Objective: Sand-dust weather conditions severely reduce visibility and pavement friction on desert expressways, substantially increasing crash risks. Existing early warning systems rely primarily on fixed thresholds and single-modal information, often neglecting driver cognitive and physiological workload. This study aimed to develop and optimize a visibility-adaptive multimodal early warning scheme for desert expressways under sand-dust weather conditions, with a focus on balancing driving safety and human workload.Methods: A high-fidelity driving simulator was used to construct four visibility scenarios: 500, 300, 100, and 50 m, representing typical sand-dust weather conditions on the Wuma Expressway. Thirty-six licensed drivers completed 64 orthogonal test conditions combining variable message signs (VMS), LED linear guidance, and voice navigation. Eye movement, driving behavior, and physiological indices (ECG and EEG) were synchronously collected. ACriteria Importance Through Intercriteria Correlation (CRITIC)-weighted multidimensional evaluation system was established, incorporating speed compliance, steering stability, heart rate (HR), and EEG β/θ ratio, to screen the optimal scheme via Euclidean distance decision-making.Results: Visibility significantly deteriorated driving performance and elevated workload. The optimal multimodal schemes varied by visibility: 500 m (60 flashes/min LEDs + speed/distance voice); 300-100 m (120 flashes/min LEDs + steering/fog-light voice); 50 m (constant LEDs + operational guidance). Compared with single-modal warnings, the optimized scheme demonstrated statistically significant improvements at 500 m and 300 m visibility (p < 0.0031, Bonferroni-corrected), increasing speed compliance by 10.6 percentage points (to 89.2%), reducing steering angle deviation by 0.005-0.01 rad and lateral acceleration deviation by 0.05-0.1 m/s[2], lowering heart rate by 4.28 bpm, and raising the β/θ ratio by 0.14. At 100 m and 50 m visibility, nonsignificant but directionally consistent trends were observed (p = 0.011 and p = 0.034, respectively; Cohen's d = 0.43 and 0.37), indicating a practical reduction in overall physiological load of approximately 15-20% that warrants further validation under stringent statistical thresholds.Conclusions: The visibility-adaptive multimodal early warning scheme effectively improves driving stability and mitigates driver workload under sand-dust weather conditions. Tiered information delivery and dynamic LED parameters enhance information perception and reduce visual fatigue. The findings offer a cognitive-load-informed framework to guide the parameter tuning of traffic management strategies and safety improvement on desert expressways during extreme sand-dust weather.

The integration of biochar into cementitious materials has emerged as a groundbreaking approach to carbon sequestration, yet its high-dosage utilization and synergistic effects with sustainable cement formulations remain largely unexplored. This study proposes a novel design for low-carbon cement composites by incorporating high levels of biochar up to 30 wt% into both ordinary Portland cement (OPC) and Limestone Calcined Clay Cement (LC[3]) systems, fundamentally altering their hydration kinetics, microstructural evolution, and mechanical performance. The findings reveal that biochar enhances the flowability of OPC pastes but slightly reduces that of LC[3] due to its high surface area and interparticle friction. It promotes the hydration process of OPC through internal curing and intensifies the early-stage reaction of LC[3] via nucleation effects. Additionally, biochar's well-developed pore network may facilitate the redistribution of calcium species and the diffusion of CO2, dramatically promoting carbonation and inducing the crystallization of vaterite and calcite, while simultaneously increasing the polymerization degree of C-(A)-S-H and reducing unhydrated clinker content for both OPC and LC[3] pastes. Despite porosity-induced reductions in the compressive strength of biochar-modified cement, plain LC[3] and LC[3] with 15% biochar achieved an 18% and 4% enhancement in flexural strength over plain OPC pastes, attributed to the formation of nanostructured rod-like ettringite. Critically, the LC[3] mix with 30% biochar exhibited remarkable carbon reduction efficiency, achieving a mitigation potential of up to 88.2 kg CO2 eq./m[3]/MPa for flexural strength and 1.1 kg CO2 eq./m[3]/MPa for compressive strength, indicating its potential to contribute to the cement industry's decarbonization efforts. Overall, this work demonstrates the feasibility of incorporating high biochar contents into LC[3] composites, highlighting their carbon mitigation potential for sustainable construction.

Compression optical coherence elastography (OCE) provides micro-scale imaging of tissue and biomaterial mechanical properties in three dimensions (3-D), showing promise in a range of biomedical applications. Despite substantial progress, most 3-D OCE techniques do not account for the nonlinear elastic response of tissue, resulting in deformation-dependent variations in estimated Young's modulus within an image that reduce reliability and confound comparison both within and between samples. In this work, we overcome these limitations by explicitly accounting for sample deformation and present the first 3-D images of the nonlinear elastic response of tissue, parameterized into Young's modulus and a nonlinear parameter, a capability not previously achieved in OCE or any other elastography modality. To achieve this, we introduce a volumetric, sparsely sampled, phase-based stretch estimation protocol to quantify finite sample deformation and estimate the nonlinear elastic response from between five and nine volumes. We also use an integrated stress sensing layer to minimize temporally varying friction. We validate these new capabilities on phantoms, demonstrating volumetric estimation of the nonlinear elastic response, with mean errors <20%, compared to >50% without the integrated layer. Finally, we apply this technique to ex vivo mouse liver, imaging Young's modulus and the nonlinear parameter in healthy and diseased tissue. This method enables more accurate and reliable mechanical characterization of tissue with potential applications in many areas, including tissue engineering, mechanobiology, and disease diagnostics. STATEMENT OF SIGNIFICANCE: Compression optical coherence elastography (OCE) provides micro-scale imaging of tissue mechanical properties in three dimensions (3-D). However, most 3-D OCE techniques do not account for the nonlinear elastic response of tissue, leading to errors in the reported elasticity. In this work, we overcome these limitations and present a technique to volumetrically image the nonlinear elastic response of tissue, a capability not previously achieved in elastography. By parameterizing the nonlinear elastic response into Young's modulus and a nonlinear parameter, our method enables more accurate mechanical characterization and additional contrast for differentiating tissue microstructure. These results establish a foundation for volumetric imaging of nonlinear tissue elasticity using OCE in a range of biomedical applications, including tissue engineering, mechanobiology, and disease diagnostics.

By using the computational power of Bayesian Regularization Optimizer Supervised Neural Networks (BRO-SNNs), this semi-analytical model, which investigates thermophoretic particle deposition in a Boger nanofluid flow over an inclined sheet using Brownian motion and Stefan blowing, has important applications in advanced heat management and materials processing. It provides a key framework for enhancing heat exchanger designs, demonstrating how controlled nanoparticle deposition can improve heat transfer or avoid surface fouling. The findings are immediately applicable to coating and thin-film manufacturing processes, allowing for fine control over deposit uniformity and thickness by manipulating thermophoresis and Stefan blowing. Furthermore, the model can be used in environmental engineering to estimate particle deposition in scrubbers and filtration systems, as well as in aircraft to manage dust or ice formation on critical components. The viscoelastic character of Boger fluids makes it especially useful for creating next-generation smart cooling systems based on polymer-based nanofluids. The HAM solves the non-dimensional non-linear governing ODEs (ordinary differential equations) that are derived following appropriate similarity transformations. The velocity field upsurges as increase the values of nanoparticles solvent friction while thermal profile decline.

Metal-organic frameworks (MOFs) demonstrate considerable potential for biomedical applications. Due to their high porosity and photoactive porphyrin ligands, PCN-224 is considered an ideal drug delivery nanocarrier. However, the synthesis strategy for tailoring the application of PCN-224 in complex pathological diseases remains unclear. In this study, we investigated the structure-activity relationship of PCN-224 nanoparticles as bifunctional nanocarriers for osteoarthritis (OA) treatment under a precisely controlled temperature gradient. By tuning the temperatures, a series of PCN-224 nanoparticles with adjustable sizes were synthesized and their morphologies transitioned from a spindle-shaped to a spherical-shaped structure. The photoluminescence intensity of PCN-224 nanoparticles decreased as the synthesis temperatures increased. Using PCN-224 nanoparticles as aqueous lubricating additives, both the friction coefficient and wear volume were significantly reduced. Among the MOFs, PCN-224 (synthesized at 105 °C) exhibited excellent antifriction performances and acid-responsive drug release properties, demonstrating their promise as bifunctional OA treatment nanocarriers. Our work enhanced the understanding of the relationships between PCN-224 synthesis conditions and its physicochemical properties relationships, expanding their potential for multifunctional biomedical applications.

The confinement effect of nanochannels (<2 nm) dictates the gas-liquid distribution at solid-liquid interfaces, yet the effect of interfacial chemistry on their kinetic behaviors lacks insightful understanding. Particularly, the interfacial CO2 transport mechanism is critical for CO2 capture in hydrated environments. Herein, we employ nonequilibrium molecular dynamics simulations combined with density functional theory calculations to elucidate CO2 transport mechanisms in fully hydrated one-dimensional micropores of covalent organic frameworks (COFs). Our results demonstrate that pore-wall chemistry regulates transport not directly through adsorption strength alone, but by reshaping the topology and dynamic organization of confined hydration networks. Without functionalization, the pristine COF channels form an ordered hydration structure that anchors CO2 on adsorption sites and imposes substantial across-layer transport resistance. Functionalization of pore walls disrupts this hydration organization, accelerating CO2 transport via distinct microscopic regimes and promoting spatial coexistence of CO2 and water. Notably, fluorine functionalization establishes a mobility-dominated regime that minimizes friction, inverting the preference from H2O-favored to CO2-favored transport and achieving a nearly 3-fold increase in axial selectivity. This work reveals that CO2 transport is controlled by hydration-mediated transport energetics. These findings offer molecular-level perspectives for design of microporous materials by highlighting importance of balancing interfacial affinity and transport resistance within confined hydration environments.

Graphene/copper (Gr/Cu) composites, which combine the exceptional electrical, thermal, and mechanical properties of both components, have emerged as a promising platform for advanced electronic and energy storage applications. Successful studies have been done on optimizing graphene incorporation and morphology, while the impact of Gr/Cu interfacial interactions on composite performance remains underexplored. Here, we systematically investigate eight Gr/Cu interfaces and clarify their interfacial coupling relationships. Our results demonstrate that the doping level of graphene closely correlates with the crystallographic orientation of Cu, where Gr/Cu(111) exhibits the highest electron doping level, and Gr/Cu(332) shows the lowest. Higher doping is accompanied by greater graphene surface friction, revealing a direct link between charge transfer at the interface and tribological behavior. Crystallographic orientation control represents an atomically precise interfacial engineering strategy for tailoring interfacial coupling. Through this approach, charge transfer and friction can be effectively tuned, paving the way for the rational design of high-performance Gr/Cu composites for applications such as efficient power transmission, reliable electrical interconnects, and low-friction systems.

Potential-of-mean-force (PMF)-matched coarse graining (CG) can make a retained coordinate structurally correct but dynamically wrong. Eliminated bath degrees of freedom carry projected memory and friction that control response curves, relaxation times, kinetics, and transport. We ask whether the observable part of this missing friction can be recovered cheaply without harming generated dynamics. Residual-force fits and scalar rescalings alone cannot answer that question because they may expose the signal or improve one summary while worsening another. We distinguish the measured finite-window error between the high-resolution reference (labeled AA throughout) and CG dynamics from the component supported by residual-memory diagnostics, formulate that component as an observable projected-memory object, and approximate its consequence with a finite-history or surrogate candidate. The candidate is deployed only when held-out continuation rollouts improve both response-curve and relaxation-time errors. In two complete experiments, the fitted increment was added to the same detailed-balance PMF transition used as the uncorrected baseline. For C6 and C5 end-to-end distances, selected strength 0.10 retained PMF histogram L1 distances of 0.054 and 0.061, and the one-sided 5% lower bounds of both dynamical error reductions were positive. Separate precorrection diagnostics assigned acetone C-O to a richer state description and ethanol heavy-atom end-to-end to a finite memory kernel, so neither received the low-cost correction. The 13-coordinate breadth panel and diagnosis-informed tests provide breadth and selectivity evidence. Against a C6-calibrated scalar clock, the finite-history candidates improved both errors in 4/4 point-estimate comparisons versus 3/4 and gave 2.8 times the mean joint gain; experiment-specific uncertainty is reported separately. A distinct OpenFF 2.3.0/OpenMM surrogate showed the same point-estimate improvement on four molecules. The resulting reproducible, cost-bounded rule corrects only when structural and rollout evidence support correction.

Trigeminal pain produces persistent facial hypersensitivity that is difficult to treat. Ion channels contribute to the pathology of trigeminal pain, but the consequences of their modulation remain poorly understood. We previously demonstrated that voltage-gated sodium channel Na v 1.7 is a therapeutic target that can be indirectly modulated via interaction with collapsin mediated response protein 2 (CRMP2) to reduce membrane expression of Na v 1.7 and trigeminal ganglion neuronal excitability. We used the Foramen Rotundum Inflammatory Constriction of the Trigeminal InfraOrbital Nerve (FRICT-ION) model of trigeminal neuropathic pain to characterize behavioral and supraspinal effects of indirectly modulating the peripheral CRMP2-Na v 1.7 interaction via our novel Compound 194 (C194). FRICT-ION produced mechanical and cold allodynia, which were reduced by C194, but had no effect on non-evoked affective behaviors. Despite behavioral improvement, C194 did not normalize heightened glutamatergic activity in the parabrachial nucleus (PBN), revealing a dissociation between behavioral analgesia and activity of a central pain circuit. These findings extend mechanistic studies of C194 in the trigeminal system and demonstrate efficacy of CRMP2-Na v 1.7 disruption in modulating facial pain-like behavior. These results support the CRMP2-Na v 1.7 axis as a promising therapeutic target while highlighting the need to define how peripheral and central adaptations interact to shape persistent facial pain.

A two-level closed-loop calibration framework is proposed to reduce odometry scale errors during motion and pose drift during stationary periods in Mecanum-wheeled mobile robots. At the upper calibration level, the planar displacement between the initial and final poses is calculated using the L2-norm, which reduces the influence of lateral deviation on distance measurements based on a single coordinate axis. Rotational displacement is obtained by accumulating normalized angular increments, thereby avoiding discontinuities when the yaw angle crosses the ±π boundary. A relay controller with a tolerance deadband is also introduced to reduce static-friction-induced stalling and oscillation near the target during low-speed calibration. At the lower odometry interface, the covariance assigned to wheel odometry measurements is adjusted according to the commanded zero-velocity state. During stationary periods, this adjustment increases the contribution of near-zero velocity measurements and limits the effect of residual velocity estimates and sensor noise on the fused pose. The identified longitudinal and rotational compensation factors are then updated online in the dead-reckoning node through an ROS 2 service. Unlike conventional ZUPT implementations, the proposed method does not require an additional zero-velocity pseudo-measurement node. Experiments were conducted on three near-horizontal surfaces: ceramic tile, epoxy resin, and asphalt. Across 720 bidirectional in-place rotation trials, the angular Error Reduction Rate ranged from (59.13%) to (96.58%). In 540 straight-line trials covering nine combinations of surface type and target distance, the overall mean absolute error decreased from 53.22 mm before calibration to 9.69 mm after calibration. Intermittent stop-and-go experiments were further performed using the EKF, UKF, RCKF, and a graph-based SLAM optimization framework implemented by slam_toolbox. For each estimation back-end, the estimated trajectory was evaluated by calculating its deviation from the corresponding synchronized /odom trajectory under the fixed-covariance and proposed ZUPT-based adaptive-covariance configurations; /odom was used as a common comparison baseline rather than as an absolute localization ground truth. The adaptive covariance strategy reduced the positional RMSE by (19.38%-67.44%) across the evaluated filtering back-ends. These results show that the proposed framework can reduce both motion-dependent odometry scale errors and stationary pose drift under the tested surface conditions.

Structural superlubricity (SSL) exhibits significant potential for applications in micro/nanoelectromechanical systems, switches, and sensors, owing to its characteristics of near-zero friction and zero wear. However, the deployment of the more universal 2D/3D SSL interfaces in efficient electronics is severely limited by an insufficient understanding of their electrical stability and failure mechanisms under high current density. In contrast to the Joule-heating-induced interlayer bonding that limits the critical current density in 2D/2D SSL interfaces, we report a fundamentally different failure mechanism for 2D/3D SSL interfaces under high current density: the interfacial Au layer melts and transitions from single-crystalline to polycrystalline state, which drastically increases surface roughness and thus causes a friction surge, severe graphite wear, and the eventual collapse of the SSL state. Notably, under this new failure mechanism, the critical current density of the interface increases by nearly an order of magnitude compared to that of 2D/2D SSL interfaces, exceeding 110 GA/m[2]. Furthermore, we developed a high-power switch prototype that significantly outperforms conventional ones, demonstrating a critical step in translating SSL from principle to practice and paving the way for addressing contact issues in high-power, long-life electronics.

We investigated the causal effect of free influenza vaccination schemes on vaccination uptake among adults aged 50 years and older across 25 European countries. All countries conducted annual information campaigns targeting older adults, but differed in whether vaccination was provided free of charge at the point of delivery and in the age at which eligibility began. Using cross-sectional data from the 2019/2020 Survey of Health, Ageing and Retirement in Europe (SHARE), we exploited this institutional variation through a difference-in-discontinuities design that compared age-based discontinuities in vaccination uptake across countries with and without free vaccination schemes, rather than relying on similarity in individual characteristics. We found that offering vaccination free of charge increased influenza vaccine uptake by around 6 percentage points at the eligibility threshold. By contrast, no discontinuity was observed in countries relying exclusively on information campaigns. These findings indicate that free access substantially increased vaccination coverage beyond the effect of information provision alone. We further found no evidence that the effect differed systematically by household income, suggesting that free vaccination schemes operated not only through the removal of direct financial barriers but also through broader reductions in non-financial frictions. Overall, our findings highlight free access as an effective policy instrument for increasing influenza vaccination uptake among older adults.