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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An optimized FM-index library for nucleotide and amino acid search

Abstract Background Pattern matching is a key step in a variety of biological sequence analysis pipelines. The FM-index is a compressed data structure for pattern matching, with search run time that is independent of the length of the database text. Implementation of the FM-index is reasonably complicated, so that increased adoption will be aided by the availability of a fast and flexible FM-index library. Results We present AvxWindowedFMindex (AWFM-index), a lightweight, open-source, thread-parallel FM-index library written in C that is optimized for indexing nucleotide and amino acid sequences. AWFM-index introduces a new approach to storing FM-index data in a strided bit-vector format that enables extremely efficient computation of the FM-index occurrence function via AVX2 bitwise instructions, and combines this with optional on-disk storage of the index’s suffix array and a cache-efficient lookup table for partial k-mer searches. The AWFM-index performs exact match count and locate queries faster than SeqAn3’s FM-index implementation across a range of comparable memory footprints. When optimized for speed, AWFM-index is $$\sim $$ ∼ 2–4x faster than SeqAn3 for nucleotide search, and $$\sim $$ ∼ 2–6x faster for amino acid search; it is also $$\sim $$ ∼ 4x faster with similar memory footprint when storing the suffix array in on-disk SSD storage. Conclusions AWFM-index is easy to incorporate into bioinformatics software, offers run-time performance parameterization, and provides clients with FM-index functionality at both a high-level (count or locate all instances of a query string) and low-level (step-wise control of the FM-index backward-search process). The open-source library is available for download at https://github.com/TravisWheelerLab/AvxWindowFmIndex.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterizing Sub-Cohorts via Data Normalization and Representation Learning

The process of identifying a cohort of interest is a very challenging task. It requires manually inspecting many patient records of complex structure that might include medical coding errors and missing data. This paper presents a computational pipeline for refining the process of cohort selection based on medical concepts recorded in the electronic health records (EHRs). The pipeline extracts EHR data for a given cohort and normalizes this data using standard vocabularies. Then a stacked denoising autoencoder is used to embed the normalized patient vectors in a low dimensional space, where the patients are subsequently clustered into sub-cohorts. The goal is to represent the cohort in a standard format and abstract variants of sub-populations. As a use-case, we applied the pipeline to 1.8 million Veterans diagnosed with major depressive disorder (MDD), and identified four meaningful sub-cohorts using the features learned by the autoencoder. Then, each sub-cohort was explored using a set of keywords for interpretation.

Rush III, Everett↗
DOE OSTI2017

Photospheric Response to an Ellerman Bomb-like Event—An Analogy of Sunrise/IMaX Observations and MHD Simulations

Ellerman Bombs are signatures of magnetic reconnection, which is an important physical process in the solar atmosphere. How and where they occur is a subject of debate. In this paper, we analyze Sunrise/IMaX data, along with 3D MHD simulations that aim to reproduce the exact scenario proposed for the formation of these features. Although the observed event seems to be more dynamic and violent than the simulated one, simulations clearly confirm the basic scenario for the production of EBs. The simulations also reveal the full complexity of the underlying process. The simulated observations show that the Fe i 525.02 nm line gives no information on the height where reconnection takes place. It can only give clues about the heating in the aftermath of the reconnection. However, the information on the magnetic field vector and velocity at this spatial resolution is extremely valuable because it shows what numerical models miss and how they can be improved.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

MicroRNA-21 promotes wound healing via the Smad7-Smad2/3-Elastin pathway

Highlights: • MicroRNA-21 promotes wound healing. • Smad7 is the target of microRNA-21. • MicroRNA-21 promotes wound healing process via targeting TGF-β pathway. Wound healing is regulated by a complex network of cells, molecules, and cytokines, as well as microRNAs (miRNAs). miRNAs were confirmed to influence the wound healing process, and miR-21, an important member of the miRNA family, was also shown to regulate wound healing. The aim of the present study was to investigate the role of miR-21 in the wound healing process and the possible underlying cell signaling pathways. We isolated GMSCs from WT and miR-21-KO mouse gingiva. Flow cytometric analysis and immunocytofluorescense staining were used to identify the GMSCs acquired from WT and miR-21-KO mice. RT-PCR, western blot analysis and immunohistofluorescence staining were performed to examine the expression of extracellular matrix components and key proteins of cell signaling pathways. TargetScan and pmiR-RB-REPORT vectors were used to verify that Smad7 was a direct target of miR-21. Compared to WT mice, miR-21-KO mice showed slower wound healing. RT-PCR and western blot analysis indicated that Elastin expression was downregulated in miR-21-deficient samples. We confirmed that Smad7 was a direct target of miR-21. miR-21 knockout resulted in increased expression of Smad7 and impaired phosphorylation of the Smad2/3 complex. The expression of the Smad7-Smad2/3-Elastin axis in palate tissues sections acquired from WT and miR-21-KO mice showed the same trend. Based on all these results, we demonstrated that miR-21 promoted the wound healing process via the Smad7-Smad2/3-Elastin pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Evaluation of dose recalculation vs dose deformation in a commercial platform for deformable image registration with a computational phantom

Deformable image registration (DIR) is an important tool for mapping both dose and contours of a new set of planning images when recurrent, that is, adaptive radiotherapy, or further treatment, that is, re-treatment, is required. The aim of this study was to evaluate the need for plan recalculation in deformed anatomies and to develop a reliable workflow for validating the DIR algorithm to be applied to dose warping such as dose accumulation (DA) for adaptive radiation therapy, and dose summation (DS) in the case of re-treatment. A set of 3 computational phantoms was developed to validate the application of B-Spline-based registrations for dose mapping among the various computed tomography image data sets. Two different versions were defined for each phantom to simulate clinical needs: adaptive radiotherapy and re-treatment; a DIR was performed to obtain a displacement vector field (DVF) for dose applications. Comparison of calculated and deformed doses was carried out by means of known markers inside the virtual phantoms. The differences were evaluated using a 3% dose index as acceptance criteria. A paired Wilcoxon signed-rank test was carried out to test the statistical significance of differences within the markers. Significant differences were only observed for the deformed dose in the DA test; no significant differences were observed for recalculated dose values in the DA and DS tests. The dose index is in accordance with these results. The warping dose process obtained by registering various sets of images was validated; a recalculation approach seems to be more accurate for DA purposes and image-guided adaptive radiation therapy (IGART) applications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Knockdown of Trnau1ap inhibits the proliferation and migration of NIH3T3, JEG-3 and Bewo cells via the PI3K/Akt signaling pathway

Highlights: • Knockdown of Trnau1ap attenuated cellular antioxidant activity. • Knockdown of Trnau1ap reduced cell migration and proliferation. • Knockdown of Trnau1ap blocked the PI3K/Akt signaling pathway. The tRNA selenocysteine 1 associated protein 1 (Trnau1ap, initially named SECp43) is involved in Selenocysteine (Sec) biosynthesis and incorporation into selenoproteins, which play a key role in biological processes, such as embryonic development. We previously reported that downregulation of Trnau1ap inhibited proliferation of cardiomyocyte-like H9c2 cells. However, the effects of Trnau1ap on cell proliferation and migration of embryonic development are not known, and the mechanisms remain elusive. Herein, lentiviral shRNA vectors were transfected in NIH3T3, JEG-3 and Bewo cells (embryonic, trophoblast and placental cells). We found that knockdown of Trnau1ap resulted in reduced expression levels of selenoproteins. The data of Cell Count Kit-8 (CCK-8) assay and wound scratch assay revealed the proliferation and migration rates were reduced in the Trnau1ap-shRNA groups. Furthermore, western blot analysis showed that the phosphorylation level of Akt in the phosphatidylinositol 3-kinase (PI3K)/Akt pathway was attenuated. These results indicate that Trnau1ap plays an important role in regulation of cell proliferation and migration through the PI3K/Akt signaling pathway, as well as being essential for embryonic development by regulating the expression of selenoproteins.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Exploring the relationship between nanoscale dynamics and macroscopic rheology in natural polymer gums

Here, we report a study connecting the nanoscale and macroscale structure and dynamics of Acacia mearnsii gum as probed by small-angle x-ray scattering (SAXS), x-ray photon correlation spectroscopy (XPCS) and rheology. Acacia gum, in general, is a complex polysaccharide used extensively in industry. Over the analyzed concentration range (15 to 30 wt%) the A. mearnsii gum is found to have a gel-like linear rheology and to exhibit shear thinning flow behavior under steady shear. The gum exhibited a steadily increasing elastic modulus with increasing time after they were prepared and also the emergence of shear thickening events within the shear thinning behavior, characteristic of associative polymers. XPCS measurements using gold nanoparticles as tracers were used to explore the microscopic dynamics within the biopolymer gels and revealed a two-step relaxation process with a partial decay at inaccessibly short times, suggesting caged motion of the nanoparticles, followed by a slow decay at later delay times. Non-diffusive motion evidenced by a compressed exponential line shape and an inverse relationship between relaxation time and wave vector characterizes the slow dynamics of A. mearnsii gum gels. Surprisingly, we have determined that the nanometer-scale mean square displacement of the nanoparticles showed a close relationship to the values predicted from the macroscopic elastic properties of the material, obtained through the rheology experiments. Our results demonstrate the potential applicability of the XPCS technique in the natural polymers field to connect their macroscale properties with their nanoscale structure and dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Boosting RDataFrame performance with transparent bulk event processing

RDataFrame is ROOT’s high-level interface for Python and C++ data analysis. Since it first became available, RDataFrame adoption has grown steadily and it is now poised to be a major component of analysis software pipelines for LHC Run 3 and beyond. Thanks to its design inspired by declarative programming principles, RDataFrame enables the development of highperformance, highly parallel analyses without requiring expert knowledge of multi-threading and I/O: user logic is expressed in terms of self-contained, small computation kernels tied together by a high-level API. This design completely decouples analysis logic from its actual execution, and opens several interesting avenues for workflow optimization. In particular, in this work we explore the benefits of moving internal data processing from an event-by-event to a bulkby-bulk loop. This refactoring dramatically reduces the framework’s runtime overheads; in collaboration with the I/O layer it improves data access patterns; it exposes information that optimizing compilers might use to auto-vectorize the invocation of user-defined computations; finally, while existing user-facing interfaces remain unaffected, it becomes possible to additionally offer interfaces that explicitly expose bulks of events, useful e.g. for the injection of GPU kernels into the analysis workflow. In order to inform similar future R&D, design challenges will be presented, as well as an investigation of the relevant timememory trade-off backed by novel performance benchmarks.

Guiraud, Enrico↗
DOE OSTI2021

Case Study of Using Kokkos and SYCLs Performance-Portable Frameworks for Milc-Dslash Benchmark on NVIDIA, AMD and Intel GPUs

Six of the top ten supercomputers in the TOP500 list from June 2021 rely on NVIDIA GPUs to achieve their peak compute bandwidth. With the announcement of Aurora, Frontier, and El Capitan, Intel and AMD have also entered the domain of providing GPUs for scientific computing. A consequence of the increased diversity in the GPU landscape is the emergence of portable programming models such as Kokkos, SYCL, OpenCL, and OpenMP, which allow application developers to maintain a single-source code across a diverse range of hardware architectures. While the portable frameworks try to optimize the compute resource usage on a given architecture, it is the programmers responsibility to expose parallelism in an application that can take advantage of thousands of processing elements available on GPUs. In this paper, we introduce a GPU-friendly parallel implementation of Milc-Dslash that exposes multiple hierarchies of parallelism in the algorithm. Milc-Dslash was designed to serve as a benchmark with highly optimized matrix-vector multiplications to measure the resource utilization on the GPU systems. The parallel hierarchies in the Milc-Dslash algorithm are mapped onto a target hardware using Kokkos and SYCL programming models. We present the performance achieved by Kokkos and SYCL implementations of Milc-Dslash on NVIDIA A100 GPU, AMD MI100 GPU, and Intel Gen9 GPU. Additionally, we compare the Kokkos and SYCL performances with those obtained from the versions written in CUDA and HIP programming models on NVIDIA A100 GPU and AMD MI100 GPU, respectively.

Dufek, Amanda S↗
DOE OSTI2025

A Dynamic Hierarchical Attention Framework for Multimodal Malware Detection

The increasing use of Android in the worldwide mobile ecosystem has come along with a significant increase in advanced malware, highlighting the critical necessity for efficient, scalable, and adaptable detection systems. Despite recent advancements in machine learning improving malware detection, the majority of current solutions are limited to one, two, or three data modalities, hence neglecting the comprehensive behavioral spectrum of contemporary multi-vector threats. This thesis presents the first comprehensive multimodal framework for Android malware detection, which combines textual, time-series (temporal), graph-based (structural), and visual information using an innovative hierarchical attention mechanism and Dynamic Fusion Controller (DFC). Our methodology consistently classifies and processes modalities as either sequential or structural, facilitating content-adaptive weighting and resilient cross-modal representation learning. We advance the implementation of cutting-edge time series techniques, such as MiniRocket, for malware detection, hence creating new opportunities for temporal analysis in cybersecurity. Comprehensive experimental assessment shows that our framework performs exceptionally well, with 99.46% classification accuracy and 97.15% detection accuracy, significantly outperforming existing approaches through effective multimodal integration and hierarchical attention mechanisms.

Nazmin, Tamanna↗
DOE OSTI2024

Understanding Event Trajectories Across Massive Temporal Datasets with Word Embeddings and Visualization

In collaboration with researchers from Virginia Tech, Savannah River National Laboratory has continued development of a natural language processing pipeline to identify and extract events of interest from massive open data sources in the domain of worldwide state-sponsored civil nuclear energy. The foundation of the pipeline is built on compass aligned temporal word embedding models, whereby contextual shifts are automatically identified by comparing keyword embedding vectors across successive time windows. Within the approach, a contextual shift indicates the occurrence of a potential event of interest. However, in such a broad topical domain that captures events at a global scale, across various life cycle stages, and across numerous different technology types, a user that is monitoring events may have broad interests in capturing many different event types with varying degrees of signal. As such, the quantity of information that may be returned from an automated event extraction pipeline can be substantial, requiring manual effort to sift through the information to identify any relevant bits of information. Therefore, a more streamlined workflow that aids in directing a user toward specific information at different points in time is necessary. The workflow presented here has been developed with this concept in mind, built on top of the initial prototype event extraction pipeline, whereby a user can analyze temporal text-based data sources at multiple different contextual levels to isolate key points in time and key subdomains captured within a data corpus. Using multiple corpuses that consist of approximately 7 million Tweets and 7 million news articles, the team has extended compass aligned temporal word embedding models to establish an interconnected and hierarchical structure that relates known key words of interest to documents, local topics (i.e., within a time window), and global topics across the corpuses. All of this information is packaged into a visual analytics system that is linked to the information extraction pipeline and enables a user to identify contextual information that describes the evolution of a high dimensional embedding space across time to isolate changes of interest and explore associated events. This report demonstrates the use of these analytics and a means to fuse information across multiple datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Three-Dimensional Flow Behavior Inside the Submerged Entry Nozzle

According to various authors, the surface quality of steel depends on the dynamic conditions that occur within the continuous casting mold’s upper region. The meniscus, found in that upper region, is where the solidification process begins. The liquid steel is distributed into the mold through a submerged entry nozzle (SEN). In this paper, the dynamic behavior inside the SEN is analyzed by means of physical experiments and numerical simulations. The particle imaging velocimetry technique was used to obtain the vector field in different planes and three-dimensional flow patterns inside the SEN volume. Moreover, large eddy simulation was performed, and the turbulence model results were used to understand the nonlinear flow pattern inside the SEN. Using scaled physical and numerical models, quasi-periodic behavior was observed due to the interaction of two three-dimensional vortices that move inside the SEN lower region located between the exit ports of the nozzle.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mild-to-wild plastic transition is governed by athermal screw dislocation slip in bcc Nb

Plastic deformation in crystals is mediated by the motion of line defects known as dislocations. For decades, dislocation activity has been treated as a homogeneous, smooth continuous process. However, it is now recognized that plasticity can be determined by long-range correlated and intermittent collective dislocation processes, known as avalanches. Here we demonstrate in body-centered cubic Nb how the long-range and scale-free dynamics at room temperature are progressively quenched out with decreasing temperature, eventually revealing intermittency with a characteristic length scale that approaches the Burgers vector itself. Plasticity is shown to be bimodal across the studied temperature regime, with conventional thermally-activated smooth plastic flow (‘mild’) coexisting with sporadic bursts (‘wild’) controlled by athermal screw dislocation activity, thereby violating the classical notion of temperature-dependent screw dislocation motion at low temperatures. An abrupt increase of the athermal avalanche component is identified at the critical temperature of the material. Our results indicate that plasticity at any scale can be understood in terms of the coexistence of these mild and wild modes of deformation, which could help design better alloys by suppressing one of the two modes in desired temperature windows.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Impact of mass generation for spin-1 mediator simplified models

In the simplified dark matter models commonly studied, the mass generation mechanism for the dark fields is not typically specified. We demonstrate that the dark matter interaction types, and hence the annihilation processes relevant for relic density and indirect detection, are strongly dictated by the mass generation mechanism chosen for the dark sector particles, and the requirement of gauge invariance. We focus on the class of models in which fermionic dark matter couples to a spin-1 vector or axial-vector mediator. However, in order to generate dark sector mass terms, it is necessary in most cases to introduce a dark Higgs field and thus a spin-0 scalar mediator will also be present. In the case that all the dark sector fields gain masses via coupling to a single dark sector Higgs field, it is mandatory that the axial-vector coupling of the spin-1 mediator to the dark matter is non-zero; the vector coupling may also be present depending on the charge assignments. For all other mass generation options, only pure vector couplings between the spin-1 mediator and the dark matter are allowed. If these coupling restrictions are not obeyed, unphysical results may be obtained such as a violation of unitarity at high energies. These two-mediator scenarios lead to important phenomenology that does not arise in single mediator models. We survey two-mediator dark matter models which contain both vector and scalar mediators, and explore their relic density and indirect detection phenomenology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Speeding up software with VecCore

Portable and efficient vectorization is a significant challenge in large software projects such as GeantV, ROOT, and experiments’ frameworks. Nevertheless, fully exploiting SIMD parallelism will be a required step in order to bridge the widening gap between the needs and availability of computing resouces for data analysis and processing in particle physics. Although there are SIMD libraries that wrap compiler intrinsics into a convenient interface, they do not always support all available architectures, or they only perform well in some of them. The VecCore library was created to address some of these performance and portability issues by providing a unified abstraction layer on top of existing libraries, such as Vc or UME::SIMD. In this article, we discuss VecCore’s programming model for SIMD code and some use cases in HEP software packages such as VecGeom and GeantV.

Amadio, G.↗
DOE OSTI2017

Unlocking Flexibility: Energy Systems Integration [Guest Editorial]

The articles in this special section focus on energy systems integration (ESI). Electric power systems around the world are experiencing great changes, including the retirement of coal and nuclear plants along with a rapid increase in the use of natural gas turbines and variable renewable technologies such as wind and solar. There is also much more use of information and communications technologies to enhance the visibility and controllability of the grid. Flexibility of operation, the ability of a power system to respond to change in demand and supply, is critical to enable higher levels of variable generation. One way to unlock this potential flexibility is to tap into other energy domains. This concept of interconnecting energy domains is called ESI. ESI is the process of coordinating the operation and planning of energy systems across multiple pathways and/or geographical scales to deliver reliable, cost-effective energy services with minimal impact on the environment. Integrating energy domains adds flexibility to the electrical power system. ESI includes interactions among energy vectors and with other large-scale infrastructures including water, transport, and data and communications networks, which are an enabling technology for ESI.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Data-Driven Robust RVFLNs Modeling of a Blast Furnace Iron-Making Process Using Cauchy Distribution Weighted M-Estimation

Optimal operation of a practical blast furnace (BF) ironmaking process depends largely on a good measurement of molten iron quality (MIQ) indices. However, measuring the MIQ online is not feasible using the available techniques. In this paper, a novel data-driven robust modeling is proposed for online estimation of MIQ using improved random vector functional-link networks (RVFLNs). Since the output weights of traditional RVFLNs are obtained by the least squares approach, a robustness problem may occur when the training dataset is contaminated with outliers. This affects the modeling accuracy of RVFLNs. To solve this problem, a Cauchy distribution weighted M-estimation based robust RFVLNs is proposed. Since the weights of different outlier data are properly determined by the Cauchy distribution, their corresponding contribution on modeling can be properly distinguished. Thus robust and better modeling results can be achieved. Moreover, given that the BF is a complex nonlinear system with numerous coupling variables, the data-driven canonical correlation analysis is employed to identify the most influential components from multitudinous factors that affect the MIQ indices to reduce the model dimension. Finally, experiments using industrial data and comparative studies have demonstrated that the obtained model produces a better modeling and estimating accuracy and stronger robustness than other modeling methods.

42 ENGINEERING↗