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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 307 records · Page 17

Role of tau versus TDP-43 pathology on medial temporal lobe atrophy in aging and Alzheimer's disease

Hippocampal atrophy on magnetic resonance imaging is an important biomarker in Alzheimer's disease (AD). While hippocampal atrophy was thought to result from tau tangles in AD, different neuropathologies can lead to hippocampal atrophy, especially TAR DNA-binding protein 43 (TDP-43) pathology. In this narrative review, we evaluate existing studies on the relative contribution of tau and TDP-43 pathology to medial temporal lobe (MTL) atrophy. We report a clear association of both tau and TDP-43 neuropathology with MTL atrophy, even after correcting for other neuropathologies. Next, we discuss a potential synergism between tau and TDP-43 and the relative timing of the effects of both neuropathologies. Finally, avenues for future research will be discussed. A better understanding of the interplay between tau and TDP-43 neuropathologies and their effect on atrophy will help with the development of more specific biomarkers for limbic-predominant age-related TDP-43 encephalopathy and pinpointing of the optimal timing for testing anti-tau and anti-TDP-43 treatments in trials.

60 APPLIED LIFE SCIENCES↗

Deep learning-based spatio-temporal fusion for high-fidelity ultra-high-speed X-ray radiography

Full-field ultra-high-speed (UHS) X-ray imaging experiments have been well established to characterize various processes and phenomena. However, the potential of UHS experiments through the joint acquisition of X-ray videos with distinct configurations has not been fully exploited. In this paper, we investigate the use of a deep learning-based spatio-temporal fusion (STF) framework to fuse two complementary sequences of X-ray images and reconstruct the target image sequence with high spatial resolution, high frame rate and high fidelity. We applied a transfer learning strategy to train the model and compared the peak signal-to-noise ratio (PSNR), average absolute difference (AAD) and structural similarity (SSIM) of the proposed framework on two independent X-ray data sets with those obtained from a baseline deep learning model, a Bayesian fusion framework and the bicubic interpolation method. The proposed framework outperformed the other methods with various configurations of the input frame separations and image noise levels. With three subsequent images from the low-resolution (LR) sequence of a four times lower spatial resolution and another two images from the high-resolution (HR) sequence of a 20 times lower frame rate, the proposed approach achieved average PSNRs of 37.57 dB and 35.15 dB, respectively. When coupled with the appropriate combination of high-speed cameras, the proposed approach will enhance the performance and therefore the scientific value of UHS X-ray imaging experiments.

deep learning↗

Effect of Illumination Area on the Ultrafast Temporal Response of MSM GaN Photodiodes

We investigate the influence of spatial illumination profiles on the temporal response of metal–semiconductor–metal GaN photodiodes. Using both simulation and experimental measurements, we compare the response curves under two scenarios: illumination confined to the active area between electrodes and extended illumination beyond the contacts. The results show that limiting the beam illumination to the active region significantly sharpens the response, reducing the long decay tails associated with slow carrier drift from peripheral regions. As a result, the experimental data closely match simulation predictions, confirming that illumination geometry plays a critical role in optimizing photodiode performance for ultrafast detection applications.

Carrier drift time↗

Temporal Study 2022-2024: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, Chlorophyll A, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin in Washington, USA

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (bi-weekly or monthly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites across the Yakima River Basin in Washington, USA. Sample and sensor data from previous years (2021-2022) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054, respectively. Related sample data from 2022-2024 are available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2562910. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions This dataset contains a folder of environmental context photographs and videos and (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) field protocols; (6) international generic sample number (IGSN) mapping file; (7) handheld sensor data; and (8) two sensor subfolders. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor time series data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and chlorophyll A. All files are .csv, .pdf, .jpg, .jpeg, .mp4, .png, or .mov.

54 ENVIRONMENTAL SCIENCES↗

Improved method for temporally interpolating radiosonde profiles in the convective boundary layer

A significantly improved technique for temporally interpolating radiosonde (RS) profiles of potential temperature and water vapor mixing ratio in the planetary boundary layer during daytime is introduced. The key innovation of this technique is its operation on a height grid normalized with the planetary boundary layer height. This study utilized a three-month dataset of three-hourly soundings from the Atmospheric Radiation Measurement Facility's Southern Great Plains site. The technique was evaluated for convective boundary layer cases, with the necessary boundary layer height data obtained from a ground-based infrared spectrometer. A total of 79 comparisons were conducted between reference soundings and interpolated profiles that did and did not employ height normalization. The results demonstrated a substantial improvement in the representation of interpolated profiles using the new technique, characterized by enhanced correlation, improved amplitude representation, and reduced bias for potential temperature, as well as improved correlation and reduced bias for water vapor mixing ratio.

convective boundary layer↗

Neurochemical phenotype of corticocortical connections in the macaque monkey: quantitative analysis of a subset of neurofilament protein-immunoreactive projection neurons in frontal, parietal, temporal, and cingulate cortices

The neurochemical characteristics of the neuronal subsets that furnish different types of corticocortical connections have been only partially determined. In recent years, several cytoskeletal proteins have emerged as reliable markers to distinguish subsets of pyramidal neurons in the cerebral cortex of primates. In particular, previous studies using an antibody to nonphosphorylated neurofilament protein (SMI-32) have revealed a consistent degree of regional and laminar specificity in the distribution of a subpopulation of pyramidal cells in the primate cerebral cortex. The density of neurofilament protein-immunoreactive neurons was shown to vary across corticocortical pathways in macaque monkeys. In the present study, we have used the antibody SMI-32 to examine further and to quantify the distribution of a subset of corticocortically projecting neurons in a series of long ipsilateral corticocortical pathways in comparison to short corticocortical, commissural, and limbic connections. The results demonstrate that the long association pathways interconnecting the frontal, parietal, and temporal neocortex have a high representation of neurofilament protein-enriched pyramidal neurons (45-90%), whereas short corticocortical, callosal, and limbic pathways are characterized by much lower numbers of such neurons (4-35%). These data suggest that different types of corticocortical connections have differential representation of highly specific neuronal subsets that share common neurochemical characteristics, thereby determining regional and laminar cortical patterns of morphological and molecular heterogeneity. These differences in neuronal neurochemical phenotype among corticocortical circuits may have considerable influence on cortical processing and may be directly related to the type of integrative function subserved by each cortical pathway. Finally, it is worth noting that neurofilament protein-immunoreactive neurons are dramatically affected in the course of Alzheimer's disease. The present results support the hypothesis that neurofilament protein may be crucially linked to the development of selective neuronal vulnerability and subsequent disruption of corticocortical pathways that lead to the severe impairment of cognitive function commonly observed in age-related dementing disorders.

Non-NASA Center↗

Temporal Investment Strategy to Enable JPL Future Space Missions

The Jet Propulsion Laboratory (JPL) formulates and conducts deep space missions for NASA (the National Aeronautics and Space Administration). The Chief Technologist of JPL has the responsibility for strategic planning of the laboratory's advanced technology program to assure that the required technological capabilities to enable future JPL deep space missions are ready as needed; as such he is responsible for the development of a Strategic Plan. As part of the planning effort, he has supported the development of a structured approach to technology prioritization based upon the work of the START (Strategic Assessment of Risk and Technology) team. A major innovation reported here is the addition of a temporal model that supports scheduling of technology development as a function of time. The JPL Strategic Technology Plan divides the required capabilities into 13 strategic themes. The results reported here represent the analysis of an initial seven.

investment strategy↗

Effects of Spatio-Temporal Aliasing on Out-the-Window Visual Systems

Designers of out-the-window visual systems face a challenge when attempting to simulate the outside world as viewed from a cockpit. Many methodologies have been developed and adopted to aid in the depiction of particular scene features, or levels of static image detail. However, because aircraft move, it is necessary to also consider the quality of the motion in the simulated visual scene. When motion is introduced in the simulated visual scene, perceptual artifacts can become apparent. A particular artifact related to image motion, spatiotemporal aliasing, will be addressed. The causes of spatio-temporal aliasing will be discussed, and current knowledge regarding the impact of these artifacts on both motion perception and simulator task performance will be reviewed. Methods of reducing the impact of this artifact are also addressed

image generator↗

Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

Segmentation↗

Knowledge Engineering for Temporal Dependency Networks as Operations Procedures

This paper presents a case study of the knowledge engineering process employed to support the Link Monitor & Control Operator Assistant (LMCOA). The LMCOA is a prototype system which automates equipment used to support space-ground communication with deep space spacecraft in NASA's Deep Space Network (DSN). The primary knowledge base in the LMCOA is the Temporal Dependency Network (TDN). The paper provides a brief background on the DSN, and describes the evolution of the TDN and supporting knowledge bases, the process used for knowledge engineering, and an analysis of the successes--and problems--of the knowledge engineering effort.

operations↗

Approaching the Lower Temporal Limit of Laser‐Produced Plasma Sources for Table‐Top Soft X‐Ray NEXAFS Measurements

Abstract The increasing popularity of time‐resolved X‐ray absorption measurements for understanding dynamics in molecular and material systems has led to many advances in table‐top sources for pulsed X‐rays. We report on a table‐top laser‐produced plasma (LPP) source that can perform soft X‐ray (SXR), near‐edge X‐ray absorption fine structure (NEXAFS) measurements using a laser source with 23 ps pulse duration. The spectrometer's key specifications, such as brilliance, resolution, and stability, are characterized against the more commonly used longer‐pulse‐duration LPP sources. The 23 ps laser produced approximately an order of magnitude weaker SXR flux than the 8 ns laser for a higher power density due to the smaller total energy absorbed by the plasma. The increased repetition rate, as well as the use of a high line‐density X‐grating, and a self‐referencing scheme still allowed for NEXAFS measurements of Si 3 N 4 and TiO 2 thin films with 2.5 minute acquisition times, a resolving power of E/ΔE=424, and a signal‐to‐noise ratio of 100. It was observed that degradation of the gas jet nozzle led to long‐term instability of the source, which can be remediated using alternative nozzle designs. This work demonstrates the feasibility of achieving higher temporal resolution in future time‐resolved X‐ray absorption measurements using table‐top LPP sources.

Nimlos, Danika [Division of Chemistry and Chemical↗

The Spatial and Temporal Variability of the Clear Convective Boundary Layer at the ARM SGP Supersite

The convective boundary layer (CBL), also known as the mixing layer, constitutes the critical lower segment of the atmosphere that significantly influences daily human activities. The growing demand for precise weather forecasts is driven by the requirements of agriculture, transportation, and routine societal functions. Here, to enhance understanding of the CBL, this study investigates the spatiotemporal variability in the CBL and its controlling factors using four-year Doppler lidar, surface flux, and profiling measurements at five ARM Southern Great Plains sites within a 100 km radius. This investigation utilizes data collected exclusively under clear-sky conditions or scattered low-cloud conditions. Results reveal significant spatial differences in CBL evolutions. Daily mixing layer heights (MLHs) vary up to 1 km (30% of the mean) in late afternoon. There is a clear east–west contrast: western sites (C1, E32, E37) exhibit higher summer MLH (1.9–2.1 km) and vertical velocity variances (1.0–1.2 m 2 s −2 ) than eastern sites (1.6–1.8 km), reversing in winter. Temporally, the MLH peaks at 70% of the sunrise–sunset interval, the lagging heat flux (HF) peaks at 50%; and the seasonal MLH maxima lag the HF by approximately one month, influenced by nighttime PBL (planetary boundary layer) properties. The HF and lower tropospheric stability are the main factors of influence for the CBL, but site-specific dependencies highlight the critical roles of local factors, underscoring the need for including them in CBL modeling.

ARM SGP site↗

Spatio-temporal multivariate cluster evolution analysis for detecting and tracking climate impacts

Recent years have seen a growing concern about climate change and its impacts. While Earth System Models (ESMs) can be invaluable tools for studying the impacts of climate change, the complex coupling processes encoded in ESMs and the large amounts of data produced by these models, together with the high internal variability of the Earth system, can obscure important source-to-impact relationships. Here, this paper presents a novel and efficient unsupervised data-driven approach for detecting statistically-significant impacts and tracing spatio-temporal source-impact pathways in the climate through a unique combination of ideas from anomaly detection, clustering and Natural Language Processing (NLP). Using as an exemplar the 1991 eruption of Mount Pinatubo in the Philippines, we demonstrate that the proposed approach is capable of detecting known post-eruption impacts/events. We additionally describe a methodology for extracting meaningful sequences of post-eruption impacts/events by using NLP to efficiently mine frequent multivariate cluster evolutions, which can be used to confirm or discover the chain of physical processes between a climate source and its impact(s).

Anomaly detection↗

Endurance exercise elicits temporal and sexual dimorphic multi-omics remodeling of liver metabolism revealed by MoTrPAC

The mechanisms by which exercise modulate liver metabolism, a central regulator of systemic metabolism, are poorly understood. Leveraging data from MoTrPAC, we analyzed liver adaptations across 1, 2, 4, and 8 weeks of exercise in male and female rats using multi-omic approaches. Female livers displayed a progressive increase in oxidative phosphorylation (OXPHOS) complexes (at the protein level), while male livers showed an increase in acetylation of OXPHOS, TCA cycle, and fatty acid oxidation enzymes. Exercise also enhanced liver cholesterol and bile acid synthesis, reducing liver lipid metabolites in males after 8 weeks of exercise. Male rats had higher fecal cholesterol and cholic acid levels, indicating a sex-specific mechanism of lipid excretion with exercise. Moreover, 8 weeks of training reduced markers related to hepatic stellate cell activation and fibrosis in both sexes. This study highlights the sexual dimorphic and temporal molecular signatures by which exercise modulates liver metabolism to provide hepatoprotective effects.

Kelty, Taylor↗

Lethality is Local, but Survival is Systemic: Temporal and Multi-Organ Responses to Chlorine Gas Exposure in a Murine Model

Chlorine gas (Cl2) is a highly toxic chemical associated with both localized lung injury and systemic health effects. While pulmonary damage has been well characterized, the systemic inflammatory and metabolic responses remain poorly understood. We aimed to define the temporal and multi-organ responses to Cl2 exposure in a murine model, with a focus on identifying spatiotemporal inflammation and its impact on survival and lethality. SKH1 mice were exposed for 10 min to varying concentrations of Cl2 (94.4–810 ppm, representative of non-lethal, LD10, and LD50 doses) and monitored for respiratory function, perfusion, and acidosis using organ-specific imaging. At multiple time points (40 min, 6 h, 24 h, and 7 d), we measured phosphoproteins, cytokines, chemokines, growth factors, and metabolic hormones in the lungs, heart, cortex, and plasma. Statistical modeling and logistic regression were used to identify biomarkers associated with lethality and survival. We found that lung injury was the primary cause of potential lethality, particularly via early phosphoprotein signaling disruptions. However, survival correlated with early systemic coordination of inflammatory and metabolic signals across organs. Perfusion and acidosis imaging were strongly associated with chemokine and hormone responses. Key survival-associated plasma biomarkers included decreased insulin, increased ghrelin, and decreased eotaxin. While potential lethality from Cl2 exposure is locally driven by pulmonary injury, survival depends on systemic, multi-organ responses that occur rapidly post-exposure. Within this model, our findings identify a potential therapeutic window to enhance survival and suggest candidate biomarkers that may be explored translationally for both triage and treatment of chlorine-related incidents.

chlorine gas↗