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At least 865 records · Page 48

Evolving language of pediatric anxiety in electronic health records

Objectives This study aimed to identify and quantify semantic drift (ie, the change in semantic meaning over time) within expert-defined anxiety-related (AR) terminology and compare it to common electronic health record (EHR) vocabulary across longitudinal pediatric clinical notes. Materials and Methods A corpus of pediatric clinical notes from 2009 to 2022 was analyzed using computational methods. Semantic drift for each term was quantified using cosine similarity between annual temporal word embeddings. Contextual meaning was examined through changes in nearest neighbors across years. The Laws of Semantic Change were applied to assess the influence of word frequency and polysemy. Vocabulary terms were categorized as AR or common EHR. Results 98% of AR terminology maintained a cosine similarity between 0.00 and 0.50, indicating moderate semantic stability, whereas 90% of common EHR terms remained between 0.00 and 0.25, showing greater contextual stability overall. Frequent terms exhibited minimal change (Frequency Coefficient = 0.04), whereas highly polysemous or abbreviated terms showed less stability (Polysemy Coefficient = 0.630). AR terminology drifted more slowly than general EHR vocabulary (Type Coefficient = −0.179), further supported by significant year–type interactions (Coef = −0.09 to −0.523). Discussion Although anxiety-related terminology demonstrates slower semantic drift than general EHR vocabulary, subtle contextual shifts still occur that may affect downstream interpretability and retrieval in automated systems. Conclusion Continuous linguistic monitoring and adaptive modeling are essential to maintain semantic fidelity and ensure the long-term reliability of clinical decision support systems as healthcare documentation evolves.

Pediatric anxiety disorders↗

Advanced blade-shaped thermal energy storage device: Development and application

Thermal energy storage (TES) using phase change materials (PCMs) is a promising approach for capturing and reusing excess thermal energy, yet widespread adoption is limited by low thermal conductivity, bulky configurations, and inadequate scalability. Here, this study presents a modular, blade-shaped TES prototype designed to address these challenges. The device integrates a lightweight aluminum shell, an embedded serpentine coil for active or passive heat exchange, and a cost-effective corrugated metal mesh for enhanced PCM thermal conductivity. With thickness-to-length and thickness-to-width ratios of 0.03 and 0.08, respectively, the blade-shaped TES achieves a compact, modular form factor suitable for space-constrained applications. Experimental testing demonstrated the efficient charge and discharge behavior of blade-shaped TES, capturing PCM superheating, phase-change transitions, and subcooling dynamics, with charging and discharging efficiencies of 94.9% and 94.6%, respectively. Also, the system can potentially achieve higher energy density than that of conventional TES designs. When integrated into a household refrigerator during the study, three blade-shaped TES modules successfully shifted 100% of peak-time compressor operation to off-peak hours, reducing energy consumption while maintaining more stable compartment temperatures. The blade-shaped TES's thin geometry, modularity, and enhanced thermal performance support scalable deployment across residential, commercial, and industrial applications, providing a versatile, cost-effective solution for high-efficiency, demand-flexible thermal energy management.

Blade-shaped↗

Atomistic simulation of brittle-to-ductile transition in silicon carbide embedded with nano-sized helium bubbles

In this study, the tensile response of cubic silicon carbide (SiC) bulk containing cavities (voids and He bubbles) has been investigated using molecular dynamic simulations. The formation of cavities in SiC leads to a significant degradation in the mechanical properties of SiC with more influence on material fracture than initial elastic deformation. The brittle-to-ductile transition occurs in cavity-embedded SiC as the pressure in He bubbles increases. This is associated with the deformation mechanism that bond breaking at a low He bubble pressure transfers to extensive dislocation activities at a higher He bubble pressure. The cavities can effectively concentrate stress around them in the direction perpendicular to the tension, which leads to preferred cracking in the region with a higher tensile stress. The failure mechanism as revealed by this study improves understanding of property degradation in SiC that may be useful for applications of SiC in advanced nuclear energy systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Review on the growth, properties and applications of self-assembled oxide–metal vertically aligned nanocomposite thin films—current and future perspectives

Self-assembled oxide–metal nanocomposite thin films have aroused great research interest owing to their wide range of functionalities, including metamaterials with plasmonic and hyperbolic optical properties, and ferromagnetic, ferroelectric and multiferroic behaviors. Oxide–metal nanocomposites typically self-assemble as metal particles in an oxide matrix or as a vertically aligned nanocomposite (VAN) with metal nanopillars embedded in an oxide matrix. Among them, the VAN architecture is particularly interesting due to the vertical strain control and highly anisotropic structure, enabling the epitaxial growth of materials with large lattice mismatch. In this review, the driving forces behind the formation of self-assembled oxide–metal VAN structures are discussed. Specifically, an updated in-plane strain compensation model based on the areal strain compensation concept has been proposed in this review, inspired by the prior linear strain compensation model. It provides a guideline for material selection for designing VAN systems, especially those involving complex orientation matching relationships. Based on the model, several case studies are discussed, comparing the microstructure and morphology of different oxide–metal nanocomposites by varying the oxide phase. Specific examples highlighting the coupling between the electrical, magnetic and optical properties are also discussed in the context of oxide–metal nanocomposites. Finally, future research directions and needs are also discussed.

36 MATERIALS SCIENCE↗

Topology-Dependent Performance of Free-Space Photonic Quantum Networks Under Noise

Photonic quantum communication enables secure and high-fidelity information transfer beyond classical limits, with direct relevance to emerging quantum networks operating in free-space environments. While physical-layer models of depolarizing noise, Gamma–Gamma turbulence statistics, entanglement swapping, and decoy-state QKD security bounds are individually well established, prior work typically treats these components in isolation or under fixed network assumptions. In this work, we develop a unified topology-aware analytical framework that simultaneously integrates free-space optical link budgets, turbulence-induced visibility degradation, depolarizing qubit noise, multi-hop entanglement cascade dynamics, teleportation fidelity thresholds, CHSH nonlocality certification, and asymptotic decoy-state secret key rate bounds across star, mesh, and ring graph structures. Rather than introducing new physical channel models, we demonstrate that identical physical links exhibit fundamentally different end-to-end performance once embedded within different network topologies. Mesh architectures minimize visibility cascade through hop-count reduction but incur quadratic hardware scaling. Star topologies minimize link count but concentrate noise and synchronization overhead at the hub. Ring configurations offer linear hardware scaling with multiplicative fidelity degradation. The results establish topology as a first-order design parameter in near-term free-space quantum networks operating without full quantum repeater infrastructures. While motivated by distributed multi-agent architectures, the framework applies broadly to terrestrial, airborne, and satellite-assisted photonic quantum communication systems.

QKD↗

Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems

Abstract Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling approaches alone have large prediction uncertainties due to the complex biogeochemical processes to model and the lack of observations to constrain many key state and flux variables. Here we propose a Knowledge-Guided Machine Learning (KGML) framework that addresses the above challenges by integrating knowledge embedded in a process-based model, high-resolution remote sensing observations, and machine learning (ML) techniques. Using the U.S. Corn Belt as a testbed, we demonstrate that KGML can outperform conventional process-based and black-box ML models in quantifying carbon cycle dynamics. Our high-resolution approach quantitatively reveals 86% more spatial detail of soil organic carbon changes than conventional coarse-resolution approaches. Moreover, we outline a protocol for improving KGML via various paths, which can be generalized to develop hybrid models to better predict complex earth system dynamics.

54 ENVIRONMENTAL SCIENCES↗

Advanced Microstructured BaTiO 3 -Embedded PVDF–HFP/PEO Film for Enhanced Triboelectric Interface in Self-Sufficient Energy Generation and Sensing

The global reliance on fossil fuels and natural gas has largely dominated the energy production field, but due to finite resource depletion and escalating greenhouse gas emissions, the immediate exploration of sustainable energy alternatives to mitigate climate change and ensure resource security has been a major concern. There has been extensive research into other more renewable methods of energy production, such as wind and hydropower. Of these current energy generation types, there are many areas of untapped potential from the mechanical movements generated ambiently not only in the large scale of power generation but also on a smaller scale. The piezoelectric and triboelectric effects are phenomena where these ambient mechanical movements can generate electrical energy. Developing a hybrid system that leverages both mechanical stress and surface charges presents an ideal opportunity to exploit these untapped energy sources. Producing a hybrid PVDF–HFP/PEO film with perovskite BaTiO 3 (BTO) enables ambient power harvesting from both mechanical movement and surface charge. The optimized cell produced a potential of up to 15 V and a current of 200 nA with a 68 kΩ resistor, a substantial increase from a base system with an average of 2.1 V and 40 nA. These hybrid TENGs offer significant potential for energy harvesting in small-scale applications, such as health monitoring devices and indicators in electric circuits.

Ybarra, Rigobert [University of Texas Rio Grande V↗

Low-Energy Electron Elastic Total Cross Sections for Ho, Er, Tm, Yb, Lu, and Hf Atoms

The robust Regge-pole methodology wherein is fully embedded the essential electron-electron correlation effects and the vital core polarization interaction has been used to explore negative ion formation in the large lanthanide Ho, Er, Tm, Yb, Lu, and Hf atoms through the electron elastic total cross sections (TCSs) calculations. These TCSs are characterized generally by dramatically sharp resonances manifesting ground, metastable, and excited negative ion formation during the collisions, Ramsauer-Townsend minima, and shape resonances. The novelty and generality of the Regge-pole approach is in the extraction of the negative ion binding energies (BEs) of complex heavy systems from the calculated electron TCSs. The extracted anionic BEs from the ground state TCSs for Ho, Er, Tm, Yb, Lu, and Hf atoms are 3.51 eV, 3.53 eV, 3.36 eV, 3.49 eV, 4.09 eV and 1.68 eV, respectively. The TCSs are presented and the extracted from the ground; metastable and excited anionic states BEs are compared with the available measured and/or calculated electron affinities. We conclude with a remark on the existing inconsistencies in the meaning of the electron affinity among the various measurements and/or calculations in the investigated atoms and make a recommendation to resolve the ambiguity.

Felfli, Zineb↗

Quantum Many-Body Scars: A Quasiparticle Perspective

Weakly interacting quasiparticles play a central role in the low-energy description of many phases of quantum matter. At higher energies, however, quasiparticles cease to be well defined in generic many-body systems owing to a proliferation of decay channels. In this review, we discuss the phenomenon of quantum many-body scars, which can give rise to certain species of stable quasiparticles throughout the energy spectrum. This goes along with a set of unusual nonequilibrium phenomena including many-body revivals and nonthermal stationary states. We provide a pedagogical exposition of this physics via a simple yet comprehensive example, that of a spin-1 XY model. We place our discussion in the broader context of symmetry-based constructions of many-body scar states, projector embeddings, and Hilbert space fragmentation. We conclude with a summary of experimental progress and theoretical puzzles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Dynamic Tunability of Memristor-Based Active Filters

When the memristor was fabricated for the first time, it launched an entirely new field of research. Many of the published papers regarding memristors are primarily theoretical and are based on computer simulations. Some recent papers analyze the memristor’s programming circuits, but to the best of the authors’ knowledge, no memristor has been embedded into a commercial analog circuit. This paper is practically oriented and it is based on the experimental results obtained by measurements on the circuit prototype. We present a solution for automated programming of a commercially available memristor and its implementation in tunable active bandpass filter design. The novelty of this paper is that the active bandpass filter’s central frequency could be programmed during the filter operation, so a pause for memristor state-switching is not required. The experimental results are promising, and open up possibilities for the memristor’s application in analog systems.

42 ENGINEERING↗

Hierarchical microstructures: a potential route to enhanced stability in structural materials for advanced nuclear reactors

The drive to increase efficiency in nuclear energy systems is leading to the need for materials that operate at higher temperatures and stress levels for extended periods, while maintaining stable microstructures to ensure their performance is not compromised. A novel route to producing materials that can perform well in such environments is the creation of hierarchical microstructures. A hierarchical microstructure is a microstructure in which features are present at multiple length scales simultaneously. In this work, a hierarchical microstructure is fabricated in a nickel-base superalloy, featuring nanometer-size gamma precipitates inside larger gamma-prime particles, which are in turn embedded in the gamma matrix phase. The hierarchical features of the microstructure lead to enhanced stability of the gamma-prime precipitates during annealing; the particle size does not follow the expected t^(1/3) growth law predicted by the classic LSW theory. Phase-field simulations are used to understand the unexpected stability of the gamma-prime precipitates.

36 MATERIALS SCIENCE↗

Hierarchical microstructures: a potential route to enhanced stability in structural materials for advanced nuclear reactors

The drive to increase efficiency in nuclear energy systems is leading to the need for materials that operate at higher temperatures and stress levels for extended periods, while maintaining stable microstructures to ensure their performance is not compromised. A novel route to producing materials that can perform well in such environments is the creation of hierarchical microstructures. A hierarchical microstructure is a microstructure in which features are present at multiple length scales simultaneously. In this work, a hierarchical microstructure is fabricated in a nickel-base superalloy, featuring nanometer-size gamma precipitates inside larger gamma-prime particles, which are in turn embedded in the gamma matrix phase. The hierarchical features of the microstructure lead to enhanced stability of the gamma-prime precipitates during annealing; the particle size does not follow the expected t^(1/3) growth law predicted by the classic LSW theory. Phase-field simulations are used to understand the unexpected stability of the gamma-prime precipitates.

36 - MATERIALS SCIENCE↗

Integrating science for water security governance

Hydrological extremes are intensifying globally, increasing the complexity of decisions required to ensure water security. Advances in hydrological science, modeling, and data systems have expanded the technical frontier of water research, yet uptake of scientific insights in policy and management decisions remains limited. This persistent science–policy gap is not primarily a failure of knowledge generation or robustness, but an institutional challenge shaped by how scientific and governance systems are organized, coordinated, and connected to support the effective use of scientific knowledge. These challenges are particularly pronounced in multi-level and transboundary water governance, where decisions span jurisdictions and require coordination across institutional and political boundaries. We synthesize research at the science–policy interface and evidence from water security initiatives to show how institutional arrangements, scientific tool development, and research practices enable or constrain the sustained use of scientific knowledge in water-security governance processes. Building on these insights, we develop ‘shared decision infrastructure’ as a framing to describe how scientific knowledge is embedded within the institutional, relational, and procedural arrangements that connect science to decision-making processes over time. We translate this framing into a practical intervention roadmap centered on institutional design, tool translation, sustained co-production, and outcome-oriented evaluation to support the integration of science into ongoing governance processes. By positioning science as shared decision infrastructure, the roadmap clarifies how researchers can design scientific efforts that support more coordinated, accountable, and adaptive water security decisions amid deepening uncertainty.

M whitney, Kristen [NASA Goddard Space Flight Cent↗

Hollow-core optical fibre sensors for operando Raman spectroscopy investigation of Li-ion battery liquid electrolytes

Improved analytical tools are urgently required to identify degradation and failure mechanisms in Li-ion batteries. However, understanding and ultimately avoiding these detrimental mechanisms requires continuous tracking of complex electrochemical processes in different battery components. Here, we report an operando spectroscopy method that enables monitoring the chemistry of a carbonate-based liquid electrolyte during electrochemical cycling in Li-ion batteries with a graphite anode and a LiNi 0.8 Mn 0.1 Co 0.1 O 2 cathode. By embedding a hollow-core optical fibre probe inside a lab-scale pouch cell, we demonstrate the effective evolution of the liquid electrolyte species by background-free Raman spectroscopy. The analysis of the spectroscopy measurements reveals changes in the ratio of carbonate solvents and electrolyte additives as a function of the cell voltage and show the potential to track the lithium-ion solvation dynamics. The proposed operando methodology contributes to understanding better the current Li-ion battery limitations and paves the way for studies of the degradation mechanisms in different electrochemical energy storage systems.

47 OTHER INSTRUMENTATION↗

The Renewable Energy Potential (reV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling

The Renewable Energy Potential (reV) model is a platform for detailed assessment of renewable energy (RE) resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP) and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for assessment of resource potential, technical potential and supply curves at varying levels of detail. The platform runs on NREL's High Performance Computing system, providing scalable and efficient performance from a single location all the way up to continental scales, for a single year or decades of time series resource data. Coupled with NREL's System Advisor Model (SAM), reV supports resource assessment from 5-minute to hourly temporal resolution and provides for analysis of long-term (i.e., year-on-year) variability of RE generation (e.g., interannual variability and exceedance probabilities). Technical potential is measured as a function of resource potential and limitations put on developable land area defined by the user. For example, the user can limit development by land ownership, terrain, land use/cover, and urban areas, as well as custom inputs. Technology, grid interconnection and operation costs, based on the latest market data and future projections, are also embedded in the model. The supply curve module is a spatial sorting algorithm based on plant siting, grid interconnection cost, and regional competition, which provides a geographically discrete estimate of levelized cost of electricity (LCOE) and supply (i.e., capacity) for specific renewable technologies. The reV model currently provides broad coverage across North America, South and Central Asia, South America and South Africa to inform national- and international-scale analyses as well as regional infrastructure and deployment planning.

13 HYDRO ENERGY↗

DMRG on Top of Plane-Wave Kohn–Sham Orbitals: A Case Study of Defected Boron Nitride

In this paper, we analyze the numerical aspects of the inherent multi reference density matrix renormalization group (DMRG) calculations on top of the periodic Kohn-Sham density functional theory using the complete active space approach. The potential of the framework is illustrated by studying hexagonal boron nitride nanoflakes embedding a charged single boron vacancy point defect by revealing a vertical energy spectrum with a prominent multireference character. We investigate the consistency of the DMRG energy spectrum from the perspective of sample size, basis size, and active space selection protocol. Results obtained from standard quantum chemical atom-centered basis calculations and plane-wave based counterparts show excellent agreement. Furthermore, we also discuss the spectrum of the periodic sheet which is in good agreement with extrapolated data of finite clusters. These results pave the way toward applying the DMRG method in extended correlated solid-state systems, such as point defect qubit in wide band gap semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large scale SiPM testing for the Cosmic Muon Veto detector

A Cosmic Muon Veto (CMV) detector using extruded plastic scintillators is being built around the mini-Iron Calorimeter (mini-ICAL) detector at the transit campus of the India based Neutrino Observatory, Madurai. The extruded plastic scintillators will be embedded with wavelength shifting (WLS) fibres to absorb scintillating photons and propgate the re-emitted photons to the silicon-photomultipliers for the electronic signals. The CMV detector will require 760 extruded plastic scintillators to shield the mini-ICAL detector, and will require 3040 SiPMs for the readout. The design goal for the cosmic muon veto efficiency of the CMV is $>$99.99\% and fake veto rate less than 10$^{-5}$. Hence, every SiPM used in the detector needs to be characterised to satisfy the design goal of the CMV. For this, a large-scale testing system was developed, using an LED driver, to measure the gain and noise rate of each SiPM, and thus determine it's breakdown voltage ($V_{br}$) and optimum operating overvoltage ($V_{ov}$).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗