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At least 145 records · Page 8

Monitoring SARS-CoV-2 in wastewater [Slides]

The monitoring of SARS-CoV-2 through individual testing is subject to inaccuracies. Wastewater biosurveillance has been used around the world to detect the presence of drugs, viruses, and other chemicals present in a population. Fecal shedding of SARS-CoV-2 implies that wastewater can be analyzed in order to detect varying levels of the virus within a given community. Pepper Mild Mottle Virus is present consistently in human fecal matter, and can be used to normalize the amount of SARS-CoV-2 detected. In this experiment, the amount of SARS-CoV-2 in the wastewater sample was compared to the amount of PMMoV present. Wastewater samples were separated into three fractions: direct wastewater, a solid pellet, and filter paper extract. An RT-qPCR test was used on the extracted RNA from each fraction to detect the relative amount of SARS-CoV-2 and PMMoV copies in each sample. The amount of SARS-CoV-2 was successfully normalized to the amount of PMMoV.

59 BASIC BIOLOGICAL SCIENCES↗

Substantial differences in soil viral community composition within and among four Northern California habitats

Abstract Viruses contribute to food web dynamics and nutrient cycles in diverse ecosystems, yet the biogeographical patterns that underlie these viral dynamics are poorly understood, particularly in soil. Here, we identified trends in soil viral community composition in relation to habitat, moisture content, and physical distance. We generated 30 soil viromes from four distinct habitats (wetlands, grasslands, woodlands, and chaparral) by selectively capturing virus-sized particles prior to DNA extraction, and we recovered 3432 unique viral ‘species’ (dsDNA vOTUs). Viral communities differed significantly by soil moisture content, with viral richness generally higher in wet compared to dry soil habitats. However, vOTUs were rarely shared between viromes, including replicates <10 m apart, suggesting that soil viruses may not disperse well and that future soil viral community sampling strategies may need to account for extreme community differences over small spatial scales. Of the 19% of vOTUs detected in more than one virome, 93% were from the same habitat and site, suggesting greater viral community similarity in closer proximity and under similar environmental conditions. Within-habitat differences indicate that extensive sampling would be required for rigorous cross-habitat comparisons, and results highlight emerging paradigms of high viral activity in wet soils and soil viral community spatial heterogeneity.

Durham, Devyn M.↗

Leafy Greens Grown on the International Space Station May Provide a Nutritious Supplement to Astronauts' Diet

Supplemental safe food production has been an essential goal of NASA to meet the nutritional needs of astronauts on the International Space Station (ISS) as well as for future long duration missions to the moon and beyond. Food crops grown in space experience different environmental conditions than plants grown on Earth (i.e. microgravity and spaceflight physical sciences impacts). To test the growth methods and effects of the space environment, red romaine lettuce Lactuca sativa cv. 'Outredgeous', was grown in Veggie plant growth chambers on the ISS. Microbiological food safety of the plants grown on the ISS was determined by heterotrophic plate counts to assess total microbial load for bacteria and fungi as well as screening for specific pathogens and isolate identification. Molecular characterization was completed using Next Generation Sequencing (NGS) to provide valuable information on the taxonomic composition and community structure of the plant microbiome. Chemical analyses of plant tissue were conducted to understand spaceflight-induced changes in key elements in the space diet, phenolics, anthocyanin levels, and Oxygen radical absorbance capacity (ORAC), a measure of antioxidant capacity. Three growth tests of red romaine lettuce were completed on ISS, VEG-01A, VEG-01B, and VEG-03A. Plants were harvested using two harvest methods, either a single terminal harvest (after 33 days) or cut-and-come-again repetitive harvesting (64 days total growth). Ground controls were grown simultaneously with a delay to accommodate condition monitoring and replication. A comparison of the plant tissue returned to Earth showed leaves from the second grow-out had significantly higher bacterial counts than the preceding or subsequent growth test or any of the ground controls. Fungal counts were significantly higher on the final cut-and-come-again harvest of the third grow out. None of the potential foodborne pathogens that were screened for were detected. Bacterial and fungal isolate identification and community characterization indicated similar diversity between VEG-01A and VEG-01B growth tests, however, there appeared to be subtle differences in diversity and distribution among the three growth tests. Chemical analysis of plant tissue revealed significant variation in a few elemental data, but variation in levels of phenolics, anthocyanins, and ORAC was not significantly different. This study indicated that leafy vegetable crops could safely provide an edible supplement to astronauts' diet, and our analysis provided baseline data for continual operation of the Veggie plant growth units on ISS. This research was funded by NASA's space biology program.

Food Production↗

Inventory of forest and rangeland and detection of forest stress

The author has identified the following significant results. Eucalyptus tree stands killed by low temperatures in December 1972 were outlined by image enhancement of two separate dates of ERTS-1 images (January 22, 1973-I.D. 1183-18175 and April 22, 1973-I.D. 1273-18183). Three stands larger than 500 meters in size were detected very accurately. In Colorado, range and grassland communities were analyzed by visual interpretation of color composite scene I.D. 1028-17135. It was found that mixtures of plant litter, amount and kind of bare soil, and plant foliage cover made classification of grasslands very difficult. Changes in forest land use were detected on areas as small as 5 acres when ERTS-1 color composite scene 1264-15445 (April 13, 1973) was compared with 1966 ASCS index mosaics (scale 1:60,000). Verification of the changes were made from RB-57 underflight CIR transparencies (scale 1:120,000).

Heller, R. C.↗

A Sterile Robotic Mars Soil Analyzer

Since the 1976 Viking Mission to Mars, follow-on efforts to resolve its controversial life detection results have been thwarted by two heretofore insurmountable difficulties: the huge expense of sterilizing the entire spacecraft to protect the integrity of life detection experiments; and the lack of a practical robotic life detection package that could produce results acceptable as unambiguous by the scientific community. We here present a method that assures sterility and the complete integrity of robotic life detection experiments, all at a negligible cost. Second, we propose a candidate set of integrated, highly sensitive experiments that we believe could produce results acceptable to the vast majority of scientists. In addition to the biology-chemistry issue, the extensively debated oxidative state of the Martian surface and other chemical and physical characteristics of the Martian soil would be determined. We present our concept for a miniaturized instrument that could carry out a number of candidate experiments to achieve the objective.

Gilbert V Levin↗

Acoustic space occupancy: Combining ecoacoustics and lidar to model biodiversity variation and detection bias across heterogeneous landscapes

There is global interest in quantifying changing biodiversity in human-modified landscapes. Ecoacoustics may offer a promising pathway for supporting multi-taxa monitoring, but its scalability has been hampered by the sonic complexity of biodiverse ecosystems and the imperfect detectability of animal-generated sounds. The acoustic signature of a habitat, or soundscape, contains information about multiple taxa and may circumvent species identification, but robust statistical technology for characterizing community-level attributes is lacking. Here, we present the Acoustic Space Occupancy Model, a flexible hierarchical framework designed to account for detection artifacts from acoustic surveys in order to model biologically relevant variation in acoustic space use among community assemblages. We illustrate its utility in a biologically and structurally diverse Amazon frontier forest landscape, a valuable test case for modeling biodiversity variation and acoustic attenuation from vegetation density. We use complementary airborne lidar data to capture aspects of 3D forest structure hypothesized to influence community composition and acoustic signal detection. Our novel analytic framework permitted us to model both the assembly and detectability of soundscapes using lidar-derived estimates of forest structure. Our empirical predictions were consistent with physical models of frequency-dependent attenuation, and we estimated that the probability of observing animal activity in the frequency channel most vulnerable to acoustic attenuation varied by over 60%, depending on vegetation density. There were also large differences in the biotic use of acoustic space predicted for intact and degraded forest habitats, with notable differences in the soundscape channels predominantly occupied by insects. This study advances the utility of ecoacoustics by providing a robust modeling framework for addressing detection bias from remote audio surveys while preserving the rich dimensionality of soundscape data, which may be critical for inferring biological patterns pertinent to multiple taxonomic groups in the tropics. Our methodology paves the way for greater integration of remotely sensed observations with high-throughput biodiversity data to help bring routine, multi-taxa monitoring to scale in dynamic and diverse landscapes.

Airborne lidar↗

Long-term warming in a Mediterranean-type grassland affects soil bacterial functional potential but not bacterial taxonomic composition

Abstract Climate warming is known to impact ecosystem composition and functioning. However, it remains largely unclear how soil microbial communities respond to long-term, moderate warming. In this study, we used Illumina sequencing and microarrays (GeoChip 5.0) to analyze taxonomic and functional gene compositions of the soil microbial community after 14 years of warming (at 0.8–1.0 °C for 10 years and then 1.5–2.0 °C for 4 years) in a Californian grassland. Long-term warming had no detectable effect on the taxonomic composition of soil bacterial community, nor on any plant or abiotic soil variables. In contrast, functional gene compositions differed between warming and control for bacterial, archaeal, and fungal communities. Functional genes associated with labile carbon (C) degradation increased in relative abundance in the warming treatment, whereas those associated with recalcitrant C degradation decreased. A number of functional genes associated with nitrogen (N) cycling (e.g., denitrifying genes encoding nitrate-, nitrite-, and nitrous oxidereductases) decreased, whereas nifH gene encoding nitrogenase increased in the warming treatment. These results suggest that microbial functional potentials are more sensitive to long-term moderate warming than the taxonomic composition of microbial community.

59 BASIC BIOLOGICAL SCIENCES↗

Imagery Applications for Advanced Event Analytics (WBS 24.3.1.3.3-IDC FY202 Final Project Report)

Accurate event locations and replicability of location analyses are essential for assessing the nature of an event, its context, ambient site conditions, and proximity to relevant facilities and infrastructure. Additionally, accurate event locations provide valuable information that reduce uncertainties, improve confidence in event analyses, and inform in-field verification activities. However, event location/relocation and replicability are difficult due to a number of factors, including spatially-sparse network coverage in some areas of the globe and variability in seismic data processing. This team proposed that the incorporation of high-fidelity imagery as a data backbone to the analytical assessment of a suspected underground explosion and/or an advanced seismic event bulletin produced by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) could reduce uncertainties and improve confidence in analyses. Specifically, temporally-separated images can reduce uncertainty by identifying areas where change has occurred (e.g., building construction or demolition, road or facilities improvements). The primary goal of this project was to develop an automated geospatial processing script for imagery change detection to better reflect needs of the technical community (including the IDC) and to make the use of such a tool accessible in a variety of settings across platforms. Technical experts at Los Alamos National Laboratory successfully built GAIA: the Geospatial Automated Imagery Analysis tool, to fill this need. GAIA combines five tool components to produce orthorectified time separated imagery and imagery change detection maps. Our toolkit (1) reduces error by providing a standardized workflow for image analyses and (2) significantly reduces processing time from between 7 and 24+ hours to approximately 5 minutes. Technical experts at Sandia National Laboratories supported GAIA via beta-testing and by introducing a web-based system approach for increased applicability. To test the function, performance, broad application, and ease-of-use of GAIA, we applied it to four separate test cases. The results of this preliminary investigation show promise in reducing uncertainty in seismic event locations: if satellite imagery can show regions where operations that produce seismic activity likely occurred, then pursuing imagery to locate epicenters of seismic nuclear events could reduce the time needed to find the true epicenter location.

58 GEOSCIENCES↗

Experimental warming accelerates positive soil priming in a temperate grassland ecosystem

Abstract Unravelling biosphere feedback mechanisms is crucial for predicting the impacts of global warming. Soil priming, an effect of fresh plant-derived carbon (C) on native soil organic carbon (SOC) decomposition, is a key feedback mechanism that could release large amounts of soil C into the atmosphere. However, the impacts of climate warming on soil priming remain elusive. Here, we show that experimental warming accelerates soil priming by 12.7% in a temperate grassland. Warming alters bacterial communities, with 38% of unique active phylotypes detected under warming. The functional genes essential for soil C decomposition are also stimulated, which could be linked to priming effects. We incorporate lab-derived information into an ecosystem model showing that model parameter uncertainty can be reduced by 32–37%. Model simulations from 2010 to 2016 indicate an increase in soil C decomposition under warming, with a 9.1% rise in priming-induced CO 2 emissions. If our findings can be generalized to other ecosystems over an extended period of time, soil priming could play an important role in terrestrial C cycle feedbacks and climate change.

54 ENVIRONMENTAL SCIENCES↗

LumaCam: a novel class of position-sensitive event mode particle detectors using scintillator screens

A new type of position-sensitive detectors is gaining attention in the neutron community. They are scintillator based detectors that detect the scintillation light on an individual photon basis via an image intensifier and a fast image sensor. Their readout operates in event mode i.e. it produces information about individual neutron interactions, reconstructed from the sensor data, thus enabling to achieve superior spatial and temporal resolutions compared to regular detectors. Although the development of current detectors is focused on neutrons, the concept is also applicable to the detection of other particles such as high-energy photons. This document provides a description on how these detectors are built, how they operate, and what their characteristics are. An example of a detector implementation based on a Timepix3 chip is described to illustrate the detector concept. This includes a detailed description of the algorithm that reconstructs the neutron interactions from the sensor data, one of the core components that sets it apart from established scintillator-based imaging detectors. Energy-resolved epithermal neutron radiography was performed at the ISIS EMMA beamline with this detector, illustrating some of the fundamental differences in the data that can be produced with the new type of detector compared to more established types of scintillator based neutron detectors. The term LumaCam is proposed to refer to this new class of position-sensitive event-mode detectors.

47 OTHER INSTRUMENTATION↗

Imagery Applications for Advanced Event Analytics (WBS 24.3.1.3.3-IDC FY2020 Final Project Report)

Accurate event locations and replicability of location analyses are essential for assessing the nature of an event, its context, ambient site conditions, and proximity to relevant facilities and infrastructure. Additionally, accurate event locations provide valuable information that reduce uncertainties, improve confidence in event analyses, and inform in-field verification activities. However, event location/relocation and replicability are difficult due to a number of factors, including spatially-sparse network coverage in some areas of the globe and variability in seismic data processing. This team proposed that the incorporation of high-fidelity imagery as a data backbone to the analytical assessment of a suspected underground explosion and/or an advanced seismic event bulletin produced by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) could reduce uncertainties and improve confidence in analyses. Specifically, temporally-separated images can reduce uncertainty by identifying areas where change has occurred (e.g., building construction or demolition, road or facilities improvements). The primary goal of this project was to develop an automated geospatial processing script for imagery change detection to better reflect needs of the technical community (including the IDC) and to make the use of such a tool accessible in a variety of settings across platforms. Technical experts at Los Alamos National Laboratory successfully built GAIA: the Geospatial Automated Imagery Analysis tool, to fill this need. GAIA combines five tool components to produce orthorectified time-separated imagery and imagery change detection maps. Our toolkit (1) reduces error by providing a standardized workflow for image analyses and (2) significantly reduces processing time from between 7 and 24+ hours to approximately 5 minutes. Technical experts at Sandia National Laboratories supported GAIA via beta-testing and by introducing a web-based system approach for increased applicability. To test the function, performance, broad application, and ease-of-use of GAIA, we applied it to four separate test cases. The results of this preliminary investigation show promise in reducing uncertainty in seismic event locations: if satellite imagery can show regions where operations that produce seismic activity likely occurred, then pursuing imagery to locate epicenters of seismic nuclear events could reduce the time needed to find the true epicenter location.

58 GEOSCIENCES↗

The effects of history and predictive information on the ability of the transport aircraft pilot to predict an alert

The early detection of a developing aircraft-subsystem fault has the potential to lessen its ultimate severity. The lack of capability for such early detection is becoming critical in the aviation community. In the commercial sector, for example, twin-engine aircraft are being used for extended transport operations over water. One method to decrease the severity of a developing problem is to predict its behavior and to take appropriate corrective action. In order to investigate pilots' ability to predict events, an experiment was conducted where eighteen airline pilots predicted the time to an alert using three different displays of dials and three different time profile complexities. The three displays of dials were as follows: standard, resembling current aircraft dial presentations; history, indicating the value five seconds in the past; and predictive, indicating the value five seconds into the future. The time profiles describing the behavior of the parameter consisted of constant velocity profiles, decelerating profiles, and accelerating then decelerating profiles. Although pilots indicated that they preferred the predictive dial, the objective data did not support its use. The objective data did show that the time profiles had the most significant effect on performance in estimating the time to an alert.

Trujillo, Anna C.↗

Community-level physiological profiling performed with an oxygen-sensitive fluorophore in a microtiter plate

Community-level physiological profiling based upon fluorometric detection of oxygen consumption was performed on hydroponic rhizosphere and salt marsh litter samples by using substrate levels as low as 50 ppm with incubation times between 5 and 24 h. The rate and extent of response were increased in samples acclimated to specific substrates and were reduced by limiting nitrogen availability in the wells.

NASA Discipline Life Support Systems↗

Noninvasive Medical Diagnostics & Treatment Using Ultrasonics

In parallel to the industrial application of NDE to flaw detection and material property determination, the medical community has succesfully adapted such methods to the noninvasaive diagnostics and treatment of many conditions and disorders of the human body.

NDE noninvasive diagnostics destruction of blood c↗

Directed Design of Experiments (DOE) for Determining Probability of Detection (POD) Capability of NDE Systems (DOEPOD)

This viewgraph presentation reviews some of the problems that are encountered by designers of Non-Destructive Examination (NDE) have in determining the probability of detection. According to the author "[the] NDE community should not blindly accept statistical results due to lack of knowledge." This is an attempt to bridge the gap between people doing NDE, and statisticians.

Generazio, Edward R.↗

Resilience of Alaska's Boreal Forest to Climatic Change

This paper assesses the resilience of Alaska s boreal forest system to rapid climatic change. Recent warming is associated with reduced growth of dominant tree species, plant disease and insect outbreaks, warming and thawing of permafrost, drying of lakes, increased wildfire extent, increased postfire recruitment of deciduous trees, and reduced safety of hunters traveling on river ice. These changes have modified key structural features, feedbacks, and interactions in the boreal forest, including reduced effects of upland permafrost on regional hydrology, expansion of boreal forest into tundra, and amplification of climate warming because of reduced albedo (shorter winter season) and carbon release from wildfires. Other temperature-sensitive processes for which no trends have been detected include composition of plant and microbial communities, long-term landscape-scale change in carbon stocks, stream discharge, mammalian population dynamics, and river access and subsistence opportunities for rural indigenous communities. Projections of continued warming suggest that Alaska s boreal forest will undergo significant functional and structural changes within the next few decades that are unprecedented in the last 6000 years. The impact of these social ecological changes will depend in part on the extent of landscape reorganization between uplands and lowlands and on policies regulating subsistence opportunities for rural communities.

Chapin, F. S., III↗

Merged and Gridded GPM and Atmospheric River Data Product

The Global Precipitation Measurement (GPM) Mission Core Observatory satellite launched in 2014 as a joint mission between National Aeronautics and Space Administration (NASA) and JAXA. Global Precipitation Measurement (GPM) has, since that time, provided continuous, valuable dual-frequency radar and passive microwave radiometer observations. Here, we introduce a gridded data set of collocated GPM Core Observatory observational products merged with a reanalysis-derived Atmospheric river (AR) data set in the North Atlantic and North Pacific sectors. The three data sets that are merged and gridded are: (a) the NASA Goddard Profiling (GPROF) precipitation product, which uses GPM passive microwave radiometer observations to derive surface precipitation rates, (b) a water vapor data product derived from the GPM Core Observatory radiometer, provided by Remote Sensing Systems (RSS), and (c) the Mattingly et al. (2018, https://doi.org/10.1029/2018jd028714) AR data set that is specifically tuned to the high-latitude regions. This novel merged data set spans from May 2014 to December 2022 with plans to update annually through 2026 at minimum. This gridded product combines RSS passive water vapor and precipitation estimates with coincident AR detection. This data product benefits the scientific community by providing (a) user-friendly gridded satellite data compared to standard satellite data sets, while maintaining high temporal resolution, and (b) coincident satellite observations to assess the link between ARs and precipitation.

Marian E Mateling↗

Detector Materials Scoping Study: Research and Development Recommendations

Radiation detection materials have a unique role in many nuclear security missions. The variety of different applications requires the use of different materials whose characteristics are determined by the specific application requirements. While baseline capabilities have been established to use radiation detection in these applications, the potential to greatly advance those capabilities still exists through the development of superior radiation detection materials and/or the development of new materials that enable new technologies to be implemented more effectively. In 2024 the Defense Nuclear Nonproliferation Research and Development (DNN R&D) Near Field Detection Portfolio charged a detector materials scoping study, composed of a group of radiation-detection materials subject matter experts, to produce a community-wide consensus view of the current state of radiation materials research and to set recommendations for expanded investment over a ten-year time frame. This scoping study sought to understand and document the landscape of how radiation detection materials are used, what characteristics drive the selection of various materials, and what developments are needed to drive the state of the art. To respond to this charge, the scoping study created three working groups, each focusing on a different topical area in radiation detection materials research - Semiconductor Materials, Inorganic Scintillators and Organic Scintillators - with the task to identify the current state of the art in materials research and to provide mission-relevant research and development recommendations. Each working group was chaired by two members of the project team with widely recognized expertise in the field. Solicitations were sent out to experts at the DOE national laboratories, industry, academia and federal government agencies to participate in these working groups. The working groups met at regular intervals throughout 2024 and early 2025, each delivering a technical roadmap designed to enable the pursuit of R&D more intensely on high-impact materials challenges and detector solutions that are deemed as the greatest strategic value to DNN R&D and its stakeholders. The roadmap is also intended to help communicate recommended programmatic priorities within DNN R&D and across the nonproliferation and research communities.

36 MATERIALS SCIENCE↗