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At least 991 records · Page 55

Elastostatic stress analysis of orthotropic rectangular center-cracked plates

A mapping-collocation method was developed for the elastostatic stress analysis of finite, anisotropic plates with centrally located traction-free cracks. The method essentially consists of mapping the crack into the unit circle and satisfying the crack boundary conditions exactly with the help of Muskhelishvili's function extension concept. The conditions on the outer boundary are satisfied approximately by applying the method of least-squares boundary collocation. A parametric study of finite-plate stress intensity factors, employing this mapping-collocation method, is presented. It shows the effects of varying material properties, orientation angle, and crack-length-to-plate-width and plate-height-to-plate-width ratios for rectangular orthotropic plates under constant tensile and shear loads.

Gyekenyesi, G. S.↗

Acquisition and Implementation of a Comprehensive Environmental Permits Linking Tool at Savannah River Site - 20234

Historically, Savannah River Nuclear Solutions LLC (SRNS) tracked environmental regulatory commitments and the requirements from hundreds of permits at the Savannah River Site (SRS) using several separate methods, making integrated compliance assurance cumbersome and labor-intensive. When SRNS experienced an increase in environmental issues in 2017, SRNS management and U.S. Department of Energy - Savannah River (DOE-SR) management decided a single, proactive approach was needed to capture environmental permit information (including regulations, Consent Orders, DOE Orders, and any other state or federally issued statement of requirements), track the tasks necessary to ensure compliance with these requirements, and thereby mitigate the risk of noncompliance. SRNS developed a list of mandatory objectives that the tool must meet to function as a Comprehensive Environmental Permits Linking Tool (CEPLT). A key requirement was the ability to map Site permits to their governed locations and display the associated requirements at the compliance point (e.g., outfall, stack, waste unit, etc.). Several options included modifying existing onsite resources, building a custom onsite solution, purchasing an off-the-shelf solution, and contracting an offsite developer to build a custom solution. SRNS concluded an off-the-shelf solution with configuration and customization options would provide the flexibility to fit the unique needs of Savannah River Site (SRS) while taking advantage of industry-tested software and providing a reduced deployment timeline. SRNS chose Gensuite{sup R} a, a cloud-based solution that offers numerous a la carte applications in the environmental, health, and safety arenas, as the best candidate. SRNS selected three (3) integrated applications (Compliance Calendar, Permit Manager, and Mapper) to function as the CEPLT. The Compliance Calendar module allows for creation and tracking of regulatory commitment tasks assigned to responsible environmental professionals. Permit Manager organizes permits and other requirement documents, linking the commitments in each to Compliance Calendar tasks and/or implementing procedures. Mapper provides GIS capability for mapping the data from the other two modules to their physical onsite locations. The CEPLT was configured to allow for other SRS Site Tenants to eventually utilize the applications. Additionally, DOE-SR uses the CEPLT to provide an overview of contractor environmental compliance activities and to organize DOE-specific documents and tasks. The CEPLT fulfilled the requirement of meeting current compliance needs as well as providing the ability to grow as new organizations are incorporated and functionality is expanded. SRNS now uses the CEPLT to more effectively manage permit requirements, improve knowledge transfer, and increase the Site's overall protection of the environment, the Site worker, and the public. Possible future uses of the system include integration of mobile applications for timely communication of potential non-compliant conditions and DOE complex-wide deployment allowing for enhanced DOE site and Head Quarters oversight. Implementation of CEPLT will result in cost savings, both in terms of dollars and man-hours. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Genome-Wide Analysis of RNA Decay in the Cyanobacterium Synechococcus sp. Strain PCC 7002

ABSTRACT RNA degradation is an important process that influences the ultimate concentration of individual proteins inside cells. While the main enzymes that facilitate this process have been identified, global maps of RNA turnover are available for only a few species. Even in these cases, there are few sequence elements that are known to enhance or destabilize a native transcript; even fewer confer the same effect when added to a heterologous transcript. To address this knowledge gap, we assayed genome-wide RNA degradation in the cyanobacterium Synechococcus sp. strain PCC 7002 by collecting total RNA samples after stopping nascent transcription with rifampin. We quantified the abundance of each position in the transcriptome as a function of time using RNA-sequencing data and later analyzed the global mRNA decay map using machine learning principles. Half-lives, calculated on a per-ORF (open reading frame) basis, were extremely short, with a median half-life of only 0.97 min. Despite extremely rapid turnover of most mRNA, transcripts encoding proteins involved in photosynthesis were both highly expressed and highly stable. Upon inspection of these stable transcripts, we identified an enriched motif in the 3′ untranslated region (UTR) that had similarity to Rho-independent terminators. We built statistical models for half-life prediction and used them to systematically identify sequence motifs in both 5′ and 3′ UTRs that correlate with stabilized transcripts. We found that transcripts linked to a terminator containing a poly(U) tract had a longer half-life than both those without a poly(U) tract and those without a terminator. IMPORTANCE RNA degradation is an important process that affects the final concentration of individual mRNAs, affecting protein expression and cellular physiology. Studies of how RNA is degraded increase our knowledge of this fundamental process as well as enable the creation of genetic tools to manipulate RNA stability. By studying global transcript turnover, we searched for sequence elements that correlated with transcript (in)stability and used these sequences to guide tool design. This study probes global RNA turnover in a cyanobacterium, Synechococcus sp. strain PCC 7002, that both has a unique array of RNases that facilitate RNA degradation and is an industrially relevant strain that could be used to convert CO 2 and sunlight into useful products.

59 BASIC BIOLOGICAL SCIENCES↗

Harnessing the predicted maize pan-interactome for putative gene function prediction and prioritization of candidate genes for important traits

Abstract The recent assembly and annotation of the 26 maize nested association mapping population founder inbreds have enabled large-scale pan-genomic comparative studies. These studies have expanded our understanding of agronomically important traits by integrating pan-transcriptomic data with trait-specific gene candidates from previous association mapping results. In contrast to the availability of pan-transcriptomic data, obtaining reliable protein–protein interaction (PPI) data has remained a challenge due to its high cost and complexity. We generated predicted PPI networks for each of the 26 genomes using the established STRING database. The individual genome-interactomes were then integrated to generate core- and pan-interactomes. We deployed the PPI clustering algorithm ClusterONE to identify numerous PPI clusters that were functionally annotated using gene ontology (GO) functional enrichment, demonstrating a diverse range of enriched GO terms across different clusters. Additional cluster annotations were generated by integrating gene coexpression data and gene description annotations, providing additional useful information. We show that the functionally annotated PPI clusters establish a useful framework for protein function prediction and prioritization of candidate genes of interest. Our study not only provides a comprehensive resource of predicted PPI networks for 26 maize genomes but also offers annotated interactome clusters for predicting protein functions and prioritizing gene candidates. The source code for the Python implementation of the analysis workflow and a standalone web application for accessing the analysis results are available at https://github.com/eporetsky/PanPPI.

Genetics & Heredity↗

Cardiovascular function following reduced aerobic activity

PURPOSE: The aim of this study was to test the hypothesis that a sustained reduction of physical activity (deconditioning) would alter the cardiovascular regulatory function. METHODS: Nineteen young, healthy volunteers participated in physical deconditioning for a period of 8 wk. Before (pre) and following (post) physical deconditioning, the responses of heart rate (HR), mean arterial pressure (MAP, measured by Finapres), central venous pressure (CVP), stroke volume (SV, Doppler), and forearm blood flow (FBF, plethysmography) were determined during lower body negative pressure (LBNP). The carotid baroreflex (CBR) function was assessed using a train of pulsatile neck pressure (NP) and suction, and the aortic baroreflex control of HR was assessed during steady-state phenylephrine (PE) infusion superimposed by LBNP and NP to counteract the PE increased CVP and carotid sinus pressure, respectively. RESULTS: Active physical deconditioning significantly decreased maximal oxygen uptake (-7%) and LBNP tolerance (-13%) without a change in baseline hemodynamics. Plasma volume (-3% at P = 0.135), determined by Evans Blue dilution, and blood volume (-4% at P = 0.107) were not significantly altered. During LBNP -20 to -50 torr, there was a significantly greater drop of SV per unit decrease in CVP in the post- (14.7 +/- 1.6%/mm Hg) than predeconditioning (11.2 +/- 0.7%/mm Hg) test accompanied by a greater tachycardia. Deconditioning increased the aortic baroreflex sensitivity (pre vs post: -0.61 +/- 0.12 vs -0.84 +/- 0.14 bpm.mm-1 Hg, P = 0.009) and the slope of forearm vascular resistance (calculated from [MAP-CVP]/FBF) to CVP (-2.75 +/- 0.26 vs -4.94 +/- 0.97 PRU/mm Hg, P = 0.086). However, neither the CBR-HR (-0.28 +/- 0.03 VS -0.39 +/- 0.10 bpm.mm-1 Hg) nor the CBR-MAP (-0.37 +/- 0.16 vs -0.25 +/- 0.07 mm Hg/mm Hg) gains were statistically different between pre- and postdeconditioning. CONCLUSIONS: We concluded that the functional modification of the cardiac pressure-volume relationship resulted in the reduced LBNP tolerance, despite the accentuated aortic and cardiopulmonary baroreflex function following deconditioning.

Non-NASA Center↗

Characterizing 4-string contact interaction using machine learning

Abstract The geometry of 4-string contact interaction of closed string field theory is characterized using machine learning. We obtain Strebel quadratic differentials on 4-punctured spheres as a neural network by performing unsupervised learning with a custom-built loss function. This allows us to solve for local coordinates and compute their associated mapping radii numerically. We also train a neural network distinguishing vertex from Feynman region. As a check, 4-tachyon contact term in the tachyon potential is computed and a good agreement with the results in the literature is observed. We argue that our algorithm is manifestly independent of number of punctures and scaling it to characterize the geometry ofn-string contact interaction is feasible.

Physics↗

Autonomous scanning probe microscopy investigations over WS2 and Au{111}

Abstract Individual atomic defects in 2D materials impact their macroscopic functionality. Correlating the interplay is challenging, however, intelligent hyperspectral scanning tunneling spectroscopy (STS) mapping provides a feasible solution to this technically difficult and time consuming problem. Here, dense spectroscopic volume is collected autonomously via Gaussian process regression, where convolutional neural networks are used in tandem for spectral identification. Acquired data enable defect segmentation, and a workflow is provided for machine-driven decision making during experimentation with capability for user customization. We provide a means towards autonomous experimentation for the benefit of both enhanced reproducibility and user-accessibility. Hyperspectral investigations on WS 2 sulfur vacancy sites are explored, which is combined with local density of states confirmation on the Au{111} herringbone reconstruction. Chalcogen vacancies, pristine WS 2 , Au face-centered cubic, and Au hexagonal close-packed regions are examined and detected by machine learning methods to demonstrate the potential of artificial intelligence for hyperspectral STS mapping.

36 MATERIALS SCIENCE↗

Automated scanning probe microscopy of combinatorial ferroelectric libraries: Gaussian-process-guided exploration and noise-aware experiment planning

Combinatorial materials libraries provide an efficient route for mapping composition–property relationships, but their broader impact depends on rapid, quantitative, and functionally relevant characterization. Scanning Probe Microscopy (SPM), including piezoresponse force microscopy (PFM), offers significant potential for quantitative, functionally relevant combi-library readouts. Here, we implement a fully automated SPM workflow for ferroelectric combinatorial libraries and benchmark Gaussian-process-based Bayesian optimization strategies for autonomous experiment planning. The workflow integrates automated probe motion, contact optimization, imaging, and dual amplitude resonance tracking-PFM spectroscopy, and uses scalarized spectroscopic observables to guide subsequent measurements. Stage motion, probe engagement, in-contact tuning, imaging, spectroscopy, and the choice of the next measurement location all proceed without human input. We demonstrate the approach on Sm-doped BiFeO 3 and Zn x Mg 1−x O libraries. By comparing vanilla Bayesian optimization with a measured-noise variant, we show that explicit treatment of local reproducibility can improve modeling of composition-dependent response when the measured variance is physically meaningful, but can also reduce robustness when variability is dominated by outliers or topographic artifacts. Furthermore, these results establish automated SPM as a bridge between combinatorial synthesis and quantitative functional characterization.

Liu, Yu [University of Tennessee, Knoxville, TN (U↗

Transcription factor bHLH121 regulates root cortical aerenchyma formation in maize

Root anatomical phenotypes present a promising yet underexploited avenue to deliver major improvements in yield and climate resilience of crops by improving water and nutrient uptake. For instance, the formation of root cortical aerenchyma (RCA) significantly increases soil exploration and resource capture by reducing the metabolic costs of root tissue. A key bottleneck in studying such phenotypes has been the lack of robust high-throughput anatomical phenotyping platforms. We exploited a phenotyping approach based on laser ablation tomography, termed Anatomics , to quantify variation in RCA formation of 436 diverse maize lines in the field. Results revealed a significant and heritable variation for RCA formation. Genome-wide association studies identified a single-nucleotide polymorphism mapping to a root cortex-expressed gene-encoding transcription factor bHLH121. Functional studies identified that the bHLH121 Mu transposon mutant line and CRISPR/Cas9 loss-of-function mutant line showed reduced RCA formation, whereas an overexpression line exhibited significantly greater RCA formation when compared to the wild-type line. Characterization of these lines under suboptimal water and nitrogen availability in multiple soil environments revealed that bHLH121 is required for RCA formation developmentally as well as under studied abiotic stress. Overall functional validation of the bHLH121 gene’s importance in RCA formation provides a functional marker to select varieties with improved soil exploration and thus yield under suboptimal conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Spatially quasi-periodic water waves of finite depth

We present a numerical study of spatially quasi-periodic gravity-capillary waves of finite depth in both the initial value problem and travelling wave settings. We adopt a quasi-periodic conformal mapping formulation of the Euler equations, where one-dimensional quasi-periodic functions are represented by periodic functions on a higher-dimensional torus. We compute the time evolution of free surface waves in the presence of a background flow and a quasi-periodic bottom boundary and observe the formation of quasi-periodic patterns on the free surface. Two types of quasi-periodic travelling waves are computed: small-amplitude waves bifurcating from the zero-amplitude solution and larger-amplitude waves bifurcating from finite-amplitude periodic travelling waves. We derive weakly nonlinear approximations of the first type and investigate the associated small-divisor problem. We find that waves of the second type exhibit striking nonlinear behaviour, e.g. the peaks and troughs are shifted non-periodically from the corresponding periodic waves due to the activation of quasi-periodic modes.

Science & Technology - Other Topics↗

Deconvoluting thermomechanical effects in X-ray diffraction data using machine learning

X-ray diffraction is ideal for probing the sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and because of the inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach that uses combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis. The method builds on a previous effort to extract thermal strain distribution information from diffraction data. The new approach is applied to extract the evolution of the thermomechanical state during laser melting of an Inconel 625 wall specimen which produces significant residual stress upon cooling. A combination of heat transfer and fluid flow, elasto-plasticity and X-ray diffraction simulations is used to generate training data for machine-learning (Gaussian process regression, GPR) models that map diffracted intensity distributions to underlying thermomechanical strain fields. First-principles density functional theory is used to determine accurate temperature-dependent thermal expansion and elastic stiffness used for elasto-plasticity modeling. The trained GPR models are found to be capable of deconvoluting the effects of thermal and mechanical strains, in addition to providing information about underlying strain distributions, even from complex diffraction patterns with irregularly shaped peaks.

36 MATERIALS SCIENCE↗

Knocking out the carboxyltransferase interactor 1 (CTI1) in Chlamydomonas boosted oil content by fivefold without affecting cell growth

Summary The first step in chloroplast de novo fatty acid synthesis is catalysed by acetyl‐CoA carboxylase (ACCase). As the rate‐limiting step for this pathway, ACCase is subject to both positive and negative regulation. In this study, we identify a Chlamydomonas homologue of the plant carboxyltransferase interactor 1 (CrCTI1) and show that this protein interacts with the Chlamydomonas α‐carboxyltransferase (Crα‐CT) subunit of the ACCase by yeast two‐hybrid protein–protein interaction assay. Three independent CRISPR‐Cas9 mediated knockout mutants for CrCTI1 each produced an ‘enhanced oil’ phenotype, accumulating 25% more total fatty acids and storing up to fivefold more triacylglycerols (TAGs) in lipid droplets. The TAG phenotype of the crcti1 mutants was not influenced by light but was affected by trophic growth conditions. By growing cells under heterotrophic conditions, we observed a crucial function of CrCTI1 in balancing lipid accumulation and cell growth. Mutating a previously mapped in vivo phosphorylation site (CrCTI1 Ser108 to either Ala or to Asp), did not affect the interaction with Crα‐CT. However, mutating all six predicted phosphorylation sites within Crα‐CT to create a phosphomimetic mutant reduced this pairwise interaction significantly. Comparative proteomic analyses of the crcti1 mutants and WT suggested a role for CrCTI1 in regulating carbon flux by coordinating carbon metabolism, antioxidant and fatty acid β‐oxidation pathways, to enable cells to adapt to carbon availability. Taken together, this study identifies CrCTI1 as a negative regulator of fatty acid synthesis in algae and provides a new molecular brick for the genetic engineering of microalgae for biotechnology purposes.

Li, Zhongze [Aix‐Marseille Université, CEA, CNRS, ↗

Canonical Transformation of Potential Model Hamiltonian Mechanics to Geometrical Form I

Using the methods of symplectic geometry, we establish the existence of a canonical transformation from potential model Hamiltonians of standard form in a Euclidean space to an equivalent geometrical form on a manifold, where the corresponding motions are along geodesic curves. The advantage of this representation is that it admits the computation of geodesic deviation as a test for local stability, shown in recent previous studies to be a very effective criterion for the stability of the orbits generated by the potential model Hamiltonian. We describe here an algorithm for finding the generating function for the canonical transformation and describe some of the properties of this mapping under local diffeomorphisms. We give a convergence proof for this algorithm for the one-dimensional case, and provide a precise geometric formulation of geodesic deviation which relates the stability of the motion in the geometric form to that of the Hamiltonian standard form. We apply our methods to a simple one-dimensional harmonic oscillator and conclude with a discussion of the relation of bounded domains in the two representations for which Morse theory would be applicable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Size dependent lattice pseudosymmetry for frustrated decahedral nanoparticles

Geometric frustration—where geometry prevents simultaneous satisfaction of local interactions—generates pseudosymmetry and emergent behaviors across physical and biological systems. At the nanoscale, pseudosymmetric features in crystalline materials manifest as local strain and distortion, but how they depend on particle size and control structural stability remains unclear. Here, we report the first study of a size-dependent crossover in pseudosymmetry in multi-twinned gold nanoparticles (NPs), combining four-dimensional scanning transmission electron microscopy with nanoscale strain mapping grounded in continuum solid mechanics. Analysis of more than 20 decahedral NPs (20–55 nm) reveals pronounced heterogeneity in multiple modes of in-plane strain and displacement field in small NPs as five tetrahedral grains close the geometric gap, without extended defects. With increasing particle size, strain fields homogenize across grains and local phases shift from predominantly low-symmetry body-centered tetragonal motifs at small sizes to face-centered cubic character approaching the bulk limit. We identify a crossover particle size of ~35 nm, well below bulk, correlating with a transition from modified-Wulff shapes to pentagonal bipyramids, consistent with finite element predictions. This quantitative framework for mapping size-dependent strain and pseudosymmetry enables precise design and control of functional crystalline solids and phase transformation for catalysis, photonics, electronics, and energy storage.

Lin, Oliver [University of Illinois at Urbana-Cham↗

Raptor

Raptor is an efficient Python-based tool for predicting the formation and morphology of stochastic lack of fusion defects in metal AM processes. A major obstacle for the qualification and certification of additively manufactured parts in critical applications continues to be performance variability caused in part by porosity-related defects. High-fidelity process models that could predict these defect features are currently too computationally expensive for component-level analysis. To address this, Raptor employs a high-performance geometric method to model the dynamic melt pool rather than relying on computationally intensive thermal fluid dynamics. This allows Raptor to rapidly identify regions of unmelted material that correspond to lack of fusion pores. The efficiency of this approach significantly reduces the time and resources needed for generating 3D defect predictions, which enables users to conduct large-scale parameter studies and evaluate how process variations affect part quality. The framework offers operational flexibility; users can execute simulations through a simple command line interface or integrate core functions as a library within larger computational workflows. Simulation outputs include 3D porosity maps for visualization and tools for quantitative morphological analysis. These results are suitable for direct comparison with experimental characterization data from methods such as X-ray computed tomography and can be used for statistical process optimization.

Subraveti, Vamsi [Vanderbilt Univ., Nashville, TN ↗

Empirical solar proton model for orbiting spacecraft applications

An empirical model for energetic solar proton fluxes is presented. With this model the effects of such protons on geocentric space missions, to be flown during the next solar active period (1977-1983), and with orbits involving partial magnetospheric shielding, may be estimated. A synoptic background review is given, followed by a detailed discussion of the model's use, errors, uncertainties, and limitations, including sample calculations which demonstrate the application of specific or general project missions. Finally, for circular trajectories, percentage exposure maps are presented, depicting fractional mission times spent outside particular L shells as functions of orbit altitude and inclination.

Stassinopoulos, E. G.↗

Isophotometry of the nuclei of M31 and M51

Isophotic contour maps derived from blue plates confirm the change in position angle as a function of distance from the center of M31 in the red region reported by Peterson, Ford, and Rubin (1977). The techniques used for M31 were then applied to a study of M51, for which similar results were obtained for the nuclear region. The spiral arms of M51 were traced for an additional half turn near the center of the galaxy.

Feibelman, W. A.↗

A low-order global gravity field of Venus and dynamical implications

An estimate of sixth-degree and sixth-order harmonic coefficients of the global gravity field of Venus is obtained by processing the long periodic variations of the mean orbital elements of the Pioneer Venus orbiter. Approximately 220 days of data are included in this reduction, which provides almost complete longitudinal coverage. Oblateness is estimated to be -5.97 + or - 3.2 x 10 to the -6. It is noted that the amplitudes of other coefficients are similar to the predicted coefficients using Kaula's rule under equal stress assumption. Atmospheric density values as a function of altitude are obtained to help model drag perturbation. A radial acceleration map at 100 km above the Venus surface is generated, and correlation between gravity anomalies and major topographic features is observed. Spectral analysis of the harmonic model suggests that the interior density anomalies are like those on earth. The orientation angles of the principal axes of the moments of inertia are computed, and deviation of the maximum moment of inertia axis from the spin axis is observed to be small (less than 5 deg). It is found that the minimum moment of inertia axis passes through the Aphrodite and Beta regions.

Ananda, M. P.↗