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Disaster risk and artificial intelligence: A framework to characterize conceptual synergies and future opportunities

Artificial intelligence (AI) methods have revolutionized and redefined the landscape of data analysis in business, healthcare, and technology. These methods have innovated the applied mathematics, computer science, and engineering fields and are showing considerable potential for risk science, especially in the disaster risk domain. The disaster risk field has yet to define itself as a necessary application domain for AI implementation by defining how to responsibly balance AI and disaster risk. (1) How is AI being used for disaster risk applications; and how are these applications addressing the principles and assumptions of risk science, (2) What are the benefits of AI being used for risk applications; and what are the benefits of applying risk principles and assumptions for AI-based applications, (3) What are the synergies between AI and risk science applications, and (4) What are the characteristics of effective use of fundamental risk principles and assumptions for AI-based applications? This study develops and disseminates an online survey questionnaire that leverages expertise from risk and AI professionals to identify the most important characteristics related to AI and risk, then presents a framework for gauging how AI and disaster risk can be balanced. This study is the first to develop a classification system for applying risk principles for AI-based applications. This classification contributes to understanding of AI and risk by exploring how AI can be used to manage risk, how AI methods introduce new or additional risk, and whether fundamental risk principles and assumptions are sufficient for AI-based applications.

97 MATHEMATICS AND COMPUTING↗

Editorial for Special Issue: Grid-Interactive Efficient Buildings - Part 1

We are pleased to present starting with this volume of ASME Journal of Engineering for Sustainable Buildings and Cities (JESBC), a series of peer-reviewed papers related to some of ongoing research projects and applications of Grid-interactive Efficient Buildings (GEBs). As part of a new program initiated by the Building Technology Office (BTO) with the US Department of Energy (DOE), GEBs are characterized as highly energy-efficient buildings that are equipped with smart technologies and distributed energy resources that can be dynamically controlled to meet grid needs and minimize electricity system costs, while meeting occupants’ comfort and productivity requirements. In simple terms,DOE defines GEBs as efficient, connected, smart, and flexible buildings. The GEB technologies touch on the main topical areas of JESBC aimed at fostering sustainable buildings and cities by providing results of evaluation studies and demonstration projects. Indeed, one of the main goals for JESBC is to disseminate solutions to enhance the built environment energy efficiencies, low carbon services, inter-connectivity services, resilient multi-services, and healthy and comfortable living spaces.

buildings↗

Dual mechanism of the OXA-23 carbapenemase inhibition by the carbapenem NA-1-157

Carbapenem-resistant Acinetobacter baumannii continues to be a leading cause of life-threatening infections that result in high mortality rates. The major cause of carbapenem resistance in this pathogen is the production of class D carbapenemases, enzymes that inactivate the last resort carbapenem antibiotics, thus significantly diminishing the available therapeutic options. In this study, we evaluated the interaction of OXA-23, the most widely disseminated class D carbapenemase in A. baumannii clinical isolates, with the atypically modified carbapenem, NA-1-157. The MICs of this compound against strains producing OXA-23 were reduced from highly resistant levels observed for the commercial carbapenems meropenem and imipenem (16–128 µg/mL) to sensitive or intermediate levels (2–4 µg/mL). Kinetic studies showed that NA-1-157 inhibits the enzyme due to a significant decrease (>2,000-fold) in the deacylation rate relative to its closest structural analog, meropenem. Structural studies and molecular dynamics simulations demonstrated that inhibition is caused by both the inability of a water molecule to get close enough to the scissile bond to perform deacylation and by partial decarboxylation of the catalytic lysine residue upon formation of the acyl-enzyme intermediate.

Acinetobacter baumannii↗

Host-specific adaptation in Fusarium oxysporum correlates with distinct accessory chromosome content in human and plant pathogenic strains

ABSTRACT Fusarium oxysporumis a cross-kingdom pathogen. While some strains cause disseminated fusariosis and blinding corneal infections in humans, others are responsible for devastating vascular wilt diseases in plants. To better understand the distinct adaptations ofF. oxysporumto animal or plant hosts, we conducted a comparative phenotypic and genetic analysis of two strains: MRL8996 (isolated from a keratitis patient) and Fol4287 (isolated from a wilted tomato [Solanum lycopersicum]). Infection of mouse corneas and tomato plants revealed that, while both strains cause symptoms in both hosts, MRL8996 caused more severe corneal disease in mice, whereas Fol4287 induced more pronounced wilting symptoms in tomato plants.In vitroassays using abiotic stress treatments revealed that the human pathogen MRL8996 was better adapted to elevated temperatures, whereas the plant pathogen Fol4287 was more tolerant to osmotic and cell wall stresses. Both strains displayed broad resistance to antifungal treatment, with MRL8996 exhibiting the paradoxical effect of increased tolerance to higher concentrations of the antifungal caspofungin. We identified a set of accessory chromosomes (ACs) that encode genes with different functions and have distinct transposon profiles between MRL8996 and Fol4287. Interestingly, ACs from both genomes also encode proteins with shared functions, such as chromatin remodeling and post-translational protein modifications. Our phenotypic assays and comparative genomics analyses lay the foundation for future studies correlating genotypes with phenotype and for developing targeted antifungals for agricultural and clinical uses. IMPORTANCE Fusarium oxysporumis a cross-kingdom fungal pathogen that infects both plants and animals. In addition to causing many devastating wilt diseases, this group of organisms was recently recognized by the World Health Organization as a high-priority threat to human health. Climate change has increased the risk ofFusariuminfections, asFusariumstrains are highly adaptable to changing environments. Deciphering fungal adaptation mechanisms is crucial to developing appropriate control strategies. We performed a comparative analysis ofFusariumstrains using an animal (mouse) and plant (tomato) host andin vitroconditions that mimic abiotic stress. We also performed comparative genomics analyses to highlight the genetic differences between human and plant pathogens and correlate their phenotypic and genotypic variations. We uncovered important functional hubs shared by plant and human pathogens, such as chromatin modification, transcriptional regulation, and signal transduction, which could be used to identify novel antifungal targets.

Microbiology↗

Sac1 links phosphoinositide turnover to cryptococcal virulence

Cryptococcus neoformans is an environmentally acquired fungal pathogen that causes over 140,000 deaths per year. Cryptococcal infection occurs when infectious particles are deposited into the lung, where they encounter host phagocytic cells. C. neoformans may be engulfed by these phagocytes, an important step of infection that leads to outcomes ranging from termination of infection to cryptococcal dissemination. To study this critical process, we screened approximately 4,700 cryptococcal gene deletion mutants for altered uptake, using primary mouse and human phagocytic cells. Among the hits of these two screens, we identified 93 mutants with perturbed uptake in both systems, as well as others with differences in uptake by only one cell type. We further screened the hits for changes in thickness of the capsule, a protective polysaccharide layer around the cell which is an important cryptococcal virulence factor. The combination of our three screens yielded 45 mutants, including one lacking the phosphatidylinositol-4-phosphate phosphatase Sac1. In this work, we implicate Sac1 in both host cell uptake and capsule production. We found that sac1 mutants exhibit lipid trafficking defects, reductions in secretory system function, and changes in capsule size and composition. Many of these changes occur specifically in tissue culture media, highlighting the role of Sac1 phosphatase activity in responding to the stress of host-like conditions. Overall, these findings show how genome-scale screening can identify cellular factors that contribute to our understanding of cryptococcal biology and demonstrate the role of Sac1 in determining fungal virulence.

59 BASIC BIOLOGICAL SCIENCES↗

Biophysical and Biochemical Characterization of TP0037, a D-Lactate Dehydrogenase, Supports an Acetogenic Energy Conservation Pathway in Treponema pallidum

A longstanding conundrum in Treponema pallidum biology concerns how the spirochete generates sufficient energy to fulfill its complex pathogenesis processes during human syphilitic infection. For decades, it has been assumed that the bacterium relies solely on glucose catabolism (via glycolysis) for generation of its ATP. However, the organism’s robust motility, believed to be essential for human tissue invasion and dissemination, would require abundant ATP likely not provided by the parsimony of glycolysis. As such, additional ATP generation, either via a chemiosmotic gradient, substrate-level phosphorylation, or both, likely exists in T. pallidum. Along these lines, we have hypothesized that T. pallidum exploits an acetogenic energy conservation pathway that relies on the redox chemistry of flavins. Central to this hypothesis is the apparent existence in T. pallidum of an acetogenic pathway for the conversion of d-lactate to acetate. Herein we have characterized the structural, biophysical, and biochemical properties of the first enzyme (d-lactate dehydrogenase [d-LDH]; TP0037) predicted in this pathway. Binding and enzymatic studies showed that recombinant TP0037 consumed d-lactate and NAD+ to produce pyruvate and NADH. The crystal structure of TP0037 revealed a fold similar to that of other d-acid dehydrogenases; residues in the cofactor-binding and active sites were homologous to those of other known d-LDHs. The crystal structure and solution biophysical experiments revealed the protein’s propensity to dimerize, akin to other d-LDHs. This study is the first to elucidate the enzymatic properties of T. pallidum’s d-LDH, thereby providing new compelling evidence for a flavin-dependent acetogenic energy conservation (ATP-generating) pathway in T. pallidum.

59 BASIC BIOLOGICAL SCIENCES↗

Plasmid-Encoded Traits Vary across Environments

Plasmids are well known for their role in the transmission of antibiotic resistance-conferring genes. Beyond human and clinical settings, however, they disseminate many other types of genes, including those that contribute to microbially driven ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

PlasmidHostFinder: Prediction of Plasmid Hosts Using Random Forest

Plasmids play a major role facilitating the spread of antimicrobial resistance between bacteria. Understanding the host range and dissemination trajectories of plasmids is critical for surveillance and prevention of antimicrobial resistance. Identification of plasmid host ranges could be improved using automated pattern detection methods compared to homology-based methods due to the diversity and genetic plasticity of plasmids. In this study, we developed a method for predicting the host range of plasmids using machine learning—specifically, random forests. We trained the models with 8,519 plasmids from 359 different bacterial species per taxonomic level; the models achieved Matthews correlation coefficients of 0.662 and 0.867 at the species and order levels, respectively. Our results suggest that despite the diverse nature and genetic plasticity of plasmids, our random forest model can accurately distinguish between plasmid hosts. This tool is available online through the Center for Genomic Epidemiology (https://cge.cbs.dtu.dk/services/PlasmidHostFinder/).

59 BASIC BIOLOGICAL SCIENCES↗

Early immune response to Coccidioides is characterized by robust neutrophil and fibrotic macrophage recruitment and differentiation

Coccidioidomycosis, or Valley fever, is an emerging respiratory disease caused by soil-dwelling fungi of the Coccidioides genus that is expected to spread from the southwest into the central U.S. by 2050. While 60% of infections are asymptomatic, the other 40% of patients experience a range of symptoms, from self-limiting pneumonia to life-threatening disseminated disease. The immunological events that underlie the progression to severe disease remain underdefined. Here, we probed the early immune response to Coccidioides using a high dose of an attenuated strain of Coccidioides posadasii in a mouse model of infection coupled with single-cell RNA sequencing. At 24 h post-infection, robust immune infiltration is detected in the lung, marked by high levels of inflammatory PD-L1 + neutrophils and fungal-contact-dependent pro-fibrotic Spp1 + macrophages. These findings elucidate the early dynamics of the host response to Coccidioides and provide a deeper understanding of host-pathogen interactions in the lung.

Coccidioides↗

Versatile allelic replacement and self-excising integrative vectors for plasmid genome mutation and complementation

ABSTRACT The ability to better understand the function of proteins expressed by bacteria has typically relied upon the development of genetic mutant strains. This approach has been especially challenging for plasmid-encoded genes, as most of the previously described allelic replacement vectors are inefficient for plasmid genome mutation as they either rely on plasmid-derived counterselection toxins or depend on other strategies suchsacB,tetA, andrpsLwhich have been proven to be less efficient for mutant selection. Integrative vectors lack chromophore indicators, thus requiring laborious screening or excision of the vector’s backbone relies on the introduction of a flippase (FLP)-expressing plasmid. The allelic replacement vector, designated here as pDG1, expresses an X-Gal hydrolyzing enzyme (BgaB) that can be used for blue/white screening allowing identification of colonies that integrated and successfully removed the mutagenesis plasmid without a bias for those still carrying it. pDG1 was further improved by including the rhamnose-inducible Tse2 toxin as a potent counterselection system. The efficacy of pDG1 was validated by deleting portions of the plasmid-encoded VirB4/D4 type IV secretion system and aerobactin-synthesizing operons inSalmonella enterica. The integrative vectors, which contain an ΦC31attPsite and genes encoding ΦC31 integrase (int), can seamlessly integrate to target ΦC31attBonSalmonellaplasmids or chromosome. These vectors were improved by insertingbgaBand FLP-encoding genes so that, following integration, most of the vector’s backbone encompassingint,bgaB, and FLP genes can be excised by FLP, without the need for another FLP-expressing vector, creating white colonies carrying a stably integrated target gene. As such, we were able to integrate a 9.3-kb DNA fragment toSalmonellachromosome and flipped out most of the integrated vector in one step, leaving the target fragment in the chromosome. IMPORTANCE In spite of the dissemination of multidrug-resistant plasmids among Gram-negative pathogens, including those carrying virulence genes, vector tools for studying plasmid-born genes are lacking. The allelic replacement vectors can be used to generate plasmid or chromosomal mutations including markless point mutations. This is the first report describing a self-excising integrative vector that can be used as a stable single-copy complementing tool to study medically important pathogens includingin vivostudies without the need for antibiotic selection. Overall, our newly developed vectors can be applied for the assessment of the function of plasmid-encoded genes by specifically creating mutations, moving large operons between plasmids and to/from the chromosome, and complementing phenotypes associated with gene mutation. Furthermore, the vectors express chromophores for the detection of target gene modification or colony isolation, avoiding time-consuming screening procedures.

Microbiology↗

Experiences Readying Applications for Exascale

The advent of Exascale computing invites an assessment of existing best practices for developing application readiness on the world's largest supercomputers. This work details observations from the last four years in preparing scientific applications to run on the Oak Ridge Leadership Computing Facility's (OLCF) Frontier system. This paper addresses a range of topics in software including programmability, tuning, and portability considerations that are key to moving applications from existing systems to future installations. A set of representative workloads provides case studies for general system and software testing. We evaluate the use of early access systems for development across several generations of hardware. Finally, we discuss how best practices were identified and disseminated to the community through a wide range of activities including user-guides and trainings. We conclude with recommendations for ensuring application readiness on future leadership computing systems.

exascale↗

TrackTable Trajectory Analysis

Tracktable is designed for analysis and rendering of the trajectories of moving objects such as planes, trains, automobiles and ships. Its purpose is to operate on large sets of trajectories (millions) to help a user detect, analyze and display patterns. It will also be used to disseminate trajectory research results from Sandia's PANTHER Grand Challenge LDRD.

Wilson, AndrewT.↗

Grid Reliability Statistics [SWR-25-45]

This codebase houses a suite of statistical and descriptive analyses of NERC GADS data of interest to grid modelers and planners. This repository is envisioned to house a collection of statistical and descriptive summaries of NERC GADS data, particularly summaries that on their own might be insufficient to warrant publication. In addition, it is intended to disseminate results rather than to enable reproduction as GADS is non-public.

Murphy, Sinnott [National Renewable Energy Laborat↗

PERSIANN Dynamic Infrared–Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset

This study presents the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR-Now) near-real-time precipitation dataset. This dataset provides hourly, quasi-global, infrared-based precipitation estimates at 0.04° × 0.04° spatial resolution with a short latency (15–60 min). It is intended to supersede the PERSIANN–Cloud Classification System (PERSIANN-CCS) dataset previously produced as the near-real-time product of the PERSIANN family. We first provide a brief description of the algorithm’s fundamentals and the input data used for deriving precipitation estimates. Second, we provide an extensive evaluation of the PDIR-Now dataset over annual, monthly, daily, and subdaily scales. Last, the article presents information on the dissemination of the dataset through the Center for Hydrometeorology and Remote Sensing (CHRS) web-based interfaces. The evaluation, conducted over the period 2017–18, demonstrates the utility of PDIR-Now and its improvement over PERSIANN-CCS at all temporal scales. Specifically, PDIR-Now improves the estimation of rain/no-rain days as demonstrated by a critical success index (CSI) of 0.53 compared to 0.47 of PERSIANN-CCS. In addition, PDIR-Now improves the estimation of seasonal and diurnal cycles of precipitation as well as regional precipitation patterns erroneously estimated by PERSIANN-CCS. Finally, an evaluation is carried out to examine the performance of PDIR-Now in capturing two extreme events, Hurricane Harvey and a cluster of summer thunderstorms that occurred over the Netherlands, where it is shown that PDIR-Now adequately represents spatial precipitation patterns as well as subdaily precipitation rates with a correlation coefficient (CORR) of 0.64 for Hurricane Harvey and 0.76 for the Netherlands thunderstorms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying Meteorological Drivers for Errors in Modeled Winds along the Northern California Coast

Abstract An accurate wind resource dataset is required for assessing the potential energy yield of floating offshore wind farms that are expected along the California outer continental shelf. The National Renewable Energy Laboratory has developed and disseminated an updated wind resource dataset offshore of California, using the Weather Research and Forecasting Model, referred to as the CA20 dataset. As compared to buoy lidar measurements that have become available recently, the CA20 dataset showed significant positive biases for 100-m wind speeds along Northern California wind energy lease areas. To investigate the meteorological drivers for the model errors, we first consider two 1-yr simulations run with two different planetary boundary layer (PBL) parameterizations: the Mellor–Yamada–Nakanishi–Niino (MYNN) PBL scheme (the chosen configuration in the CA20 dataset) and the Yonsei University PBL scheme (which significantly reduces the bias in modeled winds). By comparing the 1-yr simulations to the concurrent lidar buoy observations, we find that errors are larger with the MYNN PBL scheme in warm seasons. We then dive deeper into the analysis by running simulations for short-term (3-day) case studies to evaluate the sensitivity of initial/boundary condition forcings on model results. By analyzing the short-term simulations, we find that during synoptic-scale northerly flows driven by the North Pacific high and inland thermal low, a coastal warm bias in the MYNN simulation is mainly responsible for the modeled wind speed bias by altering the boundary layer thermodynamics. The results of our analysis will help guide the creation of an updated version of the CA20 dataset.

17 WIND ENERGY↗

Interactive Web Application for Traffic Simulation Data Management and Visualization

As traffic simulation software becomes more effective for realistically simulating and analyzing traffic dynamics and vehicle interactions on the mesoscopic and microscopic level, the management, dissemination, and collaborative visualization of traffic simulation results produced by individual transportation planners presents a significant challenge. Existing online content management systems have a very limited capability in allowing users to query specific traffic simulation scenarios and geospatially visualize simulation results through shareable and interactive web interfaces. This paper presents a web-based application for promoting the archiving, sharing, and visualization of large-scale traffic simulation outputs. The application is developed to enhance cyber-physical controls, communications, and public education for collaborative transportation planning. Unique features of the web application include: (a) allowing users to upload their new traffic simulation scenarios (parameters and outputs), as well as search existing scenarios using easily accessible interfaces; (b) optimizing simulation output files with heterogeneous data formats and projected coordinate systems for web-based storage and management using a scalable and searchable data/metadata standard; (c) standardizing user-uploaded simulation outputs using web interfaces and data processing libraries with parallel computing capacity; and (d) providing shareable web visual interfaces for visualizing the traffic flow and signal information stored in simulation outputs (e.g., regional traffic patterns and individual vehicle interactions) and visually comparing multiple simulation outputs both spatially and temporally. Furthermore, the paper presents the conceptual design and implementation of this application, and demonstrates the application’s performance for sharing, comparing, and visualizing simulation outputs from VISSIM and SUMO, two commonly used traffic simulation software programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A core lighting curriculum for university students and lighting professionals

Here, in collaboration with a group of lighting professionals, learning outcomes were defined, prioritized, organized and mapped to a three-course sequence of lighting courses within a Bachelor of Science in Architectural Engineering degree programme. Syllabi and educational exercises were developed to support the learning outcomes – including classroom activities, homework assignments and design projects. The learning exercises balance the technical foundations of applied illuminating engineering with the artistic aspects of applied lighting design and are intended to promote significant and lasting learning by providing students with education that is useful and relevant to current lighting practice. The process for identifying and prioritizing lighting content is described, a process that could be adapted by other lighting educators to other pedagogical contexts. The syllabi and learning exercises are disseminated for reuse or adaptation, or for self-study by independent learners.

42 ENGINEERING↗