Results for “rapid evolution” — Page 7

DOE OSTI2024

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Electronic Interactions Between the Receptor-Binding Domain of Omicron Variants and Angiotensin-Converting Enzyme 2: A Novel Amino Acid–Amino Acid Bond Pair Concept

SARS-CoV-2 remains a severe threat to worldwide public health, particularly as the virus continues to evolve and diversify into variants of concern (VOCs). Among these VOCs, Omicron variants exhibit unique phenotypic traits, such as immune evasion, transmissibility, and severity, due to numerous spike protein mutations and the rapid subvariant evolution. These Omicron subvariants have more than 15 mutations in the receptor-binding domain (RBD), a region of the SARS-CoV-2 spike protein that is important for recognition and binding with the angiotensin-converting enzyme 2 (ACE2) human receptor. To address the impact of these high numbers of Omicron mutations on the binding process, we have developed a novel method to precisely quantify amino acid interactions via the amino acid–amino acid bond pair (AABP). We applied this concept to investigate the interface interactions of the RBD–ACE2 complex in four Omicron Variants (BA.1, BA.2, BA.5, and XBB.1.16) with its Wild Type counterpart. Based on the AABP analysis, we have identified all the sites that are affected by mutation and have provided evidence that unmutated sites are also impacted by mutation. We have calculated that the binding between RBD and ACE2 is strongest in OV BA.1, followed by OV BA.2, WT, OV BA.5, and OV XBB.1.16. We also present the partial charge values for all 311 residues across these five models. Our analysis provides a detailed understanding of changes caused by mutation in each Omicron interface complex.

Biochemistry & Molecular Biology↗

DOE OSTI2025

Files_used_for_figures

This folder includes all the relevant files used to generate the main Figures in the paper.

DNA repair↗

NASA NTRS1985

Investigations of Planetary Ring Phenomena

The structure of Jupiter's rings was studied in an effort to understand the processes that generate the rings. The faint material in the Saturn system was investigated leading to the discovery of a new ring and a way to interpret the wavy features surrounding Encke's division in terms of perturbing moonlets. The interaction of faint rings and magnetospheres helped identify some of the charged particle absorbers seen by Pioneer 11 in the neighborhood of the F ring. Angular momentum drain might account for the slow rotations of intermediate sized asteroids. Much of the Jovian ring structure can be understood in terms of debris loss from satellites, rapid orbital evolution, resonance, and charged dust dynamics.

Burns, J. A.↗

NASA NTRS1991

Nonlinear penetration of whistler pulses into collisional plasmas via conductivity modifications

A strong electromagnetic impulse (about 0.2 microsec) with central frequency in the whistler-wave regime is applied to a large laboratory plasma dominated by Coulomb collisions. Local electron heating at the antenna and transport along B0 create a channel of high conductivity along which the whistler pulse penetrates with little damping. Because of its rapid temporal evolution, this new form of modulational instability does not involve ducting by density gradients which require ion time scales to develop.

Urrutia, J. M.↗

NASA NTRS1992

The breakup of a meteorite parent body and the delivery of meteorites to earth

Whether many of the 10,000 meteorites collected in the Antarctic are unlike those falling elsewhere is contentious. The Antarctic H chondrites, one of the major classes of stony meteorites, include a number of individuals with higher induced thermoluminescence peak temperatures than observed among non-Antarctic H chondrites. The proportion of such individuals decreases with the mean terrestrial age of the meteorites at the various ice fields. These H chondrites have cosmic-ray exposure ages of about 8 million years, experienced little cosmic-ray shielding, and suffered rapid postmetamorphic cooling. Breakup of the H chondrite parent body, 8 million years ago, may have produced two types of material with different size distributions and thermal histories. The smaller objects reached earth more rapidly through more rapid orbital evolution.

Benoit, Paul H.↗

NASA NTRS1993

Deep, wide-field, multi-band imaging of z approximately equal to 0.4 clusters and their environs

The existence of an excess population of blue galaxies in the cores of distant, rich clusters of galaxies, commonly referred to as the 'Butcher-Oemler' effect is now well established. Spectroscopy of clusters at z = 0.2-0.4 has confirmed that the luminous blue populations comprise as much as 20 percent of these clusters. This fraction is much higher that the 2 percent blue fraction found for nearby rich clusters, such as Coma, indicating that rapid galaxy evolution has occurred on a relatively short time scale. Spectroscopy has also shown that the 'blue' galaxies can basically be divided into three classes: 'starburst' galaxies with large (O II) equivalent widths, 'post-starburst' E+A galaxies (i.e. galaxies with strong Balmer lines shortward of 4000A but elliptical-like colors, and normal spiral/irregulars. Unfortunately, it is difficult to obtain enough spectra of individual galaxies in these intermediate redshift clusters to say anything statistically meaningful. Thus, limited information is available about the relative numbers of these three classes of 'blue' galaxies and the associated E/SO population in these intermediate redshift clusters. More statistically meaningful results can be derived from deep imaging of these clusters. However, the best published data to date (e.g. MacLaren et al. 1988; Dressler & Gunn 1992) are limited to the cluster cores and do not sample the galaxy luminosity functions very deeply at the bluest wavelengths. Furthermore, only limited spectro-energy distribution data is available below 4000A in the observed cluster rest frame providing limited sensitivity to 'recent' star formation activity. To improve this situation, we are currently obtaining deep, wide-field UBRI images of all known rich clusters at z approx. equals 0.4. Our main objective is to obtain the necessary color information to distinguish between the E+SO, 'E+A', and spiral/irregular galaxy populations throughout the cluster/supercluster complex. At this redshift, UBRI correspond to rest-frame 2500A/UVR bandpasses. The rest-frame UVR system provides a powerful 'blue' galaxy discriminate given the expected color distribution. Moreover, since 'hot' stars peak near 2500A, that bandpass is a powerful probe of recent star formation activity in all classes of galaxies. In particular, it is sensitive to ellipticals with 'UV excess' populations (MacLaren et al. 1988).

Silva, David R.↗

NASA NTRS1993

Stellar black holes in globular clusters

The recent discovery of large populations of millisec pulsars associated with neutron stars in globular clusters indicates that several hundred stellar black holes of about 10 solar masses each can form within a typical cluster. While, in clusters of high central density, the rapid dynamical evolution of the black-hole population leads to an ejection of nearly all holes on a short timescale, systems of intermediate density may involve a normal star's capture by one of the surviving holes to form a low-mass X-ray binary. One or more such binaries may be found in the globular clusters surrounding our galaxy.

Kulkarni, S. R.↗

NASA NTRS2007

Testing Prospects for Reliable Diatom Nanotechnology in Microgravity

The worldwide effort to grow nanotechnology, rather than use lithography, focuses on diatoms, single cell eukaryotic algae with ornate silica shells, which can be replaced by oxides and ceramics, or reduced to elemental silicon, to create complex nanostructures with compositions of industrial and electronics importance. Diatoms produce an enormous variety of structures, some of which are microtubule dependent and perhaps sensitive to microgravity. The NASA Single Loop for Cell Culture (SLCC) for culturing and observing microorganisms permits inexpensive, low labor in-space experiments. We propose to send up to the International Space Station diatom cultures of the three diatom species whose genomes are being sequenced, plus the giant diatoms of Antarctica (up to 2 mm diameter for a single cell) and the unique colonial diatom, Bacillaria paradoxa. Bacillaria cells move against each other in partial synchrony, like a sliding deck of cards, by a microfluidics mechanism. Will normal diatoms have aberrant pattern and shape or motility compared to ground controls? The generation time is typically one day, so that many generations may be examined from one flight. Rapid, directed evolution may be possible running the SLCC as a compustat. The shell shapes and patterns are preserved in hard silica, so that the progress of normal and aberrant morphogenesis may be followed by drying samples on a moving filter paper "diatom tape recorder". With a biodiversity of 100,000 distinct species, diatom nanotechnology may offer a compact and portable nanotechnology toolkit for exploration anywhere.

Gordon, Richard↗

NASA NTRS2004

Sensor Web Dynamic Measurement Techniques and Adaptive Observing Strategies

Sensor Web observing systems may have the potential to significantly improve our ability to monitor, understand, and predict the evolution of rapidly evolving, transient, or variable environmental features and events. This improvement will come about by integrating novel data collection techniques, new or improved instruments, emerging communications technologies and protocols, sensor mark-up languages, and interoperable planning and scheduling systems. In contrast to today's observing systems, "event-driven" sensor webs will synthesize real- or near-real time measurements and information from other platforms and then react by reconfiguring the platforms and instruments to invoke new measurement modes and adaptive observation strategies. Similarly, "model-driven" sensor webs will utilize environmental prediction models to initiate targeted sensor measurements or to use a new observing strategy. The sensor web concept contrasts with today's data collection techniques and observing system operations concepts where independent measurements are made by remote sensing and in situ platforms that do not share, and therefore cannot act upon, potentially useful complementary sensor measurement data and platform state information. This presentation describes NASA's view of event-driven and model-driven Sensor Webs and highlights several research and development activities at the Goddard Space Flight Center.

Talabac, Stephen J.↗

NASA NTRS2019

Nasa GeneLab Computomics Reveal Horizontal Gene Transfer on International Space Station Environmental Metagenomes

Prokaryotic lifeforms can be observed to demonstrate many keen adaptive advantages, perhaps facilitated by a nature simplistic relative to divergent domains of life. In particular, decompartmentalized gene expression facilitates adaptation by allowing free exchange of genetic material, albeit at the cost of increased susceptibility to genetic damage. Thus, these lifeforms must compensate by embracing diverse investment strategies in an attempt to “brute force” the evolvability equation through precipitous genesis, lean metabolic efficiency, and sheer population. This prokaryotic archetype also enables symbiotic relationships with secondary mobile genetic elements known as plasmids, which have been shown to drive evolution on rapid temporal scales through processes such as conjugation and transformation. This study attempts to decipher whether these mechanisms of horizontal gene transfer (HGT) are major factors in determining prokaryote fitness within a unique isolated environment, the International Space Station (ISS). The ISS Microbial Tracking (MT) project has generated a wealth of data concerning the successive reigns of microbial genera that appear to thrive amidst harsh conditions for life. Despite relatively higher doses of ionizing radiation as compared to Earth, complications associated with microgravity, and the anti-microbial mélange deployed, microbial life still persists in this environment. The NASA GeneLab serves as a data repository and analysis platform to enable researchers to access space flight factor related data. With the use of GeneLab’s modern computational suites (computomics), phylogenetic and functional genomic investigations of HGT events were conducted on the data generated from the MT-1 project. The putative data concerning the plasmid population (plasmidome) of the ISS was algorithmically derived and compared to those of habitats with similar environmental dynamics- such as living quarters and hospitals- to investigate whether these HGT elements may play crucial role(s) in shaping the microbiome of this closed habitat that serves as the only inhabited structure in space.

Bense, Nicholas↗

NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗

NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗

NASA NTRS1985

Rapid Solidification of Magnetic Oxides

The enhanced control over microstructural evolution inherent in rapid solidification processing techniques are exploited to create novel ceramic magnetic materials. The great sensitivity of magnetic properties to local structure provides a powerful probe both for the study of structure and of microscopic solidification mechanisms. The first system studied is the SrO-Fe2O3 binary, which contains the commercially important hard magnetic compound strontium hexaferrite. The products were analyzed by transmission electron microscopy, Mossbauer spectroscopy, magnetic measurements, and differential thermal analysis. As-quenched ribbons contain high concentrations of super-paramagnetic particles, 80 to 250 Angstroms in diameter, in a glassy matrix. This suggests the possibility of crystallizing monodomain strontium hexaferrite during subsequent heat treatment, with a resulting increase in coercivity over conventionally processed ferrite magnets. That magnetic properties can be controlled in solidification processing by varying the quench rate is demonstrated.

Kalonji, G.↗

NASA NTRS1990

Impact constraints on the environment for chemical evolution and the continuity of life

The moon and the earth were bombarded heavily by planetesimals and asteroids that were capable of interfering with chemical evolution and the origin of life. This paper explores the frequency of giant terrestrial impacts able to stop prebiotic chemistry in the probable regions of chemical evolution. The limited time available between impacts disruptive to prebiotic chemistry at the time of the oldest evidence of life suggests the need for a rapid process for chemical evolution of life. On the other hand, rapid chemical evolution in cloud systems and lakes or other shallow evaporating water bodies would have been possible because reactants could have been concentrated and polymerized rapidly in this environment. Thus life probably could have originated near the surface between frequent surface-sterilizing impacts. There may not have been continuity of life depending on sunlight because there is evidence that life, existing as early as 3.8 Gyr ago, may have been destroyed by giant impacts. The first such organisms on earth were probably not the ancestors of present life.

Oberbeck, Verne R.↗

NASA NTRS1991

Prebiotic chemistry in clouds

The chemical evolution hypothesis of Woese (1979), according to which prebiotic reactions occurred rapidly in droplets in giant atmospheric reflux columns was criticized by Scherer (1985). This paper proposes a mechanism for prebiotic chemistry in clouds that answers Scherer's concerns and supports Woese's hypothesis. According to this mechanism, rapid prebiotic chemical evolution was facilitated on the primordial earth by cycles of condensation and evaporation of cloud drops containing clay condensation nuclei and nonvolatile monomers. For example, amino acids supplied by, or synthesized during entry of meteorites, comets, and interplanetary dust, would have been scavenged by cloud drops containing clay condensation nuclei and would be polymerized within cloud systems during cycles of condensation, freezing, melting, and evaporation of cloud drops.

Oberbeck, Verne R.↗

NASA NTRS2016

Recent Variability Observations of Solar System Giant Planets: Fresh Context for Understanding Exoplanet and Brown Dwarf Weather

Over the past several years a number of high cadence photometric observations of solar system giant planets have been acquired by various platforms. Such observations are of interest as they provide points of comparison to the already expansive set of brown dwarf variability observations and the small, but growing, set of exoplanet variability observations. By measuring how rapidly the integrated light from solar system giant planets can evolve, variability observations of substellar objects that are unlikely to ever be resolved can be placed in a fuller context. Examples of brown dwarf variability observations include extensive work from the ground (e.g., Radigen et al. 2014), Spitzer (e.g., Metchev et al. 2015), Kepler (Gizis et al. 2015), and HST (Yang et al. 2015).Variability has been measured on the planetary mass companion to the brown dwarf 2MASS 1207b (Zhou et al. 2016) and further searches are planned in thermal emission for the known directly imaged planets with ground based telescopes (Apai et al. 2016) and in reflected light with future space based telescopes. Recent solar system variability observations include Kepler monitoring of Neptune (Simon et al. 2016) and Uranus, Spitzer observations of Neptune (Stauffer et al. 2016), and Cassini observations of Jupiter (West et al. in prep). The Cassini observations are of particular interest as they measured the variability of Jupiter at a phase angle of approximately 60 deg, comparable to the viewing geometry expected for space based direct imaging of cool extrasolar Jupiters in reflected light. These solar system analog observations capture many of the characteristics seen in brown dwarf variability, including large amplitudes and rapid light curve evolution on timescales as short as a few rotation periods. Simon et al. (2016) attribute such variations at Neptune to a combination of large scale, stable cloud structures along with smaller, more rapidly varying, cloud patches. The observed brown dwarf and exoplanet variability may well arise from comparable cloud structures. In my presentation I will compare and contrast the nature of the variability observed for the various solar system and other substelar objects and present a wish list for future observations.

giant planets↗

NASA NTRS2019

Hybrid Simulation of Solar-Wind-Like Turbulence

We present 2.5D hybrid simulations of the spectral and thermodynamic evolution of an initial state of magnetic field and plasma variables that in many ways represents solar wind fluctuations. In accordance with Helios near-Sun high-speed stream observations, we start with Alfvénic fluctuations along a mean magnetic field in which the fluctuations in the magnitude of the magnetic field are minimized. Since fluctuations in the radial flow speed are the dominant free energy in the observed fluctuations, we include a field-aligned v∥(k⊥) with an k(exp −1) spectrum of velocity fluctuations to drive the turbulent evolution. The flow rapidly distorts the Alfvénic fluctuations, yielding spectra (determined by spacecraft-like cuts) transverse to the field that become comparable to the k∥ fluctuations, as in spacecraft observations. The initial near constancy of the magnetic field is lost during the evolution; we show this also takes place observationally. We find some evolution in the anisotropy of the thermal fluctuations, consistent with expectations based on Helios data. We present 2D spectra of the fluctuations, showing the evolution of the power spectrum and cross-helicity. Despite simplifying assumptions, many aspects of simulations and observations agree. The greatly faster evolution in the simulations is at least in part due to the small scales being simulated, but also to the non-equilibrium initial conditions and the relatively low overall Alfvénicity of the initial fluctuations.

Roberts, D. Aaron↗