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At least 1,495 records · Page 83

Chemotaxonomic patterns in intracellular metabolites of marine microbial plankton

Most biological diversity on Earth is contained within microbial communities. In the ocean, these communities dominate processes related to carbon fixation and nutrient recycling. Yet, specific factors that determine community composition and metabolic activity are difficult to resolve in complex microbial populations, complicating predictions of microbial processes in a changing ocean. Microbial metabolism generates small organic molecules that reflect both the biochemical and physiological diversity as well as the taxonomic specificity of these biological processes. These small molecules serve as the conduit for taxon-specific signaling and exchange. Here, we use liquid chromatography-mass spectrometry (LC-MS)-based metabolomics to taxonomically categorize 111 metabolites that include small molecules in central and secondary metabolism across 42 taxa representing numerically dominant and metabolically important lineages of microbial autotrophs and heterotrophs. Patterns in metabolite presence-absence broadly reflected taxonomic lineages. A subset of metabolites that includes osmolytes, sulfur-containing metabolites, sugars, and amino acid derivatives provided chemotaxonomic information among phytoplankton taxa. A variety of phytohormones and signaling molecules were predominantly found in the heterotrophic bacteria and archaea, expanding knowledge of metabolites implicated in modulating interactions between microbes. This chemotaxonomic inventory of marine microbial metabolites is a key step in deciphering metabolic networks that influence ocean biogeochemical cycles.

54 ENVIRONMENTAL SCIENCES↗

The molecular dimension of microbial species: 3. Comparative genomics of Synechococcus strains with different light responses and in situ diel transcription patterns of associated putative ecotypes in the Mushroom Spring microbial mat

Genomes were obtained for three closely related strains of Synechococcus that are representative of putative ecotypes (PEs) that predominate at different depths in the 1 mm-thick, upper-green layer in the 60°C mat of Mushroom Spring, Yellowstone National Park, and exhibit different light adaptation and acclimation responses. The genomes were compared to the published genome of a previously obtained, closely related strain from a neighboring spring, and differences in both gene content and orthologous gene alleles between high-light-adapted and low-light-adapted strains were identified. Evidence of genetic differences that relate to adaptation to light intensity and/or quality, CO 2 uptake, nitrogen metabolism, organic carbon metabolism, and uptake of other nutrients were found between strains of the different putative ecotypes. In situ diel transcription patterns of genes, including genes unique to either low-light-adapted or high-light-adapted strains and different alleles of an orthologous photosystem gene, revealed that expression is fine-tuned to the different light environments experienced by ecotypes prevalent at various depths in the mat. This study suggests that strains of closely related PEs have different genomic adaptations that enable them to inhabit distinct ecological niches while living in close proximity within a microbial community.

59 BASIC BIOLOGICAL SCIENCES↗

Decoding the EEG patterns induced by sequential finger movement for brain-computer interfaces

Objective In recent years, motor imagery-based brain–computer interfaces (MI-BCIs) have developed rapidly due to their great potential in neurological rehabilitation. However, the controllable instruction set limits its application in daily life. To extend the instruction set, we proposed a novel movement-intention encoding paradigm based on sequential finger movement. Approach Ten subjects participated in the offline experiment. During the experiment, they were required to press a key sequentially [i.e., Left→Left (LL), Right→Right (RR), Left→Right (LR), and Right→Left (RL)] using the left or right index finger at about 1 s intervals under an auditory prompt of 1 Hz. The movement-related cortical potential (MRCP) and event-related desynchronization (ERD) features were used to investigate the electroencephalography (EEG) variation induced by the sequential finger movement tasks. Twelve subjects participated in an online experiment to verify the feasibility of the proposed paradigm. Main results As a result, both the MRCP and ERD features showed the specific temporal–spatial EEG patterns of different sequential finger movement tasks. For the offline experiment, the average classification accuracy of the four tasks was 71.69%, with the highest accuracy of 79.26%. For the online experiment, the average accuracies were 83.33% and 82.71% for LL-versus-RR and LR-versus-RL, respectively. Significance This paper demonstrated the feasibility of the proposed sequential finger movement paradigm through offline and online experiments. This study would be helpful for optimizing the encoding method of motor-related EEG information and providing a promising approach to extending the instruction set of the movement intention-based BCIs.

Liu, Chang↗

Extracellular ATP acts as a damage-associated molecular pattern (DAMP) signal in plants

As sessile organisms, plants have evolved effective mechanisms to protect themselves from environmental stresses. Damaged (i.e., wounded) plants recognize a variety of endogenous molecules as danger signals, referred to as damage-associated molecular patterns (DAMPs). ATP is among the molecules that are released by cell damage, and recent evidence suggests that ATP can serve as a DAMP. Although little studied in plants, extracellular ATP is well known for its signaling roles in animals, including acting as a DAMP during the inflammatory response and wound healing. If ATP acts outside the cell, then it is reasonable to expect that it is recognized by a plasma membrane-localized receptor. Recently, DORN1, a lectin receptor kinase, was shown to recognize extracellular ATP in Arabidopsis. DORN1 is the founding member of a new purinoceptor subfamily, P2K (P2 receptor kinase), which is plant-specific. P2K1 (DORN1) is required for ATP-induced cellular responses (e.g., cytosolic Ca2+ elevation, MAPK phosphorylation, and gene expression). Genetic analysis of loss-of-function mutants and overexpression lines showed that P2K1 participates in the plant wound response, consistent with the role of ATP as a DAMP. In this review, we summarize past research on the roles and mechanisms of extracellular ATP signaling in plants, and discuss the direction of future research on extracellular ATP as a DAMP signal.

54 ENVIRONMENTAL SCIENCES↗

Understanding Electric Vehicle Range and Charging Needs: Interactions Between Ambient Temperature, Commute Patterns, and State-of-Charge Usage

Electric vehicle (EV) performance can vary substantially under real-world operating conditions, particularly due to ambient temperature effects on energy consumption, battery behavior, and thermal management requirements. This study quantifies how weather conditions, daily driving patterns, and State-of-Charge (SOC) usage strategies jointly influence EV driving range, charging frequency, and overall energy efficiency. A detailed and experimentally validated Autonomie vehicle model is developed, integrating a powertrain, a mono-zonal cabin model, and a battery electro-thermal model. Three battery sizes (200-, 300-, and 400-mile homologated ranges) are assessed across five commute profiles (20–200 miles) and six ambient temperatures (−18 °C to 50 °C), including scenarios with and without preconditioning. Results show that extreme temperatures could significantly decrease the maximum achievable range by up to 55% in cold conditions (−18 °C) and 40% in hot conditions (50 °C), relative to moderate conditions. Larger battery packs retain a greater fraction of their nominal range under thermal stress, while smaller packs experience sharper relative penalties due to the higher contribution of thermal loads to total energy demand. The analysis further demonstrates that limiting operation to partial SOC windows (e.g., 80–20%), a common real-world practice, significantly reduces achievable range and increases charging frequency, particularly in cold weather. Thermal preconditioning while plugged in is shown to mitigate these effects for short trips, reducing energy consumption by up to 31% in hot conditions and 7% in cold conditions. The findings demonstrate how climate, SOC usage behavior, and thermal management jointly shape the practical driving capability of EVs, highlighting the importance of efficient thermal management and realistic user charging strategies for ensuring reliable EV operation across diverse climatic scenarios.

33 ADVANCED PROPULSION SYSTEMS↗

Pulsed Laser-Assisted Helium Ion Nanomachining of Monolayer Graphene—Direct-Write Kirigami Patterns

A helium gas field ion source has been demonstrated to be capable of realizing higher milling resolution relative to liquid gallium ion sources. One drawback, however, is that the helium ion mass is prohibitively low for reasonable sputtering rates of bulk materials, requiring a dosage that may lead to significant subsurface damage. Manipulation of suspended graphene is, therefore, a logical application for He+ milling. We demonstrate that competitive ion beam-induced deposition from residual carbonaceous contamination can be thermally mitigated via a pulsed laser-assisted He+ milling. By optimizing pulsed laser power density, frequency, and pulse width, we reduce the carbonaceous byproducts and mill graphene gaps down to sub 10 nm in highly complex kiragami patterns.

36 MATERIALS SCIENCE↗

THE HYDROGEN EPOCH OF REIONIZATION ARRAY DISH. I. BEAM PATTERN MEASUREMENTS AND SCIENCE IMPLICATIONS

The Hydrogen Epoch of Reionization Array (HERA) is a radio interferometer aiming to detect the power spectrum of 21 cm fluctuations from neutral hydrogen from the epoch of reionization (EOR). Drawing on lessons from the Murchison Widefield Array and the Precision Array for Probing the EOR, HERA is a hexagonal array of large (14 m diameter) dishes with suspended dipole feeds. The dish not only determines overall sensitivity, but also affects the observed frequency structure of foregrounds in the interferometer. This is the first of a series of four papers characterizing the frequency and angular response of the dish with simulations and measurements. In this paper, we focus on the angular response (i.e., power pattern), which sets the relative weighting between sky regions of high and low delay and thus apparent source frequency structure. We measure the angular response at 137 MHz using the ORBCOMM beam mapping system of Neben et al. We measure a collecting area of 93 m{sup 2} in the optimal dish/feed configuration, implying that HERA-320 should detect the EOR power spectrum at z ∼ 9 with a signal-to-noise ratio of 12.7 using a foreground avoidance approach with a single season of observations and 74.3 using a foreground subtraction approach. Finally, we study the impact of these beam measurements on the distribution of foregrounds in Fourier space.

79 ASTRONOMY AND ASTROPHYSICS↗

Polarization Characteristics of Zebra Patterns in Type IV Solar Radio Bursts

The polarization characteristics of zebra patterns (ZPs) in type IV solar bursts were studied. We analyzed 21 ZP events observed by the Assembly of Metric-band Aperture Telescope and Real-time Analysis System between 2010 and 2015 and identified the following characteristics: a degree of circular polarization (DCP) in the range of 0%–70%, a temporal delay of 0–70 ms between the two circularly polarized components (i.e., the right- and left-handed components), and dominant ordinary-mode emission in about 81% of the events. For most events, the relation between the dominant and delayed components could be interpreted in the framework of fundamental plasma emission and depolarization during propagation, though the values of DCP and delay were distributed across wide ranges. Furthermore, it was found that the DCP and delay were positively correlated (rank correlation coefficient R = 0.62). As a possible interpretation of this relationship, we considered a model based on depolarization due to reflections at sharp density boundaries assuming fundamental plasma emission. The model calculations of depolarization including multiple reflections and group delay during propagation in the inhomogeneous corona showed that the DCP and delay decreased as the number of reflections increased, which is consistent with the observational results. The dispersive polarization characteristics could be explained by the different numbers of reflections causing depolarization.

79 ASTRONOMY AND ASTROPHYSICS↗

Axial Asymmetry Studies in Gaia Data Release 2 Yield the Pattern Speed of the Galactic Bar

Our recent studies of axial-symmetry breaking in the nearby ($d <3 \,{\rm kpc}$) star counts are sensitive to the distortions of stellar orbits perpendicular and parallel to the orientation of the bar just within and beyond the outer Lindblad resonance (OLR) radius. Using the location of the sign flip in the left-right asymmetry in stars counts about the anticenter line to determine the OLR radius $R_{\rm OLR}$, and treating the bar as if it were a weakly non-axisymmetric effect, we use $R_{\rm OLR}$ and recent measurements of the Galactic rotation curve and the Sun-Galactic-center distance $R_{0}$ to determine the pattern speed $\Omega_{\rm p}$ of the Galactic bar, as well as the Galactic corotation radius $R_{\rm CR}$. After removing the effect of the Large and Small Magellanic clouds from our asymmetry measurement, we find that $R_{\rm OLR}=(0.96 \pm 0.03)R_0 = 7.85 \pm 0.25 \ \rm kpc$, $\Omega_{\rm p} = 49.3 \pm 2.2 \ \rm km \ s^{-1} \ kpc^{-1}$, $R_{\rm CR}=(0.58 \pm 0.04)R_0 = 4.76 \pm 0.27 \ \rm kpc$, revealing, as we shall show, that the Milky Way's bar is likely both weak and fast, though we also note possible evidence for non-steady-state effects in the bar region.

79 ASTRONOMY AND ASTROPHYSICS↗

A Framework for Characterizing the Initial Thermal Conditions of Light-Duty Vehicles in Response to Representative Utilization Patterns, Ambient Conditions, and Vehicle Technologies

It is widely understood that the thermal state of a light-duty vehicle at the beginning of a trip influences the vehicle performance throughout the drive cycle. Cold starts, or initial states with component temperatures near ambient conditions, are strongly correlated with reduced vehicle performance and energy efficiency and with increased emissions. Despite this understanding, there is little literature available that characterizes initial thermal states beyond empirical studies and simplified analyses of dwell times. We introduce a framework that considers vehicle activity patterns, including the previous drive event, duration of the previous dwell event, and relevant ambient conditions occurring during these events. Moreover, the framework allows for technologies to influence the prominence of cold starts and warm starts. An example application of the methodology using a powertrain model approach revealed the significance of all constituent factors: controlling for ambient conditions, the shortest dwell lengths corresponded to an average initial oil temperature of 70°C versus 23°C for the long dwell length simulations, and aggressive conditioning cycles corresponded to an average initial oil temperature of 51°C versus only 35°C for a short conditioning cycle. The coldest ambient conditions evaluated (-30°C to -10°C) produced a weighted initial oil temperature of 19°C versus 57°C for the warmest ambient conditions evaluated (30°C to 50°C). Finally, we introduce weighting factors that account for the real-world frequency of conditioning cycle and dwell length combinations. The procedure outlined may be useful for discovering real-world performance improvements associated with vehicle technologies, a topic of interest to both vehicle manufacturers and regulators.

33 ADVANCED PROPULSION SYSTEMS↗

Particle phase-state variability in the North Atlantic free troposphere during summertime is determined by atmospheric transport patterns and sources

Abstract. Free tropospheric aerosol particles have important but poorly constrained climate effects due to transformations of their physicochemical properties during long-range transport. In this study, we investigate the chemical composition and provide an overview of the phase states of individual particles that have undergone long-range transport over the North Atlantic Ocean in June and July 2014, 2015, and 2017 to the Observatory of Mount Pico (OMP) in the Azores. The OMP is an ideal site for studying long-range-transported free tropospheric particles because local emissions have a negligible influence and contributions from the boundary layer are rare. We used the FLEXible PARTicle Lagrangian particle dispersion model (FLEXPART) to determine the origins and transport trajectories of sampled air masses and found that most of them originated from North America and recirculated over the North Atlantic Ocean. The FLEXPART analysis showed that the sampled air masses were highly aged (average plume age >10 d). Size-resolved chemical compositions of individual particles were probed using computer-controlled scanning electron microscopy with an energy-dispersive X-ray spectrometer (CCSEM-EDX) and scanning transmission X-ray microscopy with near-edge X-ray absorption fine structure spectroscopy (STXM-NEXAFS). CCSEM-EDX results showed that the most abundant particle types were carbonaceous (∼ 29.9 % to 82.0 %), sea salt (∼ 0.3 % to 31.6 %), and sea salt with sulfate (∼ 2.4 % to 31.5 %). We used a tilted stage interfaced within an environmental scanning electron microscope (ESEM) to determine the phase states of individual submicron particles. We found that most particles (∼ 47 % to 99 %) were in the liquid state at the time of collection due to inorganic inclusions. Moreover, we also observed substantial fractions of solid and semisolid particles (∼ 0 % to 30 % and ∼ 1 % to 42 %, respectively) during different transport patterns and events, reflecting the particles' phase-state variability for different atmospheric transport events and sources. Combining phase state measurements with FLEXPART CO tracer analysis, we found that wildfire-influenced plumes can result in particles with a wide range of viscosities after long-range transport in the free troposphere. We also used temperature and RH values extracted from the Global Forecast System (GFS) along the FLEXPART-simulated path to predict the phase state of the particles during transport and found that neglecting internal mixing with inorganics would lead to an overestimation of the viscosity of free tropospheric particles. Our findings warrant future investigation aiming at the quantitative assessment of the influence of internal mixing on the phase states of the individual particles. This study also provides insights into the chemical composition and phase state of free tropospheric particles, which can help models to reduce uncertainties about the effects of ambient aerosol particles on climate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Water-stress-induced breakdown of carbon–water relations: indicators from diurnal FLUXNET patterns

Understanding of terrestrial carbon and water cycles is currently hampered by an uncertainty in how to capture the large variety of plant responses to drought. In FLUXNET, the global network of CO 2 and H 2 O flux observations, many sites do not uniformly report the ancillary variables needed to study drought response physiology. To this end, we outline two data-driven indicators based on diurnal energy, water, and carbon flux patterns derived directly from the eddy covariance data and based on theorized physiological responses to hydraulic and non-stomatal limitations.Hydraulic limitations (i.e. intra-plant limitations on water movement) are proxied using the relative diurnal centroid ( C ET * ), whichmeasures the degree to which the flux of evapotranspiration (ET) is shiftedtoward the morning. Non-stomatal limitations (e.g. inhibitions of biochemical reactions, RuBisCO activity, and/or mesophyll conductance) are characterized by the Diurnal Water–Carbon Index (DWCI), which measures the degree of coupling between ET and gross primary productivity (GPP) within each day.As a proof of concept we show the response of the metrics at six European sites during the 2003 heat wave event, showing a varied response of morning shifts and decoupling. Globally, we found indications of hydraulic limitations in the form of significantly high frequencies of morning-shifted days in dry/Mediterranean climates and savanna/evergreen plant functional types (PFTs), whereas high frequencies of decoupling were dominated by dry climates and grassland/savanna PFTs indicating a prevalence of non-stomatal limitations in these ecosystems. Wholly, both the diurnal centroid and DWCI were associated with high net radiation and low latent energy typical of drought. Using three water use efficiency (WUE) models, we found the mean differences between expected and observed WUE to be - 0.09 to0.44 µ mol mmol -1 and - 0.29 to - 0.40 µ mol mmol -1 for decoupled and morning-shifted days, respectively, compared to mean differences - 1.41 to - 1.42 µ mol mmol -1 in dry conditions, suggesting that morning shifts/hydraulic responses are associated with an increase in WUE,whereas decoupling/non-stomatal limitations are not.

58 GEOSCIENCES↗

Indices of extremes: geographic patterns of change in extremes and associated vegetation impacts under climate intervention

Extreme weather events have been demonstrated to be increasing in frequency and intensity across the globe and are anticipated to increase further with projected changes in climate. Solar climate intervention strategies, specifically stratospheric aerosol injection (SAI), have the potential to minimize some of the impacts of a changing climate while more robust reductions in greenhouse gas emissions take effect. However, to date little attention has been paid to the possible responses of extreme weather and climate events under climate intervention scenarios. We present an analysis of 16 extreme surface temperature and precipitation indices, as well as associated vegetation responses, applied to the Geoengineering Large Ensemble (GLENS). GLENS is an ensemble of simulations performed with the Community Earth System Model (CESM1) wherein SAI is simulated to offset the warming produced by a high-emission scenario throughout the 21st century, maintaining surface temperatures at 2020 levels. GLENS is generally successful at maintaining global mean temperature near 2020 levels; however, it does not completely offset some of the projected warming in northern latitudes. Some regions are also projected to cool substantially in comparison to the present day, with the greatest decreases in daytime temperatures. The differential warming–cooling also translates to fewer very hot days but more very hot nights during the summer and fewer very cold days or nights compared to the current day. Extreme precipitation patterns, for the most part, are projected to reduce in intensity in areas that are wet in the current climate and increase in intensity in dry areas. We also find that the distribution of daily precipitation becomes more consistent with more days with light rain and fewer very intense events than currently occur. In many regions there is a reduction in the persistence of long dry and wet spells compared to present day. However, asymmetry in the night and day temperatures, together with changes in cloud cover and vegetative responses, could exacerbate drying in regions that are already sensitive to drought. Overall, our results suggest that while SAI may ameliorate some of the extreme weather hazards produced by global warming, it would also present some significant differences in the distribution of climate extremes compared to the present day.

54 ENVIRONMENTAL SCIENCES↗

Topological data analysis and machine learning for recognizing atmospheric river patterns in large climate datasets

Identifying weather patterns that frequently lead to extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Here, we propose an automated method for recognizing atmospheric rivers (ARs) in climate data using topological data analysis and machine learning. The method provides useful information about topological features (shape characteristics) and statistics of ARs. We illustrate this method by applying it to outputs of version 5.1 of the Community Atmosphere Model version 5.1 (CAM5.1) and the reanalysis product of the second Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). An advantage of the proposed method is that it is threshold-free – there is no need to determine any threshold criteria for the detection method – when the spatial resolution of the climate model changes. Hence, this method may be useful in evaluating model biases in calculating AR statistics. Further, the method can be applied to different climate scenarios without tuning since it does not rely on threshold conditions. We show that the method is suitable for rapidly analyzing large amounts of climate model and reanalysis output data.

54 ENVIRONMENTAL SCIENCES↗

Dataset for "Climatic and socioeconomic drivers of water use and their spatio-temporal patterns for small and mid-sized cities in the Contiguous United States"

This dataset contains all code for calibrating and analyzing machine learning models for "Climatic and socioeconomic drivers of water use and their spatio-temporal patterns for small and mid-sized cities in the Contiguous United States". Please unzip the folders and follow the instructions from 'README.txt'. Required python modulessklearn=1.2.2numpy=1.23.3xgboost=2.0.2joblib=1.2.0 Required R libraryshapFlex:devtools::install_github("nredell/shapFlex")library(shapFlex)

Dave, Hari [Civil and Environmental Engineering De↗

A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs

Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer data is a high priority for corporations and government agencies around the world. Cyber defenders need to analyze massive-scale, high-resolution network flows to identify, categorize, and mitigate attacks involving net- works spanning institutional and national boundaries. Many of the cyber attacks can be described as subgraph patterns, with promi- nent examples being insider infiltrations (path queries), denial of service (parallel paths) and malicious spreads (tree queries). This motivates us to explore subgraph matching on streaming graphs in a continuous setting. The novelty of our work lies in using the subgraph distributional statistics collected from the streaming graph to determine the query processing strategy. We introduce a “Lazy Search" algorithm where the search strategy is decided on a vertex-to-vertex basis depending on the likelihood of a match in the vertex neighborhood. We also propose a metric named “Relative Selectivity" that is used to se- lect between different query processing strategies. Our experiments performed on real online news, network traffic stream and a syn- thetic social network benchmark demonstrate 10-100x speedups over selectivity agnostic approaches.

graphs, cybersecurity↗

Natural Fracture Pattern Development Using 3D Coupled Numerical Model: Mechanics and Diagenesis

In the earth's crust, while tectonic processes can mechanically create natural fractures, cementation can simultaneously grow on the surfaces of the fractures. This crystallization can affect the growth of the fractures. To more accurately address the modeling of natural fracture development, both mechanical deformation and chemical diagenesis should be carried out in an integrated manner. Here, we achieve this with a three-dimensional (3D) simulator that couples mechanical and chemical processes for natural fracture pattern development in layer confined situations. Tectonic loading over geologic time is mimicked by displacement driven boundary conditions in a 3D displacement discontinuity method (DDM) scheme. Quartz diagenesis competes with mechanical fracture opening, resulting in three different cementation conditions - open, bridging or fully infilled – which define fracture element stiffness that is used as feedback within the 3D-DDM code during propagation. An important milestone of this work is that this coupled structural diagenetic model can reproduce power-law aperture population statistics which cannot be generated using mechanics alone. More accurately estimated mechanical fracture apertures and their cementation condition is a critical step toward better permeability estimation and fluid path analysis for subsurface reservoirs.

58 GEOSCIENCES↗

High Contrast Pattern Projection To Enable Background Oriented Schlieren Based Air Leak Detection Through Any Interior Or Exterior Building Surface

Air leakage in buildings wastes an estimated 4 quads of energy per year in the United States. Finding and sealing leakage sites is critical in existing buildings. Previous work has shown that background oriented Schlieren (BOS) imaging can be used to visualize air leakage but requires the leak to exit through a high contrast surface like a brick wall. To remedy this, different techniques of projecting various high contrast patterns on low contrast building surfaces like interior gypsum walls or vinyl siding were investigated. For each technique, the background quality was measured and compared to an ideal printed random dot background. The background quality metrics were correlated with the measured visualization metrics to understand which metrics are most important for maximizing air leak visualization performance. In this work, leakage visualization performance is presented for these various projected backgrounds with an aim to expand the building surfaces suitable for the BOS leak detector.

Jatana, Gurneesh [ORNL] (ORCID:0000000288903225)↗