Browse Articles

Stability analysis and noise reduction of a cone-type poppet valve in an aero-hydraulic system

Thermodynamic stability and kinetic control of capsid morphologies in hepatitis B virus

Polymorphism has been observed in viral capsid assembly, demonstrating the ability of identical protein dimers to adopt multiple geometries under the same solution conditions. A well-studied example is the hepatitis B virus (HBV), which forms two stable capsid morphologies both in vivo and in vitro. These capsids differ in diameter, containing either 90 or 120 protein dimers. Experiments have shown that their relative prevalence depends on the ionic conditions of the solution during assembly. We developed a model that incorporates salt effects by altering the intermolecular binding free energy between capsid proteins, thereby shifting the relative thermodynamic stability of the two morphologies. This model reproduces experimental results on the prevalence ratios of the large and small HBV capsids. We also constructed a kinetic model that captures the time-dependent ratio of the two morphologies under subcritical capsid concentrations, consistent with experimental data.

Application and optimization of adaptive genetic algorithm in fencing training load prediction: a data visualization-based analytical approach

Accessing the universal phase behavior of block copolymer melts with complex-Langevin field-theoretic simulations

The universal phase behavior of block copolymer melts demonstrated previously with particle-based simulations is reproduced using complex-Langevin field-theoretic simulations (CL-FTSs) combined with the Morse calibration. For comparison purposes, the calculations are repeated using conventional Langevin field-theoretic simulations (L-FTSs), where the partial saddle-point approximation (PSPA) is applied to the pressure field. Both FTS methods produce consistent results down to invariant polymerization indices of N̄≈105, implying that the inaccuracies in the PSPA are well compensated for by the Morse calibration. At lower N̄, however, the complex fields of the CL-FTSs become prone to the formation of hot spots, causing the simulations to fail. Previous studies have shown that finite-range interactions can help stabilize CL-FTSs. Aided by the L-FTSs, we locate conditions at N̄=104, under which the universality is expected to hold and the CL-FTSs are stable. While the L-FTSs continue to obey universality, the CL-FTSs deviate significantly. A number of potential explanations are considered, but only one appears credible. Given the documented problems with CL simulations of nonpolymeric models, it is likely that the inconsistency with universality results from a “silent failure” in the CL-FTSs, preceding the formation of hot spots.

Cross-dataset late fusion of Camera–LiDAR and radar models for object detection

Abstract This paper presents a modular late-fusion framework that integrates Camera, LiDAR, and Radar modalities for object classification in autonomous driving. Rather than relying on complex end-to-end fusion architectures, we train two lightweight yet complementary neural networks independently: a CNN for Camera + LiDAR using KITTI, and a GRU-based radar classifier trained on RadarScenes. A unified 5-class label space is constructed to align the heterogeneous datasets, and we verify its validity through class-distribution analysis. The fusion rule is formally defined using a confidence-weighted decision mechanism. To ensure statistical rigor, we conduct 3-fold cross-validation with three random seeds, reporting mean and standard deviation of mAP and per-class AP. Results show that the Camera + LiDAR model achieves a strong average mAP of 95.34%, while Radar achieves 33.89%, reflecting its robustness but lower granularity. Using the proposed late-fusion rule, performance increases to 94.97% mAP versus KITTI ground truth and 33.74% versus RadarScenes. Cross-validated per-class trends confirm complementary sensing: Camera + LiDAR excels at Cars, Bicycles, and Pedestrians, while Radar contributes stability under adverse conditions. The paper also provides a complexity and latency analysis, discusses dataset limitations, clarifies temporal handling for radar, and includes updated literature up to 2025. Findings show that lightweight late fusion can achieve high reliability while remaining computationally efficient, making it suitable for real-time embedded autonomous driving systems.

Theory meets experiment in ammonia decomposition on Li14Cr2N8O: From order to disorder under reaction conditions

Heterogeneous catalysts have long been considered rigid structures hosting localized active sites, but growing evidence from both experiments and simulations is revealing a more dynamic picture in which the entire catalyst evolves under reaction conditions. In this study, we explore such behavior in Li14Cr2N8O, a lithium chromium nitride oxide recently proposed as a candidate for ammonia decomposition. Using machine learning-accelerated molecular dynamics, combined with in situ x-ray diffraction and catalytic activity measurements, we show that the pristine material undergoes significant structural transformation upon exposure to ammonia at elevated temperature. Surface disorder, lithium mobility, and the progressive formation of amides and imides give rise to a reactive interface, where chromium centers mediate key redox processes. These interfacial fluctuations create the conditions necessary for key steps in ammonia decomposition, including N–N coupling, hydride formation, and hydrogen release. Our findings highlight the importance of a global, dynamic view of heterogeneous catalysts under operando conditions, where activity arises not from predefined sites but from the evolving nature of the catalyst.

Barium calcium zirconium titanate thin film-based capacitive thermoelectric converter for low-grade waste heat

Abstract A capacitive thermoelectric device can harvest thermal energy and convert it to electrical energy by employing a temperature-dependent dielectric material whose permittivity sharply changes with temperature. Electricity can be generated by fluctuating the temperature of the capacitor. Currently, capacitive thermoelectric devices are not broadly used, which can be attributed to the low efficiency of the existing solutions, the lack of dielectric materials with suitable temperature non-linearity of the dielectric permittivity, and the complexity of modulating heat flux on the dielectric material. Here, we propose a device based on (Ba 0.85 Ca 0.15 )(Ti 0.92 Zr 0.08 )O 3 and (Ba 0.73 Ca 0.27 )(Ti 0.98 Zr 0.02 )O 3 thin films. It demonstrates power outputs of 0.06 mW to 0.3 mW across ΔT = 5–20 °C at 15 V bias, and a dynamic workload of an Intel E5-2630 microprocessor. These results highlight the potential of barium calcium zirconium titanate thin films to be used for a capacitive thermoelectric converter.

On the Jacobi stability of systems of ODEs for chemical oscillators using Kosambi–Cartan–Chern (KCC) theory

In this article, the Kosambi–Cartan–Chern (KCC) theory, which uses geometric invariants to characterize the time evolution of systems of ordinary differential equations, is employed for systems of ordinary differential equations describing chemical oscillations. This study demonstrates the utility of the KCC theory in providing a geometric framework for stability analysis, highlighting its ability to complement traditional Lyapunov stability assessments.

Credibility measurement of cloud services based on information entropy and Markov chain

Erratum: “Comparison of microscopic dynamics and continuum theory for Poiseuille and diffusioosmotic flows in a microchannel” [J. Chem. Phys. 163, 134902 (2025)]

An intelligent prediction method for ROP in drilling based on optimized PSO-BP neural network

From hindrance to catalyst: Potential roughness accelerates escape far from equilibrium

Activated escape from metastable states is a foundational concept in rate theory, underpinning diverse phenomena from chemical reactions to protein folding. A long-standing paradigm posits that potential energy landscape roughness invariably impedes kinetics by creating a multitude of local traps that suppress escape rates. Challenging this established paradigm, we investigate particles driven by discrete, non-equilibrium shot noise and reveal a striking inversion of this role. We demonstrate that, contrary to expectation, roughness can transform from a kinetic impediment into a potent catalyst, dramatically accelerating escape. The escape rate exhibits a striking non-monotonic dependence on the roughness amplitude, peaking at an optimal value. We attribute this counter-intuitive effect to a non-equilibrium mechanism we term slide inhibition, where local minima act as transient anchors. These anchors arrest dissipative relaxation between stochastic kicks, enabling a cumulative, ratchet-like ascent over the main energy barrier. The intrinsically non-equilibrium character of this synergy is powerfully underscored by the finding that thermal noise becomes destructive, destabilizing these crucial footholds. Our work unveils a constructive synergy between spatial disorder and non-equilibrium fluctuations, fundamentally recasting landscape roughness from a passive obstacle into a functional element for manipulating activated transport far from equilibrium.

Enhanced trajectory tracking and robustness in magnetic levitation via takagi-sugeno fuzzy control: experimental approach

Abstract Robust control of magnetic levitation (maglev) plant remains a significant challenge due to its inherent non-linearities and uncertainty to exogenous perturbations, though maglev technology has a wide range of usages, from high-speed trains to advanced robotics. To solve these problems and improve the maglev system’s trajectory-tracking performance and robustness, this research proposes a control technique that involves synthesizing a T-S fuzzy controller using the parallel distributed compensation (PDC) method. The controller design is further augmented with a velocity-compensation technique to enable smooth and frictionless ball levitation in a maglev system. The gravitational bias acting on the maglev system is controlled by integrating the feed-forward controller ( $$F_f$$ ) with the PDC-TS fuzzy scheme. The Lyapunov function candidate and linear matrix inequalities (LMIs) are explored to determine the proposed TS fuzzy scheme’s global asymptotic stability. Finally, the effectiveness of the control technique is experimentally evaluated for several test cases using hardware-in-loop (HIL) testing on the maglev system. The results corroborate that the T-S fuzzy control strategy offers robustness and trajectory tracking of the system with stable levitation over the traditional PIV scheme.

Phase transition and chirality switching of dibenzopentacene on Pb(111) surface driven by Coulomb expansion

The dibenzopentacene (DBPen) molecules on the Pb(111) substrate have been investigated using low-temperature scanning tunneling microscopy. Under the influence of an electric field, DBPen molecules undergo the phase transitions between the 2D mobile phase and the close-packed phase, as well as point and organizational chirality switching. First-principles calculations demonstrate that the electric field significantly modulates the charge transfer from the substrate to the molecules and induces the Coulomb expansion of the molecular lattice, resulting in phase transitions and chirality switching. Our results contribute to understanding the phase control and chirality manipulation of self-assembled molecular structures on solid surfaces.

Decadal stability of radiocesium inventories and soil to tree transfer in forests affected by the Fukushima nuclear accident

Abstract Understanding the long-term dynamics of radiocesium ( 137 Cs) in forests contaminated by the Fukushima nuclear accident requires determining when these dynamics reach a quasi-equilibrium state, in which the flux of 137 Cs between soil and trees becomes approximately balanced. In this study, we analyzed time-series variations from 2011 to 2020 in the total 137 Cs inventory and 137 Cs distribution in aboveground compartments (needles/leaves, branches, bark, sapwood, and heartwood). Time-series analysis using a dynamic linear model indicated that the decay-corrected total 137 Cs inventory (as of September 1, 2020) and its distribution in the aboveground compartments remained stable from 2017 onward, suggesting that a quasi-equilibrium state had been reached. Given this stability in both inventory and distribution, the aggregated transfer factor ( T ag )—defined as the 137 Cs activity concentration in aboveground tree tissues divided by the total 137 Cs inventory in soil—measured approximately 6 years after the Fukushima nuclear accident can be considered representative of the long-term transfer of 137 Cs from forest soil to trees. These findings on the stability of 137 Cs in forests provide valuable insights for validating the accuracy of models that predict long-term 137 Cs activity concentration in stem wood.

Optimal noise for vortex of self-propelled particles around an obstacle

We investigate the influence of thermal noise on the formation and dynamics of vortex of self-propelled particles (SPPs) around a circular obstacle using numerical simulations. In the absence of symmetry-breaking factors, spherical SPPs can spontaneously form a sustained vortex near the obstacle when particle activity is sufficiently high and the obstacle size lies within a suitable range. We show that noise not only induces transition between the vortex state and the random state but also plays a non-monotonic role in the behaviors of the vortex. In particular, there exists an optimal noise level that maximizes both the vortex speed and polarity alignment of the first particle layer, as well as the rate of their linear decay with distance from the obstacle. The underlying mechanism arises from the noise-dependent particle exchange process and the biased selection of incoming particles according to their polarities. In addition, the angular fluctuation of cluster thickness and the interlayer friction of particles also exhibit non-monotonic variations with noise. Pressure analysis demonstrates that the swimming pressure dominates and decreases near the obstacle due to tangential particle orientation, analogous to the reduced pressure in flowing fluids compared to stationary ones. Remarkably, the radial pressure shows a non-monotonic dependence on noise as well, reflecting the complex role of thermal noise in mediating the coupling between particle velocity and orientation. Our results highlight the constructive role of thermal noise in promoting collective vortex motion, thereby enriching the understanding of noise-induced effects in active matter systems.

Dual-specificity phosphatase 6 interferes with the repressive activity of forkhead box O1 towards CYP4A11 that mediates lipid accumulation in the liver

Charge accumulation and solvation in <i>β</i> -NiOOH: Surface chemistry of an OER catalyst from ML-aided simulations

Electrochemical water splitting is a key technology for a sustainable energy transition, providing a route to store surplus electricity from renewable sources. A central bottleneck is the sluggish oxygen evolution reaction (OER), which drives the search for catalysts that are active, stable, and inexpensive enough for large-scale deployment. Within this context, pure and doped NiOxHy combine high activity with low cost, making them prime candidates for alkaline OER. Yet, despite extensive study, the atomistic structure of NiOOH under operando conditions and the associated reaction mechanisms remain debated. Here, we investigate the structural complexity of pure β-NiOOH, the scaffold for its doped derivatives. We systematically investigate the oxidation of the surface adsorbates via proton-coupled electron transfer steps across relevant facets and sites, identifying the most probable sequence of deprotonation events. Our results reveal asymmetric charge accumulation on Wulff-relevant surfaces and show how applied potential can promote morphological restructuring. Explicit solvation is included through machine-learning interatomic potential molecular dynamics of the NiOOH/water interface, which allows us to resolve the hydrophobic and hydrophilic character of different surfaces and the associated interfacial water structure. Together, these insights demonstrate how surface chemistry and solvation jointly govern the stability of NiOOH and the accumulation of surface charge, with possible implications for catalytic performance.

Age distribution of high-risk HPV infection and cervical lesions in an unvaccinated adult Brazilian population within an organized screening program

Information encoding in spherical DFT

Spherical density functional theory (DFT) is a reformulation of the classic theorems of DFT, in which the role of the total density of a many-electron system is replaced by a set of sphericalized densities, constructed by spherically averaging the total electron density about each atomic nucleus. In Hohenberg–Kohn DFT and its constrained-search generalization, the electron density suffices to reconstruct the spatial locations and atomic numbers of the constituent atoms, and thus the external potential. However, the original proofs of spherical DFT require knowledge of the atomic locations at which each sphericalized density originates, in addition to the set of sphericalized densities themselves. In the present work, we utilize formal results from geometric algebra—in particular, the subfield of distance geometry—to show that for Coulombic systems, this spatial information is encoded within the ensemble of sphericalized densities themselves and does not require independent specification. Consequently, the set of sphericalized densities uniquely determines the total external potential of the system, exactly as in Hohenberg–Kohn DFT. This theoretical result is illustrated through numerical examples for LiF and for glycine, the simplest amino acid. In addition to establishing a sound practical foundation for spherical DFT as applied to Coulombic systems, the extended theorem provides a rationale for the use of sphericalized atomic basis densities—rather than orientation-dependent basis functions—when designing classical or machine-learned potentials for atomistic simulation.