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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Emergence of nosocomial associated opportunistic pathogens in the gut microbiome after antibiotic treatment

Introduction: According to the Centers for Disease Control’s 2015 Hospital Acquired Infection Hospital Prevalence Survey, 1 in 31 hospital patients was infected with at least one nosocomial pathogen while being treated for unrelated issues. Many studies associate antibiotic administration with nosocomial infection occurrence. However, to our knowledge, there is little to no direct evidence of antibiotic administration selecting for nosocomial opportunistic pathogens. Aim: This study aims to confirm gut microbiota shifts in an animal model of antibiotic treatment to determine whether antibiotic use favors pathogenic bacteria. Methodology: We utilized next-generation sequencing and in-house metagenomic assembly and taxonomic assignment pipelines on the fecal microbiota of a urinary tract infection mouse model with and without antibiotic treatment. Results: Antibiotic therapy decreased the number of detectable species of bacteria by at least 20-fold. Furthermore, the gut microbiota of antibiotic treated mice had a significant increase of opportunistic pathogens that have been implicated in nosocomial infections, like Acinetobacter calcoaceticus/baumannii complex, Chlamydia abortus, Bacteroides fragilis, and Bacteroides thetaiotaomicron. Moreover, antibiotic treatment selected for antibiotic resistant gene enriched subpopulations for many of these opportunistic pathogens. Conclusions: Oral antibiotic therapy may select for common opportunistic pathogens responsible for nosocomial infections. In this study opportunistic pathogens present after antibiotic therapy harbored more antibiotic resistant genes than populations of opportunistic pathogens before treatment. Our results demonstrate the effects of antibiotic therapy on induced dysbiosis and expansion of opportunistic pathogen populations and antibiotic resistant subpopulations of those pathogens. Follow-up studies with larger samples sizes and potentially controlled clinical investigations should be performed to confirm our findings.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Opportunistic experiments to constrain aerosol effective radiative forcing

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2022

Opportunistic Experiments to Constrain Aerosol Effective Radiative Forcing

Aerosol-cloud interactions (ACI) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The non-linearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well defined sources provide ‘opportunistic experiments’ (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatio-temporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors.We review the different experimental conditions and conduct a synthesis of the available satellite data sets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

Matthew W Christensen↗
DOE OSTI2020

Opportunistic Hybrid Communications Systems for Distributed PV Coordination

A full-scale, operational implementation of the opportunistic hybrid communications systems for distributed photovoltaic (PV) coordination was successfully developed, simulated, and validated in this 3-year project. The system is considered hybrid because it uses different communications pathways from the scale of residential PV inverters to a transmission network; primary technologies harnessed include Low-Power Wireless Personal Area Network (LoWPAN), Power Line Communication (PLC), WiFi mesh, Worldwide Interoperability for Microwave Access (WiMAX), Ethernet cable, and Optical Ethernet systems. It is opportunistic in that it chooses to route messages through each of these systems based on recent data about latency and availability to ensure reliable message passing.

14 SOLAR ENERGY↗
DOE OSTI2023

Opportunistic CP violation

In the electroweak sector of the Standard Model, CP violation arises through a very particular interplay between the three quark generations, as described by the Cabibbo-Kobayashi-Maskawa (CKM) mechanism and the single Jarlskog invariant J 4 . Once generalized to the Standard Model Effective Field Theory (SMEFT), this peculiar pattern gets modified by higher-dimensional operators, whose associated Wilson coefficients are usually split into CP-even and odd parts. However, CP violation at dimension four, i.e., at the lowest order in the EFT expansion, blurs this distinction: any Wilson coefficient can interfere with J 4 and mediate CP violation. In this paper, we study such interferences at first order in the SMEFT expansion, $\mathcal{O}(1/Λ^2)$, and we capture their associated parameter space via a set of 1551 linear CP-odd flavor invariants. This construction describes both new, genuinely CP-violating quantities as well as the interference between J 4 and CP-conserving ones. We call this latter possibility opportunistic CP violation. Relying on an appropriate extension of the matrix rank to Taylor expansions, which we dub Taylor rank, we define a procedure to organize the invariants in terms of their magnitude, so as to retain only the relevant ones at a given precision. We explore how this characterization changes when different assumptions are made on the flavor structure of the SMEFT coefficients. Interestingly, some of the CP-odd invariants turn out to be less suppressed than J 4 , even when they capture opportunistic CPV, demonstrating that CP-violation in the SM, at dimension 4, is accidentally small.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

A Field Guide to Corralling the Chaos: A Conceptual Framework for Using Models to Guide Opportunistic Field Studies of Natural Disturbances

Watersheds regulate biogeochemical processes and provide ecosystem services to human societies, but disturbances can fundamentally alter these processes across space and time. Determining when and where to sample to capture disturbance impacts in watersheds remains a central challenge. Manipulation studies and long-term monitoring are often constrained by scope, and opportunistic studies often lack pre-disturbance data needed to statistically determine disturbance impacts. We identify a persistent knowledge gap: the absence of a clear, transferable framework to guide opportunistic disturbance research where pre-disturbance data collection is not a feasible option. To address this gap, we present a conceptual framework that intentionally integrates modeling and empirical observation in an iterative, stepwise model–experiment workflow. We demonstrate its application through two contrasting case studies: wildfire impacts on headwater streams using a pre-disturbance preparedness approach, and saltwater flooding impacts on coastal forests using an ‘ex-post-facto’ approach. From these applications, we assess strengths, limitations, and the critical role of team science for transferability across disturbance types and study designs. Broadly, this framework offers a scalable path towards more rigorous, timely, and actionable disturbance science that can inform watershed management, hazard risk reduction, and ecosystem resilience.

Coastal Biogeochemistry↗
DOE OSTI2020

Distributed Acoustic Sensing (DAS) on Opportunistic Networks_ A Feasibility Study Utilizing Fiber Optic Infrastructure at NEON Sites for DAS

This study demonstrates the feasibility of using Distributed Acoustic Sensing (DAS) on the opportunistic optical fiber infrastructure presented by NEON (National Ecological Observatory Network) sites. The test took place at the NEON Terrestrial Site designated D10 CPER. Unlit portions of the local fiber network were successfully spliced together and optimized for length and a Silixa iDAS sensor was installed. The resulting array (composed of 12 spliced fiber runs) totaled 875m in length. Over a period of 2 weeks, we gathered a high spatial and temporal resolution data set to characterize discernable signals and understand background noise. The data set was reviewed to extract wave signatures of identifiable origin, both anthropogenic and otherwise. Continent wide distribution of these sites makes them an interesting candidate for DAS and identifying measurable signal sources informs future DAS application on opportunistic fiber networks. These observations validate the utility of both the NEON and similarly small fiber networks (<1km) for geoscience, environmental, and security DAS applications and indicate possibilities for further inquiry in methods for DAS data collection and analysis.

42 ENGINEERING↗
NASA NTRS2019

InSight/MarCO Opportunistic Multiple Spacecraft Per Antenna (OMSPA) demonstration

Opportunistic Multiple Spacecraft Per Antenna(OMSPA),maybe particularly suited to smallsats. In the concept for this technique, smallsats within the scheduled ground antenna beam of some other spacecraft, make opportunistic use of that spacecraft’s beam by transmitting “open-loop” to a recorder associated with the antenna. These transmissions get captured on the recorder and can be later retrieved, demodulated, and decoded so that the smallsats can recover their data – all without them having to schedule the antenna itself and compete with larger missions for antenna time. Widespread use of such a technique could lead to more efficient use of receiver antenna resources and result in a dramatic increase in downlink throughput. An opportunity to demonstrate the technique occurred in May 2018, when the Mars CubeSat One (MarCO) mission, consisting of two nanospacecraft (MarCO-A & B) launched alongside InSight, a NASA Mars lander mission.

Conner, Charles D.↗
DOE OSTI2023

Assessing residential activity in a home plumbing system simulator: monitoring the occurrence and relationship of major opportunistic pathogens and phagocytic amoebas

Opportunistic premise plumbing pathogens (OPPPs) have been detected in buildings’ plumbing systems causing waterborne disease outbreaks in the United States. In this study, we monitored the occurrence of OPPPs along with free-living amoeba (FLA) and investigated the effects of residential activities in a simulated home plumbing system (HPS). Water samples were collected from various locations in the HPS and analyzed for three major OPPPs: Legionella pneumophila, nontuberculous mycobacterial species (e.g., Mycobacterium avium, M. intracellulare, and M. abscessus), and Pseudomonas aeruginosa along with two groups of amoebas (Acanthamoeba and Vermamoeba vermiformis). A metagenomic approach was also used to further characterize the microbial communities. Results show that the microbial community is highly diverse with evidence of spatial and temporal structuring influenced by environmental conditions. L. pneumophila was the most prevalent pathogen (86% of samples), followed by M. intracellulare (66%) and P. aeruginosa (21%). Interestingly, M. avium and M. abscessus were not detected in any samples. The data revealed a relatively low prevalence of Acanthamoeba spp. (4%), while V. vermiformis was widely detected (81%) across all the sampling locations within the HPS. Locations with a high concentration of L. pneumophila and M. intracellulare coincided with the highest detection of V. vermiformis, suggesting the potential growth of both populations within FLA and additional protection in drinking water. After a period of stagnation lasting at least 2-weeks, the concentrations of OPPPs and amoeba immediately increased and then decreased gradually back to the baseline. Furthermore, monitoring the microbial population after drainage of the hot water tank and partial drainage of the entire HPS demonstrated no significant mitigation of the selected OPPPs. This study demonstrates that these organisms can adjust to their environment during such events and may survive in biofilms and/or grow within FLA, protecting them from stressors in the supplied water.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗
DOE OSTI2020

Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment

Although disinfection is key to infection control, the colonization patterns and resistomes of hospital-environment microbes remain underexplored. We report the first extensive genomic characterization of microbiomes, pathogens and antibiotic resistance cassettes in a tertiary-care hospital, from repeated sampling (up to 1.5 years apart) of 179 sites associated with 45 beds. Deep shotgun metagenomics unveiled distinct ecological niches of microbes and antibiotic resistance genes characterized by biofilm-forming and human-microbiome-influenced environments with corresponding patterns of spatiotemporal divergence. Quasi-metagenomics with nanopore sequencing provided thousands of high-contiguity genomes, phage and plasmid sequences (>60% novel), enabling characterization of resistome and mobilome diversity and dynamic architectures in hospital environments. Phylogenetics identified multidrug-resistant strains as being widely distributed and stably colonizing across sites. Comparisons with clinical isolates indicated that such microbes can persist in hospitals for extended periods (>8 years), to opportunistically infect patients. These findings highlight the importance of characterizing antibiotic resistance reservoirs in hospitals and establish the feasibility of systematic surveys to target resources for preventing infections.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1991

Biofilms and the survival of opportunistic pathogens in recycled water

Microorganisms are likely to develop an organic film on pipes, water reservoirs and filters used for waste water reclamation during extended missions in space. These biofilms can serve to protect and concentrate potentially pathogenic microorganisms. Our investigation has emphasized the survival strategy of opportunistic pathogenic bacteria in distilled water. Pseudomonas aeruginosa and Staphylococcus aureus were used as test organisms. Cultures were incubated at 10 degrees, 25 degrees, and 37 degrees C. No viable Staphylococcus cells were detected after the first week of incubation. P. aeruginosa, however, survived in distilled water up to 5 months at all three temperatures tested. The starved cells were able to form a biofilm layer on stainless steel. The cells exhibited a negative surface charge. The charge may be involved in the adhesion of this bacterium to metal substrata. We are currently investigating the importance of adhesion in the survival of this and other potential human pathogens found in water recycling systems.

NASA Discipline Life Support Systems↗
NASA NTRS2004

Planning for rover opportunistic science

The Mars Exploration Rover Spirit recently set a record for the furthest distance traveled in a single sol on Mars. Future planetary exploration missions are expected to use even longer drives to position rovers in areas of high scientific interest. This increase provides the potential for a large rise in the number of new science collection opportunities as the rover traverses the Martian surface. In this paper, we describe the OASIS system, which provides autonomous capabilities for dynamically identifying and pursuing these science opportunities during longrange traverses. OASIS uses machine learning and planning and scheduling techniques to address this goal. Machine learning techniques are applied to analyze data as it is collected and quickly determine new science gods and priorities on these goals. Planning and scheduling techniques are used to alter the behavior of the rover so that new science measurements can be performed while still obeying resource and other mission constraints. We will introduce OASIS and describe how planning and scheduling algorithms support opportunistic science.

artificial intelligence↗
NASA NTRS2006

Opportunistic Planning and Execution for Planetary Exploration

We are developing technologies to increase the autonomous capabilities of future rover missions. Our objectives are to make rovers easier to command and to enable them to make more effective use of rover resources when problems arise or when things go better than expected. We will demonstrate OASIS (Onboard Analysis Science Investigation System) which combined planning and scheduling techniques with machine learning to enable rovers to perform robust and opportunistic science operations.

autonomous planning↗
NASA NTRS2010

Robust and Opportunistic Autonomous Science for a Potential Titan Aerobot

We are developing onboard planning and execution technologies to provide robust and opportunistic mission operations for a potential Titan aerobot. Aerobot have the potential for collecting a vast amount of high priority science data. However, to be effective, an aerobot must address several challenges including communication constraints, extended periods without contact with Earth, uncertain and changing environmental conditions, maneuverability constraints and potentially short-lived science opportunities. We are developing the AerOASIS system to develop and test technology to support autonomous science operations for a potential Titan Aerobot. The planning and execution component of AerOASIS is able to generate mission operations plans that achieve science and engineering objectives while respecting mission and resource constraints as well as adapting the plan to respond to new science opportunities. Our technology leverages prior work on the OASIS system for autonomous rover exploration. In this paper we describe how the OASIS planning component was adapted to address the unique challenges of a Titan Aerobot and we describe a field demonstration of the system with the JPL prototype aerobot.

autonomous science↗
NASA NTRS2011

Evaluation of Robotic Systems to Carry Out Traverse Execution, Opportunistic Science, and Landing Site Evaluation Tasks

This report covers the execution of and results from the activities proposed and approved in Exploration Analogs and Mission Development (EAMD) Field Test Protocol HMP2010: Evaluation of Robotic Systems to carry out Traverse Execution, Opportunistic Science, and Landing Site Evaluation Tasks. The field tests documented in this report examine one facet of a larger program of planetary surface exploration. This program has been evolving and maturing for several years, growing from a broad policy statement with a few specified milestones for NASA to an international effort with much higher fidelity descriptions of systems and operations necessary to accomplish this type of exploration.

Hoffman, Stephen J.↗
NASA NTRS2018

Evaluation of Opportunistic Contact Graph Routing in Random Mobility Environments

Routing in networks where nodes move randomly is particularly challenging due their potentially unpredictable, and rapidly changing topology. Several routing algorithms have been presented in the literature to address the needs of such networks, most of them implementing variants of controlled network flooding in the hope of successful data delivery. In this note, we compare the results of previous routing algorithms with Opportunistic Contact Graph Routing (OCGR), an enhanced version of Contact Graph Routing (CGR) that is suitable for networks where contacts cannot always be scheduled ahead of time. To perform the benchmark, we simulate a network of nodes moving in a certain space according to the Random Waypoint Mobility Model, and then take measurements of bundle delivery probabilty and overhead ratio as metrics of performance and cost respectively. Through this exercise, we demonstrate that the performance of OCGR is highly dependent on the type of network under consideration (e.g. very sparse vs. densely connected) and the assumed mobility model.

Burleigh, Scott↗
NASA NTRS2020

Opportunistic Arraying

This paper discusses recent activities at JPL that are focused on extending the Opportunistic Multiple Spacecraft Per Antenna (OMSPA) concept to include arraying multiple antennas. Specifically, we explore the ability to process multiple open loop recordings associated with multiple antennas and perform the appropriate alignment and combining. We focus on using the symbol stream combining technique and provide examples of performance measurements on actual spacecraft signals for MarCO A and B as well as the Mars Express.

Johnstone, Andrew↗