Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “KEYING”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Efficient Public-key Revocation Management for Secure Smart Meter Communications using One-way Cryptographic Accumulators

Advanced Metering Infrastructure (AMI) forms a communication network for the collection of power data from smart meters in Smart Grid. As the communication within an AMI needs to be secure, public-key cryptography can be used to reduce the overhead of key management. However, it still has certain challenges in terms of certificate revocation and management. In particular, distribution and storage of the Certificate Revocation List (CRL), which holds the revoked certificates, is a major challenge due to its overhead. To address this challenge, in this paper, we propose a novel revocation management scheme by utilizing cryptographic accumulators which not only reduces the space requirements for revocation information but also enables convenient distribution of revocation information to all smart meters. We implemented this oneway cryptographic accumulator-based revocation scheme on ns-3 using IEEE 802.11s mesh standard as a model for AMI and demonstrated its superior performance with respect to traditional methods of CRL management through extensive simulations.

42 ENGINEERING↗
DOE OSTI2024

Key Strategies in Industry for Circular Economy: Analysis of Remanufacturing and Beneficial Reuse

Manufacturing, in the effort to be more sustainable, is increasingly focusing on energy efficiency and waste reduction. DOE's Better Buildings Better Plants Program has established Waste Reduction Network that works with 32 industrial partners to achieve higher material efficiency and reduce waste. United States generates 7.6 Billion Tons of industrial solid waste as estimated by EPA. In a linear economy as the economy grows, so does the waste – increasing strain on resources and the environment. The Circular Economy (CE) model keeps the available resources in circulation for longer period of time easing the burden on the environment.Remanufacturing and (Beneficial) reuse are widely accepted channels in 9R methodology and established pillars of CE. This chapter reviews the two key strategies and their adoption in different industrial sectors. It reviews the key barriers faced by manufacturers in implementing these methodologies and discusses the possible solutions to those barriers. The chapter also reviews impact of these CE strategies on sustainability, material efficiency and the economic and social benefits. Finally, this chapter presents two case studies from DOE's Better Plants partners – one on remanufacturing of components in heavy vehicles industry and one on beneficial reuse of spent foundry sand, a non-hazardous solid waste, and discusses the project impacts.

Chaudhari, Subodh↗
DOE OSTI2016

Conformational flexibility of BECN1: Essential to its key role in autophagy and beyond: BECN1 Structure and Mechanism

BECN1 (Beclin 1), a highly conserved eukaryotic protein, is a key regulator of autophagy, a cellular homeostasis pathway, and also participates in vacuolar protein sorting, endocytic trafficking, and apoptosis. BECN1 is important for embryonic development, the innate immune response, tumor suppression, and protection against neurodegenerative disorders, diabetes, and heart disease. BECN1 mediates autophagy as a core component of the class III phosphatidylinositol 3-kinase complexes. However, the exact mechanism by which it regulates the activity of these complexes, or mediates its other diverse functions is unclear. BECN1 interacts with several diverse protein partners, perhaps serving as a scaffold or interaction hub for autophagy. Based on extensive structural, biophysical and bioinformatics analyses, BECN1 consists of an intrinsically disordered region (IDR), which includes a BH3 homology domain (BH3D); a flexible helical domain (FHD); a coiled-coil domain (CCD); and a β-α-repeated autophagy-specific domain (BARAD). Each of these BECN1 domains mediates multiple diverse interactions that involve concomitant conformational changes. Thus, BECN1 conformational flexibility likely plays a key role in facilitating diverse protein interactions. Further, BECN1 conformation and interactions are also modulated by numerous post-translational modifications. A better structure-based understanding of the interplay between different BECN1 conformational and binding states, and the impact of post-translational modifications will be essential to elucidating the mechanism of its multiple biological roles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

In silico identification of key genes and signaling pathways targeted by a panel of signature microRNAs in prostate cancer

Accumulating evidence have suggested that some microRNAs are aberrantly expressed in prostate cancer. In our previous work, we had identified a panel of four differentially expressed microRNAs in prostate cancer. In the present study, we have investigated common molecular targets of this panel of miRNAs (DEMs) and key hub genes that can serve as potential candidate biomarkers in the pathogenesis and progression of prostate cancer. A joint bioinformatics approach was employed to identify differentially expressed genes (DEGs) in prostate cancer. Gene enrichment analysis followed by the protein–protein interaction (PPI) network construction and selection of hub genes was further performed using String and Cytoscape, respectively. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the identified hub genes was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. In total, 496 genes were identified to be common targets of DEMs in prostate cancer and 13 key hub genes were identified from three modules of the PPI network of the DEGs. Further top five genes viz Rhoa, PI3KCA, CDC42, MAPK3, TP53 were used for Enrichment analysis which revealed their association with vital cellular and functional pathways in prostate cancer indicating their potential as candidate biomarkers in prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Proteomic analyses reveal the key roles of BrlA and AbaA in biogenesis of gliotoxin in Aspergillus fumigatus

The opportunistic human pathogenic fungus Aspergillus fumigatus primarily reproduces by forming a large number of asexual spores (conidia). Sequential activation of the central regulators BrlA, AbaA and WetA is necessary for the fungus to undergo asexual development. In this study, to address the presumed roles of these key developmental regulators during proliferation of the fungus, we analyzed and compared the proteomes of vegetative cells of wild type (WT) and individual mutant strains. Approximately 1300 protein spots were detectable from 2-D electrophoresis gels. Among these, 13 proteins exhibiting significantly altered accumulation levels were further identified by ESI-MS/MS. Markedly, we found that the GliM and GliT proteins associated with gliotoxin (GT) biosynthesis and self-protection of the fungus from GT were significantly down-regulated in the ΔabaA and ΔbrlA mutants. Moreover, mRNA levels of other GT biosynthetic genes including gliM, gliP, gliT, and gliZ were significantly reduced in both mutant strains, and no and low levels of GT were detectable in the ΔbrlA and ΔabaA mutant strains, respectively. As GliT is required for the protection of the fungus from GT, growth of the ΔbrlA mutant with reduced levels of GliT was severely impaired by exogenous GT. Our studies demonstrate that AbaA and BrlA positively regulate expression of the GT biosynthetic gene cluster in actively growing vegetative cells, and likely bridge morphological and chemical development during the life-cycle of A. fumigatus. - Highlights: • Proteome analyses of WT and mutants reveal 13 differentially expressed proteins. • The GliT and GliM proteins are significantly down-regulated by ΔabaA and ΔbrlA. • Expression of other gliotoxin biosynthetic genes is lowered by ΔabaA and ΔbrlA. • Growth of ΔbrlA strain lacking GliT is completely inhibited by exogenous gliotoxin. • BrlA and AbaA play key roles in biogenesis of gliotoxin in Aspergillus fumigatus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Feedback autophagy activation as a key resistance factor of Ku-0060648 in colorectal cancer cells

The current study evaluated the potential anti-colorectal cancer (CRC) activity by Ku-0060648, a novel DNA-PKcs and PI3K duel inhibitor. In both CRC cell lines (HCT-116 and HT-29) and primary human colon cancer cells, Ku-0060648 exposure at nM concentrations efficiently inhibited cell proliferation. Meanwhile, Ku-0060648 provoked apoptosis in CRC cells. Ku-0060648 was yet ineffective to the normal colon epithelial cells. Ku-0060648 blocked PI3K-AKT-mTOR cascade and in-activated DNA-PKcs in CRC cells. Intriguingly, Ku-0060648 treatment induced feedback autophagy activation in HCT-116 cells. On the other hand, pharmacological autophagy inhibitors (3-methyladenine or chloroquine) or silencing key autophagy proteins (Beclin-1 or ATG-7) dramatically potentiated Ku-0060648-induced HCT-116 cell apoptosis. Together, these results suggest that feedback autophagy activation is a key resistance factor of Ku-0060648 in CRC cells, and autophagy inhibition sensitizes Ku-0060648-induced anti-CRC activity. - Highlights: • Ku-0060648 inhibits colorectal cancer (CRC) cell proliferation. • Ku-0060648 provokes apoptosis in CRC cells. • Ku-0060648 concurrently in-activates AKT-mTOR and DNA-PK in CRC cells. • Ku-0060648 induces feedback autophagy activation in CRC cells. • Autophagy inhibition sensitizes Ku-0060648-meidated anti-CRC cell activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The hazard components of representative key risks. The physical climate perspective

The framework of Representative Key Risks (RKRs) has been adopted by the Intergovernmental Panel on Climate Change Working Group II in order to categorize, assess and communicate a wide range of regional and sectoral key risks, expected to become severe as a consequence of the potentially detrimental convergence of changing climate conditions, exposure and vulnerability of human and natural systems, and responses through (mal)adaptation measures. Other papers in this special issue treat each of eight RKRs by holistically assessing their current status and future evolution as a result of this convergence. However, their treatment cannot always organize such assessment according to a systematic gradation of climatic changes, often times having to extrapolate the big-picture evolution of risk from either qualitative effects of “low” medium” and “high” warming, or limited/focused analysis of the consequences of particular mitigation choices (e.g., benefits of limiting warming to 1.5 or 2C). In this study we offer as systematic a representation as possible – given current literature and assessments – of the future evolution of the hazard components of RKRs. We draw on the assessment of changes in climatic impact-drivers relevant to RKRs described in the 6th Assessment Report by Working Group 1 (WGI) supplemented when needed by more recent literature. We identify the relevant hazards for each RKR, based upon the WGII authors’ assessment, and we report on their current state and expected future changes in magnitude, intensity and/or frequency, linking these changes to Global Warming Levels to the extent possible. For some of these quantities - like regional trends in oceanic and atmospheric temperature and precipitation, some heat and precipitation extremes, permafrost thaw and Northern Hemisphere snow cover - a strong and quantitative relationship with global average temperature change has been assessed. For others - like frequency and intensity of tropical cyclones and extra-tropical storms, and fire weather - the link to increasing global temperatures can only be described qualitatively. For some processes - like the behavior of ice-sheets, or changes in circulation dynamics - large uncertainties about the effects of different levels of warming remain, and for a few others - like ocean pH and air pollution - the composition of the scenario of anthropogenic emissions is most relevant, rather than the warming reached. In almost all cases, however, the basic message remains that every small increment in CO2 concentration in the atmosphere and associated warming will bring changes in climate phenomena that will contribute to increasing risk of impacts on human and natural systems when these changes happen in conjunction with these systems’ conditions of exposure and vulnerability, and in lack of effective adaptation. Our picture of the evolution of RKR-relevant climatic impact-drivers complements and enriches the treatment of RKRs in the other papers in at least two ways: by filling in an often only cursory or limited representation of the physical climate aspects driving impacts, and by providing a fuller representation of their future possible evolution which represents an important component – if never the only one – of the potential future evolution of risk severity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Customer enrollment and participation in building demand management programs: A review of key factors

Increasing the efficiency and flexibility of electricity demand is necessary for ensuring a cost-effective and reliable transition to zero-carbon electricity systems. Such demand-side management (DSM) resources have been procured by utilities for decades via energy efficiency and demand response programs; however, the key drivers of program enrollment and customer participation levels remain poorly understood — even as governments and grid planners seek to scale up the deployment of DSM assets to meet climate targets. Here we systematically review the evidence on multiple factors that may influence customer enrollment and participation in building DSM programs, focusing primarily on residential and commercial buildings. We examine the contexts in which relationships between DSM factors and outcomes are most often explored and with which methods; we also score the strength, direction, and internal consistency of each factor's reported impact on the enrollment and participation outcomes. We find that studies most commonly assess the effects of economic incentives for load flexibility on program participation levels, often using simulation-based methods in lieu of measured data. Few studies focus on program enrollment outcomes or regulatory drivers of either enrollment or participation, and gaps are also evident in the coverage of emerging DSM opportunities like load electrification. Removal of structural barriers (e.g., the lack of controls infrastructure) and the use of third party services (e.g., load aggregators) are the factors with the largest positive impacts on DSM outcomes, but no single factor emerges as clearly most impactful. For a given factor, the range of reported impacts typically varies widely across the relevant studies reviewed. Our findings provide a snapshot of the state of knowledge about building DSM and customer decision-making, and they expose key gaps in understanding that must be filled if building DSM is to expand as a critical resource for operating clean power grids.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Characterization of lignin-degrading enzyme PmdC, which catalyzes a key step in the synthesis of polymer precursor 2-pyrone-4,6-dicarboxylic acid

Pyrone-2,4-dicarboxylic acid (PDC) is a valuable polymer precursor that can be derived from the microbial degradation of lignin. The key enzyme in the microbial production of PDC is 4-carboxy-2-hydroxymuconate-6-semialdehyde (CHMS) dehydrogenase, which acts on the substrate CHMS. We present the crystal structure of CHMS dehydrogenase (PmdC from Comamonas testosteroni) bound to the cofactor NADP, shedding light on its three-dimensional architecture, and revealing residues responsible for binding NADP. Using a combination of structural homology, molecular docking, and quantum chemistry calculations, we have predicted the binding site of CHMS. Key histidine residues in a conserved sequence are identified as crucial for binding the hydroxyl group of CHMS and facilitating dehydrogenation with NADP. Mutating these histidine residues results in a loss of enzyme activity, leading to a proposed model for the enzyme's mechanism. These findings are expected to help guide efforts in protein and metabolic engineering to enhance PDC yields in biological routes to polymer feedstock synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

From Computed Tomography–Guided to Magnetic Resonance Imaging–Guided Intracavitary Brachytherapy for Cervical Cancer: What Do the Key Stakeholders Have to Say about the Transition?

International brachytherapy consortiums are advocating for the incorporation of magnetic resonance imaging (MRI) into the cervical brachytherapy process as a standard-of-care. Although some evaluations have been performed to quantify the effect on procedural time, little is known about the views and experiences of key stakeholders during the transition from computed tomography to MR-guided brachytherapy. This qualitative research project explored insights from key stakeholders related to a change in the gynaecologic brachytherapy process.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SiC layer microstructure in AGR-1 and AGR-2 TRISO fuel particles and the influence of its variation on the effective diffusion of key fission products

Tristructural isotropic (TRISO) coated particle fuel is a promising fuel form for advanced reactor concepts such as high temperature gas-cooled reactors (HTGR) and is being developed domestically under the US Department of Energy’s Nuclear Reactor Technologies Initiative in support of Advanced Reactor Technologies. The fuel development and qualification plan includes a series of fuel irradiations to demonstrate fuel performance from the laboratory to commercial scale. The first irradiation campaign, AGR-1, included four separate TRISO fuel variants composed of multiple, laboratory-scale coater batches. The second irradiation campaign, AGR-2, included TRISO fuel particles fabricated by BWX Technologies with a larger coater representative of an industrial-scale system. The SiC layers of as-fabricated particles from the AGR-1 and AGR-2 irradiation campaigns have been investigated by electron backscatter diffraction (EBSD) to provide key information about the microstructural features relevant to fuel performance. The results of a comprehensive study of multiple particles from all constituent batches are reported. The observations indicate that there were microstructural differences between variants and among constituent batches in a single variant. Finally, insights on the influence of microstructure on the effective diffusivity of key fission products in the SiC layer are also discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Assessing the role of mini-applications in predicting key performance characteristics of scientific and engineering applications

Computational science and engineering application programs are typically large, complex, and dynamic, and are often constrained by distribution limitations. As a means of making tractable rapid explorations of scientific and engineering application programs in the context of new, emerging, and future computing architectures, a suite of miniapps has been created to serve as proxies for full scale applications. Each miniapp is designed to represent a key performance characteristic that does or is expected to significantly impact the runtime performance of an application program. In this paper we introduce a methodology for assessing the ability of these miniapps to effectively represent these performance issues. We applied this methodology to four miniapps, examining the linkage between them and an application they are intended to represent. Herein we evaluate the fidelity of that linkage. This work represents the initial steps required to begin to answer the question, ''Under what conditions does a miniapp represent a key performance characteristic in a full app?''

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Key insights from US Department of Energy Better Plants workforce development bootcamps (2022–2025)

This study examines the effectiveness of the US Department of Energy’s Better Plants Program Bootcamps, which are designed to enhance participants’ technical skills in improving energy efficiency and optimizing operations in manufacturing facilities. Through the analysis of survey data collected from 529 participants across 9 bootcamps, the research investigates the motivations, benefits, and demographic trends of attendees. The findings reveal that skill acquisition and improvement are primary drivers for participation, with key benefits including hands-on training on diagnostic equipment and software tools, networking opportunities, and access to technical resources. The analysis shows strong participation from sectors characterized by high energy consumption and employment, such as chemical and transportation equipment manufacturing. Over 50% of participants have job titles that include “EHS” or “Energy” showing their key roles in leading energy efficiency and energy management efforts in manufacturing. Furthermore, the analysis highlights the distribution of participants across managerial, engineering, and technical roles, revealing a higher representation of managers and engineers. This observation suggests a need for targeted outreach to engage technicians, equipment operators, maintenance staff, and floor workers to ensure comprehensive workforce development. The post-bootcamp survey showed that the participants highly valued the opportunities for peer learning and idea exchange, and the benefits they gained from them. This research contributes to the advancement of manufacturing education by demonstrating the efficacy of specialized training in addressing critical industry challenges and fostering a more competent and empowered workforce.

Energy efficiency↗
DOE OSTI2016

A mouse model of alcoholic liver fibrosis-associated acute kidney injury identifies key molecular pathways

Clinical data strongly indicate that acute kidney injury (AKI) is a critical complication in alcoholic hepatitis, an acute-on-chronic form of liver failure in patients with advanced alcoholic fibrosis. Development of targeted therapies for AKI in this setting is hampered by the lack of an animal model. To enable research into molecular drivers and novel therapies for fibrosis- and alcohol-associated AKI, we aimed to combine carbon tetrachloride (CCl{sub 4})-induced fibrosis with chronic intra-gastric alcohol feeding. Male C57BL/6J mice were administered a low dose of CCl{sub 4} (0.2 ml/kg 2 × week/6 weeks) followed by alcohol intragastrically (up to 25 g/kg/day for 3 weeks) and with continued CCl{sub 4}. We observed that combined treatment with CCl{sub 4} and alcohol resulted in severe liver injury, more pronounced than using each treatment alone. Importantly, severe kidney injury was evident only in the combined treatment group. This mouse model reproduced distinct pathological features consistent with AKI in human alcoholic hepatitis. Transcriptomic analysis of kidneys revealed profound effects in the combined treatment group, with enrichment for damage-associated pathways, such as apoptosis, inflammation, immune-response and hypoxia. Interestingly, Havcr1 and Lcn2, biomarkers of AKI, were markedly up-regulated. Overall, this study established a novel mouse model of fibrosis- and alcohol-associated AKI and identified key mechanistic pathways. - Highlights: • Acute kidney injury (AKI) is a critical complication in alcoholic hepatitis • We developed a novel mouse model of fibrosis- and alcohol-associated AKI • This model reproduces key molecular and pathological features of human AKI • This animal model can help identify new targeted therapies for alcoholic hepatitis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Ceramic–Metal (Cermet) Composites: A Review of Key Properties and Synthesis Methods Focused on Nuclear Waste Immobilization

Here this paper reviews key properties, applications, and examples of ceramic-metal composites (cermets), and metal matrix composites (MMC) with emphasis on their applicability as waste forms for immobilizing nuclear waste. While the literature is mature for vitrified and cementitious radioactive waste forms, cermet materials have not received adequate attention as potential candidates for immobilizing nuclear waste. To promulgate this effort, this review connects cermet and MMC design, such as hardened tools, with the chemistry of radioactive waste streams. A discussion on certification and qualification standards for cermet waste forms, literature gaps, and “how-to” sections on cermet processing techniques. Key parameters discussed include thermal conductivity, chemical durability, and waste loading, as well as examples for metal-containing waste forms. As cermet waste forms gain momentum within the community, this review paper aims ensure the end-of-life nuclear fuel cycle is addressed from a materials and waste disposition perspective.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Tunable Repression of Key Photosynthetic Processes Using Cas12a CRISPR Interference in the Fast-Growing Cyanobacterium Synechococcus sp. UTEX 2973

Cyanobacteria are photoautotrophic prokaryotes that serve as key model organisms to study basic photosynthetic processes and are potential carbon-negative production chassis for commodity and high-value chemicals. The development of new synthetic biology tools and improvement of current ones is a requisite for furthering these organisms as models and production vehicles. CRISPR interference (CRISPRi) allows for targeted gene repression using a DNase-dead Cas nuclease (“dCas”). Here, we describe a titratable dCas12a (dCpf1) CRISPRi system and apply it to repress key photosynthetic processes in the fast-growing cyanobacterium Synechococcus sp. UTEX 2973 (S2973). The system relies on a lac repressor system that retains tight regulation in the absence of inducer (0–10% repression) while maintaining the capability for >90% repression of high-abundance gene targets. We determined that dCas12a is less toxic than dCas9. We tested the efficacy of the system toward eYFP and three native targets in S2973: the phycobilisome antenna, glycogen synthesis, and photosystem I (PSI), an essential part of the photosynthetic electron transport chain in oxygenic photoautotrophs. PSI was knocked down indirectly by repressing the protein factor BtpA involved in stabilizing core PSI proteins. We could reduce cellular PSI titer by 87% under photoautotrophic conditions, and we characterized these cells to gain insights into the response of the strain to the low PSI content. The ability to tightly regulate and time the (de)repression of essential genes in trans will allow for the study of photosynthetic processes that are not accessible using knockout mutants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine Learning of Key Variables Impacting Extreme Precipitation in Various Regions of the Contiguous United States

Abstract Amplification in extreme precipitation intensity and frequency can cause severe flooding and impose significant social and economic consequences. Variations in extreme precipitation intensity, frequencies, and return periods can be attributed to many physical variables across spatial and temporal scales. Here we employ ensemble machine learning (ML) methods, namely random forest (RF), eXtreme Gradient Boosting (XGB), and artificial neural networks (ANN), to explore key contributing variables to monthly extreme precipitation intensity and frequency in six regions over the United States. We further establish emulators for return periods. Results show that the ML models for intensity perform better in regions with obvious seasonality (i.e., Northern Great Plains, Southern Great Plains, and West Coast) than the other three regions (Northeast, Southwest, and Rocky Mountains), while for frequency the models perform well for most regions. The Shapley additive explanation is used to help explain the relationships between extreme precipitation characteristics and identify top variables for RF and XGB. We find that latent heat flux, relative humidity, soil moisture, and large‐scale subsidence are key common variables across the regions for both monthly intensity and frequency, and their compound effects are non‐negligible. The developed ML models capture the probability and return period of extreme precipitation well for all regions and may be used for decision making (e.g., infrastructure planning and design).

54 ENVIRONMENTAL SCIENCES↗