Browse Articles

Accurate and robust analysis of molecular kinetics with random features

Metastable states and the conformational transitions in between them are key to understanding the dynamical behavior and function of large-scale molecular systems. By combining basic dimensionality reduction techniques with a state-of-the-art approximation of the Koopman operator associated with molecular dynamics simulations (MD), we show that these states and transitions can be analyzed very efficiently based on MD simulation data. To construct the Koopman approximation, we employ a kernel-based method and solve the associated matrix equations using random Fourier features, leading to accurate solutions while maintaining low computational effort. On a benchmark set of fast-folding proteins, we demonstrate that key properties such as transition timescales, free energies, secondary structure elements, and hydrogen bonding patterns can be computed with remarkable robustness across hyperparameter regimes.

Dynamics of a discrete-time predator-prey model with exponential prey growth and saturated response

Abstract Recent studies have increasingly focused on the stability of predator-prey systems incorporating the Holling functional response and Ricker population model. This work investigates the influence of the Holling effect on a discrete-time predator-prey model, demonstrating through bifurcation theory and the central manifold theorem that the system exhibits period-doubling and Neimark-Sacker bifurcations at equilibrium points. Numerical simulations reveal complex dynamical behaviors, with bifurcation diagrams illustrating transitions from stability to periodic oscillations and chaos. Using phase portraits, Lyapunov exponents, and bifurcation analysis, we show how the Ricker map progresses from order to chaos. Our findings enhance the understanding of predator-prey dynamics and provide insights for ecological population management, highlighting the system’s rich behavior under parameter variations.

Influence of magnetic nanoparticle diameter on three-layer MEMS actuation via Casimir and hydrodynamic forces

Here, we investigate the dynamical response of a three-layer microsystem, with a ferrofluid as the intervening layer, to variations in the optical properties of the interacting components under the influence of Casimir and hydrodynamic forces. It is shown that increasing the magnetic nanoparticle diameter, for a fixed nanoparticle concentration, leads to an increase in the Casimir force. Hence, the performance sensitivity of the system has been studied for various diameters of the nanoparticles across different concentrations. Furthermore, it is explored how to achieve a condition in which the ferrofluid has no influence on the magnitude of the Casimir force by adjusting the nanoparticle diameters to a critical value. The dependence of the latter on the nanoparticle concentration at different separations between the components of the three-layer microsystem has also been explored. Subsequently, the impact of nanoparticle diameter on the phase space trajectories of the microsystem and the effect of different velocities of the moving parts have also been investigated. As a result, it has been demonstrated that an increment of the nanoparticle diameter leads to a higher probability of adhesion, also known as stiction, between the moving microsystem components. Finally, in driven microsystems, under the influence of a time dependent periodic external force, the change of the nanoparticle diameter not only affects the adhesion of the moving components but also significantly influences the stable periodic working range of the microsystem for both high and low driven frequencies.

Atorvastatin reduces recurrent decompensation events in advanced cirrhosis in a randomized placebo-controlled trial

Abstract Statins exhibit pleiotropic anti-inflammatory and antifibrotic properties that may attenuate the progression of cirrhosis. This study aimed to evaluate the efficacy and safety of atorvastatin in preventing recurrent decompensation events (DDs) and in modulating the gut–liver axis among patients with decompensated cirrhosis. In this randomized, double -blind, placebo-controlled trial, 100 adults with decompensated cirrhosis were randomly assigned in a 1:1 ratio to receive either atorvastatin (20 mg/day) or placebo for six months. The primary endpoint was the incidence of recurrent decompensation events (DDs). Secondary outcomes included changes in biomarkers of oxidative stress (malondialdehyde [MDA]), systemic inflammation (nuclear factor kappa B [NF-κB], C-reactive protein [CRP], and erythrocyte sedimentation rate [ESR]), intestinal permeability (zonulin), and endotoxemia (lipopolysaccharide [LPS]). Atorvastatin treatment significantly reduced the cumulative recurrence of cirrhosis-related complications compared to placebo (36% vs. 72%; HR 0.50; 95% CI, 0.33–0.75; P  < 0.001). Notably, atorvastatin conferred complete protection against hepatorenal syndrome (HRS) (0% vs. 20% in the placebo group; all Type 2). These clinical improvements were mirrored by significant reductions in MDA, NF-κB, LPS, and zonulin levels ( P  < 0.05), indicating a robust attenuation of systemic inflammation and restoration of intestinal barrier integrity. Atorvastatin was well-tolerated; while mild myalgia was more frequent in the intervention group (14% vs. 2%), elevations in transaminases were transient and clinically insignificant. In this randomized trial, atorvastatin was associated with a lower recurrence of decompensation events and a reduced incidence of hepatorenal syndrome compared with placebo. These effects were accompanied by improvements in biomarkers related to systemic inflammation and gut–liver axis dysfunction. Atorvastatin was generally well tolerated, although mild myalgia occurred more frequently and warrants clinical monitoring. While these findings suggest a potential role for atorvastatin as an adjunctive therapy in decompensated cirrhosis, confirmation in larger, multicenter studies is required before broader clinical application. Clinical trial number : NCT05563389 ( https://register.clinicaltrials.gov/prs/beta/studies/S000CHKM00000052/recordSummary ).

Bath-induced stabilization of classical non-linear response in two-dimensional infrared spectroscopy

A characteristic feature of the nonlinear response of integrable classical systems is divergence at long times, a consequence of the continuous spectrum of oscillation frequencies possible in anharmonic classical systems. Although bath-induced dissipation and dephasing can eliminate such instabilities, little is known about the specific conditions on system–bath interactions needed to stabilize classical nonlinear response functions. Here, we address this gap by incorporating system–bath interactions into a diagrammatic expansion for classical nonlinear response recently developed for weakly anharmonic systems. The resulting expression for the weakly anharmonic response function is remarkably simple and exhibits a one-to-one correspondence with the quantum counterpart in the ℏ → 0 limit, offering potential computational advantages in extending the approach to large, multi-oscillator systems. We find that, to lowest order in anharmonicity, the bath-induced stabilization of both linear and nonlinear classical response functions depends sensitively on the nature of spectral density, particularly on the balance between low-frequency and high-frequency components. Application of this classical diagrammatic approach to 2D IR spectroscopy of the amide I band captures the characteristic population-time-dependent dynamics associated with spectral diffusion, suggesting that the approach may prove useful in describing real experimental systems at ambient temperatures.

Research on the frictional contact behaviors of high-speed motorized spindle bearing with oil-air lubrication

Abstract As an important supporting element of rotating mechanisms, the frictional wear of rolling bearing causes low motion accuracy. To simulate the service statuses of rolling bearing under different lubrication conditions, the wear and frictional behavior between the GCr15 ball-on-disc contact pairs was experimentally analyzed to investigate the effects of rotating speed, loading, supplied oil quantity and air pressure on the friction and wear properties of the point contact pairs. As the experimental results show, the use of oil-air lubrication yields the smallest friction coefficient as compared to those of the grease and the oil lubrication modes, which can suppress the temperature rise effectively and attain the lowest wear rates. The increase of oil volume fraction for the oil-air lubrication led to diminished wear scar depth and low wear rates, while the supplied oil quantity and air pressure were constant, the increase of rotating speed resulted in slight decline of friction coefficient, as well as gradual elevation of temperature and wear rates. Regarding loading, its enhancement made the friction coefficient and wear scar depth went up initially and then reduced, which also caused the wear rates decreased. The findings of this research provide a useful basis for selecting the optimal high-speed bearing lubrication method and their operating parameters.

Correlation functions in heterodyne optical fiber dynamic light scattering: A laser velocimetry method for tracking active matter at the nanoscale

Heterodyne dynamic light scattering is a powerful interferometer allowing determination of velocities and directions of nano-sized objects that are too small to be tracked using conventional optical microscopy. Here, their scattered signal is directly mixed in optical fibers with that of a local oscillator (LO) originating from the same laser source, thus offering easy and precise control of the LO reference signal and high detection sensitivity over the entire range of scattering vectors. In this paper, we detail the expression of the heterodyne intensity correlation functions, which depend both on the modulation produced by the particle scattering processes but also on the phase shift introduced by the difference in optical path taken by the two interfering fields in the fiber. We subsequently study various situations ranging from pure Brownian diffusion to ballistic motion. In particular, we detail the analysis of the motion of photocatalytic active nanoparticles capable of autonomous propulsion when exposed to UV irradiation. In such a case, the heterodyne intensity–intensity correlation function is an oscillating function of the lag time with a velocity-dependent frequency allowing both speed and propulsion direction of active nanoparticles to be accurately determined.

Wearable optomyography enables continuous neuroprosthetic control

Lindblad theory for incoherently driven electron transport in molecular nanojunctions

We study electron transport in molecular nanojunctions that are driven by incoherent radiation using Markovian quantum dynamics based on the Lindblad quantum master equation. General expressions for the transient electron and photon currents between the system and the reservoir are derived. For experimentally relevant nanojunction configurations that include on-site Coulomb repulsion, electron tunneling, spontaneous photon emission, and incoherent driving, we show that Lindblad theory can reproduce stationary conductance features reported in the literature, such as negative differential conductance, Coulomb blockade, and current-induced light emission. Light-induced currents are predicted for two-site configurations with ground-level tunneling when the incoherent driving rate is comparable with the transfer rate to contact electrodes. Model extensions to include coherent light–matter interaction are suggested.

Malnutrition and its multidimensional determinants in institutionalized older adults: a cross-sectional study from resource-limited nursing homes in China

Molecular insight on ultra-confined ionic transport in wetting films: The key role of friction

Nanofluidic transport is ubiquitous in natural systems, from extracellular communication in biology to geological phenomena, and promotes the emergence of new technologies such as energy harvesting and water desalination. While experimental access to ultraconfined fluids has advanced rapidly, their behavior challenges conventional theoretical descriptions based on Poisson–Boltzmann theory or the Stokes equation, whose possible extension remains an open question. In this study, we use molecular dynamics simulations to investigate ionic transport within wetting films of water confined on silica surfaces down to the sub-nanometer scale. We then analyze these results using a simple one-dimensional theoretical framework. Remarkably, we show that this model remains valid even at confinement close to the molecular scale. Our results reveal that ion dynamics play a key role in ionic transport through ion adsorption at the water–silica interface. Adsorbed cations do not participate in ionic conduction but instead generate molecular-scale roughness and transmit additional frictional forces to the substrate. This mechanism produces an apparent viscosity increase in electrostatically driven flows, reaching up to four times the bulk value in the case of potassium. Our findings highlight the critical role of interfacial ion adsorption in nanoscale hydrodynamics and provide new insights for interpreting experiments and designing nanofluidic systems.

Choice-induced preference change under a sequential sampling model framework

Abstract Sequential sampling models of choice, such as the drift–diffusion model (DDM), are frequently fit to empirical data to account for a variety of effects related to accuracy/consistency, response time (RT), and sometimes confidence. However, no model in this class has been shown to account for the phenomenon known as choice-induced preference change , wherein decision makers tend to rate options higher after they choose them and lower after they reject them (and often choose the option that they had initially rated lower). Studies have reported choice-induced preference change for many decades, and the principal findings are robust. The resulting spreading of alternatives (SoA) in terms of their subjective value ratings is not considered by the traditional sequential sampling approach, which assumes the rated values of the options to be stationary throughout choice deliberation. Here, we propose that relaxing that assumption can allow this class of model to account for SoA. We show that the DDM can generate SoA (while simultaneously accounting for consistency and RT), as well as the relationships between SoA and choice difficulty, attribute disparity, and RT previously reported in the literature. Even the basic DDM can reproduce some empirical results, including multi-attribute evidence is necessary for others, and allowing different start times for each attribute enables a better match with the experimental data.

Aggregation of polyampholytes: Influence of salt concentration

We study the salt-dependent self-assembly of polyampholytes (PAs) using coarse-grained molecular dynamics simulations with explicit mobile salt ions, supported by theoretical analysis within the random phase approximation (RPA). The sensitivity of aggregation to salt is found to be sequence dependent, in line with the salt sensitivity of the mesophase instability predicted by RPA. For PA chains with distinct charge sequences, we quantify salt-induced changes in aggregation, single-chain dimensions, and structural correlations. Blocky sequences exhibit pronounced, weakly non-monotonic salt responses, with aggregation enhanced at intermediate screening and weakened at higher salt, whereas well-mixed sequences display much weaker and nearly monotonic behavior. In both cases, at sufficiently high salt concentration, the sequence dependence diminishes and the system ultimately collapses into a single large aggregate. We further present the salt dependence of aggregate size distributions, real-space correlation functions, and partial structure factors, the latter evaluated over the restricted wave vector range accessible within the finite simulation box. Charge–charge structure factors reveal enhanced long-wavelength charge fluctuations with increasing salt, consistent with the observed aggregation trends. Within the RPA framework, salt shifts the spinodal lines toward smaller hydrophobicity and reduces the characteristic wave vector of the microphase instability, in correspondence with simulation results. A brief comparison with the highly charged intrinsically disordered protein ProTα underscores the role of a large net charge on salt-induced aggregation.

Topiramate protects against neuroinflammation in response to traumatic brain injury via activating Sirt1 signaling

Melanin concentrating hormone regulates bone cell activities and calcium metabolism in regenerating goldfish scales

Vaccine-derived T-cell responses are insufficient to generate protective immunity to SARS-CoV-2

Pacemaker implantation is associated with post-ablation atrial fibrillation recurrence mediated by plasma CILP1

Nanomotion-enabled ultra-rapid antibiotic susceptibility testing with magnetic bead-based pathogen enrichment for accelerated sepsis diagnostics

Comparative evaluation of activated sludge and electrocoagulation for microplastics removal from sewage

Abstract Microplastics (MPs) are persistent emerging contaminants of global concern due to their potential ecological and human health risks. Sewage Treatment Plants (STPs) represent major pathways for MP discharge into aquatic environments, while conventional treatment processes are often insufficient for their complete removal, especially at small size ranges. In this study, influent and effluent samples were collected from an STP in Kafr Saad City, Damietta Governorate, Egypt, to evaluate the occurrence, characteristics, and removal efficiency of MPs. Identification was performed using visual inspection, stereomicroscopy, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and SEM–energy dispersive X-ray spectroscopy (SEM-EDX). Electrocoagulation (EC) was applied as a post-treatment using aluminum anodes and stainless-steel cathodes. The influent of STP contained 136 MPs/L, dominated by fibers (55.1%) and fragments (16.9%), while the effluent of STP after activated sludge treatment contained 23 MPs/L, corresponding to 83.1% removal. After EC treatment, MP concentrations decreased to 12 MPs/L in the influent and 2 MPs/L in the effluent, achieving over 91% removal. FTIR and SEM-EDX confirmed polyethylene and polypropylene as predominant polymers. The results highlight the limitations of conventional STPs and demonstrate EC as an effective post-treatment strategy for MP mitigation.

Study on the impact of industrial intelligence and the digital economy on China’s regional total factor carbon productivity under carbon neutrality

Abstract Improving total factor carbon productivity (TFCP) is the core pathway to China’s low-carbon economic transformation and achieving the “dual carbon” goals. Based on panel data of 30 Chinese provincial-level regions from 2010 to 2023, this paper measures regional TFCP via an undesirable-output super-efficiency SBM model and empirically analyzes the impacts and spatial spillover characteristics of industrial intelligence and the digital economy on TFCP using a Spatial Durbin Model (SDM). Results show China’s TFCP rose overall but exhibited a widening regional gap of “higher in the east, lower in the west”, with significant positive spatial autocorrelation in regional TFCP. The digital economy exerts a significantly positive direct effect and strong positive spatial spillover effect on TFCP, forming a “local driving + spatial radiation” promotion pattern. Industrial intelligence has an insignificantly negative direct effect on local TFCP, yet its positive spatial spillover effect is significant at the 1% level, leading to a significantly positive total effect that reflects its obvious spatial externality, with low-carbon dividends more prominent in regional coordination. Both factors show notable regional heterogeneity: industrial intelligence has a significantly negative direct effect in the east, significantly positive in the central region and insignificant in the west, with positive indirect effects in the east and west; the digital economy presents “local-spillover dual drive” in the east, “local-dominated drive” in the central region and “spillover-dominated drive” in the west. Among control variables, coal-based energy consumption structure and secondary industry-dominated industrial structure significantly inhibit regional TFCP with strong negative spatial spillovers; green finance has an insignificant positive effect, while FDI shows an insignificantly positive direct effect and significantly negative indirect effect due to the “pollution haven” effect. The work clarifies the spatial effects and regional heterogeneity of industrial intelligence and the digital economy on TFCP, providing empirical evidence and policy references for formulating differentiated regional coordination policies, leveraging the two as a “dual engine” to boost China’s regional TFCP and advance high-quality green and low-carbon economic development.