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At least 235 records · Page 13

Results From Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation

Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider threat detection and mitigation (ITDM). Advances in artificial neural networks (ANN) provide more robust pathways for capturing, analyzing, and collating disparate data signals into quantitative descriptions of operational workplace patterns. In response, a joint study by Sandia National Laboratories and the University of Texas at Austin explored the effectiveness of commercial artificial neural network (ANN) software to improve ITDM. Overall, this research demonstrates the benefit of learning patterns of organizational behaviors, detecting off-normal (or anomalous) deviations from these patterns, and alerting when certain types, frequencies, or quantities of deviations emerge for improving ITDM. Evaluating nearly 33,000 access control data points and over 1,600 intrusion sensor data points collected over a nearly twelve-month period, this study's results demonstrated the ANN could recognize operational patterns at the Nuclear Engineering Teaching Laboratory (NETL) and detect off-normal behaviors—suggesting that ANNs can be used to support a data-analytic approach to ITDM. Several representative experiments were conducted to further evaluate these conclusions, with the resultant insights supporting collective behavior-based analytical approaches to quantitatively describe insider threat detection and mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Rationalizing the role of structural motif and underlying electronic structure in the finite temperature behavior of atomic clusters

Melting in finite size systems is an interesting but complex phenomenon. Many factors affect melting and owing to their interdependencies it is a challenging task to rationalize their roles in the phase transition. In this work, we demonstrate how structural motif of the ground state influences melting transition in small clusters. Here, we report a case with clusters of aluminum and gallium having same number of atoms, valence electrons, and similar structural motif of the ground state but drastically different melting temperatures. We have employed Born-Oppenheimer molecular dynamics to simulate the solid-like to liquid-like transition in these clusters. Our simulations have reproduced the experimental trends fairly well. Further, the detailed analysis of isomers has brought out the role of the ground state structure and underlying electronic structure in the finite temperature behavior of these clusters. For both clusters, isomers accessible before cluster melts have striking similarities and does have strong influence of the structural motif of the ground state. Further, the shape of the heat capacity curve is similar in both the cases but the transition is more spread over for Al{sub 36} which is consistent with the observed isomerization pattern. Our simulations also suggest a way to characterize transition region on the basis of accessibility of the ground state at a specific temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dual-Wavelength Simultaneous Patterning of Degradable Thermoset Supports for One-Pot Embedded 3D Printing

Vat photopolymerization (VP) techniques have enabled the fabrication of complex geometries while balancing high precision and fast processing times. 3D printed objects are traditionally built layer-by-layer with newly cured layers being structurally supported by previous ones. Fabricating unsupported features such as overhangs and arches risks misalignment and sagging, limiting the range of accessible designs. To overcome this issue, support structures are fabricated along with the primary object as temporary scaffolds that provide stability and conserve print fidelity. For VP specifically, patterning dissolvable sacrificial supports is attractive to avoid manual removal after printing. In this study, we demonstrate a base-degradable thermoset to pattern print supports in a one-pot formulation along with the primary structural material. Efficient printing is enabled using a dual-wavelength negative imaging (DWNI) DLP printer that patterns the degradable thermoset with visible light and the permanent network with UV light, which are simultaneously projected using a single digital micromirror device (DMD). Printed objects undergo thermal postprocessing to enhance the final conversion of the primary material, after which thermoset supports are degraded in a basic, aqueous solution. This approach provides a robust method for the dual-wavelength patterning of sacrificial thermoset supports, broadening the range of accessible 3D printable materials and geometries.

3D printing↗

Long-term bat abundance in sagebrush steppe

Bats of western North America face many threats, but little is known about current population changes in these mammals. We compiled 283 surveys from 49 hibernacula over 32 years to investigate population changes of Townsend’s big-eared bats (Corynorhinus townsendii townsendii) and western small-footed myotis (Myotis ciliolabrum) in Idaho, USA. This area comprises some of the best bat habitat in the western USA, but is threatened by land-use change. Bats in this area also face invasion by the pathogen causing white-nose syndrome. Little is known about long-term trends of abundance of these two species. In our study, estimated population changes for Townsend’s big-eared bats varied by management area, with relative abundance increasing by 186% and 326% in two management areas, but decreasing 55% in another. For western small-footed myotis, analysis of estimated population trend was complicated by an increase in detection of 141% over winter. After accounting for differences in detection, this species declined region-wide by 63% to winter of 1998–1999. The population fully recovered by 2013–2014, likely because 12 of 23 of its hibernacula were closed to public access from 1994 to 1998. Our data clarify long-term population patterns of two bat species of conservation concern, and provide important baseline understanding of western small-footed myotis prior to the arrival of white-nose syndrome in this area.

54 ENVIRONMENTAL SCIENCES↗

Low-temperature magnetic characterization of optimum and etch-damaged in-plane magnetic tunnel junctions

We describe low-temperature characterization of magnetic tunnel junctions (MTJs) patterned by reactive ion etching for spin-transfer-torque magnetic random access memory. Magnetotransport measurements of typical MTJs show increasing tunneling magnetoresistance (TMR) and larger coercive fields as temperature is decreased down to 10 K. However, MTJs selected from the high-resistance population of an MTJ array exhibit stable intermediate magnetic states when measured at low temperature and show TMR roll-off below 100 K. These non-ideal low-temperature behaviors arise from edge damage during the etch process and can have negative impacts on thermal stability of the MTJs.

36 MATERIALS SCIENCE↗

A Phylogeny-Based Global Nomenclature System and Automated Annotation Tool for H1 Hemagglutinin Genes from Swine Influenza A Viruses

A fundamental goal in the biological sciences is the definition of groups of organisms based on evolutionary history and the naming of those groups. For influenza A viruses (IAVs) in swine, understanding the hemagglutinin (HA) genetic lineage of a circulating strain aids in vaccine antigen selection and allows for inferences about vaccine efficacy. Previous reporting of H1 virus HA in swine relied on colloquial names, frequently with incriminating and stigmatizing geographic toponyms, making comparisons between studies challenging. To overcome this, we developed an adaptable nomenclature using measurable criteria for historical and contemporary evolutionary patterns of H1 global swine IAVs. We also developed a web-accessible tool that classifies viruses according to this nomenclature. This classification system will aid agricultural production and pandemic preparedness through the identification of important changes in swine IAVs and provides terminology enabling discussion of swine IAVs in a common context among animal and human health initiatives.

H1N1↗

TermGenie – a web-application for pattern-based ontology class generation

Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. Lastly, TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

97 MATHEMATICS AND COMPUTING↗

Hourly Load Profile Dataset for Electric Port Cargo Handling Equipment in the United States

Historically, ports have relied on fossil fuels, particularly diesel, as their primary energy source. Transitioning to electric cargo handling equipment (eCHE) offers a promising solution, as this relatively mature technology eliminates tailpipe emissions, reduces harmful airborne particulates, lowers noise pollution, and supports decarbonization. This study develops an initial estimation of hourly electricity demand for eCHE at the top 25 container ports (by tonnage) in the United States. These datasets, accessible at data.nrel.gov/submissions/281, provide valuable insights into the electricity demand patterns and potential grid impacts associated with widespread eCHE adoption, forming a foundation for future refinement based on stakeholder feedback.

33 ADVANCED PROPULSION SYSTEMS↗

Real-time Urban Population Monitoring Using Pervasive Sensor Network

It is estimated that 50% of the global population lives in urban areas occupying just 0.4% of the Earth’s surface. Understanding urban activity constitutes monitoring population density and its changes over time, in urban environments. Currently, there are limited mechanisms to non-intrusively monitor population density in real-time. The pervasive use of cellular phones in urban areas is one such mechanism that provides a unique opportunity to study population density by monitoring the mobility patterns in near real-time. Cellular carriers such as AT&T harvest such data through their cell towers; however, this data is proprietary and the carriers restrict access, due to privacy concerns. In this work, we propose a system that passively senses the population density and infers mobility patterns in an urban area by monitoring power spectral density in cellular frequency bands using periodic beacons from each cellphone without knowing who and where they are located. A wireless sensor network platform is being developed to perform spectral monitoring along with environmental measurements. Algorithms are developed to generate real-time population density and mobility estimates. Data generated using this system is demonstrated for driving modeling and simulation for optimized transportation and aid in generating new understanding of urban infrastructure domains.

Killough, Stephen M.↗

Competitive Exclusion and Metabolic Dependency among Microorganisms Structure the Cellulose Economy of an Agricultural Soil

Microorganisms that degrade cellulose utilize extracellular reactions that yield free by-products which can promote interactions with noncellulolytic organisms. We hypothesized that these interactions determine the ecological and physiological traits governing the fate of cellulosic carbon (C) in soil. We performed comparative genomics with genome bins from a shotgun metagenomic-stable isotope probing experiment to characterize the attributes of cellulolytic and noncellulolytic taxa accessing 13 C from cellulose. We hypothesized that cellulolytic taxa would exhibit competitive traits that limit access, while noncellulolytic taxa would display greater metabolic dependency, such as signatures of adaptive gene loss. We tested our hypotheses by evaluating genomic traits indicative of competitive exclusion or metabolic dependency, such as antibiotic production, growth rate, surface attachment, biomass degrading potential, and auxotrophy. The most 13 C-enriched taxa were cellulolytic Cellvibrio (Gammaproteobacteria) and Chaetomium (Ascomycota), which exhibited a strategy of self-sufficiency (prototrophy), rapid growth, and competitive exclusion via antibiotic production. Auxotrophy was more prevalent in cellulolytic Actinobacteria than in cellulolytic Proteobacteria, demonstrating differences in dependency among cellulose degraders. Noncellulolytic taxa that accessed 13 C from cellulose (Planctomycetales, Verrucomicrobia, and Vampirovibrionales) were also more dependent, as indicated by patterns of auxotrophy and 13 C labeling (i.e., partial labeling or labeling at later stages). Major 13 C-labeled cellulolytic microbes (e.g., Sorangium, Actinomycetales, Rhizobiales, and Caulobacteraceae) possessed adaptations for surface colonization (e.g., gliding motility, hyphae, attachment structures) signifying the importance of surface ecology in decomposing particulate organic matter. Our results demonstrated that access to cellulosic C was accompanied by ecological trade-offs characterized by differing degrees of metabolic dependency and competitive exclusion.

59 BASIC BIOLOGICAL SCIENCES↗

Policy and Regulatory Environment for Utility-Scale Energy Storage: Bangladesh

Bangladesh has experienced significant economic growth and poverty reduction over the past several decades. Recognizing the central role electricity plays in economic development, the Government of Bangladesh (GOB) has established policies to accelerate the growth of the electric power sector. The Bangladesh power grid is transforming into one marked by declining reliance on domestic natural gas reserves and oil-based rental power plants, increasing renewable energy contribution, and shifting demand patterns. The GOB is now reconsidering its prior plans to increase the share of coal capacity in the generation mix to meet demand, shifting its focus instead to electricity imports from neighboring countries, nuclear generation, liquified natural gas imports, and domestic renewable resources such as wind and solar. However, investments in the transmission and distribution system, as well as ancillary services, have not kept pace with investments in generation resources over the past decade. Thus, Bangladesh electricity consumers still experience outages and poor power quality despite adequate installed capacity. On the demand side, population growth and industrialization have fueled steady growth in electricity consumption as efforts to expand access to electricity enabled near-universal electricity access by mid-2020. The combined changes in the mix of generation resources and patterns of electricity demand present new challenges and opportunities in operating and maintaining a reliable power system. Energy storage has the potential to help meet these challenges and accelerate Bangladesh’s energy transition. Declining costs for some energy storage technologies make them increasingly cost-effective solutions to provide a wide range of grid services. Previous analyses of energy storage in the region have identified several potential applications for storage at the bulk system level, including energy arbitrage, ancillary services, and transmission network support. The potential for storage to meet these needs depends on many factors, including physical characteristics of the power system and the policy and regulatory environments in which these energy storage assets would operate. This report applies an Energy Storage Readiness Assessment the National Renewable Energy Laboratory developed for policy makers and regulators to identify priority areas of focus as they continue to develop the appropriate suite of policies, programs, and regulations to enable storage deployment. This assessment uses a simple evaluation scheme to identify the barriers and opportunities for utility-scale energy storage within Bangladesh’s policy and regulatory environment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Construction and comparison of three reference-quality genome assemblies for soybean

Here, we report reference-quality genome assemblies and annotations for two accessions of soybean (Glycine max) and for one accession of Glycine soja, the closest wild relative of G. max. The G. max assemblies provided are for widely used US cultivars: the northern line Williams 82 (Wm82) and the southern line Lee. The Wm82 assembly improves the prior published assembly, and the Lee and G. soja assemblies are new for these accessions. Comparisons among the three accessions show generally high structural conservation, but nucleotide difference of 1.7 single-nucleotide polymorphisms (snps) per kb between Wm82 and Lee, and 4.7 snps per kb between these lines and G. soja. snp distributions and comparisons with genotypes of the Lee and Wm82 parents highlight patterns of introgression and haplotype structure. Comparisons against the US germplasm collection show placement of the sequenced accessions relative to global soybean diversity. Analysis of a pan-gene collection shows generally high conservation, with variation occurring primarily in genomically clustered gene families. We found approximately 40-42 inversions per chromosome between either Lee or Wm82v4 and G. soja, and approximately 32 inversions per chromosome between Wm82 and Lee. We also investigated five domestication loci. For each locus, we found two different alleles with functional differences between G. soja and the two domesticated accessions. The genome assemblies for multiple cultivated accessions and for the closest wild ancestor of soybean provides a valuable set of resources for identifying causal variants that underlie traits for the domestication and improvement of soybean, serving as a basis for future research and crop improvement efforts for this important crop species.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of Geography on Prostate Cancer Treatment

Several definitive treatment options are available for prostate cancer, but geographic access to those options is not uniform. We created maps illustrating provider practice patterns relation to patients and assessed the influence of distance to treatment receipt.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Improving the performance of first- and last-mile mobility services through transit coordination, real-time demand prediction, advanced reservations, and trip prioritization

Socio-demographic trends and recent economic development patterns have resulted in travel behavior changes that call for more flexible and accessible public transit options. Because flexible transit services vary in scope, size, and service type, new data-informed methods are useful to optimize services based on the specific needs of local communities and riders. In this study, real-world demand and vehicle trajectory data were used to evaluate and optimize system performance for an existing first-mile–last-mile (FMLM) service in Robinson Township, PA. A general FMLM model for arbitrary demand and service supply was then developed to quantify system performance—both travel time costs and day-to-day reliability—for various operational polices considering spatio-temporal demand variation and transportation network dynamics. Heuristics were used for optimal real-time vehicle routing in sizable real-world networks accommodating various service types and scopes. In this case study, total user costs were reduced by 18.6% when rides were coordinated with mainline fixed-route transit. Predictive routing strategies were shown to marginally improve system performance under sparse and variable spatio-temporal demand. The case study also highlights potentially large travel time and user reliability improvements—reductions of 51% and 53.8%, respectively—when trip requests were made in advance of their desired pickup time. Finally, we show that travel time reliability can be improved for time-inflexible trips with trip prioritization without increasing total user costs. These results were stable to changes in demand density.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Native Top-Down Mass Spectrometry Characterization of Model Integral Membrane Protein Bacteriorhodopsin

Bacteriorhodopsin (bR) from Halobacterium salinarum has been a model system for structural biology and is a structural template for the characterization of membrane G-protein couple receptors (GPCRs) in particular. Here, in this study, wild-type bacteriorhodopsin and two single-residue mutants were characterized by native top-down mass spectrometry (nTD-MS) with Orbitrap-based high-energy collision dissociation (HCD) and electron capture dissociation (ECD). After in-source dissociation ejected the membrane protein from detergent micelles, high-resolution native MS measurement allowed for identification of multiple proteoforms as well as lipid-bound forms. Further top-down MS measurements by HCD produced a large number of product ions for in-depth sequencing and unambiguous localization of post-translational modifications. For the first time, native TD-MS with ECD was used to characterize an integral membrane protein. ECD yielded fragments originating from all helices and loop regions, even accessing a sequence stretch that HCD could not. Combining HCD and ECD fragmentation patterns significantly enhanced the sequence coverage of bR. We propose bR to be a model analyte for testing nTD-MS performance for membrane proteins.

crystal cleavage↗

Structure-based mechanism of cysteinyl leukotriene receptor inhibition by antiasthmatic drugs

The G protein–coupled cysteinyl leukotriene receptor CysLT 1 R mediates inflammatory processes and plays a major role in numerous disorders, including asthma, allergic rhinitis, cardiovascular disease, and cancer. Selective CysLT 1 R antagonists are widely prescribed as antiasthmatic drugs; however, these drugs demonstrate low effectiveness in some patients and exhibit a variety of side effects. To gain deeper understanding into the functional mechanisms of CysLTRs, we determined the crystal structures of CysLT 1 R bound to two chemically distinct antagonists, zafirlukast and pranlukast. The structures reveal unique ligand-binding modes and signaling mechanisms, including lateral ligand access to the orthosteric pocket between transmembrane helices TM4 and TM5, an atypical pattern of microswitches, and a distinct four-residue–coordinated sodium site. These results provide important insights and structural templates for rational discovery of safer and more effective drugs.

60 APPLIED LIFE SCIENCES↗

Micellar Surfactant Association in the Presence of a Glucoside-based Amphiphile Detected via High-Throughput Small Angle X-ray Scattering

The interactions of mixtures of anionic and amphoteric surfactants with sugar amphiphiles were studied via high throughput small angle x-ray scattering (SAXS). The sugar amphiphile was composed of Caprate, Caprylate, and Oleate mixed ester of methyl glucoside, MeGCCO. Optimal surfactant interactions are sought which have desirable physical properties, which must be identified in a cost effective manner that can access the large phase space of possible molecular combinations. X-ray scattering patterns obtained via high throughput SAXS can probe a combinatorial sample space and reveal the incorporation of MeGCCO into the micelles and the molecular associations between surfactant molecules. Such data make it possible to efficiently assess the effects of the new amphiphiles in the formulation. A specific finding of this study is that formulations containing comparatively monodisperse and homogeneous surfactant mixtures can be reliably tuned by addition of NaCl, which swells the surfactant micelles with a monotonic dependence on salt concentration. In contrast, the presence of multiple different surfactants destroys clear correlations with NaCl concentration, even in otherwise similar series of formulations.

36 MATERIALS SCIENCE↗

Adiabatic quantum optimization for associative memory recall

Hopfield networks are a variant of associative memory that recall patterns stored in the couplings of an Ising model. Stored memories are conventionally accessed as fixed points in the network dynamics that correspond to energetic minima of the spin state. We show that memories stored in a Hopfield network may also be recalled by energy minimization using adiabatic quantum optimization (AQO). Numerical simulations of the underlying quantum dynamics allow us to quantify AQO recall accuracy with respect to the number of stored memories and noise in the input key. We investigate AQO performance with respect to how memories are stored in the Ising model according to different learning rules. Our results demonstrate that AQO recall accuracy varies strongly with learning rule, a behavior that is attributed to differences in energy landscapes. Consequently, learning rules offer a family of methods for programming adiabatic quantum optimization that we expect to be useful for characterizing AQO performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗