Search Results (3,486)

Externally excited synchronous machines (EESMs) are a rare-earth-free solution for traction applications. However, variable field excitation and magnetic coupling increase control complexity. Efficient validation of the resulting control functionalities can be carried out using hardware-in-the-loop (HIL) testing, which requires high-fidelity real-time simulation models. This paper presents a semi-analytical, discrete-time EESM model tailored for HIL applications. Nonlinear magnetic saturation and magnetic coupling are captured using an inverted flux–current characteristic combined with a rotating coordinate transformation, which improves resource utilization. Spatial harmonics are included through a Fourier decomposition of the angle-dependent inverse characteristics. Additionally, different loss mechanisms are considered to accurately represent the physical behavior of the machine. The model is parameterized using finite element analysis (FEA) results from a 100$\mathrm{k}$$\mathrm{W}$ salient-pole EESM. It is implemented on a field-programmable gate array to achieve real-time capability at a simulation frequency of $2.5$$\mathrm{M}$$\mathrm{Hz}$. Validation results for the typical operating range show deviations below $0.1$ compared to detailed FEA results, demonstrating accurate real-time simulation of the electromagnetic behavior. Full article

This article presents the synthesis, real-time implementation, and experimental validation of an approximated adaptive dynamic programming (AADP) actor–critic controller for precise flow rate regulation of a variable-displacement axial-piston pump designed for open-circuit hydraulic systems. Replacing the conventional hydro-mechanical regulator with an electrohydraulic proportional spool valve, the model-free controller employs two compact two-layer neural networks: the actor generates valve PWM signals from the flow tracking error, its integral, and measured discharge pressure, while the critic approximates the infinite-horizon quadratic cost-to-go via the online solution of the Bellman equation through gradient descent on Bellman residuals. Lyapunov analysis establishes closed-loop stability under bounded learning rates, with initial weights tuned via nominal plant simulation to ensure convergence from feasible starting policies. After extensive laboratory testing across four fixed loading conditions and dynamic load variations, the adaptive controller demonstrated superior performance compared with a proportional-integral (PI) controller, a Lyapunov model-reference adaptive controller (LMRAC), and an H_∞ controller (Hinf). Real-time metrics confirm bounded critic signals and near-zero Bellman errors, validating optimal policy convergence amid unmodeled hydraulic nonlinearities. Full article

This paper presents a theoretical framework for predicting molten jet breakup at the outlet of a rotating granulation system operating without forced excitation. The study focuses on the critical regime in which mechanical excitation is absent, and jet disintegration is governed solely by intrinsic hydrodynamic instabilities. The analysis is based on the linear stability theory of viscous liquid jets, employing the Rayleigh–Plateau and Tomotika approaches adapted to melt conditions typical of industrial granulation processes. The Navier–Stokes equations are formulated in a cylindrical coordinate system for an axisymmetric, incompressible viscous jet with appropriate kinematic and dynamic boundary conditions at the free surface. The breakup mechanism is characterized using key dimensionless parameters, including the Ohnesorge, Weber, Reynolds, and Capillary numbers, enabling identification of the dominant instability regime. Analytical expressions are derived for the most unstable wavelength, perturbation growth rate, breakup time, and characteristic droplet diameter. These relationships are evaluated for representative thermophysical properties of molten urea. Theoretical predictions obtained from classical Rayleigh theory, viscosity-corrected models, and modern empirical correlations show strong agreement, with deviations not exceeding 7%. Sensitivity analysis indicates limited dependence of the predicted droplet diameter on moderate variations in viscosity, surface tension, and jet velocity. The proposed model provides a physically grounded basis for predicting and controlling granule size distribution in rotating granulation systems operating without external mechanical excitation. Full article

Objectives: To evaluate extrusion-free survival following glaucoma drainage device (GDD) surgery using EverPatch Plus^® (EPP) and to compare outcomes with conventional scleral patch grafts using propensity score-based survival analysis. Methods: This retrospective case series included 19 eyes that underwent GDD implantation with EPP and 105 control eyes that received conventional scleral patch grafts. To adjust for baseline differences between groups, a propensity score for EPP use was estimated using multivariable logistic regression incorporating age, neovascular glaucoma, prior glaucoma surgery, preoperative intraocular pressure, number of glaucoma medications, quadrant of patch placement, and insertion site. Stabilized inverse probability of treatment weighting was applied. Because follow-up in the EPP group did not exceed 12 months, all survival analyses were performed with administrative censoring at 12 months. Extrusion-free survival was evaluated using Kaplan–Meier analysis and Cox proportional hazards modeling. Results: Within 12 months, patch extrusion occurred in 3 of 19 eyes in the EPP group and in 12 of 105 eyes in the scleral patch graft group. After inverse probability weighting, estimated 12-month extrusion-free survival was 83.5% in the EPP group and 88.4% in the scleral patch graft group, indicating no statistically significant difference between groups (log-rank test, p = 0.498). In an inverse probability-weighted Cox model, EPP use was not significantly associated with extrusion risk (hazard ratio ≈ 1.3; 95% confidence interval ≈ 0.4–4.0). Conclusions: After adjustment for baseline covariates and restriction of follow-up to 12 months, extrusion-free survival following glaucoma drainage device surgery using EPP was comparable to that achieved with conventional scleral patch grafts. Full article

Drifting fish aggregating devices (DFADs) are central to tropical tuna purse-seine fisheries, yet their hydrodynamic performance under realistic seas has not been adequately addressed, particularly for emerging eco-friendly designs. A three-dimensional framework based on computational fluid dynamics is developed to assess the motion response and mooring loads of full-scale DFADs comprising raft buoys, biodegradable cotton rope, and iron sinkers, using four buoy layouts (Models A to D). Unsteady Reynolds-averaged Navier–Stokes (URANS) simulations are performed with a realizable k–ε closure, volume of fluid (VOF) free-surface capturing, the Euler overlay method, dynamic overset meshes, and catenary mooring coupling. Regular waves representative of operational conditions (T = 1.40 to 2.40 s, H = 0.10 to 0.40 m) are imposed via a VOF wave-forcing technique, and mesh/time-step sensitivity analyses demonstrate the accurate reproduction of the first-order wave elevation (error < 0.8%). Surge drift per cycle and heave response amplitude operators, with the relative mooring force, are evaluated as functions of the relative wavelength (λ/L_a) and wave steepness (H/λ). The results reveal that the buoy layout exerts first-order control on DFAD dynamics, whereas short, steep waves dominate motion and line loads. The intermediate end-point sinker mass achieves a favorable balance between motion suppression and mooring load control, whereas distributing a fixed total sinker mass along the rope reduces heave response and mooring force by improving the tension redistribution and overall stability. Across all sea states, Models A and D reduced motion envelopes and mooring forces, indicating their suitability as robust, low-impact configurations. The proposed framework and design recommendations provide quantitative guidance for optimizing eco-DFAD geometry and deployment strategies, supporting safer and more sustainable DFAD-based tuna fisheries. Full article

Aiming at the problems of difficult hard-constraint enforcement and weak environmental generalization ability in the safe trajectory planning of manipulators in complex environments, a Policy-Guided Model Predictive Path Integral (PG-MPPI) planning framework is proposed. This framework integrates the advantages of reinforcement learning and model predictive control to construct a global prior guidance, local real-time optimization and hard-constraint safety assurance: a Constraint-Discounted Soft Actor–Critic (CD-SAC) offline learning policy is designed, which incorporates the configuration-space distance field as a safety guidance term to realize the learning of obstacle avoidance behavior; the offline policy is used to guide the online sampling and optimization of MPPI, improving sampling efficiency and planning quality; and a Control Barrier Function (CBF) safety filter is introduced to revise control commands in real time, ensuring the strict satisfaction of constraints. Taking the SIASUN T12B manipulator as the research object, simulation comparison experiments are carried out in multi-obstacle scenarios. The results show that the PG-MPPI algorithm outperforms the comparison algorithms in the success rate of collision-free target reaching, ensures the smoothness and feasibility of the trajectory, and has a good adaptive capacity to complex environments with unknown obstacle configurations, thus providing an efficient solution for the autonomous and safe operation of manipulators. Full article

Ensuring the safety of gluten-free foods is essential for individuals with coeliac disease and other gluten-related disorders, for whom even minimal gluten exposure can cause adverse effects; this study aimed to evaluate the long-term compliance of gluten-free labeled foods marketed in Italy. A total of 4139 pre-packaged gluten-free products were collected between 2015 and 2024 and analyzed using validated analytical methods. Products were categorized into macro-categories: cereal-based foods, processed non-cereal-based foods, confectionery, flours, baby foods, and dietary supplements. A descriptive analysis and risk modeling were generated to visualize relative risks. Overall non-compliance remained consistently very low (<1%) throughout the 10-year period, with an average rate of 0.27% and minor peaks in 2016 and 2018. The highest frequencies of gluten contamination were observed in cereal-based products and flours-particularly corn flour-while occasional non-compliance occurred in some processed non-cereal-based foods and confectionery; no non-compliance was detected in baby foods or dietary supplements. These findings are reassuring and consistent with, or better than, available EU data, confirming the effectiveness of current control systems and highlighting the importance of continuous monitoring, validated analytical methods and effective allergen management strategies. Strengthened collaboration among regulators and manufacturers remains essential to prevent cross-contamination and protect consumer health. Full article

Vortex generators (VGs) are considered in this study as an effective means of controlling the boundary-layer structure and suppressing flow separation on the suction sides of wind turbine blades. An original geometry of a surface-mounted VG has been developed and experimentally investigated, providing a stable modification of the near-wall flow over a wide range of incoming flow velocities. The aerodynamic effect is attributed to the formation of spatially diverging vortex structures that enhance momentum transfer from the outer flow region toward the near-wall layer, thereby increasing the energy level of the boundary layer. This results in an extension of the attached-flow region and an increase in the mean flow velocity over the suction side of the airfoil by up to 6.5%. The proposed configuration enables a 15% increase in the installation spacing of surface-mounted VGs without loss of control efficiency. Experimental investigations were carried out in a subsonic aerodynamic facility using the Particle Image Velocimetry (PIV) method at free-stream velocities of up to 30 m/s. The obtained data will be used for the development and validation of a mathematical model intended for parametric studies of the influence of surface-mounted VGs on various wind turbine blade airfoils under a wide range of atmospheric turbulence conditions. Full article

Reliable evaluation of emotional expression in large language model (LLM) outputs remains methodologically under-specified, particularly for long-form generation where label-only correctness provides limited evidence of affective reliability. A claim-conditioned framework is introduced for cross-model comparison under matched elicitation conditions, with TEAS (Text Emotion Adherence Score) as its core continuous metric. Defined in a shared prototype space induced by a frozen reference encoder, TEAS combines affective separability with entropy-aware uncertainty, enabling reliability assessment beyond discrete agreement within a fixed evaluator. Evaluation is conducted on a controlled synthetic corpus under a ground-truth-free, claim-conditioned protocol across four widely used LLM families (Gemini, GPT, Grok, and Mistral). In addition to overall comparative ordering, auxiliary diagnostic measures are reported to localize failure modes and support interpretation of model behavior, together with Holm-corrected pairwise comparisons, sequence-level drift analysis, and local hyperparameter sensitivity analysis. Empirical results show stable endpoint separation, aggregation-sensitive differences among close models, measurable sequence-level degradation, and stable relative orderings under tested local parameter variations. Overall, the study provides an interpretable and statistically grounded protocol for assessing emotion-expression reliability in LLM-generated text within a fixed reference space rather than as a human gold measure of emotional truth. Full article

To address the challenge of autonomous process adaptation in non-standard components with continuously varying groove angles, this study proposes an intelligent decision-making framework based on Response Surface Methodology (RSM) for oscillation welding. Instead of solely identifying a single optimal parameter set, RSM is employed as a knowledge-modeling tool to reveal adaptive relationships between groove geometry and key welding parameters. A Central Composite Design (CCD) is utilized to establish predictive models for weld geometry under varying conditions: wire feed rate (8–12 m/min), travel speed (5–9 mm/s), travel angle (70–110°), oscillation amplitude (2–6 mm), dwell time (0.2–0.6 s), and groove angle (80–100°). The significance and adequacy of the models are validated through analysis of variance (ANOVA), demonstrating high predictive accuracy with all coefficients of determination (R²) exceeding 0.82. Furthermore, defect-aware physical constraints derived from the formation mechanism of bottom humping are incorporated into the optimization process, specifically restricting the travel angle to a push angle of 70–85° to ensure feasible and reliable decision outputs. Based on the established response surfaces, geometry-dependent parameter selection rules are derived to simultaneously optimize root penetration (target 8.5–10.5 mm) and sidewall fusion (>2.5 mm) for groove angles ranging from 80° to 100°. Experimental validation confirms that the proposed decision-making strategy achieves stable bead formation and defect-free fusion, demonstrating high quantitative reliability with root penetration prediction errors below 7% and bead width errors below 13%. This work bridges the gap between geometric perception and process control, providing a practical pathway toward intelligent and adaptive robotic welding of non-standard components. Full article

The proliferation of Internet of Things (IoT) devices has introduced significant security challenges. Resource-constrained devices face sophisticated threats but lack the computational capacity for advanced security analysis. This study investigates optimal security task allocation in Cognitive IoT (CIoT) networks. It specifically examines when IoT devices should process security tasks locally or offload them to Mobile Edge Computing (MEC) servers. The problem is formulated as a Continuous-Time Markov Decision Process (CTMDP). The study demonstrates that the optimal offloading policy has a threshold structure. Security tasks are offloaded to MEC servers when the offloading queue length is below a critical threshold, $k^{\ast }$. Otherwise, tasks are processed locally. This structural property is robust to changes in MEC server configurations and threat arrival patterns. It ensures an optimal and easily implementable security policy under the exponential model. Theoretical analysis establishes upper bounds on the performance of AI-based security controllers using the same models. The results also show that standard model-free Q-learning algorithms can recover optimal thresholds without any prior knowledge of the system parameters. Simulations across multiple reinforcement learning architectures, including Q-learning, State–Action–Reward–State–Action (SARSA), and Deep Q-networks (DQN), confirm that all methods converge to the predicted threshold. This empirically validates the analytical findings. The threshold structure remains effective under practical imperfections such as imperfect sensing and parameter estimation errors. Systems maintain 85% to 93% of their optimal performance. This work extends threshold Markov Decision Process (MDP) analysis from classical queuing theory to the context of CIoT security offloading. It provides optimal and practical policies and model-free algorithms for use by resource-constrained devices. Full article

Based on the detrimental impact of network rumors, we employ the Laplacian matrix to reconstruct a diffusion term and establish a rumor propagation model that extends from traditional physical space to cyberspace. In this paper, we analyze the occurrence conditions for Turing instability in both homogeneous and heterogeneous networks and generalize the necessary conditions for Turing instability in higher-order systems. Through numerical simulations, we demonstrate the existence of Turing patterns. Additionally, we explore the intricate nature of Turing patterns within various network structures. The findings from the homogeneous network indicate that the $BA$ scale-free network is better suited for real-world scenarios. When implementing rumor-refuting policies, prioritizing individuals in key nodes can effectively control rumors throughout the entire network, significantly enhancing rumor control efficiency. The results on heterogeneous networks demonstrate that altering the key layer instead of modifying the entire three-layer network structure can also achieve the goal of rumor governance. This discovery substantially reduces the complexity associated with rumor control. Full article

Dragonflies exhibit remarkable flight stability in unsteady environments, largely due to aerodynamic interaction between their forewings and hindwings. This study investigates gust response in dragonfly-inspired micro-aerial vehicles (MAVs) from a system dynamics perspective, with emphasis on the aerodynamic role of tandem-wing interaction rather than control compensation. A six-degree-of-freedom (6DOF) rigid-body framework is developed and coupled with a quasi-steady aerodynamic model that includes explicit phase-dependent interaction between forewing and hindwing forces. Gusts are introduced as time-varying inflow perturbations, allowing physically consistent analysis of how disturbances propagate through aerodynamic loading into vehicle motion. Simulations are performed for representative flight conditions, including gliding, hovering, and gust-perturbed ascent. The results show bounded trajectory, velocity, and attitude responses under sustained gust excitation, even with conservative baseline control. Force and energy analyses indicate that wing–wake interaction redistributes aerodynamic loads in time and reduces peak force and moment fluctuations before they reach the rigid-body dynamics. This behavior is interpreted as passive aerodynamic filtering of gust disturbances inherent to the tandem-wing configuration. Comparative simulations using backstepping control and Active Disturbance Rejection Control (ADRC) further show that the dominant gust attenuation arises from aerodynamic configuration rather than from control action. Although the aerodynamic model is quasi-steady, the framework reproduces key trends reported in biological and CFD-based studies and provides a numerical foundation for future wind-tunnel and free-flight experiments on configuration-level gust attenuation. Full article

The porcine epidemic diarrhea virus (PEDV) causes a gastrointestinal disease generating mortality rates approaching 100% in piglets worldwide. The S glycoprotein of PEDV is the main target for the development of vaccines. Two vaccines approved by the Ministry of Agriculture and Rural Development are used in Mexico: the first vaccine is based on an inactivated virus isolated more than a decade ago, whereas the second vaccine is based on mRNA technology. The most important tool for controlling PEDV outbreaks is vaccination; however, coronaviruses are characterized by the accumulation of multiple mutations, which compromise the immune response elicited by outdated vaccines. In this work, we classified the Mexican strains of PEDV reported so far in GenBank, according to their genotypes. Subsequently, we searched for B and T cell epitopes conserved in Mexican PEDV strains using bioinformatic tools. In addition, we explored whether these epitopes can induce allergies, autoimmunity, and/or toxic effects. Next, we determined the localization of B cell epitopes in the S glycoprotein using the protein crystal and protein modeling of several S glycoproteins. Finally, we carried out molecular docking analysis to assess whether these T cell epitopes could interact with the peptide-binding groove of the Swine Leukocyte Antigens (SLAs). Five conserved B cell epitopes were found to be exposed on the surface of the S glycoprotein, whereas several promiscuous CTL and HTL epitopes were bound, with low free energy, to the peptide-binding grooves of SLA-I and SLA-II, respectively. The best epitopes were used to generate a plasmid carrying the sequence to produce a recombinant protein. This plasmid was used for transfection experiments in PK-15 cell culture. The B cell epitopes reported here were recognized by the sera from pigs infected with PEDV but not by the sera from uninfected animals. These results justify future evaluations of the ability of these epitopes to stimulate cytokine production by T cells, antibody generation, and their neutralizing activity. Full article

The secondary effluent from printing and dyeing wastewater contains recalcitrant organic pollutants, such as azo dye derivatives. Their persistence in aquatic environments not only creates ecological risks but also hampers the high-value reuse of reclaimed water. This study investigated the influence of typical binary anions on the degradation performance of low-concentration azo dye wastewater using a Ti/RuO₂-IrO₂ anode electrochemical oxidation system. The results demonstrated that maximum COD removal efficiency could reach 50.22%, and the controlling factors synergistically regulated the contribution and competition between Reactive Chlorine Species and free radicals. This led to a characteristic “rapid rise–decline–slow rebound” phenomenon in the COD removal rate, with the inflection points co-influenced by the current density, conductivity, and binary anion ratio of the electrochemical process. Furthermore, it alters the degradation pathway of the azo dye to “azo bond cleavage → demethylation/desulfonation → dehydroxylation/deamination oxidation → benzene ring opening”. Within a fixed duration of 60 min, the Response Surface Methodology model identified the optimal COD degradation conditions as follows: current density of 19.72 mA/cm², Cl⁻/SO₄²⁻ ratio of 5.40, and conductivity of 8.30 mS/cm. This research elucidates the differences between the electrochemical oxidation degradation pathway of low-concentration azo dye wastewater under the regulation of typical binary anions and the conventional pathway. It also reveals the regulatory effects of current density, conductivity, and binary anion ratio on the degradation patterns. Full article