Search Results (349)

To address the challenges of high-dimensional nonlinearity, multimodal landscapes, and stringent constraints prevalent in modern engineering design, traditional meta-heuristic algorithms often suffer from a loss of population diversity and premature convergence. Inspired by the social collaborative predation and collective information interaction behaviors of P. prominens (jumping spiders), this study proposes a novel bio-inspired meta-heuristic optimization algorithm, termed the Experience Exchange Strategy-Enhanced Philoponella Prominens Optimization (EESPPO). The proposed EESPPO integrates an Experience Exchange Strategy framework to reshape the search dynamics of the population through three progressive evolutionary stages: (1) In the Experience Scarcity (ESC) stage, the algorithm focuses on the construction and dynamic maintenance of an experience library to ensure the effective preservation of high-quality historical information; (2) In the Experience Crossover (ECR) stage, a random guidance vector generation mechanism is introduced to significantly enhance population behavioral diversity and the capability to escape local optima; (3) In the Experience Sharing (ESH) stage, an adaptive fusion update strategy is employed to achieve efficient information interaction and co-evolution among individuals. These three stages operate synergistically within the optimization cycle to establish a dynamic balance between global exploration and local exploitation, effectively overcoming the inherent defects of premature convergence in traditional meta-heuristics. Extensive empirical analysis based on the CEC2017 benchmark functions confirms that EESPPO comprehensively outperforms 12 existing advanced algorithms (including PPO, HSO, SGA, PSO, FLO, DE, HO, WOA, KEO, GWO, FDB-AGSK, and IVYPSO) in terms of convergence accuracy and robustness. Furthermore, the application of EESPPO to four challenging engineering design problems confirms its superiority. The experimental results validate the high precision and feasibility of EESPPO in solving complex constrained engineering problems. Full article

The IMO Net-Zero Framework and its carbon regulations impose binding constraints on fuel selection and fleet evolution. A techno-economic optimization model is developed to quantify this interaction along the Shanghai–Los Angeles green shipping corridor. The framework integrates vessel-level Mixed-Integer Non-Linear Programming (MINLP) with a Multinomial Logit formulation to simulate fleet diffusion, minimizing Total Cost of Ownership (TCO) over 2026–2050. The results identify a persistent marginal compliance regime driven by the tiered carbon penalty structure. Rather than achieving full compliance, fleets systematically position their Greenhouse Gas Fuel Intensity (GFI) near the penalty threshold, where limited penalties remain economically preferable to high-cost zero-carbon fuels. This behavior sustains fossil LNG as the dominant transitional option and delays the TCO crossover with ammonia until 2043. Under intensified penalties, the crossover advances to approximately 2030, triggering rapid cost escalation for LNG and eliminating the economic viability of drop-in biofuel strategies. Across all scenarios, absolute zero GHG emissions are not achieved due to residual fossil dependence and upstream Well-to-Wake (WTW) emissions. The transition is therefore bounded by the interaction between penalty avoidance behavior and the pace of Power-to-X fuel deployment. These findings indicate that carbon penalty levels determine the timing of decarbonization, while relative fuel prices govern technology selection, with direct implications for corridor-specific fuel infrastructure and investment decisions. Full article

The dynamic spreading behavior of droplets impacting surfaces with different wettability is a critical hydrodynamic issue in industrial applications such as inkjet printing, spray cooling, and pesticide spraying. The maximum spreading diameter coefficient (${\beta }_{max}$) is the key parameter characterizing this process. Existing theoretical models often overlook the gravitational potential energy of droplets, resulting in significant discrepancies between the calculated viscous dissipation times and experimental results, which compromises the prediction accuracy. In this study, we incorporated gravitational potential energy into the energy balance system based on the principle of system energy conservation. We introduced the Bond number (Bo) to characterize the coupling effect of gravity and surface tension. By fitting experimental data, we corrected the viscous dissipation time, obtaining $t_c$ = 3.17$d_0/v_0$, which improves the reliability of dissipated energy calculation. Using Young’s equation and the Cassie model, we derived a fourth-order ${\beta }_{max}$ prediction model that includes the Weber number (We), Reynolds number (Re), contact angle (${\theta }_c$), and Bo number. The results show that regulating the impact height and droplet diameter will affect the trend of the maximum spreading coefficient model curve: the crossover Weber numbers are 41.519 and 41.530 for different liquid viscosities under the specific experimental and modeling conditions of this study. Below these thresholds, the maximum spreading diameter coefficients are more sensitive to impact height (inertial and kinetic-energy) than to droplet diameter (volume, mass, surface energy, gravitational potential energy, Bond number). Above the critical value, the influence of droplet diameter on the maximum spreading diameter coefficient becomes more pronounced. These intersections reflect the balance between size-dependent effects and impact-inertia-related effects under specific conditions, rather than universal physical thresholds. Compared with selected classical models, the proposed model shows better consistency with experimental data and provides improved prediction for the maximum spreading coefficient of water droplets on surfaces with different wettability. This study supplements the perspective of energy analysis for the modeling of droplet impact dynamics, and can provide a basis for the theoretical optimization of spray systems and interfacial fluid control. Full article

Clinical trials suggest that daily vinegar ingestion improves fasting blood glucose concentrations, postprandial glucose excursions, and hemoglobin A1c levels in patients with prediabetes and type 2 diabetes. With the recent commercialization of continuous glucose monitoring (CGM) technologies, diabetes patients as well as other health-conscious individuals can evaluate the impact of food choices in real-time and make data-driven decisions to improve dietary behaviors. This 9-day, randomized crossover study documented CGM-derived glycemic patterns during vinegar ingestion in adults with prediabetes. Participants consumed two tablespoons of vinegar twice daily with meals for four days or a control tablet each morning for four days in random order. For each phase, fasting blood glucose on day four, average blood glucose across three days, and peak glucose excursion across three days were calculated. Fasting glucose concentrations of participants (n = 10 women; 36.6 ± 15.6 y; 33.9 ± 6.5 kg/m²) averaged 105.8 ± 20.6 mg/dL at baseline. Vinegar ingestion was associated with significant reductions in the mean glucose concentration (−4.4 mg/dL) and the frequency of blood glucose excursions > 140 mg/dL (−10%) in comparison to the control treatment, but fasting glucose concentrations were unaffected. These data suggest that vinegar-induced improvements in blood glucose can be observed in real-time using a CGM device in adults with prediabetes. Full article

We study the thermodynamics of the (2+1)-dimensional Gross–Neveu model inspired from graphene. We focus on the entropy density of the Gaussian fluctuation beyond the mean field. The full in-medium, momentum-dependent evaluation reveals that the fluctuations give a substantial contribution, even comparable to that of the mean field. We argue that the back-reaction from the fluctuations to the mean field should be included, which reduces the contribution mainly coming from the Landau-damping region. To treat this self-consistently, we use the generalized version of the Beth–Uhlenbeck approach for the entropy density. Compared with the standard Beth–Uhlenbeck formulation, the generalized version suppresses the low-energy contributions while preserving the bound-state effects. To illustrate this, we consider the respective contributions of the bound excitons and unbound fermions to the total entropy. This shows a sharper crossover between the degrees of freedom compared to the standard Beth–Uhlenbeck approach. This behavior is consistent with Mott-transition physics in two-dimensional materials. Full article

The transport experiments reveal that the low-temperature resistivity in the normal state of cuprate superconductors is quadratic in temperature (T-quadratic) in the underdoped pseudogap phase, while it is linear in temperature (T-linear) in the overdoped strange-metal phase; however, the full understanding of these different behaviors is still a challenging issue. Here starting from the microscopic electronic structure of cuprate superconductors, the low-temperature resistivity in the normal state is investigated from the underdoped pseudogap phase to the overdoped strange-metal phase. It is shown that the mechanism requires both the impurity scattering and the umklapp scattering: the impurity scattering is needed to restrict the modification of the distribution function to at and around the antinodal region, while the impurity-scattering assisted umklapp scattering from a spin excitation is at the heart of the behavior in the low-temperature resistivity, where the doping dependence of the temperature scale exists, and presents a similar behavior of the antinodal spin pseudogap crossover temperature. In the low-temperature region above the temperature scale in the overdoped strange-metal phase, the resistivity is T-linear; however, in the low-temperature region below the temperature scale in the underdoped pseudogap phase, the opening of the spin pseudogap lowers the spin excitation density of states at and around the antinodal region, which reduces the strength of the electron umklapp scattering from a spin excitation associated with the antinode, and thus leads to a T-quadratic behavior of the resistivity. Full article

Indium oxide (In₂O₃) has recently emerged as a promising semiconductor for advanced electronics due to its high electron mobility and wide bandgap. In this article, the lateral scaling characteristics of top-gate In₂O₃ thin-film transistors (TFTs) featuring a 1.5 nm thick channel and a 7 nm thick HfO₂ gate dielectric are investigated by two-dimensional device simulation. The analysis covers short-channel effects, DC characteristics, transconductance behavior, and small-signal radio frequency (RF) metrics across a gate-length (L_G) range of 20 nm to 700 nm. Simulation results identify a critical gate length near 100 nm for the transition from long-channel to short-channel behavior. For L_G ≤ 100 nm, pronounced short-channel effects emerge, featuring a significant negative V_TH shift and a drain-induced barrier lowering (DIBL) coefficient up to ~130 mV/V. A non-classical gm scaling behavior is observed, where g_{m_max} initially increases with L_G, then remains within a narrow range and eventually evolves toward the conventional long-channel trend. Further analysis of the lateral electric field distribution, field-dependent mobility, and transconductance efficiency indicates that this behavior originates from a crossover between short-channel field-assisted transport and gate-controlled channel modulation. The devices show strong RF potential, with f_T and f_max reaching 124.32 GHz and 157.64 GHz, respectively, at L_G = 20 nm. The high-mobility In₂O₃ channel leads to a less distinct f_T scaling transition from the classical 1/L²_G dependence to the short-channel 1/L_G dependence, while f_max scaling evolves through different regimes governed by capacitance-related limitations, intrinsic transport enhancement, and short-channel non-idealities. This work provides physical insight into the lateral scaling behavior of ultrathin top-gate In₂O₃ TFTs and highlights their potential for high-frequency and power-dense applications. Full article

Background/Objectives: A sub-anesthetic dose of ketamine has shown promise in reducing craving, withdrawal symptoms, and use of drugs such as alcohol, cocaine, and opioids among individuals with substance use disorders. Ketamine’s therapeutic potential for tobacco use is unknown. Here, we investigated a single sub-anesthetic dose among adults with tobacco use disorder who were not interested in changing their smoking behavior. Methods: Utilizing a randomized, within-subject crossover, double-blinded, counter-balanced, midazolam-controlled design, participants (n = 18) received a 0.71 mg/kg infusion of ketamine and a 0.025 mg/kg infusion of midazolam (i.e., active placebo) at least two weeks apart. Participants were asked to abstain from smoking after the infusions until the post-infusion sessions, 1 day following infusion, where participants completed measures of smoking behavior, craving, and withdrawal symptoms. Participants continued to record their smoking behavior over the 7 days following infusion. Participants also completed a semi-structured qualitative interview regarding their experiences. Results: Compared to midazolam, ketamine infusion led to a non-significant reduction (p = 0.10, η_p² = 0.153) in the number of cigarettes smoked during the requested abstinence period. Following this period, there were no significant differences in ad lib smoking. Ketamine showed no effect on craving or withdrawal symptoms. Participants reported more intense psychological experiences following ketamine infusion (p < 0.001, η_p² = 0.830) and about half reported it felt easier to abstain from smoking after the ketamine infusion. Conclusions: While well tolerated, these findings suggest ketamine has little to no direct effect on quantitative measures of cigarette smoking, craving, or withdrawal. However, the qualitative measures suggest ketamine improves mood and reduces craving in some individuals for several days. Future studies should investigate whether ketamine can indirectly support smoking cessation among individuals with comorbid psychiatric indications for ketamine treatment. Full article

Molecular spin-crossover (SCO) compounds constitute prototypical systems exhibiting first-order phase transitions. These transitions involve an abrupt switch between two well-defined states with distinctly different magnetic, optical, and vibrational properties. One state is diamagnetic (low-spin), while the other is paramagnetic (high-spin). Upon heating, the transition occurs at a characteristic temperature, T_up. Upon cooling, it takes place at a lower temperature, T_down < T_up, thereby giving rise to thermal hysteresis. Accordingly, each SCO compound is defined by a distinct pair of transition temperatures, T_up and T_down. The investigation of these molecular solids is of great importance, both for elucidating first-order phase transitions—including the potential emergence of re-entrant phases—and for their broad range of prospective applications. The critical temperatures T_up and T_down are pivotal in defining their practical utility. We present a strategy to modify and tune the transition temperatures of spin-crossover (SCO) compounds to suit different applications. The approach combines a given SCO material with layers of a second SCO system, enabling precise control of the characteristic temperatures of the resulting heterostructure. We illustrate this method with three case studies that span the 100 K–400 K temperature range. All simulations were performed using Monte Carlo methods within the Metropolis algorithm framework. Full article

High-temperature proton exchange membrane fuel cells (HT-PEMFCs) coupled with methanol reforming hold promise for distributed energy systems, yet channel hydrodynamics and geometry optimization remain underexplored. This study develops a 3D multiphysics model to investigate coupled behaviors in HT-PEMFCs fueled by methanol reformate. Results reveal bifurcation-induced Dean vortices have dual effects: they cause flow maldistribution (15–18% velocity deviation) and contribute 50% of inlet pressure loss, while generating a lateral pumping effect that enhances local mass transfer. A continuous parametric sweep of channel widths (0.9–1.9 mm) identifies a voltage-dependent performance crossover—narrower channels (1.3 mm) excel at high voltages by improving electronic conduction, whereas wider channels (1.5 mm) perform better at low voltages by mitigating mass transfer limitations. These findings provide quantitative design criteria for optimizing flow field geometry in HT-PEMFC stacks. Full article

Path planning of mobile robots on grid maps is a complex optimization problem, and applying standard particle swarm optimization (PSO) to this task often leads to stagnation and premature convergence. To address these issues, a particle swarm optimizer enhanced by fluid mechanics and differential evolution (FMDEPSO) is proposed. The method integrates fluid-inspired neighborhood feedback with a differential evolution recombination mechanism to construct a semi-discrete population evolution framework. Specifically, FMDEPSO introduces a pressure repulsion term and a viscous diffusion term to mitigate early population collapse and suppress oscillations caused by abrupt velocity variations. Meanwhile, a gas–liquid phased adaptive scheduling strategy is adopted to dynamically adjust the learning factors, thereby balancing exploration and exploitation. In addition, the mutation–crossover–greedy selection operator of differential evolution (DE) is embedded into the update process to preserve population diversity and enhance the capability of escaping local optima. On the CEC2017 benchmark suite, FMDEPSO achieved the best mean results on 17, 19, and 17 functions under 30-, 50-, and 100-dimensional settings, respectively, compared with eight representative PSO variants. It maintained a top-three ranking on the majority of functions and obtained the overall best average rank according to the Friedman test. The Wilcoxon rank-sum test further confirmed its statistical advantage on most benchmark functions. In grid-based path-planning experiments on multi-scale environments ($20\times 20$, $40\times 40$, and $60\times 60$), FMDEPSO generates smooth and goal-directed feasible trajectories in successful runs and achieves the best overall performance among PSO-based methods while maintaining a favorable balance among path quality, success rate, and runtime across different complexity levels. Overall, the proposed method exhibits stable convergence behavior and competitive solution quality in both numerical benchmark optimization and mobile robot path-planning tasks. Full article

Spatial confinement strongly affects matter by altering structural stability, relaxation times, and equilibrium properties. Interest in hydrogen storage within carbon nanotube bundles has grown because it addresses practical energy needs while revealing rich confined-fluid physics. Understanding how geometry and defects influence hydrogen structure and dynamics is essential to the development of effective storage materials. Here, we investigate how confinement in single-walled carbon nanotube (SWCNT) bundles with vacancies alters the spatial distribution and phase behavior of physisorbed hydrogen. At low temperature, hydrogen forms solid-like, cylindrical layered structures both inside and outside the tubes. Raising the temperature broadens these layers and produces a liquid-like arrangement within the confined regions. This confined solid-to-liquid crossover controls storage capacity and release behavior and can be tuned by temperature, confinement dimensions, and vacancy defects. Full article

To reduce charging time and improve operational efficiency at integrated energy stations (IESs) for electric vehicles (EVs), this paper develops a sustainability-oriented collaborative optimization model by coupling vehicle routing behavior with charging decision-making. Firstly, a dynamic road network model is established to simulate vehicle arrivals at IESs from different network nodes. Then, considering grid peak–valley electricity prices, station electricity procurement costs and EV charging demand, a dynamic pricing strategy for IESs is proposed to guide EVs to charge at off-peak hours so as to realize peak shaving and valley filling for the power grid. Meanwhile, the NSGA-III algorithm is improved through the introduction of Good Point Set initialization and an adaptive crossover mechanism, and the Good Point Set initialization and Adaptive Crossover NSGA-III (GPS-AC-NSGA-III) algorithm is proposed to solve the scheduling optimization problem. Finally, the CRITIC-based TOPSIS method is employed to identify the optimal compromise solution from the Pareto-optimal set. Case studies further prove the effectiveness of the proposed multi-objective collaborative optimization model for EVs and IESs. Compared with scenarios without dynamic Dijkstra-based navigation and dynamic pricing, the IES daily revenue increased by 39.83%, pollutant emissions decreased by 0.4%, and the peak-to-valley load difference ratio was reduced by 4.94%. The results indicate that dynamic Dijkstra-based vehicle routing improves travel efficiency, while the proposed dynamic pricing strategy enhances station profitability and smooths grid load fluctuations. Overall, the proposed framework contributes to sustainable transportation and energy systems by reducing pollutant emissions, improving energy efficiency, and enhancing the operational stability of integrated energy infrastructure, thereby supporting the transition toward low-carbon and sustainable urban energy systems. Full article

Objective: The classic excitation/inhibition dichotomy may be insufficient to describe rTMS mechanisms in the aging brain. This study investigated immediate whole-brain resting-state functional connectivity effects of 10 Hz (high-frequency) and 1 Hz (low-frequency) rTMS over the left dorsolateral prefrontal cortex (DLPFC) in healthy older adults. Methods: Thirty healthy older adults (aged 60–75 years) participated in a randomized, single-blind, crossover study, and underwent 20-min 10 Hz and 1 Hz rTMS in separate visits. A 106-channel fNIRS system was used to record resting-state activity before and immediately after each intervention. Functional connectivity was analyzed at the channel, region-of-interest (ROI) and network summary levels, including graph-theoretic metrics and distance-stratified connectivity summaries. Results: At the network summary level, 10 Hz stimulation was associated with relatively more positive changes in global topology and spatially distributed connectivity summaries, whereas 1 Hz stimulation showed the opposite overall trend. In the graph-theoretic analyses, stimulation frequency × time interaction effects were observed for global efficiency, local efficiency, clustering coefficient, and mean node strength. At the edge level, only a small number of effects survived FDR correction, and the broader connection-wise patterns were therefore interpreted as exploratory. Uncorrected analyses suggested widespread enhancement after 10 Hz stimulation and widespread reduction after 1 Hz stimulation, together with localized paradoxical effects, including selective decreases after 10 Hz and selective increases after 1 Hz (e.g., bilateral primary motor cortex connectivity). Conclusions: These findings suggest that 10 Hz and 1 Hz rTMS over the left DLPFC are associated with different patterns of immediate whole-brain network reconfiguration in healthy older adults. The presence of localized paradoxical effects further suggests that rTMS responses in the aging brain may involve more complex forms of reorganization than a simple excitatory/inhibitory dichotomy would predict. Significance: The present study provides preliminary support for a network-level perspective on neuromodulation in older adults and highlights the value of whole-brain fNIRS for characterizing distributed responses to rTMS. Larger, sham-controlled, behavior-linked, and longitudinal studies are needed to determine the robustness and functional significance of these effects. Full article

Metaheuristic algorithms have become indispensable for solving high-dimensional, non-convex, and constrained optimization problems arising in science and engineering. However, no single method can simultaneously provide strong global exploration, accurate local exploitation, and robust performance across diverse problem classes. This paper proposes JADEFLO, a new hybrid nature-inspired metaheuristic that couples Adaptive Differential Evolution with Optional External Archive (JADE) and Frilled Lizard Optimization (FLO) in a two-stage search framework. In the first stage, JADE drives global exploration using p-best mutation, an external archive, and adaptive control of the mutation factor and crossover rate to maintain population diversity. In the second stage, FLO performs intensive local refinement by mimicking the hunting and tree-climbing behaviors of frilled lizards through dedicated exploration and exploitation moves. The resulting algorithm has linear time complexity with respect to the population size, dimensionality, and number of iterations. JADEFLO is evaluated on the IEEE CEC 2022 single-objective benchmark suite (F1–F12) and three constrained engineering design problems (Pressure Vessel, tension/compression spring, and speed reducer), using 30 independent runs and comparisons against more than thirty state-of-the-art metaheuristics, including GA, PSO, DE variants, GWO, WOA, MFO, and FLO. The results show that JADEFLO attains the best overall rank on the CEC functions, delivers faster convergence and higher accuracy on most test cases, and matches or improves the best-known designs with markedly reduced variance. These findings indicate that JADEFLO is a promising general-purpose optimizer and a flexible foundation for future extensions to multi-objective and large-scale optimization. Full article