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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 289 records · Page 16

Drosophila melanogaster pigmentation demonstrates adaptive phenotypic parallelism over multiple spatiotemporal scales

Abstract Populations are capable of responding to environmental change over ecological timescales via adaptive tracking. However, the translation from patterns of allele frequency change to rapid adaptation of complex traits remains unresolved. We used abdominal pigmentation in Drosophila melanogaster as a model phenotype to address the nature, genetic architecture, and repeatability of rapid adaptation in the field. We show that D. melanogaster pigmentation evolves as a highly parallel and deterministic response to shared environmental variation across latitude and season in natural North American populations. We then experimentally evolved replicate, genetically diverse fly populations in field mesocosms to remove any confounding effects of demography and/or cryptic structure that may drive patterns in wild populations; we show that pigmentation rapidly responds, in parallel, in fewer than 15 generations. Thus, pigmentation evolves concordantly in response to spatial and temporal climatic axes. We next examined whether phenotypic differentiation was associated with allele frequency change at loci with established links to genetic variance in pigmentation in natural populations. We found that across all spatial and temporal scales, phenotypic patterns were associated with variation at pigmentation-related loci, and the sets of genes we identified at each scale were largely nonoverlapping. Therefore, our findings suggest that parallel phenotypic evolution is associated with distinct components of the polygenic architecture shifting across each environmental axis to produce redundant adaptive patterns.

Evolutionary Biology↗

Spatiotemporal cytokinin response imaging and ISOPENTENYLTRANSFERASE 3 function in Medicago nodule development

Most legumes can establish a symbiotic association with soil rhizobia that trigger the development of root nodules. These nodules host the rhizobia and allow them to fix nitrogen efficiently. The perception of bacterial lipo-chitooligosaccharides (LCOs) in the epidermis initiates a signaling cascade that allows rhizobial intracellular infection in the root and de-differentiation and activation of cell division that gives rise to the nodule. Thus, nodule organogenesis and rhizobial infection need to be coupled in space and time for successful nodulation. The plant hormone cytokinin (CK) contributes to the coordination of this process, acting as an essential positive regulator of nodule organogenesis. However, the temporal regulation of tissue-specific CK signaling and biosynthesis in response to LCOs or Sinorhizobium meliloti inoculation in Medicago truncatula remains poorly understood. In this study, using a fluorescence-based CK sensor (pTCSn::nls:tGFP), we performed a high-resolution tissue-specific temporal characterization of the sequential activation of CK response during root infection and nodule development in M. truncatula after inoculation with S. meliloti. Loss-of-function mutants of the CK-biosynthetic gene ISOPENTENYLTRANSFERASE 3 (IPT3) showed impairment of nodulation, suggesting that IPT3 is required for nodule development in M. truncatula. Simultaneous live imaging of pIPT3::nls:tdTOMATO and the CK sensor showed that IPT3 induction in the pericycle at the base of nodule primordium contributes to CK biosynthesis, which in turn promotes expression of positive regulators of nodule organogenesis in M. truncatula.

59 BASIC BIOLOGICAL SCIENCES↗

Flying focus with arbitrary directionality for spatiotemporal control of laser intensity

Flying focus techniques produce laser pulses whose focal points travel at arbitrary, controllable velocities. While this flexibility can enhance a broad range of laser-based applications, existing techniques constrain the motion of the focal point to the propagation direction of the pulse. Here, we introduce a flying focus configuration that decouples the motion of the focus from the propagation direction. Here, a chirped laser pulse focused and diffracted by a diffractive lens and grating creates a focal point that can move both along and transverse to the propagation direction. The focal length of the lens, grating period, and chirp can be tuned to control the direction and velocity of the focus. Simulations demonstrate this control for a holographic configuration suited to high-power pulses, in which two off-axis pump beams with different focal lengths encode the equivalent phase of a chromatic lens and grating in a gas or plasma. For low-power pulses, conventional solid-state or adaptive optics can be used instead. Multi-dimensional control over the focal trajectory enables new configurations for applications, including laser wakefield acceleration of ions, nonlinear Thomson scattering, and surface-plasmon emission of THz radiation.

Classical optics↗

Spatiotemporal analysis of a final-state shape resonance in interferometric photoemission from Cu(111) surfaces

Photoemission from solid targets includes the excitation and motion of electrons inside the substrate, followed by their propagation in vacuum and detection. It thus depends on the electronic band structure of the solid in the two distinct spectral domains of bound initial and continuum final states. While the imprint of the static (initial-state) valence electronic structure of solids on photoemission spectra is routinely examined in standard photoemission spectroscopy in the energy domain, state-of-the-art time-resolved photoelectron spectroscopy allows, in addition, the scrutiny of photoelectron propagation in the electronic continuum. Within a quantum-mechanical model for attosecond time-resolved interferometric photoelectron emission from solids, we calculated photoemission spectra as a function of the delay between the exciting primary attosecond pulse train and assisting infrared (IR) laser pulse. Accounting for final-state interactions of the photoelectron with the IR laser electric field and the periodic substrate, our numerical results for interferometric photoemission from the 3d-valence band of Cu(111) surfaces show a striking resonantly enhanced sideband yield at photoelectron kinetic energies near 24 eV, in conjunction with a pronounced increase of the photoelectron wave-function amplitude inside the solid on a length scale of a few nanometers. In this work, this resonant shift of final-state photoelectron-probability density towards the bulk can be interpreted as an increase in the photoelectron propagation time in the solid and is commensurate with the resonantly enhanced spectral sideband-phase shifts observed in recent two-pathway two-photon interference spectra by Kasmi et al.

74 ATOMIC AND MOLECULAR PHYSICS↗

Nucleation of spatiotemporal structures from defect turbulence in the two-dimensional complex Ginzburg-Landau equation

We numerically investigate nucleation processes in the transient dynamics of the two-dimensional complex Ginzburg--Landau equation towards its "frozen'' state with quasi-stationary spiral structures. We study the transition kinetics from either the defect turbulence regime or random initial configurations to the frozen state with a well-defined low density of quasi-stationary topological defects. Nucleation events of spiral structures are monitored using the characteristic length between the emerging shock fronts. We study two distinct situations, namely either when the system is quenched far away from the transition limit or near it. In the former deeply quenched case, the average nucleation time for different system sizes is measured over many independent realizations. We employ an extrapolation method as well as a phenomenological formula to account for and eliminate finite-size effects. The non-zero (dimensionless) barrier for the nucleation of single spiral droplets in the extrapolated infinite system size limit suggests that the transition to the frozen state is discontinuous. Here, we also investigate the nucleation of spirals for systems that are quenched close to but beyond the crossover limit, and of target waves which emerge if a specific spatial inhomogeneity is introduced. In either of these cases, we observe long, "fat'' tails in the distribution of nucleation times, which also supports a discontinuous transition scenario.

97 MATHEMATICS AND COMPUTING↗

Framework for idealized climate simulations with spatiotemporal stochastic clouds and planetary-scale circulations

In climate predictions, clouds are the leading source of uncertainty. This is partly because, to simulate the fluid dynamics of climate over the entire globe, a large grid spacing must be used, so clouds are a subgrid-scale parametrization rather than a resolved feature. Here, a framework is investigated with finer grid spacing of O(1) or O(10)km so that some clouds are not subgrid-scale; instead, clouds evolve on the numerical grid. This cloud evolution is achieved using stochastic modeling. Hence, the framework is idealized in the sense that the full fluid dynamics of cloud circulations is still not resolved, and simplified vertical structures are used. Nevertheless, the fluid dynamics model includes evolving clouds that interactively adjust in size, shape, lifetime, and regional coverage. In addition, different cloud types are included with different roles in the climate system, including deep convective clouds and also boundary-layer clouds such as shallow cumulus and stratocumulus clouds. Other basic aspects of the idealized climate system are planetary-scale circulations (e.g., Walker circulation) and radiation. With these ingredients (evolving clouds, planetary-scale circulations, and radiation), the framework has the potential for idealized investigations of climate change with interactive cloud–radiative feedback of individual clouds. Here, the formulation of the model equations is presented, and numerical simulations are shown to illustrate the model dynamics and climate change.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SPATIOTEMPORAL TRACKING OF WIDE AREA POWER OUTAGE FROM NIGHT-TIME LIGHT IMAGERY

Monitoring progress of power restoration following extreme events is essential for situational awareness about spatio-temporal distribution of populations without power and to help with response efforts. Because of the proprietary nature of restoration data, and the difficulty in obtaining power outage data from utility companies in near real-time (e.g., during hurricane Maria (2017)), this project used satellite derived nighttime lights data from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) to (i) monitor wide area power outage and (ii) estimate impacted customers over time to assist with restoration. A discussion of the methodology and its implementation during hurricanes Maria (2017) and Eta (2020) is presented in this paper. Future work will focus on calibrating estimated customers based on light intensity and density distribution, and generation of restoration profiles for emergency response.

Kar, Bandana↗

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Laboratory-based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Additionally, there is a growing concern on characterizing the non-uniformity of field exposure. Therefore, data from field surveys are critical to assess the performance of component lifetimes. Using a documented field survey protocol, 19 field surveys were conducted. The focus of this survey strategy is to investigate spatial continuity in degradation modes. By combining field survey data with real-time satellite weather data, stressor / response models have been trained. Generalized additive Models (GAM) model was created to predict the value of degradation based on measured predictors. Two different GAM constructions were testing using different implementations of basis splines. The model includes variables on the environmental stressors of the system and the location of each measurement in the PV mounting structure. The incorporation of hierarchical structure into the models allowed for material specific degradation rates, while maintaining the assumption of a global trend. The model performed well with an adjusted R2 of 0.975 for yellowness index prediction.

backsheet↗

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A genetically encoded biosensor reveals spatiotemporal variation in cellular phosphate content in Brachypodium distachyon mycorrhizal roots

Arbuscular mycorrhizal (AM) symbiosis is accompanied by alterations to root cell metabolism and physiology, and to the pathways of orthophosphate (Pi) entry into the root, which increase with Pi delivery to cortical cells via arbuscules. How AM symbiosis influences the Pi content and Pi response dynamics of cells in the root cortex and epidermis is unknown. Using fluorescence resonance energy transfer (FRET)-based Pi biosensors, here we mapped the relative cytosolic and plastidic Pi content of Brachypodium distachyon mycorrhizal root cells, analyzed responses to extracellular Pi and traced extraradical hyphae-mediated Pi transfer to colonized cells. Colonized cortical cells had a higher cytosolic Pi content relative to noncolonized cortical and epidermal cells, while plastidic Pi content was highest in cells at the infection front. Pi application to the entire mycorrhizal root resulted in transient changes in cytosolic Pi that differed in direction and magnitude depending on cell type and arbuscule status; cells with mature arbuscules showed a substantial transient increase in cytosolic Pi while those with collapsed arbuscules showed a decrease. Directed Pi application to extraradical hyphae resulted in measurable changes in cytosolic Pi of colonized cells 18 h after application. Our experiments reveal that cells within a mycorrhizal root vary in Pi content and Pi response dynamics.

32Pi tracing↗

Spatiotemporal analysis of lung immune dynamics in lethal Coccidioides posadasii infection

Coccidioidomycosis, or Valley fever, is a lung disease caused by inhalation of Coccidioides fungi, prevalent in the Southwestern United States, Mexico, and parts of Central and South America. Annually, the United States reports 10,000–20,000 cases, although those numbers are expected to increase as climate change expands the fungal geographic range. While 60% of infections are asymptomatic, 40% symptomatic infections are often misdiagnosed due to similarities with bronchitis or pneumonia. A small subset of infection progress to severe illness, necessitating a better understanding of immune responses during lethal infection. Using single-cell RNA sequencing and spatial transcriptomics, we characterized lung responses during Coccidioides infection. We identified monocyte-derived Spp1-expressing macrophages as potential mediators of tissue remodeling and fibrosis, marked by high expression of profibrotic and proinflammatory transcripts. These macrophages showed elevated TGF-β and IL-6 signaling, pathways involved in fibrosis pathogenesis. Additionally, we observed significant neutrophil infiltration and defective lymphocyte responses, indicating severe adaptive immunity dysregulation in lethal, acute infection. These findings enhance our understanding of Coccidioides infection and suggest new therapeutic targets.

59 BASIC BIOLOGICAL SCIENCES↗