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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 451 records · Page 25

Impact of longitudinal phase-matching variations on three-wave nonlinear interactions

A general study of three-wave nonlinear mixing in the presence of longitudinal variations in phase-matching conditions is presented. The efficiency of second-harmonic generation and optical parametric amplification is quantified using a normalized set of equations and a polynomial description of the wave-vector mismatch as a function of the longitudinal coordinate. These modeling results are used to estimate the impact of spatial variations in wave-vector mismatch experimentally obtained for five partially deuterated potassium dihydrogen phosphate crystals. The longitudinal inhomogeneities in the properties of crystals of similar quality are not expected to have a significant impact on their use for second-harmonic generation and optical parametric amplification, but the efficiency of nonlinear processes in crystals with larger variations could decrease.

36 MATERIALS SCIENCE↗

Cross-Correlation Analysis of Digital Speckle Photography

This paper describes new algorithms for processing noisy specklograms, which permit quantitative diagnostics of the microstructure of shock-wave flows with a subpicosecond accuracy with the use of statistical analysis of numerically registered speckle fields disturbed by the refraction in the investigated flows. The software developed by us permits reconstructing up to 10,000 vector angles of probe radiation deflection in a two-dimensional region of size 20 × 30 mm{sup 2} in imaging a speckle field with optical magnification M = 1.

42 ENGINEERING↗

Predicting measures of soil health using the microbiome and supervised machine learning

Soil health encompasses a range of biological, chemical, and physical soil properties that sustain the commercial and ecological value of agroecosystems. Monitoring soil health requires a comprehensive set of diagnostics that can be cost-prohibitive for routine analyses. The soil microbiome provides a rich source of information about soil properties, which can be assayed in a high-throughput, cost-effective way. We evaluated the accuracy of random forest (RF) and support vector machine (SVM) regression and classification models in predicting 12 measures of soil health, tillage status, and soil texture from 16S rRNA gene amplicon data with an operationally relevant sample set. We validated the efficacy of the best performing models against independent datasets and also tested best practices for processing microbiome data for use in machine learning. Soil health metrics could be predicted from microbiome data with the best models achieving a Kappa value of ~0.65, for categorical assessments, and a R2 value of ~0.8, for numerical scores. Biological health ratings were better predicted than chemical or physical ratings. Validation with independent datasets revealed that models had general predictive value for soil properties, including yield. The ecological profiles of several taxa important for model accuracy matched the observed relationships with soil health, including Pyrinomonadaceae, Nitrososphaeraceae, and Candidatus Udeaobacter. Models trained at the highest taxonomic resolution proved most accurate, with losses in accuracy resulting from rarefying, sparsity filtering, and aggregating at higher taxonomic ranks. Furthermore, our study provides the groundwork for developing scalable technology to use microbiome-based diagnostics for the assessment of soil health.

16S rRNA gene↗

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗

Data exchange and processing synchronization in distributed systems

Systems, methods, techniques and apparatuses of asynchronous communication is distributed systems are disclosed. One exemplary embodiment is a method determining, with a plurality of agent nodes structured to communicate asynchronously in a distributed system, a first set of iterations including an iteration determined by each of the plurality of agent nodes; determining, with a first agent node of the plurality of agent nodes, a local vector clock; receiving, with the first agent node, a first iteration of the first set of iterations and a remote vector clock determined based on the first iteration; updating, with the first agent node, the local vector clock based on the received remote vector clock; and determining a first iteration of a second set of iterations based on the first set of iterations after determining all iterations of the first set of iterations have been received based on the local vector clock.

Cintuglu, Mehmet H.↗

Cross-beam energy transfer in direct-drive ICF. I. Nonlinear and kinetic effects

Results are presented from a series of simulations examining the susceptibility of the cross-beam energy transfer (CBET) instability to nonlinear processes in the context of direct-drive inertial confinement fusion experiments on the OMEGA laser facility. These form the basis for the second paper of this series [A. G. Seaton, L. Yin, R. Follett, B. J. Albright, and A. Le, “Cross-beam energy transfer in direct-drive ICF. II. Theory and simulation of mitigation through increased laser bandwidth,” Phys. Plasmas 29, 042707 (2022)], where we examine the efficacy of increases in laser bandwidth at suppressing CBET. We choose laser and plasma conditions for the simulations that are favorable to CBET and promote nonlinearity. Through a comparison of outputs from the particle-in-cell code vector particle in cell (VPIC) and the linearized fluid code laser-plasma simulation environment (LPSE), a series of nonlinear effects have been identified in the kinetic simulations that include particle trapping, the two-ion wave decay, and ion-acoustic wave self-focusing. These effects produce time-dependent energy transfer, in contrast to the linearized fluid simulations in which a steady state is reached after an initial transient. Ion trapping is shown to allow for increased energy transfer relative to fluid simulations, with the remaining nonlinear processes acting to reduce the energy transfer. Nonlinear dynamics is contrasted for low- and high-intensity beams as well as between speckled and planar beams. For the parameters under consideration, beam profile has a significant effect on nonlinear dynamics, though the greatest sensitivity is to beam intensity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A new model to study cell-to-cell transfer of αSynuclein in vivo

Highlights: • Parkinson's disease involved the loss of dopaminergic neurons associated with the accumulation of misfolded alpha-synuclein. • The neurodegeneration in Parkinson's disease spread through the brain by the transfer of alpha-synuclein from cell to cell. • The mechanisms involved alpha-synuclein secretion, uptake and spreading are not well understood. • In this study we developed a new model to monitor cell-to-cell transfer of alpha-Synuclein in vivo. Parkinson's disease (PD) compromises motor control due to the loss of dopaminergic neurons in the substantia nigra pars compacta. At the histopathological level, PD is characterized by the accumulation of Lewy bodies, large protein inclusions containing aggregated αSynuclein (αSyn). The progression of PD involves the spreading of αSyn misfolding through the brain mediated by a prion-like mechanism, where the protein is transferred between cells. Here we report that αSyn internalization is a dynamic process, where the protein transits through different sub-cellular compartments. Importantly, cells incorporating αSyn develop larger protein-like inclusions when compared to αSyn producing cells. We developed a new tool to monitor cell-to-cell transfer of αSyn in vivo using an adeno-associated viral (AAV) vector expressing αSyn fused to a red fluorescent protein in addition to soluble EGFP to label donor cells. Intra-nigral delivery of this reporter AAV construct allowed the visualization of αSyn incorporation into surrounding neurons. This work provides a new tool to study αSyn cell-to-cell transfer in vivo and may open new opportunities to study PD pathogenesis.

60 APPLIED LIFE SCIENCES↗

LncRNA embryonic stem cells expressed 1 (Lncenc1) is identified as a novel regulator in neuropathic pain by interacting with EZH2 and downregulating the expression of Bai1 in mouse microglia

LncRNA embryonic stem cells expressed 1 (Lncenc1), named after its high expression in naïve embryonic stem cells (nESCs), has been rarely studied in almost all pathological processes. Evidences suggest that Lncenc1 is likely to work in the form of RNA-protein complex. Here, we found that Lncenc1 in dorsal root ganglion (DRG) was significantly upregulated in response to mouse nerve injury caused by partial sciatic nerve ligation (pSNL). Overexpression of Lncenc1 mediated by adenoviral expression vector promoted the activation of microglia and the production of inflammatory cytokines including TNF-α, IL-1β and MCP-1. In contrast, knockdown of Lncenc1 suppressed activation of microglia and production of inflammatory cytokines. In the mechanism exploration, we found that Lncenc1 could bind with the RNA binding protein (RBP) enhancer of zeste homologue 2 (EZH2), an identified contributor in microglial activation and neuropathic pain. Lncenc1 interacted with EZH2 and downregulated the expression of brain-specific angiogenesis inhibitor 1 (BAI1). Either inhibition of EZH2 or overexpression of BAI1 could reverse the effects of Lncenc1 overexpression on microglial activation and neuroinflammation. Finally, the Lncenc1-siRNA was intrathecally injected into pSNL mice, and its effects on neuropathic pain were evaluated. Knockdown of Lncenc1 attenuated the development and maintenance of mechanical and thermal hyperalgesia of pSNL mice, accompanied by an increase in BAI1 expression and decrease in inflammatory cytokines. In conclusion, Lncenc1 contributes to neuropathic pain by interacting with EZH2 and downregulating the BAI1 gene in mouse microglia.

60 APPLIED LIFE SCIENCES↗

Type IV-like pili facilitate transformation in naturally competent archaea

Naturally competent organisms are capable of DNA uptake directly from the environment through the process of transformation. Despite the importance of transformation to microbial evolution, DNA uptake remains poorly characterized outside the bacterial domain. Here, we identify the pilus as a necessary component of the transformation machinery in archaea. We describe two naturally competent organisms: Methanococcus maripaludis and Methanoculleus thermophilus. In M. maripaludis, replicative vectors were transferred with an average efficiency of 2.4 x 10 3 transformants μg -1 DNA. In M. thermophilus, integrative vectors were transferred with an average efficiency of 2.7 x 10 3 transformants μg -1 DNA. Additionally, natural transformation of M. thermophilus could be used to introduce chromosomal mutations. To our knowledge, this is the first demonstration of a method to introduce targeted mutations in a member of the order Methanomicrobiales. For both organisms, mutants lacking structural components of the type IV-like pilus filament were defective for DNA uptake, demonstrating the importance of pili for natural transformation. Interestingly, competence could be induced in a non-competent strain of M. maripaludis by expressing pilin genes from a replicative vector. Furthermore, these results expand the known natural competence pili to include examples from the archaeal domain and highlight the importance of pili for DNA uptake in diverse microbial organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Interflow Is Not Binary: A Continuous Shallow Perched Layer Does Not Imply Continuous Connectivity

Hillslopes exert critical controls on the quality and quantity of downstream waters. To understand and model dominant headwater catchment processes, we need to estimate the relative importance of different runoff generation processes. In this work we analyze published data from studies of 17 hillslopes from a range of landscapes to better understand the relative role of interflow, that is, shallow lateral subsurface flow moving over a layer impeding percolation, in streamflow generation. For each slope, we calculated downslope interflow travel distances, that is, the potential distance a water parcel travels downslope above an impeding layer until it percolates into the impeding layer. The downslope travel distances for the 17 hillslopes ranged from around 1 m to several hundred meters. The vector analysis of downslope travel distances revealed that all but three hillslopes had slope lengths that were much longer than downslope travel distances. For the remaining 14 cases we could show that most water perched above a shallow impeding layer percolates through the impeding layer before reaching the valley or the stream channel. Thus, interflow usually contributes directly to valley water or streamflow only from the lower portions of the hillslope in most landscapes. A critical finding of our analysis is that a continuously perched saturated zone with downslope flow does not imply continuous connectivity to the stream. Such a continuous connectivity is the exception rather than the rule in most landscapes. Future hillslope and headwater processes and modeling studies will need to account for this.

60 APPLIED LIFE SCIENCES↗

Forbidden scalar dark matter and dark Higgses

As experimental searches for WIMP dark matter continue to yield null results, models beyond the WIMP paradigm have proliferated in order to elude ever improving observational constraints, among them that of sub-GeV dark matter mediated by a massive vector portal (a dark photon) associated with a new dark U(1) gauge symmetry. It has been previously noted that for a significant range of the parameter space of this class of models, the annihilation of dark matter particles into a pair of dark photons can dominate the freeze-out process even when this process is kinematically forbidden for dark matter at rest — this is known as the “forbidden dark matter” (FDM) regime. Prior studies of this regime, however, assume that any “dark Higgs” associated with breaking the dark U(1) and imparting mass to the dark photon is decoupled from the dark matter and as such plays no role in the freeze-out process. In this paper, we explore the effects of a dark Higgs on sub-GeV dark matter phenomenology in this FDM regime by considering the simplest possible construction in which there exist non-trivial dark matter-dark Higgs couplings: a model with a single complex scalar DM candidate coupled directly to the dark Higgs field. We find that for a wide range of parameter space, the dark Higgs can alter the resulting relic abundance by many orders of magnitude, and that this effect can remain significant even for a small dark matter-dark Higgs coupling constant. Considering measurements from direct detection and measurements of the CMB, we further find that points in this model’s parameter space which recreate the appropriate dark matter relic abundance suffer only mild constraints from other sources at present, but may become accessible in near-future direct detection experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Cloning, Purification, and Characterization of Recombinant Thermostable β-Xylanase Tnap-0700 from Thermotoga naphthophila

The gene of a β-xylanase (Tnap-0700) was cloned from a hyperthermophilic Thermotoga naphthophila strain ATCC BAA-489 and expressed in Escherichia coli BL21 (DE3) via pET-21a (+) as an expression vector. The growth steps were upgraded for highest β-xylanase expression via several factors, for example, IPTG concentration, time of induction, pH, and temperature. The pH and temperature optima for the extreme expression of β-xylanase were 7.0 pH and 37 °C, correspondingly. Recombinant enzyme purified by heat treatment process, then later by immobilized metal ion affinity chromatography. Molecular mass of the purified β-xylanase was 38 kDa observed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The enzyme was stable at room temperature for 30 days. It exhibited high stability over wide series of temperature 50–90 °C and pH 4.0–9.0 upon the addition of 1 mM Ca{sup +2} and reduced in the existence of Cu{sup +2} and EDTA. The addition of about 10–30% different organic solvents have no considerable effect on enzyme. However, SDSF and urea acting as an inhibitor leads to decrease in the enzyme activity. The β-xylanase enzyme was active to hydrolyze xylan from beechwood forming xylose. Thermostable β-xylanase causes the breakdown of complex carbohydrates into monosaccharide components. This thermostable β-xylanase revealed remarkable properties, which make it an encouraging candidate for various industrial applications especially in the alteration of renewable biomaterials into ethanol production, and biofuels from lignocellulosics has acknowledged much devotion subsequently in the last decade.

60 APPLIED LIFE SCIENCES↗

A data-centric weak supervised learning for highway traffic incident detection

Using the data from loop detector sensors for near-real-time detection of traffic incidents on highways is crucial to averting major traffic congestion. While recent supervised machine learning methods offer solutions to incident detection by leveraging human-labeled incident data, the false alarm rate is often too high to be used in practice. Specifically, the inconsistency in the human labeling of the incidents significantly affects the performance of supervised learning models. To that end, we focus on a data-centric approach to improve the accuracy and reduce the false alarm rate of traffic incident detection on highways. We develop a weak supervised learning workflow to generate high-quality training labels for the incident data without the ground truth labels, and we use those generated labels in the supervised learning setup for final detection. This approach comprises three stages. First, we introduce a data preprocessing and curation pipeline that processes traffic sensor data to generate high-quality training data through leveraging labeling functions, which can be domain knowledge-related or simple heuristic rules. Second, we evaluate the training data generated by weak supervision using three supervised learning models-random forest, k-nearest neighbors, and a support vector machine ensemble-and long short-term memory classifiers. The results show that the accuracy of all of the models improves significantly after using the training data generated by weak supervision. Third, we develop an online real-time incident detection approach that leverages the model ensemble and the uncertainty quantification while detecting incidents. Finally, we show that our proposed weak supervised learning workflow achieves a high incident detection rate (0.90) and low false alarm rate (0.08).

97 MATHEMATICS AND COMPUTING↗

Calcium-mediated nitrogen reduction for electrochemical ammonia synthesis

Ammonia (NH 3 ) is a key commodity chemical for the agricultural, textile and pharmaceutical industries, but its production via the Haber–Bosch process is carbon-intensive and centralized. Alternatively, an electrochemical method could enable decentralized, ambient NH 3 production that can be paired with renewable energy. The first verified electrochemical method for NH 3 synthesis was a process mediated by lithium (Li) in organic electrolytes. So far, however, elements other than Li remain unexplored in this process for potential benefits in efficiency, reaction rates, device design, abundance and stability. In our demonstration of a Li-free system, we found that calcium can mediate the reduction of nitrogen for NH 3 synthesis. Here we verified the calcium-mediated process using a rigorous protocol and achieved an NH 3 Faradaic efficiency of 40 ± 2% using calcium tetrakis(hexafluoroisopropyloxy)borate (Ca[B(hfip) 4 ] 2 ) as the electrolyte. Our results offer the possibility of using abundant materials for the electrochemical production of NH 3 , a critical chemical precursor and promising energy vector

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revisiting supernova constraints on a light CP-even scalar

A light CP-even Standard Model (SM) gauge-singlet scalar S can be produced abundantly in the supernova core, via the nucleon bremsstrahlung process NN → NNS, due to its mixing with the SM Higgs boson. Including the effective S coupling to both nucleons and the pion mediators, we evaluate the production amplitude for the S particle and point out a key difference with the well-known light CP-odd scalar (axion) and vector boson (dark photon) cases. Taking the subsequent decay and re-absorption of S into account, we present a complete calculation of the energy loss rate for the S particle. We then use the SN1987A luminosity constraints to derive updated supernova limits on the mixing of the scalar S with the SM Higgs boson. We find that the mixing angle sin θ with the SM Higgs is excluded only in the narrow range of 3.9 × 10 -7 to 7.0 × 10 -6 , depending on the scalar mass up to about 147 MeV, beyond which the supernova limit disappears.

79 ASTRONOMY AND ASTROPHYSICS↗

Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool

Scientific inquiry often requires analysis of multiple spatio-temporal datasets, ranging in type and size, using complex multi-step processes demanding an understanding of GIS theory and software. Cumulative Spatial Impact Layers (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi-format, multi-source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built-in flexibility of the CSIL tool allows users to answer a range of spatially-driven questions. Example applications are provided in this paper to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision-making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSILs provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses.

58 GEOSCIENCES↗

Vector elastic deconvolution migration with dual wavefield decomposition

Here, we report elastic-wave imaging using multicomponent data can provide more useful subsurface information than acoustic-wave imaging, but it is usually algorithmically challenging. We have developed a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method uses a vector deconvolution imaging condition based on dual wavefield decomposition, including an explicit directional wavefield separation using the Hilbert transform and a P/S vector wavefield decomposition using the low-rank decomposition method. Using three elastic models, we numerically determine that our new method produces notably higher resolution and more amplitude-balanced elastic images compared with a crosscorrelation-based vector elastic reverse time migration method.

58 GEOSCIENCES↗

Pushing the Limits of Micro battery Capacity and Energy

Micro battery with higher energy density will extend the service life of the miniature sensors so that the scientists and engineers could be able to collect more data along with the time in ecological and environmental vectors, such as animal tracking. Within this project, a completely new cell design (Gen2) for micro batteries to further increase their cell capacity and energy is developed. The new cell design directly packages the active material in a hard aluminum case, decreasing the percentage of non-active components. The manufacturing process to improve wetting ability is studied and the trial run is finally given to evaluate the feasibility of the proposed technology. It’s found that both the capacity and energy with same battery size could be increased by 30% comparing with Gen1 micro battery technology previously developed by PNNL. The yield of Gen2 micro batteries is still lower due to the high degree of manual operation, especially for drilling process where more precise position control is needed. More effort is still required to improve the capability of automatic manufacturing processes. The new battery technology will support the development of smaller and lighter miniature sensors at PNNL and could potentially contribute to the large-scale manufacturing capabilities of micro batteries in US with reliable performances and long-term shelf life.

25 ENERGY STORAGE↗