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At least 1,297 records · Page 72

Methods for Improving Long-Range Wireless Communication Between Extreme Terrain Vehicles

Axel is an extreme terrain, two-wheeled rover designed to traverse rocky surface and sub-surface landscapes in order to conduct remote science experiments in hard-to-reach locations. The rover's design meets many requirements for a mobile research platform capable of reaching water seeps on Martian cliff sides. Axel was developed by the Mobility and Robotic Systems section at the Caltech Jet Propulsion Laboratory. Unique design criteria associated with extreme terrain mobility led to a unique rover solution, consisting of a central module, which provides long-term energy storage and space for large-scale science payloads, and two detachable Axels that can detach and explore extreme terrain locations that are inaccessible to conventional rovers. The envisioned mission could involve a four-wheeled configuration of Axel called 'DuAxel' that is able to traverse the benign, flattened terrain of a landing site and approach the edge of the targeted crater or cave where it would deploy anchoring legs and detach one of the Axel rovers [1]. A tether provides a secure link between the Axel rover and the central module, acting as an anchor to allow Axel to descend along steep crater walls to collect data from the scientifically relevant sites along the water seeps or crater ledges. After completing its scientific mission Axel would hoist itself up to the central module and dock autonomously (using its on-board stereo cameras), allowing the once-again recombined DuAxel to travel to another location to repeat data collection.

wireless communication↗

Technologies and Methods Used at the Laboratory for Atmospheric and Space Physics (LASP) to Serve Solar Irradiance Data

The Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado in Boulder, USA operates the Solar Radiation and Climate Experiment (SORCE) NASA mission, as well as several other NASA spacecraft and instruments. Dozens of Solar Irradiance data sets are produced, managed, and disseminated to the science community. Data are made freely available to the scientific immediately after they are produced using a variety of data access interfaces, including the LASP Interactive Solar Irradiance Datacenter (LISIRD), which provides centralized access to a variety of solar irradiance data sets using both interactive and scriptable/programmatic methods. This poster highlights the key technological elements used for the NASA SORCE mission ground system to produce, manage, and disseminate data to the scientific community and facilitate long-term data stewardship. The poster presentation will convey designs, technological elements, practices and procedures, and software management processes used for SORCE and their relationship to data quality and data management standards, interoperability, NASA data policy, and community expectations.

Pankratz, Chris↗

High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.

James Casaletto↗

Data Archive and Portal (DAP) Platform for Solid Phase Processing Technologies

The scale and speed of data generated by modern scientific experiments have constantly challenged the research community to store, curate, manage and optimally use it to drive scientific discoveries. In this work, we have developed a data archive and portal (DAP) platform including analytics capabilities to collect, curate, and manage data and metadata stream for solid phase processing (SPP) techniques. We successfully hosted around ~347K files of data related to processing parameters, microscopic images, and spectroscopic data related to solid phase processing. The DAP platform for SPP will establish an enduring capability to support machine learning and grow collaboration at the intersection of materials science and data science.

36 MATERIALS SCIENCE↗

State of the Data Union, 1992

This is the first report on the State of the Data Union (SDU) for the NASA Office of Space Science and Applications (OSSA). OSSA responsibilities include the collection, analysis, and permanent archival of data critical to space science research. The nature of how this is done by OSSA is evolving to keep pace with changes in space research. Current and planned missions have evolved to be more complex and multidisciplinary, and are generating much more data and lasting longer than earlier missions. New technologies enable global access to data, transfer of huge volumes of data, and increasingly complex analysis. The SDU provides a snapshot of this dynamic environment, identifying trends in capabilities and requirements. The current space science data environment is described and parameters which capture the pulse of key functions within that environment are presented. Continuous efforts of OSSA to improve the availability and quality of data provided to the scientific community are reported, highlighting efforts such as the Data Management Initiative.

Source record↗

Analysis of TRMM Microphysical Measurements: Tropical Rainfall Measuring Mission (TRMM)

SPEC Incorporated participated in three of the four TRMM field campaigns (TEFLUN-A, TEFLUN-B and KWAJEX), installing and operating a cloud particle imager (CPI) and a high volume precipitation spectrometer (HVPS) on the SPEC Learjet in TEFLUN-A, the University of North Dakota Citation in TEFLUN-B and KWAJEX, and a CPI on the NASA DC-8 in KWAJEX. This report presents and discusses new software tools and algorithms that were developed to analyze microphysical data collected during these field campaigns, as well as scientific interpretations of the data themselves. Software algorithms were developed to improve the analysis of microphysical measurements collected by the TRMM aircraft during the field campaigns. Particular attention was paid to developing and/or improving algorithms used to compute particle size distributions and ice water content. Software was also developed in support of production of the TRMM Common Microphysical Product (CMP) data files. CMP data files for TEFLUN-A field campaign were produced and submitted to the DAAC. Typical microphysical properties of convective and stratiform regions from TEFLUN-A and KWAJEX clouds were produced. In general, it was found that in the upper cloud region near -20 to -25 C, stratiform clouds contain very high (greater than 1 per cubic centimeter) concentrations of small ice particles, which are suspected to be a residual from homogeneous freezing and sedimentation of small drops in a convective updraft. In the upper cloud region near -20 to -25 C, convective clouds contain aggregates, which are not found lower in the cloud. Stratiform clouds contain aggregates at all levels, with the majority in the lowest levels. Convective cloud regions contain much higher LWC and drop concentrations than stratiform regions at all levels, and higher LWC in the middle and upper regions. Stratiform clouds contain higher IWC than convective clouds only at the lowest level. Irregular shaped ice particles are found in very high concentrations throughout both convective and stratiform cloud regions. A striking difference in particle shape in cirrus formed in situ, cirrus formed from maritime anvils and cirrus formed from continental anvils. Over 50% of the mass of in situ cirrus ice particles is composed of bullet rosettes, while bullet rosettes are virtually non-existent in maritime and tropical anvils. Tropical anvils are composed of mostly singular, plates, capped columns, and blocky irregular shapes, while continental anvils have a much higher percentage of aggregates, some of which are chains of small spheroidal particles that appear to result from homogeneous freezing of drops. A correlation between high electric fields in continental anvils and the formation of aggregates is hypothesized.

Source record↗

Transport and Meteorological Analysis

The objectives of this work are twofold. First, to provide real-time meteorological satellite guidance to airborne field missions for NASA's Upper Atmosphere Research Program, the Global Tropospheric Experiment, and the Atmospheric Effects of Aviation Project. Extensive meteorological satellite datasets were provided for use by the mission scientist and by the science team. These same data were then archived for postdeployment data analysis by the science team. Second, to provide scientific analysis of the data from the airborne field missions supported. The results of these analyses were made public through peer-reviewed publications.

Pfister, Leonhard↗

EOS MLS Level 1B Data Processing, Version 2.2

A computer program performs level- 1B processing (the term 1B is explained below) of data from observations of the limb of the Earth by the Earth Observing System (EOS) Microwave Limb Sounder (MLS), which is an instrument aboard the Aura spacecraft. This software accepts, as input, the raw EOS MLS scientific and engineering data and the Aura spacecraft ephemeris and attitude data. Its output consists of calibrated instrument radiances and associated engineering and diagnostic data. [This software is one of several computer programs, denoted product generation executives (PGEs), for processing EOS MLS data. Starting from level 0 (representing the aforementioned raw data, the PGEs and their data products are denoted by alphanumeric labels (e.g., 1B and 2) that signify the successive stages of processing.] At the time of this reporting, this software is at version 2.2 and incorporates improvements over a prior version that make the code more robust, improve calibration, provide more diagnostic outputs, improve the interface with the Level 2 PGE, and effect a 15-percent reduction in file sizes by use of data compression.

Perun, Vincent↗

(abstract) Recent Developments in Active Microwave Systems at JPL

This paper provides an overview of some of the recent developments in active microwave systems at JPL. The first section summarizes the engineering and scientific results that were obtained from the two recent flights of the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) on the Shuttle Endeavor. Specific examples of the applications of these data to various scientific disciplines will be discussed. The second section of the paper describes the recent progress in the development of an interferometric SAR system for high-resolution digital topography mapping. Examples of measurements from this technique over areas with earthquakes will be shown. The final section of the paper addresses development of meteorological radars for rain and cloud measurements. The design of an airborne rain mapping radar that was developed to support the Tropical Rain Measuring Mission is summarized. The technical design challenges for this high-frequency radar system will be described.

radar↗

Computer sciences

The Computer Science Program provides advanced concepts, techniques, system architectures, algorithms, and software for both space and aeronautics information sciences and computer systems. The overall goal is to provide the technical foundation within NASA for the advancement of computing technology in aerospace applications. The research program is improving the state of knowledge of fundamental aerospace computing principles and advancing computing technology in space applications such as software engineering and information extraction from data collected by scientific instruments in space. The program includes the development of special algorithms and techniques to exploit the computing power provided by high performance parallel processors and special purpose architectures. Research is being conducted in the fundamentals of data base logic and improvement techniques for producing reliable computing systems.

Smith, Paul H.↗

The Lifecycle of NASA's Earth Science Enterprise Data Resources

A major endeavor of NASA's Earth Science Enterprise (ESE) is to acquire, process, archive and distribute data from Earth observing satellites in support of a broad set of science research and applications in the U. S. and abroad. NASA policy directives specifically call for the agency to collect, announce, disseminate and archive all scientific and technical data resulting from NASA and NASA-funded research. During the active life of the satellite missions, while the data products are being created, validated and refined, a number of NASA organizations have the responsibility for data and information system functions. Following the completion of the missions, the responsibility for the long-term stewardship of the ocean and atmospheric, and land process data products transitions to the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS), respectively. Ensuring that long-term satellite data be preserved to support global climate change studies and other research topics and applications presents some major challenges to NASA and its partners. Over the last several years, with the launch and operation of the EOS satellites and the acquisition and production of an unprecedented volume of Earth science data, the importance of addressing these challenges has been elevated. The lifecycle of NASA's Earth science data has been the subject of several agency and interagency studies and reports and has implications and effects on agency charters, policies and budgets and on their data system's requirements, implementation plans and schedules. While much remains to be done, considerable progress has been made in understanding and addressing the data lifecycle issues.

McDonald, Kenneth R.↗

Acquisition of a Biomedical Database of Acute Responses to Space Flight during Commercial Personal Suborbital Flights

There is currently too little reproducible data for a scientifically valid understanding of the initial responses of a diverse human population to weightlessness and other space flight factors. Astronauts on orbital space flights to date have been extremely healthy and fit, unlike the general human population. Data collection opportunities during the earliest phases of space flights to date, when the most dynamic responses may occur in response to abrupt transitions in acceleration loads, have been limited by operational restrictions on our ability to encumber the astronauts with even minimal monitoring instrumentation. The era of commercial personal suborbital space flights promises the availability of a large (perhaps hundreds per year), diverse population of potential participants with a vested interest in their own responses to space flight factors, and a number of flight providers interested in documenting and demonstrating the attractiveness and safety of the experience they are offering. Voluntary participation by even a fraction of the flying population in a uniform set of unobtrusive biomedical data collections would provide a database enabling statistical analyses of a variety of acute responses to a standardized space flight environment. This will benefit both the space life sciences discipline and the general state of human knowledge.

Charles, John B.↗

Performance assessment of ensembles of in situ workflows under resource constraints

Summary Scientific breakthroughs in biomolecular methods and improvements in hardware technology have shifted from a long‐running simulation to a large set of shorter simulations running simultaneously, called an ensemble. In an ensemble, simulations are usually coupled with analyses of data produced by the simulations. In situ methods can be used to analyze large volumes of data generated by scientific simulations at runtime (i.e., simulations and analyses are performed concurrently). In this work, we study the execution of ensemble‐based simulations paired with in situ analyses using in‐memory staging methods. Using an ensemble of molecular dynamics in situ workflows with multiple simulations and analyses, we first show that collecting traditional metrics such as makespan, instructions per cycle, memory usage, or cache miss ratio is not sufficient to characterize complex behaviors of ensembles. We propose a method to evaluate the performance of ensembles of workflows that captures multiple resource usage aspects: resource efficiency, resource allocation, and resource provisioning. Experimental results demonstrate that the proposed method can effectively distinguish the performance of different component placements in an ensemble with up to 32 ensemble members. By evaluating different co‐location scenarios, our proposed performance indicators demonstrate benefits of co‐locating simulation and coupled analyses within a compute node.

Do, Tu Mai Anh↗

Data Announcement Bulletin: Space Shuttle OSTA 1 payload data

Data from the scientific payload, OSTA 1, is available. Images of the Earth's surface taken from the Shuttle Imaging Radar-A were processed, and can be obtained in the form of photographic prints, negatives, or positive transparencies. Magnetic tapes containing data for the ocean color experiment and the Shuttle multispectral infrared radiometer are also available.

Source record↗

Working Safely at LANL during the COVID-19 Pandemic (Rev. 2)

The COVID-19 pandemic is an emerging, rapidly evolving public health emergency. The content of this course reflects the most up-to-date guidance and information from the Centers for Disease Control and Prevention (CDC), World Health Organization (WHO) and scientific literature available at the time the course was developed. Check the LANL COVID-19 Hub for the latest information and guidance. Updates to the course will be made as necessary to reflect evolving guidance form public health authorities and new data form the scientific literature.

60 APPLIED LIFE SCIENCES↗

An Acceleration Measurement Capability on International Space Station Supporting Microgravity Science Payloads

The conditions present in low-earth-orbit have enabled various scientific investigations to be conducted. A fundamental reason that space is a useful environment for science is the presence of a decreased effect of gravity while in orbital free-fall. Science investigations are conducted to study phenomena occurring as a result of reductions in buoyancy forces and phenomena enabled as a result of the apparent lack of gravity. The science community requires knowledge of the environment in which their experiments are being conducted. A general purpose measurement system was developed in the 1980's to supply scientific investigators with data of the residual acceleration environment. The Space Acceleration Measurement System, or SAMS, has flown aboard the NASA shuttle fleet over fourteen times, successfully acquiring acceleration measurement data in support of microgravity science experiments. As NASA continues its development of the International Space Station and its associated research payloads, it once again becomes necessary to address the requirement to measure the residual acceleration in support of the planned scientific investigations. As a follow-on to the SAMS project, SAMS-2 was initiated to investigate the requirements and develop the measurement system to support the microgravity science payloads aboard the International Space Station. The characteristics of the payload complement to be supported by SAMS-2 and the different capabilities provided by the station requires a fresh look at the design implementation of a general purpose measurement system. Not only is there a requirement for measurements in support of numerous, potentially simultaneous experiments, but this support is required to be provided for at least ten years of on-orbit operation as compared to a ten to fourteen day mission on shuttle. These differences in fundamental requirements result in the design configuration of the space station-based SAMS-2 being significantly different than that of the shuttle-based SAMS. This paper describes these differences in requirements and the planned features to be provided to the science user community. Some of the unique challenges faced in developing a general purpose measurement system are also discussed.

Sutliff, Thomas J.↗