow. We introduce a semiempirical model of the three-dimensional spectrum of F region irregularities that is consistent with the one-dimensional spectra of density fluctuations observed by sounding rockets and with the axial ratio of irregularities determined recently. Normalized to data from one of the rocket flights on Kwajalein, the model predicts the 3-m scattering cross-section measured by CUPRI to within a few decibels.

Hysell, D. L.↗

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a data-driven alternative that uses local neural operators, trained on spatiotemporal microscopic/mesoscopic data, to obtain efficient short-time solution operators. These surrogates are employed within Krylov subspace methods to compute coarse steady and unsteady-states, while also providing Jacobian information in a matrix-free manner. Krylov-Arnoldi iterations then approximate the dominant eigenspectrum, yielding reduced models that capture the open-loop slow dynamics without explicit Jacobian assembly. Both discrete-time Linear Quadratic Regulator (dLQR) and pole-placement (PP) controllers are based on this reduced system and lifted back to the full nonlinear dynamics, thereby closing the feedback loop.

93B52, 93C20, 47N70, 65J15, 65M32, 68T07, 68T20, 6↗

On the localness of the spectral energy transfer in turbulence

Data for the energy transfer function are used to estimate the degree of localness of energy transfer in homogeneous turbulence. It is found that in regions where the energy which enters a wavenumber band is greater than the energy leaving, much of the energy entering the band is produced by wavenumbers an order of magnitude smaller. Thus for both low and high Reynolds numbers, spectral energy transfer is nonlocal. The tendency of the energy to jump between separated wavenumber regions agrees with the theory that turbulence forms concentrated regions of large velocity gradients. It is also felt that the universal equilibrium theory may be applicable if the Reynolds number of the turbulence is very high.

Deissler, R. G.↗

Characterizing parallel file-access patterns on a large-scale multiprocessor

Rapid increases in the computational speeds of multiprocessors have not been matched by corresponding performance enhancements in the I/O subsystem. To satisfy the large and growing I/O requirements of some parallel scientific applications, we need parallel file systems that can provide high-bandwidth and high-volume data transfer between the I/O subsystem and thousands of processors. Design of such high-performance parallel file systems depends on a thorough grasp of the expected workload. So far there have been no comprehensive usage studies of multiprocessor file systems. Our CHARISMA project intends to fill this void. The first results from our study involve an iPSC/860 at NASA Ames. This paper presents results from a different platform, the CM-5 at the National Center for Supercomputing Applications. The CHARISMA studies are unique because we collect information about every individual read and write request and about the entire mix of applications running on the machines. The results of our trace analysis lead to recommendations for parallel file system design. First the file system should support efficient concurrent access to many files, and I/O requests from many jobs under varying load conditions. Second, it must efficiently manage large files kept open for long periods. Third, it should expect to see small requests predominantly sequential access patterns, application-wide synchronous access, no concurrent file-sharing between jobs appreciable byte and block sharing between processes within jobs, and strong interprocess locality. Finally, the trace data suggest that node-level write caches and collective I/O request interfaces may be useful in certain environments.

Purakayastha, Apratim↗

A local-view array library for partitioned global address space C++programs

Multidimensional arrays are an important data structure in many scientific applications. Unfortunately, built-in support for such arrays is inadequate in C++, particularly in the distributed setting where bulk communication operations are required for good performance. In this paper, we present a multidimensional library for partitioned global address space (PGAS) programs, supporting the one-sided remote access and bulk operations of the PGAS model. The library is based on Titanium arrays, which have proven to provide good productivity and performance. These arrays provide a local view of data, where each rank constructs its own portion of a global data structure, matching the local view of execution common to PGAS programs and providing maximum flexibility in structuring global data. Unlike Titanium, which has its own compiler with array-specific analyses, optimizations, and code generation, we implement multidimensional arrays solely through a C++library. The main goal of this effort is to provide a library-based implementation that can match the productivity and performance of a compiler-based approach. We implement the array library as an extension to UPC++, a C++library for PGAS programs, and we extend Titanium arrays with specializations to improve performance. We evaluate the array library by porting four Titanium benchmarks to UPC++, demonstrating that it can achieve up to 25% better performance than Titanium without a significant increase in programmer effort..

Kamil, A↗

Disproportionate impacts of COVID-19 in a large US city

COVID-19 has disproportionately impacted individuals depending on where they live and work, and based on their race, ethnicity, and socioeconomic status. Studies have documented catastrophic disparities at critical points throughout the pandemic, but have not yet systematically tracked their severity through time. Using anonymized hospitalization data from March 11, 2020 to June 1, 2021 and fine-grain infection hospitalization rates, we estimate the time-varying burden of COVID-19 by age group and ZIP code in Austin, Texas. During this 15-month period, we estimate an overall 23.7% (95% CrI: 22.5–24.8%) infection rate and 29.4% (95% CrI: 28.0–31.0%) case reporting rate. Individuals over 65 were less likely to be infected than younger age groups (11.2% [95% CrI: 10.3–12.0%] vs 25.1% [95% CrI: 23.7–26.4%]), but more likely to be hospitalized (1,965 per 100,000 vs 376 per 100,000) and have their infections reported (53% [95% CrI: 49–57%] vs 28% [95% CrI: 27–30%]). We used a mixed effect poisson regression model to estimate disparities in infection and reporting rates as a function of social vulnerability. We compared ZIP codes ranking in the 75th percentile of vulnerability to those in the 25th percentile, and found that the more vulnerable communities had 2.5 (95% CrI: 2.0–3.0) times the infection rate and only 70% (95% CrI: 60%-82%) the reporting rate compared to the less vulnerable communities. Inequality persisted but declined significantly over the 15-month study period. Our results suggest that further public health efforts are needed to mitigate local COVID-19 disparities and that the CDC’s social vulnerability index may serve as a reliable predictor of risk on a local scale when surveillance data are limited.

60 APPLIED LIFE SCIENCES↗

Signal-to-noise assessment for diffusion tensor imaging with single data set and validation using a difference image method with data from a multicenter study

Purpose: To describe a quantitative method for determination of SNR that extracts the local noise level using a single diffusion data set. Methods: Brain data sets came from a multicenter study (eight sites; three MR vendors). Data acquisition protocol required b = 0, 700 s/mm{sup 2}, fov = 256 × 256 mm{sup 2}, acquisition matrix size 128 × 128, reconstruction matrix size 256 × 256; 30 gradient encoding directions and voxel size 2 × 2 × 2 mm{sup 3}. Regions-of-interest (ROI) were placed manually on the b = 0 image volume on transverse slices, and signal was recorded as the mean value of the ROI. The noise level from the ROI was evaluated using Fourier Transform based Butterworth high-pass filtering. Patients were divided into two groups, one for filter parameter optimization (N = 17) and one for validation (N = 10). Six white matter areas (the genu and splenium of corpus callosum, right and left centrum semiovale, right and left anterior corona radiata) were analyzed. The Bland–Altman method was used to compare the resulting SNR with that from the difference image method. The filter parameters were optimized for each brain area, and a set of “global” parameters was also obtained, which represent an average of all regions. Results: The Bland–Altman analysis on the validation group using “global” filter parameters revealed that the 95% limits of agreement of percent bias between the SNR obtained with the new and the reference methods were −15.5% (median of the lower limit, range [−24.1%, −8.9%]) and 14.5% (median of the higher limits, range [12.7%, 18.0%]) for the 6 brain areas. Conclusions: An FT-based high-pass filtering method can be used for local area SNR assessment using only one DTI data set. This method could be used to evaluate SNR for patient studies in a multicenter setting.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Role of karyopherin nuclear transport receptors in nuclear transport by nuclear trafficking peptide

Nuclear trafficking peptide (NTP), a cell-penetrating peptide (CPP) composed of 10 amino acids (aa) (RIFIHFRIGC), has potent nuclear trafficking activity. Recently, we established a protein-based cell engineering system by using NTP, but it remained elusive how NTP functions as a CPP with nuclear orientation. In the present study, we identified importin subunit β1 (IMB1) and transportin 1 (TNPO1) as cellular proteins underlying the activity of NTP. These karyopherin nuclear transport receptors were identified as candidate molecules by liquid chromatography/mass spectrometry analysis, and downregulation of each protein by small interfering RNA significantly reduced NTP activity (P < 0.01). Biochemical analyses revealed that NTP bound directly to both molecules, and the forced expression of an IMB1 fragment (296–516 aa) or TNPO1 fragment (1–297 aa), which both contain binding sites to NTP, reduced nuclear NTP-green fluorescent protein (GFP) levels when it was added to cell culture medium. NTP is derived from viral protein R (Vpr) of human immunodeficiency virus-1, and Vpr enters the nucleus and exerts pleiotropic functions. Notably, Vpr bound directly to IMB1 and TNPO1, and its function was significantly impaired by the forced expression of the 296–516-aa fragment of IMB1 and 1–297-aa fragment of TNPO1. Interestingly, NTP completely blocked the physical association of Vpr with IMB1 and TNPO1. Although the nuclear localization mechanism of Vpr remains unknown, our data suggest that NTP functions as a novel nuclear localization signal of Vpr.

60 APPLIED LIFE SCIENCES↗

Morphology and movements of polarization features on Venus

Ground and spacecraft based polarization observations of Venus detected the signature of the so called 1-micron radius cloud particles that constitute the main cloud deck on Venus, as well as that of sub-micron sized particles that form a haze above this main cloud layer. Whether such observations showed any local clustering or organization in the polarimetry data remained uncertain until the relatively high resolution observations from the Pioneer Venus Orbiter Cloud Photopolarimeter (OCPP) became available. The available polarization data from this instrument was studied to see whether local organization was present, to study the morphology of such features or polarization clouds, and finally, to see if they can be followed in a sequence of observations to study their motions.

Limaye, S. S.↗

Matrix Factorizations at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies

We explore the trade-offs of performing linear algebra using Apache Spark, compared to traditional C and MPI implementations on HPC platforms. Spark is designed for data analytics on cluster computing platforms with access to local disks and is optimized for data-parallel tasks. We examine three widely-used and important matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquity) and CX (for data interpretability). We apply these methods to 1.6TB particle physics, 2.2TB and 16TB climate modeling and 1.1TB bioimaging data. The data matrices are tall-and-skinny which enable the algorithms to map conveniently into Spark’s data parallel model. We perform scaling experiments on up to 1600 Cray XC40 nodes, describe the sources of slowdowns, and provide tuning guidance to obtain high performance.

Gittens, Alex↗

Surveillance of Aedes aegypti indoors and outdoors using Autocidal Gravid Ovitraps in South Texas during local transmission of Zika virus, 2016 to 2018

The yellow fever mosquito, Aedes aegypti, has facilitated the re-emergence of dengue virus (DENV) and emergence of chikungunya virus (CHIKV) and Zika virus (ZIKV) in the Americas and the Caribbean. The recent transmission of these arboviruses in the continental United States has been limited, to date, to South Florida and South Texas despite Ae. aegypti occurring over a much larger geographical region within the country. The main goal of our study was to provide the first long term longitudinal study of Ae. aegypti and enhance the knowledge about the indoor and outdoor relative abundance of Ae. aegypti as a proxy for mosquito-human contact in South Texas, a region of the United States that is at high risk for mosquito-borne virus transmission. Here, the relative abundance of indoors and outdoors mosquitoes of households in eight different communities was described. Surveillance was done weekly from September 2016 to April 2018 using the CDC Autocidal Gravid Ovitraps in low- and middle-income communities. A total of 69 houses were included in this survey among which 36 were in the low-income communities (n = 11 for Donna, n = 15 for Progresso, n = 5 for Mesquite, n = 5 for Chapa) and 33 in middle-income communities (n = 9 for La Feria, n = 8 for Weslaco, n = 11 for McAllen, and n = 5 for Rio Rico). Overall, Ae. aegypti was the dominant species (59.2% of collections, n = 7255) followed by Culex spp. mosquitoes (27.3% of collections, n = 3350). Furthermore, we demonstrated for Ae. aegypti that 1) outdoor relative abundance was higher compared to indoor relative abundance, 2) low-income communities were associated with an increase in mosquito relative abundance indoors when compared to middle-income communities, 3) no difference was observed in the number of mosquitoes collected outdoors between low-income and middle-income communities, and 4) warmer months were positively correlated with outdoor relative abundance whereas no seasonality was observed in the relative abundance of mosquitoes indoors. Additionally, Ae. aegypti mosquitoes collected in South Texas were tested using a specific ZIKV/CHIKV multiplex real-time PCR assay, however, none of the mosquitoes tested positive. Our data highlights the occurrence of mosquitoes indoors in the continental United States and that adults are collected nearly every week of the calendar year. These mosquito data, obtained concurrently with local ZIKV transmission of 10 locally acquired cases in nearby communities, represent a baseline for future studies in the Lower Rio Grande Valley (LRGV) including vector control interventions relying on the oviposition behavior to reduce mosquito populations and pathogen transmission.

59 BASIC BIOLOGICAL SCIENCES↗

Six More Ultra-faint Milky Way Companions Discovered in the DECam Local Volume Exploration Survey

We report the discovery of six ultra-faint Milky Way satellites identified through matched-filter searches conducted using Dark Energy Camera (DECam) data processed as part of the second data release of the DECam Local Volume Exploration (DELVE) survey. Leveraging deep Gemini/GMOS-N imaging (for four candidates) as well as follow-up DECam imaging (for two candidates), we characterize the morphologies and stellar populations of these systems. We find that these candidates all share faint absolute magnitudes (M$_{V}$ ≥ −3.2 mag) and old, metal-poor stellar populations (τ > 10 Gyr, [Fe/H] < −1.4 dex). Three of these systems are more extended (r$_{1/2}$ > 15 pc), while the other three are compact (r$_{1/2}$ < 10 pc). From these properties, we infer that the former three systems (Boötes V, Leo Minor I, and Virgo II) are consistent with ultra-faint dwarf galaxy classifications, whereas the latter three (DELVE 3, DELVE 4, and DELVE 5) are likely ultra-faint star clusters. Using data from the Gaia satellite, we confidently measure the proper motion of Boötes V, Leo Minor I, and DELVE 4, and tentatively detect a proper-motion signal from DELVE 3 and DELVE 5; no signal is detected for Virgo II. We use these measurements to explore possible associations between the newly discovered systems and the Sagittarius dwarf spheroidal, the Magellanic Clouds, and the Vast Polar Structure, finding several plausible associations. Our results offer a preview of the numerous ultra-faint stellar systems that will soon be discovered by the Vera C. Rubin Observatory and highlight the challenges of classifying the faintest stellar systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Sampling and Control Circuit Board for an Inertial Measurement Unit

A circuit board that serves as a control and sampling interface to an inertial measurement unit ("IMU") is provided. The circuit board is also configured to interface with a local oscillator and an external trigger pulse. The circuit board is further configured to receive the external trigger pulse from an external source that time aligns the local oscillator and initiates sampling of the inertial measurement device for data at precise time intervals based on pulses from the local oscillator. The sampled data may be synchronized by the circuit board with other sensors of a navigation system via the trigger pulse.

Chelmins, David T↗