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At least 631 records · Page 35

Qualitative Discovery in Medical Databases

Implication rules have been used in uncertainty reasoning systems to confirm and draw hypotheses or conclusions. However a major bottleneck in developing such systems lies in the elicitation of these rules. This paper empirically examines the performance of evidential inferencing with implication networks generated using a rule induction tool called KAT. KAT utilizes an algorithm for the statistical analysis of empirical case data, and hence reduces the knowledge engineering efforts and biases in subjective implication certainty assignment. The paper describes several experiments in which real-world diagnostic problems were investigated; namely, medical diagnostics. In particular, it attempts to show that: (1) with a limited number of case samples, KAT is capable of inducing implication networks useful for making evidential inferences based on partial observations, and (2) observation driven by a network entropy optimization mechanism is effective in reducing the uncertainty of predicted events.

Maluf, David A.↗

Magnetic TRAnsition Region Probe (MTRAP)

MTRAP (Magnetic Transition Region Probe) will reveal the fine-scale physical processes in the Sun's magnetic transition region, the complex layer from the upper photosphere to the upper chromosphere/lower transition region. In the magnetic transition region plasma forces and magnetic forces are of comparable strength, which results in complex interplay of the two, which interplay governs the coupling of the convectively-driven deeper layers to the magnetically-driven upper transition region and inner corona. The fine-scale magnetic structure, processes, and events in the magnetic transition region are key to the genesis of the Sun's entire hot, dynamic outer atmosphere and to the initiation of large eruptive events. MTRAP will be a single spacecraft in Sun-synchronous Earth orbit. Because MTRAP will probe and measure the 3-D structure and dynamics of the magnetic field and plasma in the chromosphere and transition region with unprecedented resolution, the required telescope size and telemetry rates dictate that MTRAP be in Earth orbit, not in deep space. The observations will feature visible and infrared maps of vector magnetic and velocity fields in the magnetic transition region and photosphere. These will have large field of view (greater than 100,000 km), high resolution (greater than 100 km), and high sensitivity (greater than 30 G in transverse field). These observations of the lower atmosphere will be complemented by UV maps of the structure, velocity, and magnetic field (including the full vector field if technically feasible) higher up, in the upper chromosphere and lower transition region. MTRAP will also have an EUV imaging spectrograph observing coronal structure and dynamics in the same field of view with comparable resolution. Specific phenomena to be analyzed include spicules, bright points, jets, the base of plumes, and the triggering of eruptive flares and coronal mass ejections. Additional information is included in the original extended abstract.

Moore, R. L.↗

Advancing Clean Energy Equity

This year’s Financial Innovations Roundtable (June 16-17, 2022) focused on advancing clean energy equity and was co-hosted by the University of New Hampshire's Carsey School of Public Policy and the Federal Reserve Bank of New York. Clean energy technologies are better than ever, with costs continuing to decline. Yet the low-income and under-resourced communities – particularly communities of color, Native communities, and other traditionally marginalized populations – that are disproportionately impacted by climate and severe weather-related events lag in clean energy investments. Community Development Financial Institutions (CDFIs) have a long track record of providing access to capital to low- and moderate-income communities nationwide. Green Banks, established at state and local levels, use innovative financing to attract private capital and incentivize investments in clean and renewable energy. Together, the nation's network of more than 1,300 CDFIs and 21 Green Banks have the financing expertise and deep market understanding and relationships to finance a transition to clean energy. This event explored how Green Banks and CDFIs can funnel creditworthy projects to market and efficiently raise capital for them. Building on the Carsey School White Paper, Clean Energy Project Development for Low-Income Communities: Strengthening the Ecosystem for Delivering Solar Energy and Deep Efficiency Retrofits (Hangen, 2022), the FIR sought to identify options and create opportunities for Green Banks, CDFIs, and impact investors to collaborate in offering a range of products, approaches, and tools to better serve communities and individuals who have thus far been left out of the transition to clean energy. The event had 101 participants from a variety of sectors including CDFIs, Green Banks, mission-driven clean energy organizations, government agencies, banks, and impact investment professionals.

14 SOLAR ENERGY↗

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗

Temporal sequence transformer to advance long-term streamflow prediction

Accurate streamflow prediction is crucial for understanding climate change impacts on water resources and for effective management of extreme hydrological events. While Long Short-Term Memory (LSTM) networks have been the dominant data-driven approach for streamflow forecasting, recent advancements in transformer architectures for time series tasks have shown promise in outperforming traditional LSTM models. This study introduces a transformer-based model that integrates historical streamflow data with climatic variables to enhance streamflow prediction accuracy. We evaluated our transformer model against a benchmark LSTM across five diverse basins in the United States. Results demonstrate that the transformer architecture consistently outperforms the LSTM model across all evaluation metrics, highlighting its potential as a more effective tool for hydrological forecasting. This research contributes to the ongoing development of advanced AI techniques for improved water resource management and climate change adaptation strategies.

Singh, Ruhaan [Farragut High School]↗

Physical phenomena and the microgravity response

The living biological cell is not a sack of Newtonian fluid containing systems of chemical reactions at equilibrium. It is a kinetically driven system, not a thermodynamically driven system. While the cell as a whole might be considered isothermal, at the scale of individual macromolecular events there is heat generated, and presumably sharp thermal gradients exist at the submicron level. Basic physical phenomena to be considered when exploring the cell's response to inertial acceleration include particle sedimentation, solutal convection, motility electrokinetics, cytoskeletal work, and hydrostatic pressure. Protein crystal growth experiments, for example, illustrate the profound effects of convection currents on macromolecular assembly. Reaction kinetics in the cell vary all the way from diffusion-limited to life-time limited. Transport processes vary from free diffusion, to facilitated and active transmembrane transport, to contractile-protein-driven motility, to crystalline immobilization. At least four physical states of matter exist in the cell: aqueous, non-aqueous, immiscible-aqueous, and solid. Levels of order vary from crystalline to free solution. The relative volumes of these states profoundly influence the cell's response to inertial acceleration. Such subcellular phenomena as stretch-receptor activation, microtubule re-assembly, synaptic junction formation, chemotactic receptor activation, and statolith sedimentation were studied recently with respect to both their basic mechanisms and their responsiveness to inertial acceleration. From such studies a widespread role of cytoskeletal organization is becoming apparent.

Todd, Paul↗

A Systematic Review on Coordinated Restoration Strategies for Power Distribution Grids

Power distribution grids are increasingly exposed to High-Impact Low-Probability (HILP) events, which cause widespread disruptions with severe societal and economic impacts. The growing complexity of modern grids, driven by the integration of distributed energy resources and smart grid technologies, has introduced new challenges to effective service restoration. While significant research has explored individual restoration strategies, such as network reconfiguration and microgrid formation, limited attention has been given to methods in which they can be effectively coordinated. Furthermore, the absence of systematic review papers addressing this issue hampers the development of cohesive restoration frameworks capable of addressing the operational complexities of modern grids. This paper presents a systematic review synthesizing existing knowledge on power grid restoration, identifying key limitations, and highlighting opportunities for coordinated strategies. By addressing research gaps and emphasizing the integration of diverse approaches, this study provides critical insights for advancing grid resiliency and recovery, offering a foundation for future research and practical applications in the face of HILP events.

Systematic review↗

Data-driven Community-centered Resilient Assessment and Planning Toolkit for Nexus of Energy and Water (DCRAPT-NEW)

Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.

13 HYDRO ENERGY↗

Absence of silicic volcanism on Mars - Implications for crustal composition and volatile abundance

It is believed that explosive basic to ultrabasic eruptions may be responsible for small cinder conelike features on Mars and perhaps for the ancient flank-scoured paterae. Eruptions of this type may have been driven by near-surface water/ice-magma interactions or volatile rich magmas. Noting that the paterae represent a unique style of volcanism that stopped approximately 2 b.y. ago, it is suggested that the volatiles associated with these features were derived from mantle sources and that the cessation of patera formation may coincide with the termination of the period of maximum planetary degassing. Since approximately 2 b.y. ago volcanism has been dominantly effusive, except for such minor explosive ash events as those that blanketed part of the summit of Hecates Tholus. It is proposed that such eruptions were driven by volatiles generated by differentiation of a magma chamber, similar to Icelandic explosive eruptions.

Francis, P. W.↗

Enhanced Component Performance Study: Motor-Driven Pumps 1998-2020

This report presents an enhanced performance evaluation of motor-driven pumps (MDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2020 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The MDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR≤1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight-hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following increasing trends were identified for MDPs for the most recent 10-year period: • Standby MDP frequency of start demands (demands per reactor year) • Standby MDP frequency of FTR≤1H hours (hours per reactor year) • Standby MDP frequency of FTR>1H hours • Normally running MDP frequency of run hours. The following decreasing trends were identified for MDPs for the most recent 10-year period: • Standby MDP FTR≤1H failure probability • Normally running MDP FTR failure rate • Standby MDP unavailability • Normally running MDP total unreliability (8-hour mission) • Standby MDP frequency of FTR≤1H events (failures per reactor year) • Normally running MDP frequency of FTR events.

99 GENERAL AND MISCELLANEOUS↗

EMIC Wave-Driven Bounce Resonance Scattering of Energetic Electrons in the Inner Magnetosphere

While electromagnetic ion cyclotron (EMIC) waves have been long studied as a scattering mechanism for ultrarelativistic (megaelectron volt) electrons via cyclotron‐resonant interactions, these waves are also of the right frequency to resonate with the bounce motion of lower‐energy (approximately tens to hundreds of kiloelectron volts) electrons. Here we investigate the effectiveness of this bounce resonance interaction to better determine the effects of EMIC waves on subrelativistic electron populations in Earth's inner magnetosphere. Using wave and plasma parameters directly measured by the Van Allen Probes, we estimate bounce resonance diffusion coefficients for four different events, illustrative of wave and plasma parameters to be encountered in the inner magnetosphere. The range of electron energies and pitch angles affected is examined to better assess the realistic effects of EMIC‐driven bounce resonance on energetic electron populations based on actual, locally observed event‐based parameters. Significant local diffusion coefficients (~ > 10(exp −6) s(exp −1)) for 50‐ to 100‐keV electrons are achieved for both H+ band wave events as well as He+ band, with diffusion coefficients peaking for near‐90° pitch angles but remaining elevated for intermediate ones as well. Diffusion coefficients for higher‐energy 200‐keV electrons are typically multiple orders of magnitude lower (ranging from 10(exp −11) to 10(exp −6) s(exp −1)) and often peak at lower pitch angles (~20–30°). These results suggest that both H+ and He+ band EMIC waves can play a role in shaping lower‐energy electron dynamics via bounce‐resonant interactions, in addition to their role in relativistic electron loss via cyclotron resonance.

Blum, L. W.↗

Exploring the connection between compact object mergers and fast X-ray transients

Context. The connection between compact object mergers and some extragalactic fast X-ray transients (FXRTs) has long been hypothesised but never ultimately established. Aims. In this work, we investigate two FXRTs, the LEIA X-ray Transient LXT 240402A and the Einstein Probe EP 250207b, whose precise positions lie close to nearby (z ≲ 0.1) quiescent galaxies with a negligible probability of chance coincidence, identifying them as particularly promising cases of merger-driven explosions in the local Universe. Methods. We used Chandra to derive accurate localisations for both events and secure otherwise ambiguous associations with their optical counterparts. Deep optical and near-infrared observations with VLT, GTC, and LBT were performed to characterise the surrounding environment and search for kilonova emission, the hallmark of neutron star mergers. Complementary early-time X-ray monitoring with Swift and Einstein Probe was used to constrain the non-thermal afterglow. Results. We find that both FXRTs remain compatible with a compact binary merger progenitor, which produced low-mass ejecta and kilonova emission subdominant to the afterglow. However, alternative explanations such as a distant (z ≳ 1) core-collapse supernova cannot be conclusively ruled out.

79 ASTRONOMY AND ASTROPHYSICS↗

Proton transparency and neutrino physics: New methods and modeling

Extracting accurate results from neutrino oscillation and cross section experiments requires accurate simulation of the neutrino-nucleus interaction. The rescattering of outgoing hadrons (final state interactions) by the rest of the nucleus is an important component of these interactions. We present a new measurement of proton transparency (defined as the fraction of outgoing protons that emerge without significant rescattering) using electron-nucleus scattering data recorded by the CLAS detector at Jefferson Laboratory on helium, carbon, and iron targets. This analysis uses a new data-driven method to extract the transparency. It defines transparency as the ratio of electron-scattering events with a detected proton to quasi-elastic electron-scattering events where a proton should have been knocked out. Our results are consistent with previous measurements that determined the transparency from the ratio of measured events to theoretically predicted events. We find that the GENIE event generator, which is widely used by oscillation experiments to simulate neutrino-nucleus interactions, needs to better describe both the nuclear ground state and proton rescattering in order to reproduce our measured transparency ratios, especially at lower proton momenta.

direct reactions↗

Search for $t\bar{t}H/A \rightarrow t\bar{t}t\bar{t}$ production in proton–proton collisions at $\sqrt{s}=13$ $\text {TeV}$ with the ATLAS detector

A search is presented for a heavy scalar (H) or pseudo-scalar (A) predicted by the two-Higgs-doublet models, where the H/A is produced in association with a top-quark pair $(t\bar{t}H/A),$ and with the H/A decaying into a $t\bar{t}$ pair. The full LHC Run 2 proton–proton collision data collected by the ATLAS experiment is used, corresponding to an integrated luminosity of $139~\text {fb}^{-1}.$ Events are selected requiring exactly one or two opposite-charge electrons or muons. Data-driven corrections are applied to improve the modelling of the $t\bar{t}$ +jets background in the regime with high jet and b-jet multiplicities. These include a novel multi-dimensional kinematic reweighting based on a neural network trained using data and simulations. An H/A-mass parameterised graph neural network is trained to optimise the signal-to-background discrimination. In combination with the previous search performed by the ATLAS Collaboration in the multilepton final state, the observed upper limits on the $t\bar{t}H/A \rightarrow t\bar{t}t\bar{t}$ production cross-section at 95% confidence level range between 14 fb and 5.0 fb for an H/A with mass between 400 GeV and 1000 GeV , respectively. Assuming that both the H and A contribute to the $t\bar{t}t\bar{t}$ cross-section, tan β values below 1.7 or 0.7 are excluded for a mass of 400 GeV or 1000 GeV , respectively. The results are also used to constrain a model predicting the pair production of a colour-octet scalar, with the scalar decaying into a $t\bar{t}$ pair.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Major Influence of Tropical Volcanic Eruptions on the Stratospheric Aerosol Layer During the Last Decade

The variability of stratospheric aerosol loading between 1985 and 2010 is explored with measurements from SAGE II, CALIPSO, GOMOS/ENVISAT, and OSIRIS/Odin space-based instruments. We find that, following the 1991 eruption of Mount Pinatubo, stratospheric aerosol levels increased by as much as two orders of magnitude and only reached background levels between 1998 and 2002. From 2002 onwards, a systematic increase has been reported by a number of investigators. Recently, the trend, based on ground-based lidar measurements, has been tentatively attributed to an increase of SO2 entering the stratosphere associated with coal burning in Southeast Asia. However, we demonstrate with these satellite measurements that the observed trend is mainly driven by a series of moderate but increasingly intense volcanic eruptions primarily at tropical latitudes. These events injected sulfur directly to altitudes between 18 and 20 km. The resulting aerosol particles are slowly lofted into the middle stratosphere by the Brewer-Dobson circulation and are eventually transported to higher latitudes.

Vernier, Jean-Paul↗

In Situ Radiometric and Exposure Age Dating of the Martian Surface

We determined radiogenic and cosmogenic noble gases in a mudstone on the floor of Gale Crater. A K-Ar age of 4.21 +/- 0.35 billion years represents a mixture of detrital and authigenic components and confirms the expected antiquity of rocks comprising the crater rim. Cosmic-ray-produced 3He, 21Ne, and 36Ar yield concordant surface exposure ages of 78 T 30 million years. Surface exposure occurred mainly in the present geomorphic setting rather than during primary erosion and transport. Our observations are consistent with mudstone deposition shortly after the Gale impact or possibly in a later event of rapid erosion and deposition. The mudstone remained buried until recent exposure by wind-driven scarp retreat. Sedimentary rocks exposed by this mechanism may thus offer the best potential for organic biomarker preservation against destruction by cosmic radiation.

age dating↗

Sequential Symmetry-Breaking Events as a Synthetic Pathway for Chiral Gold Nanostructures with Spiral Geometries

Symmetry-breaking synthetic controls allow for nanostructure geometries that are counter to the underlying crystal symmetry of a material. If suitably applied, such controls provide the means to drive an isotropic metal along a growth pathway yielding a three-dimensional chiral geometry. In this work, we present a light-driven solution-based synthesis yielding helical gold spirals from substrate-bound seeds. The devised growth mode relies on three separate symmetry-breaking events ushered in by seeds lined with planar defects, a capping agent that severely frustrates early-stage growth, and the Coulombic repulsion that occurs when identically charged growth fronts collide. Together they combine to advance a growth pathway in which planar growth emanates from one side of the seed, advances to encircle the seed from both clockwise and counterclockwise directions, and then upon collision of the two growth fronts, sees one front rise above the other to realize a self-perpetuating three-dimensional spiral structure.

36 MATERIALS SCIENCE↗

System Validation on the Europa Clipper mission in Early Implementation Phase

NASA’s next flag-ship mission - Europa Clipper, will embark on a journey to Jupiter’s icy moon Europa in 2024 to assess its environment and habitability with a highly capable spacecraft. Post Jupiter-Orbit-Insertion, the spacecraft will be commanded to perform intricate, yet meticulously planned Europa flybys to perform science investigations using a suite of instruments, while withstanding Jupiter’s harsh radiation environment. The success of this mission is dependent on a well-coordinated project and its elements such as the flight hardware and software, the ground support and mission operations teams, procedures and other cross-cutting elements. The Europa Clipper project needs to ensure that these elements are realized at a reasonable confidence level prior to launch and other mission critical events. System Validation test and analysis activities exercise and confirm the integrity of the system of all project elements in the expected flight environment with reasonable stressing conditions. These activities go beyond system design requirements verification and are driven by validation objectives that describe the end-to-end functional and operational capabilities required during nominal and off-nominal flight-like scenarios and critical events. The challenges associated with validating that the Europa Clipper project as a whole can function and perform correctly to meet the intended mission objectives with the as-delivered capabilities of all of its elements are daunting. This paper discusses the systematic methodology established in the early implementation phase of the Europa Clipper project for developing System Validation activities and their validation objectives, and addressing any validation-related challenges on the project. Approaches include decomposition of mission objectives using activity timelines in the Mission Design plan for developing nominal scenarios, use of fault trees for exploring off-nominal cases and system boundaries, and use of Model-based Systems Engineering (MBSE) tools for planning and prioritizing these activities.

Wang, Xu↗