Response Theory via Generative Score Modeling.

We introduce an approach for analyzing the responses of dynamical systems to external perturbations that combines score-based generative modeling with the generalized fluctuation-dissipation theorem. The methodology enables accurate estimation of system responses, including those with non-Gaussian statistics. We numerically validate our approach using time-series data from three different stochastic partial differential equations of increasing complexity: an Ornstein-Uhlenbeck process with spatially correlated noise, a modified stochastic Allen-Cahn equation, and the 2D Navier-Stokes equations.

Quantum Analog of Landau-Lifshitz-Gilbert Dynamics.

The Landau-Lifshitz-Gilbert (LLG) and Landau-Lifshitz (LL) equations play an essential role for describing the dynamics of magnetization in solids. While a quantum analog of the LL dynamics has been proposed in [Phys. Rev.

Granular Aluminum Parametric Amplifier for Low-Noise Measurements in Tesla Fields.

Josephson junction parametric amplifiers have become essential tools for microwave quantum circuit readout with minimal added noise. Even after improving at an impressive rate in the past decade, they remain vulnerable to magnetic fields, which limits their use in many applications such as spin qubits, Andreev and molecular magnet devices, dark matter searches, etc. Kinetic inductance materials, such as granular aluminum (grAl), offer an alternative source of nonlinearity with innate magnetic field resilience.

Tensor Network Computations That Capture Strict Variationality, Volume Law Behavior, and the Efficient Representation of Neural Network States.

We introduce a change of perspective on tensor network states that is defined by the computational graph of the contraction of an amplitude. The resulting class of states, which we refer to as tensor network functions, inherit the conceptual advantages of tensor network states while removing computational restrictions arising from the need to converge approximate contractions. We use tensor network functions to compute strict variational estimates of the energy on loopy graphs, analyze their expressive power for ground states, show that we can capture aspects of volume law time evolution, and provide a mapping of general feed-forward neural nets onto efficient tensor network functions.

Cooling of Semiconductor Devices via Quantum Tunneling.

Classical transport of electrons and holes in nanoscale devices leads to heating that severely limits performance, reliability, and efficiency. In contrast, recent theory suggests that interband quantum tunneling and subsequent thermalization of carriers with the lattice results in local cooling of devices. However, internal cooling in nanoscale devices is largely unexplored.

Exotic Synchronization in Continuous Time Crystals Outside the Symmetric Subspace.

Exploring continuous time crystals (CTCs) within the symmetric subspace of spin systems has been a subject of intensive research in recent times. Thus far, the stability of the time-crystal phase outside the symmetric subspace in such spin systems has gone largely unexplored. Here, we investigate the effect of including the asymmetric subspaces on the dynamics of CTCs in a driven dissipative spin model.

Precise Measurement of the e^{+}e^{-}→D_{s}^{+}D_{s}^{-} Cross Section at Center-of-Mass Energies from Threshold to 4.95 GeV.

Using the e^{+}e^{-} collision data collected with the BESIII detector operating at the BEPCII collider, at center-of-mass energies from the threshold to 4.95 GeV, we present precise measurements of the cross section for the process e^{+}e^{-}→D_{s}^{+}D_{s}^{-} using a single-tag method. The resulting cross section line shape exhibits several new structures, thereby offering an input for a future coupled-channel analysis and model tests, which are critical to understand vector charmonium-like states with masses between 4 and 5 GeV.

Simultaneous Unbinned Differential Cross-Section Measurement of Twenty-Four Z+jets Kinematic Observables with the ATLAS Detector.

Z boson events at the Large Hadron Collider can be selected with high purity and are sensitive to a diverse range of QCD phenomena. As a result, these events are often used to probe the nature of the strong force, improve Monte Carlo event generators, and search for deviations from standard model predictions. All previous measurements of Z boson production characterize the event properties using a small number of observables and present the results as differential cross sections in predetermined bins.

Measurement of Λ_{b}^{0}, Λ_{c}^{+}, and Λ Decay Parameters Using Λ_{b}^{0}→Λ_{c}^{+}h^{-} Decays.

A comprehensive study of the angular distributions in the bottom-baryon decays Λ_{b}^{0}→Λ_{c}^{+}h^{-}(h=π,K), followed by Λ_{c}^{+}→Λh^{+} with Λ→pπ^{-} or Λ_{c}^{+}→pK_{S}^{0} decays, is performed using a data sample of proton-proton collisions corresponding to an integrated luminosity of 9  fb^{-1} collected by the LHCb experiment at center-of-mass energies of 7, 8, and 13 TeV. The decay parameters and the associated charge-parity (CP) asymmetries are measured, with no significant CP violation observed. For the first time, the Λ_{b}^{0}→Λ_{c}^{+}h^{-} decay parameters are measured.

A comparative analysis of risk stratification tools in systemic sclerosis-associated pulmonary arterial hypertension: a EUSTAR analysis.

Objectives: The 2022 European Society of Cardiology and European Respiratory Society (ESC/ERS) Guidelines for pulmonary arterial hypertension (PAH) recommend risk stratification to optimize management. However, the performance of generic PAH risk stratification tools in patients with systemic sclerosis (SSc)-associated PAH remains unclear. Our objective was to identify the most accurate approach for risk stratification at SSc-PAH diagnosis.

Orientation selectivity properties for the affine Gaussian derivative and the affine Gabor models for visual receptive fields.

This paper presents an in-depth theoretical analysis of the orientation selectivity properties of simple cells and complex cells, that can be well modelled by the generalized Gaussian derivative model for visual receptive fields, with the purely spatial component of the receptive fields determined by oriented affine Gaussian derivatives for different orders of spatial differentiation. A detailed mathematical analysis is presented for the three different cases of either: (i) purely spatial receptive fields, (ii) space-time separable spatio-temporal receptive fields and (iii) velocity-adapted spatio-temporal receptive fields. Closed-form theoretical expressions for the orientation selectivity curves for idealized models of simple and complex cells are derived for all these main cases, and it is shown that the orientation selectivity of the receptive fields becomes more narrow, as a scale parameter ratio , defined as the ratio between the scale parameters in the directions perpendicular to vs.

Enhanced O-glycosylation Site Prediction Using Explainable Machine Learning Technique with Spatial Local Environment.

Motivation: The accurate prediction of O-GlcNAcylation sites is crucial for understanding disease mechanisms and developing effective treatments. Previous machine learning models primarily relied on primary or secondary protein structural and related properties, which have limitations in capturing the spatial interactions of neighboring amino acids. This study introduces local environmental features as a novel approach that incorporates three-dimensional spatial information, significantly improving model performance by considering the spatial context around the target site.

Recent progress on nanomaterial-based electrochemical sensors for glucose detection in human body fluids.

In the modern age, half of the population is facing various chronic illnesses due to glucose maintenance in the body, major causes of fatality and inefficiency. The early identification of glucose plays a crucial role in medical treatment and the food industry, particularly in diabetes diagnosis. In the past few years, non-enzymatic electrochemical glucose sensors have received a lot of interest for their ability to identify glucose levels accurately.

Effect of Elevated Temperature on Compressive Strength of MICCP and EICCP Biocemented Mortar.

Recently biocementation has got attention of many researchers worldwide as one of the most potent techniques for sustainable construction. Several studies have been carried out worldwide on biocementation by urea hydrolysis. Biocementation by bacterially induced calcium carbonate precipitation by different bacterial species has been among the most widely researched areas in this field.

Nanoscale Effects in the Room-Temperature UV-Visible Photoluminescence from Silica Particles and Its Cancer Cell Imaging.

Silica nano/microparticles have generated significant interest for the past decades, emerging as a versatile material with a wide range of applications in photonic crystals, bioimaging, chemical sensors, and catalysis. This study focused on synthesizing silica nano/microparticles ranging from 20 nm to 1.2 μm using the Stöber and modified Stöber methods.

An Implicit Solvation Model for Binding Free Energy Estimation in Nonaqueous Solution.

Implicit solvation models permit the approximate description of solute-solvent interactions, where water is the most often considered solvent due to its relevance in biological systems. The use of other solvents is less common but is relevant for applications such as in nuclear magnetic resonance (NMR) or chromatography. As an example, chloroform is commonly used in anisotropic NMR to measure residual dipolar couplings (RDCs) of chiral analytes weakly aligned by an alignment medium.

The common chemical logic of 'bridged' peroxo species in mononuclear non-heme iron systems.

Mononuclear non-heme iron enzymes catalyze a wide array of important oxidative transformations. They are correspondingly diverse in both structure and mechanism. Despite significant evolutionary distance, it is becoming increasingly apparent that these enzymes nonetheless illustrate a compelling case of mechanistic convergence the formation of peroxo species bridging metal and substrate.

Higher stability of nanophase GdO-CeO upon 400 keV Kr ion irradiation over bulk: role of defect annealing across grain boundaries.

The concept of inert matrix fuel (IMF) has been proposed to utilize the energetic value of Pu and transmute minor actinides in nuclear reactors. In order to offset the initial reactivity of nuclear fuel, gadolinium (Gd) is employed as a burnable poison, owing to its high neutron absorption cross-section. To gain insights into the radiation stability and influence of grain boundaries on irradiation behaviour, 5 mol% Gd-doped ceria samples, sintered at varying temperatures, were subjected to irradiation using 400 Kr ions.

Regulating Interphase Chemistry by Targeted Functionalization of Hard Carbon Anode in Ester-based Electrolytes for High-Performance Sodium-Ion Batteries.

Commercial hard carbon (HC) anode suffers from unexpected interphase chemistry rooted in the parasitic reactions between surface oxygen-functional groups and ester-based electrolytes. Herein, an innovative strategy is proposed to regulate interphase chemistry by tailoring targeted functional groups on the HC surface, where highly active undesirable oxygen-functional groups are skillfully converted into a Si-O-Si molecular layer favorable for anchoring anions. Then, an inorganic/organic hybrid solid electrolyte interphase with low interfacial charge transfer resistance and enhanced cycling durability is constructed successfully.

Large Electromechanical Response and Field-Induced Shape Memory Effect in Ferroelectric Ceramics.

Electric-field-induced shape memory effect has potential applications in electromechanical actuator. Here, this study proposes the a phase structure design routine in (1-x)(75NaBiTiO-25SrTiO)-xPbTiO ceramics to obtain large electromechanical response and shape memory effect. It is found that the shape memory effect is closely related to the bending deformation induced by asymmetric polarization between positive and negative electrodes, which is resulted from the reductions of Bi and Pb because of electron injection from negative electrode.

Melamine-Copolymerization Strategy Engineered Fluorinated Polyimides for Membrane-Based Sour Natural Gas Separation.

Membrane-based gas separation provides an energy-efficient approach for the simultaneous CO and HS removal from sour natural gas. The fluorinated polyimide (PI) membranes exhibited a promising balance between permeability and permselectivity for sour natural gas separation. To further improve the separation efficiency of fluorinated PI membranes, a melamine-copolymerization synthetic approach is devised that aims to incorporate melamine motifs with high sour gas affinity into the structure of the PI membranes.

Exploring the Conformational Space of a Sulfonyl-Based Ionic Liquid on Platinum-Based Mono and Bimetallic Surfaces.

Understanding the arrangement of ionic liquids at the interface and their interactions with the surface is crucial for enhancing selectivity in heterogeneous reactions for practical applications. In this study, we investigate the nature of the adsorption and structural orientations of a sulfonyl-based ionic liquid on platinum-based mono- and bimetallic (111) surfaces employing replica exchange molecular dynamics and first-principles density functional theory calculations. More than 30 confirmations of the ionic liquid are identified on both monometallic and bimetallic surfaces.

Pattern Separation and Pattern Completion Within the Hippocampal Circuit During Naturalistic Stimuli.

Pattern separation and pattern completion in the hippocampus play a critical role in episodic learning and memory. However, there is limited empirical evidence supporting the role of the hippocampal circuit in these processes during complex continuous experiences. In this study, we analyzed high-resolution fMRI data from the "Forrest Gump" open-access dataset (16 participants) using a sliding-window temporal autocorrelation approach to investigate whether the canonical hippocampal circuit (DG-CA3-CA1-SUB) shows evidence consistent with the occurrence of pattern separation or pattern completion during a naturalistic audio movie task.

Frontopolar Cortex Interacts With Dorsolateral Prefrontal Cortex to Causally Guide Metacognition.

Accurate metacognitive judgments about an individual's performance in a mental task require the brain to have access to representations of the quality and difficulty of first-order cognitive processes. However, little is known about how accurate metacognitive judgments are implemented in the brain. Here, we combine brain stimulation with functional neuroimaging to determine the neural and psychological mechanisms underlying the frontopolar cortex's (FPC) role in metacognition.