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At least 919 records · Page 51

Josephson magnetic rotary valve

We propose a control element for a Josephson spin valve. It is a complex Josephson device containing ferromagnetic (F) layer in the weak-link area consisting of two regions, representing 0 and π Josephson junctions, respectively. The valve's state is defined by mutual orientations of the F-layer magnetization vector and boundary line between 0 and π sections of the device. We consider possible implementation of the control element by introduction of a thin normal metal layer in a part of the device area. By means of theoretical simulations, we study properties of the valve's structure as well as its operation, revealing such advantages as simplicity of control, high characteristic frequency, and good legibility of the basic states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Excited J -- Resonances in Meson-Meson Scattering from Lattice QCD

Understanding the excited light meson spectrum is vital to our understanding of how quarks and gluons bind to become hadrons. This sector is home to a plethora of states including hadrons laying outside the quark model. Distinguishing the exotics from the rest of the spectrum would be made easier if we first had a handle on the light qq¯ spectrum. I present the first determination of excited light JP C = 1--, 2--, 3-- resonances in meson-meson scattering at the SU(3) flavor point from lattice QCD. This system can be described in the context of pseudoscalar-vector elastic scattering and I determine two 1-- resonances; a lighter broader state followed by a heavier narrow state, one broad 2-- resonance, and one narrow 3-- resonance. This is the first calculation in lattice QCD that successfully extracts two resonances from the same partial wave, as well as the first calculation of a light 2-- resonance. I present the results in terms of the physical omega*/J , phi*/J resonances decaying into final states pi rho, KK¯*, eta omega and others, and compare to experiment as well as a popular phenomenological model.

Johnson, Christopher↗

Drought and immunity determine the intensity of West Nile virus epidemics and climate change impacts

The effect of global climate change on infectious disease remains hotly debated because multiple extrinsic and intrinsic drivers interact to influence transmission dynamics in nonlinear ways. The dominant drivers of widespread pathogens, like West Nile virus, can be challenging to identify due to regional variability in vector and host ecology, with past studies producing disparate findings. Here, we used analyses at national and state scales to examine a suite of climatic and intrinsic drivers of continental-scale West Nile virus epidemics, including an empirically derived mechanistic relationship between temperature and transmission potential that accounts for spatial variability in vectors. We found that drought was the primary climatic driver of increased West Nile virus epidemics, rather than within-season or winter temperatures, or precipitation independently. Local-scale data from one region suggested drought increased epidemics via changes in mosquito infection prevalence rather than mosquito abundance. In addition, human acquired immunity following regional epidemics limited subsequent transmission in many states. We show that over the next 30 years, increased drought severity from climate change could triple West Nile virus cases, but only in regions with low human immunity. Lastly, these results illustrate how changes in drought severity can alter the transmission dynamics of vector-borne diseases.

54 ENVIRONMENTAL SCIENCES↗

Impact of nematicity on the relationship between antiferromagnetic fluctuations and superconductivity in FeSe 0.91 S 0.09 under pressure

The sulfur-substituted FeSe system, FeSe 1 - x S x , provides a versatile platform for studying the relationship among nematicity, antiferromagnetism, and superconductivity. Herein, by nuclear magnetic resonance (NMR) and resistivity measurements up to 4.73 GPa on FeSe 0.91 S 0.09 , we established the pressure- ( p -) temperature ( T ) phase diagram in which the nematic state is suppressed with pressure showing a nematic quantum phase transition (QPT) around p = 0.5 GPa , two superconductivity (SC) regions separated by the QPT appear, and antiferromagnetic (AFM) phase emerges above ~ 3.3 GPa . From the NMR results up to 2.1 GPa, AFM fluctuations are revealed to be characterized by the stripe-type wave vector which remains the same for the two SC regions. Furthermore, the electronic state is discovered to change in character from non-Fermi liquid to Fermi liquid around the nematic QPT and persists up to ~ 2.1 GPa . In addition, although the AFM fluctuations correlate with T c in both SC states, demonstrating the importance of the AFM fluctuations for the appearance of SC in the system, we found that, when nematic order is absent, T c is strongly correlated with the AFM fluctuations whereas T c weakly depends on the AFM fluctuations when nematic order is present. Our findings on FeSe 0.91 S 0.09 were shown to be applied to the whole FeSe 1 - x S x system and offer an insight into the relationship between AFM fluctuations and SC in Fe-based superconductors.

36 MATERIALS SCIENCE↗

Rigid rotators

The two-particle, steady-state Schroedinger equation is transformed to center of mass and internuclear distance vector coordinates, leading to the free particle wave equation for the kinetic energy motion of the molecule and a decoupled wave equation for a single particle of reduced mass moving in a spherical potential field. The latter describes the vibrational and rotational energy modes of the diatomic molecule. For fixed internuclear distance, this becomes the equation of rigid rotator motion. The classical partition function for the rotator is derived and compared with the quantum expression. Molecular symmetry effects are developed from the generalized Pauli principle that the steady-state wave function of any system of fundamental particles must be antisymmetric. Nuclear spin and spin quantum functions are introduced and ortho- and para-states of rotators, along with their degeneracies, are defined. Effects of nuclear spin on entropy are deduced. Next, rigid polyatomic rotators are considered and the partition function for this case is derived. The patterns of rotational energy levels for nonlinear molecules are discussed for the spherical symmetric top, for the prolate symmetric top, for the oblate symmetric top, and for the asymmetric top. Finally, the equilibrium energy and specific heat of rigid rotators are derived.

Source record↗

Surveillance of Aedes aegypti indoors and outdoors using Autocidal Gravid Ovitraps in South Texas during local transmission of Zika virus, 2016 to 2018

The yellow fever mosquito, Aedes aegypti, has facilitated the re-emergence of dengue virus (DENV) and emergence of chikungunya virus (CHIKV) and Zika virus (ZIKV) in the Americas and the Caribbean. The recent transmission of these arboviruses in the continental United States has been limited, to date, to South Florida and South Texas despite Ae. aegypti occurring over a much larger geographical region within the country. The main goal of our study was to provide the first long term longitudinal study of Ae. aegypti and enhance the knowledge about the indoor and outdoor relative abundance of Ae. aegypti as a proxy for mosquito-human contact in South Texas, a region of the United States that is at high risk for mosquito-borne virus transmission. Here, the relative abundance of indoors and outdoors mosquitoes of households in eight different communities was described. Surveillance was done weekly from September 2016 to April 2018 using the CDC Autocidal Gravid Ovitraps in low- and middle-income communities. A total of 69 houses were included in this survey among which 36 were in the low-income communities (n = 11 for Donna, n = 15 for Progresso, n = 5 for Mesquite, n = 5 for Chapa) and 33 in middle-income communities (n = 9 for La Feria, n = 8 for Weslaco, n = 11 for McAllen, and n = 5 for Rio Rico). Overall, Ae. aegypti was the dominant species (59.2% of collections, n = 7255) followed by Culex spp. mosquitoes (27.3% of collections, n = 3350). Furthermore, we demonstrated for Ae. aegypti that 1) outdoor relative abundance was higher compared to indoor relative abundance, 2) low-income communities were associated with an increase in mosquito relative abundance indoors when compared to middle-income communities, 3) no difference was observed in the number of mosquitoes collected outdoors between low-income and middle-income communities, and 4) warmer months were positively correlated with outdoor relative abundance whereas no seasonality was observed in the relative abundance of mosquitoes indoors. Additionally, Ae. aegypti mosquitoes collected in South Texas were tested using a specific ZIKV/CHIKV multiplex real-time PCR assay, however, none of the mosquitoes tested positive. Our data highlights the occurrence of mosquitoes indoors in the continental United States and that adults are collected nearly every week of the calendar year. These mosquito data, obtained concurrently with local ZIKV transmission of 10 locally acquired cases in nearby communities, represent a baseline for future studies in the Lower Rio Grande Valley (LRGV) including vector control interventions relying on the oviposition behavior to reduce mosquito populations and pathogen transmission.

59 BASIC BIOLOGICAL SCIENCES↗

Magnetization stability analysis of the Stoner-Wohlfarth model under a spin-polarized current with a tilted polarization

The stationary-state solutions of magnetization dynamics under a spin-polarized current that was polarized in an arbitrary direction were investigated by solving the Landau-Lifshitz-Gilbert-Slonczewski equation for a single-domain magnet. Taking into consideration the uniaxial magnetic anisotropy, the equilibrium directions of the magnetization vectors were analytically obtained by solving an algebraic cubic equation. It was found that one to three pairs of magnetization equilibrium states existed, depending on the current intensity and the direction of the spin polarization. By numerically analyzing the stabilities of these equilibrium states, the threshold switching current for the reversing the magnetic vector was obtained under different current polarization configurations, which may be useful for use in future spintronics devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Search for the HH → $ b\overline{b}b\overline{b} $ process via vector-boson fusion production using proton-proton collisions at $ \sqrt{s} $ = 13 TeV with the ATLAS detector

A search for Higgs boson pair production via vector-boson fusion (VBF) in the $ b\overline{b}b\overline{b} $ final state is carried out with the ATLAS experiment using 126 fb –1 of proton- proton collision data delivered at $ \sqrt{s} $ = 13 by the Large Hadron Collider. This search is sensitive to VBF production of additional heavy bosons that may decay into Higgs boson pairs, and in a non-resonant topology it can constrain the quartic coupling between the Higgs bosons and vector bosons. No significant excess relative to the Standard Model expectation is observed, and limits on the production cross-section are set at the 95% confidence level for a heavy scalar resonance in the context of an extended Higgs sector, and for non-resonant Higgs boson pair production. Interpretation in terms of the coupling between a Higgs boson pair and two vector bosons is also provided: coupling values normalised to the Standard Model expectation of κ 2V < –0.76 and κ 2V > 2.90 are excluded at the 95% confidence level in data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

On the Divergence of the Velocity Vector in Real-Gas Flow

A theoretical study was performed addressing the degree of applicability or inapplicability, to a real gas, of the occasionally stated belief that for an ideal gas, incompressibility is synonymous with a zero or very low Mach number. The measure of compressibility used in this study is the magnitude of the divergence of the flow velocity vector [V(bar) (raised dot) u (where u is the flow velocity)]. The study involves a mathematical derivation that begins with the governing equations of flow and involves consideration of equations of state, thermodynamics, and fluxes of heat, mass, and the affected molecular species. The derivation leads to an equation for the volume integral of (V(bar) (raised dot) u)(sup 2) that indicates contributions of several thermodynamic, hydrodynamic, and species-flux effects to compressibility and reveals differences between real and ideal gases. An analysis of the equation leads to the conclusion that for a real gas, incompressibility is not synonymous with zero or very small Mach number. Therefore, it is further concluded, the contributions to compressibility revealed by the derived equation should be taken into account in simulations of real-gas flows.

Bellan, Josette↗

Enabling Cybersecurity, Situational Awareness and Resilience in Distribution Grids with High Penetration of Photovoltaics (CARE-PV) (Final Report)

Since legacy distribution systems have very limited visibility beyond the substation, high penetration of PV at the grid edge presents some unique operational challenges. One approach to address these challenges is to use information from advanced metering infrastructure (AMI) and µPMUs. However, exploiting this information is impacted by a number of factors, including multi-timescale measurements, volume of data generated, communication network impairments (e.g., information loss and latency) and susceptibility to cyber-attacks. Therefore, one of the critical tasks involved in the management of a distribution grid is to develop complete situational awareness by integrating cyber-security mechanisms with state estimation strategies and leveraging this situational awareness to assure energy services at strategic locations while exploiting AMI/PV inverter/ µPMU data. This CARE-PV project addresses the fundamental challenges in situational awareness and resilience to cyber and physical vectors by exploiting the synergy between innovative modeling, estimation, data analytics, testing and validation using smart PV inverters designed at K-State and facilities at NREL. Specifically, the project involved the development, testing and validation of the following novel enabling technologies: (Thrust 1) Resilience to cyber vectors that impact data integrity was addressed via a two-level defense strategy that combines cyber intrusion detection using self-learning, cooperative smart PV inverters, and a novel moving target defense framework to combat data integrity attacks. (Thrust 2) Resilience to cyber-physical vectors that impact situational awareness by limiting data availability was addressed via novel centralized and decentralized, sparsity-based static and dynamic state estimation approaches that enhance observability even when the underlying system is unobservable. (Thrust 3) Leveraging a unique probabilistic sensitivity analysis approach accompanied by one-of-a-kind dominant influencer set computation, the vulnerability of critical infrastructure at strategic locations was evaluated so that proactive PV-based control strategies can be used to support operations under normal/outage scenarios. These CARE-PV project innovations were demonstrated on both small-scale IEEE and larger utility-scale testbeds (Thrust 4). Feedback from Industry Advisory Board members was used to formulate a commercialization pathway for a subset of CARE-PV technologies. These CARE-PV technologies will ultimately lead to reliable and secure, large-scale integration of renewable energy and mitigate the risk of energy disruption resulting from cyber incidents and other emerging threats within the energy environment.

14 SOLAR ENERGY↗

First Principles Nonadiabatic Excited-State Molecular Dynamics in NWChem

Computational simulation of non-adiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons, to name a few. Here, we report an implementation of the fewest-switches surface hopping algorithm in the NWChem computational chemistry program. Here the surface hopping method is combined with linear-response time-dependent density functional theory calculations of adiabatic excited state potential energy surfaces. To treat quantum transitions between arbitrary electronic Born{Oppenheimer states, we have implemented both numerical and analytical differentiation schemes for derivative non-adiabatic couplings. A numerical approach for the time-derivative non-adiabatic couplings together with an analytical method for calculating non-adiabatic coupling vectors is an efficient combination for surface hopping approaches. Additionally, electronic decoherence schemes and a state reassigned unavoided crossings algorithm are also implemented to improve the accuracy of the simulated dynamics and to handle trivial unavoided crossings. We apply our code to study the ultrafast decay of photoexcited benzene, including a detailed analysis of the potential energy surface, population decay time scales, and vibrational coordinates coupled to the excitation dynamics. The development presented in this work is a baseline for future implementations of more sophisticated frameworks for simulating of non-adiabatic molecular dynamics in NWChem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bulk viscosity of two-flavor color superconducting quark matter in neutron star mergers

This work investigates the bulk viscosity of warm, dense, neutrino-transparent, color-superconducting quark matter, where damping of density oscillations in the kHz frequency range arises from weak-interaction-driven direct Urca processes involving quarks. We study the two-flavor red-green paired color-superconducting (2SC) phase, while allowing for the presence of unpaired strange quarks and blue color light quarks of all flavors. Our calculations are based on the SU(3) Nambu–Jona–Lasinio model, extended to include both vector interactions and the ‘t Hooft determinant term. The primary focus is on how variations in the NJL Lagrangian parameters—specifically, the diquark and vector coupling strengths—affect both the static properties of quark matter, such as its equation of state and composition, and its dynamical behavior, including bulk viscosity and associated damping timescales. We find that the bulk viscosity and corresponding damping timescale can change by more than an order of magnitude upon varying the vector coupling by a factor of two at high densities and by a lesser degree at lower densities. This sensitivity primarily arises from the susceptibility of 2SC matter, with a smaller contribution from modifications to the weak interaction rates. In comparison, changes in the diquark coupling have a more limited impact. The damping of density oscillations in 2SC matter is similar quantitatively to nucleonic matter and can be a leading mechanism of dissipation in merging hybrid stars containing color superconducting cores.

Gravitational Waves↗

Knowledge graph-aided Bayesian active learning for top- K genetic interaction discovery

In silico methods for predicting the effects of multi-gene perturbations hold great promise for advancing functional genomics, computational drug discovery, and disease modeling. However, the development of these predictive algorithms for mammalian systems has been hampered by limited datasets and high experimental costs. In this study, we present a Bayesian active learning framework designed to discover pairwise host gene knockdowns that effectively inhibit viral proliferation in an in vitro HIV-1 infection model. Our method leverages a biological knowledge graph as side information and employs a computationally efficient batch diversification approach. We evaluated this framework using a dataset of viral load measurements obtained from multi-day dual-gene depletion experiments, encompassing all possible pairwise knockdowns of over 350 host genes associated with HIV infection. We demonstrate that our framework rapidly identifies the most effective gene knockdown pairs for reducing viral load. Furthermore, we show that incorporating side information enhances performance during the early stages of active learning (low data regime), while our batch diversification strategy significantly boosts performance in later stages (high data regime). This framework is general and can be adapted to explore gene interactions in other contexts, such as synthetic lethality prediction and mapping epistatic effects across quantitative trait loci.

Computational biology and bioinformatics↗

Complete Stokes vector analysis with a compact, portable rotating waveplate polarimeter

Accurate calibration of polarization dependent optical elements is often necessary in optical experiments. A versatile polarimeter device to measure the polarization state of light is a valuable tool in these experiments. Here we report a rotating waveplate-based polarimeter capable of complete Stokes vector analysis of collimated light. Calibration of the device allows accurate measurements over a range of wavelengths, with a bandwidth of >30 nm in this implementation. A photo-interrupter trigger system supplies the phase information necessary for full determination of the Stokes vector. An Arduino microcontroller performs rapid analysis and displays the results on a liquid crystal display. The polarimeter is compact and can be placed anywhere on an optical table on a single standard post. The components to construct the device are only a fraction of the cost of commercially available devices while the accuracy and precision of the measurements are of the same order of magnitude.

47 OTHER INSTRUMENTATION↗

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗

Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatory system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗