Search Results (5,269)

Defect detection in the hot rolling process is closely linked to the quality of the final product. Among these defects, slab camber during the intermediate rolling stage is one of the primary manifestations of asymmetry, which significantly impairs both the quality of the finished strip and the stability of subsequent rolling processes. Conventional image-based edge detection methods for slab camber are prone to detection deviations in complex industrial environments, mainly due to their weak noise robustness. To address the scientific challenge of low accuracy and poor robustness in feature extraction for hot-rolled intermediate slab camber detection, which is induced by environmental interference in complex industrial settings, we break through the technical bottlenecks of traditional edge detection methods and existing deep learning models in terms of channel–spatial feature collaborative optimization and anti-interference fusion of multi-scale features. We establish a dense perception network model integrated with a channel–spatial attention mechanism, realize robust feature recognition of slab edges under complex working conditions, and provide theoretical and technical support for the real-time quantitative detection of slab shape defects in the hot rolling process. The proposed model significantly improves detection accuracy and robustness through multi-scale feature enhancement and noise suppression, effectively meeting the requirements for real-time quantitative detection of slab camber in the roughing rolling stage. Field experiments verify that the method increases detection accuracy by 36.55% and achieves favorable performance on evaluation metrics, including ODS and OIS. Full article

Eddy-current inspection of anisotropic composites, such as aeronautical CFRP, demands models that ensure mathematical rigor, tensorial consistency, and clear energetic interpretation. This work presents a novel unified variational framework with a multiplicative tensor perturbation for the time-harmonic eddy-current problem in anisotropic media with defective regions. The formulation is posed in the natural spaces $H(\mathrm{curl};\Omega )\times H^1\left({\Omega }_c\right)$, and the well-posedness is established via the Lax–Milgram theorem under physically consistent assumptions on permeability and conductivity. The sesquilinear form admits a Hermitian decomposition that separates dissipative and reactive contributions, revealing the energetic structure of the weak formulation. Defects are modeled through multiplicative modifications of the baseline anisotropic conductivity tensor. This congruence-based approach preserves symmetry and positive definiteness, ensuring non-negative Joule losses and structural stability, allowing a modular representation of subsurface delamination, fiber breakage, conductive inclusions, and distributed porosity within a single tensorial framework. A central result of the present formulation is the reconstruction of the complex power functional from the evaluation of the weak form at the solution, showing that the active dissipated power and the magnetic reactive power arise directly from the same integral terms. Through the complex Poynting theorem, the quadratic form is linked to the internal complex power, establishing a direct connection between the variational formulation and measurable quantities such as probe impedance variations. Simulations of realistic layered CFRP configurations, including single- and multi-defect scenarios, confirm that, compared with additive perturbations, the multiplicative model provides enhanced energetic contrast, particularly in strongly anisotropic and interacting defect conditions. Agreement with experimental measurements, supported by a quantitative comparison of dissipated power variations obtained from controlled EC experiments, corroborates the physical relevance and robustness of the proposed complex power functional. Full article

This work presents the first systematic development of the inverse scattering transform for matrix nonlinear Schrödinger equations in the case where the discrete spectrum has triple poles, under nonzero boundary conditions at infinity. These systems arise physically as reductions modeling spinor Bose-Einstein condensates with hyperfine spin $F=1$ and find applications in nonlinear optics. A uniformization variable is employed to map the underlying Riemann surface to the complex plane, enabling a complete characterization of the analyticity, symmetries, and asymptotic behaviors of the Jost functions and scattering data. Extending the established framework for simple and double poles, we show that $\mathrm{rank}$$P(x,t,z_n)=3$ requires a third-order zero of $deta\left(z\right)$ at $z=z_n$, while $\mathrm{rank}$$P(x,t,z_n)=2$ necessitates a fourth-order zero—a nontrivial feature absent in lower-order cases. The discrete spectrum for both rank configurations is fully characterized, and the full singular behavior near a triple pole is derived, respecting the quartet symmetry $z_n$, $z_n^{*}$, $v{k}_0^2/z_n$, $v{k}_0^2/z_n^{*}$ imposed by the nonzero boundary conditions. Solving the resulting matrix Riemann-Hilbert problem with triple poles yields the potential reconstruction formula and, in the reflectionless case, explicit expressions for general N-triple-pole soliton solutions, with a detailed example for $N=1$ presented to illustrate the construction. Full article

Gas-cooled reactors are highly sophisticated energy systems in which numerous physical phenomena take place at the same time. Among these, the effective removal of heat from the reactor core is of great importance. In gas-cooled reactors, convective heat transfer and the conditions under which it occurs are critical to both the performance and safety of these reactors. Convective heat transfer in gas-cooled reactors is particularly complex due to the thermo-physical properties of gaseous coolants, high operating temperatures, and diverse flow regimes. It is commonly characterized using empirical and semi-empirical correlations. Each correlation is valid only within specific ranges of operating and geometric conditions, making the appropriate selection of correlations essential for accurate reactor design and reliable safety assessment. The aim of this review is to provide a comprehensive evaluation of the models and correlations applicable to the description and modeling of convective heat transfer in selected types of gas-cooled reactors. For each reactor type, the relevant correlations are categorized and summarized in tables, along with their ranges of applicability and inherent limitations. In total 154 correlations were reviewed. The findings highlight that convective heat transfer in different types of gas-cooled reactors is described differently. This article offer a consolidated reference of correlations useful for engineers and researchers working in the field of heat transfer and nuclear reactor engineering. In addition, remaining challenges are discussed and future research directions are proposed to support improved heat transfer modeling for current and next-generation gas-cooled reactor technologies. Full article

This study examines the campus-planning projects (1920–1937) of Kwan, Chu & Yang, Architects & Engineers (KCY), a major Chinese firm, against the backdrop of Sino-American cross-cultural knowledge transfer. It argues that their work exhibited a distinct compositional tendency derived from the partners’ U.S. Beaux-Arts education and contemporary American planning theory. Through historical analysis and case studies of four university projects, this research examines how composition-based spatial unity engaged with specific Chinese site conditions. The results indicate that early projects negotiated irregular boundaries, while later ones grappled with complex topography, such as historic gardens and hills. Although often unrealized, these grand schemes embodied a scientific planning methodology and served as aspirational blueprints. This study concludes that compositional practice was a significant part of China’s architectural modernization, representing both a professional design approach and a cultural response to the quest for modernity and national identity. Full article

Fenton-based processes are widely used advanced oxidation methods that are known for degrading persistent pollutants. However, these techniques often generate significant amounts of iron-containing sludge, which poses environmental disposal challenges due to its complex composition. Furthermore, the sludge produced by the Fenton process contains a high content of Fe(III) compounds, which can serve as an iron source to stimulate dissimilatory iron reduction (DIR), enhancing the performance of anaerobic digestion. Based on the characterization results from a previous study, this work investigated the use of the ferrous precipitate generated by the electrochemical peroxidation process applied to tannery wastewater treatment as an additive to enhance volatile fatty acids (VFAs) production during dark fermentation. The performance of ferrous precipitate (R-Fe₃O₄) was compared to that of conventional magnetite (Fe₃O₄) during dark fermentation under high organic loading conditions, emphasizing their potential to enhance hydrolysis efficiency and VFAs production yields, while promoting sustainable resource recovery and reuse within a circular bioeconomy framework. The results showed that the addition of both Fe₃O₄ and R-Fe₃O₄ significantly increased the VFAs yields, with a predominance of long-chain fatty acids. The presence of CaCO₃ in the ferrous precipitate contributed to maintaining a stable pH environment, supporting microbial activity and enhancing the hydrolysis of soluble compounds. Moreover, the availability of essential micronutrients within the ferrous precipitate favored greater microbial diversity. Consequently, the addition of R-Fe₃O₄ promoted VFAs production, even at higher organic loading rates, suggesting a promising application of Fenton-based by-products as functional additives to improve the economic and environmental performance of the dark fermentation process. Full article

Unmanned Aerial Vehicle (UAV) trajectory planning in complex three-dimensional environments with threats remains a challenging optimization problem requiring efficient algorithms and threat detection capabilities. This study proposes the Conservative Enhanced Dwarf Mongoose Optimization Algorithm (CEDMOA), which introduces four key innovations to the original DMOA: hybrid population initialization, adaptive vocalization parameters, elite-guided learning strategy, and intelligent restart mechanisms. This work proposed the integration of CEDMOA with a novel vision-based threat detection system using YOLO object detection technology, enabling the identification and incorporation of threats into the optimization process. CEDMOA was comprehensively evaluated on the CEC2022 benchmark test suite, demonstrating superior performance compared to other state-of-the-art algorithms in solution quality and convergence stability. The results show the approach successfully generates an optimal collision-free flight trajectory in complex environments in UAV trajectory planning with both static and dynamic threats. Combining metaheuristic optimization with computer vision technology provides a robust framework for autonomous navigation that adapts to changing threat conditions. Experimental results validate the effectiveness of both the enhanced algorithm and the vision-based threat integration approach for practical UAV operations. Full article

This work investigated the membrane fouling mechanisms during the microfiltration of oat protein–β-glucan complexes. Microfiltration experiments were conducted under various pH conditions, protein-to-polysaccharide ratios, and ionic strengths. The fouling behavior was analyzed using multiple membrane fouling models to systematically elucidate the relationships among the particle characteristics, rheological behaviors, and membrane fouling. When the pH was adjusted to 7.8, the multimodal particle size distribution of the complexes promoted the formation of a loosely structured cake layer on the membrane surface, accompanied by partial obstruction of membrane pore entrances. On the contrary, the complexes, shown as having a monomodal particle size distribution and similar particle size to the membrane pore, formed compact cake layers and strong membrane fouling resistance. At pH 4.8, protein hydrophobic aggregation generated large particulate clusters that formed a loose cake layer during microfiltration, resulting in a decrease in membrane fouling resistance. Increasing the β-glucan content reduced membrane resistance through enhancing steric hindrance and hydrophilicity. This research provides a theoretical foundation for optimizing membrane separation process parameters in the production of diversified oat-based products. Full article

This paper presents a systematic experimental comparison of three sliding-mode-based current control strategies—traditional sliding mode control (SMC), fast terminal sliding mode control (FTSMC), and super-twisting sliding mode control (STSMC)—applied to a grid-connected five-level active neutral point clamped flying capacitor (5L-ANPC-FC) inverter. Unlike existing studies that typically investigate a single controller or topology, this work provides a fair, hardware-validated benchmark under identical operating conditions, enabling a clear assessment of convergence speed, harmonic performance, robustness, and implementation complexity. All controllers are designed within a unified framework and their stability is rigorously analyzed using Lyapunov theory. Experimental evaluations are conducted under steady-state operation, step changes in reference current, grid-voltage sag/swell, and DC-link voltage variations. The results demonstrate that while all three controllers ensure robust current tracking and inherent DC-side capacitor voltage balancing without additional control loops, FTSMC achieves the lowest grid-current total harmonic distortion (THD) and fastest convergence. STSMC effectively suppresses chattering, and traditional SMC offers a simple yet reliable baseline solution. The presented findings provide practical design guidelines for selecting appropriate sliding-mode controllers in high-performance multilevel inverter applications. Among the assessed control techniques, FTSMC has the most rapid dynamic response, characterized by a rise time of 0.1 ms and a minimal grid-current THD of 1.95%, indicating exceptional steady-state and transient performance. STSMC markedly diminishes chattering and ripple, attaining a THD of 2.04% with enhanced waveform smoothness relative to traditional SMC. Conversely, traditional SMC offers a more straightforward implementation but demonstrates elevated ripple and THD levels of around 2.29%, along with a peak current inaccuracy of 6–8%. The results underscore the trade-offs between implementation simplicity, dynamic responsiveness, and harmonic performance of the evaluated control techniques. Full article

Eye-tracking is a key enabling technology for smart eyewear, supporting hands-free interaction, accessibility, and context-aware human–machine interfaces under strict constraints on size, power consumption, and computational complexity. While camera-based solutions provide high accuracy, their integration into lightweight and low-power wearable platforms remains challenging. This paper is a feasibility study for the design, simulation, and experimental evaluation of a photosensor oculography (PSOG) eye-tracking system that is fully integrated into an eyewear frame, based on near-infrared (NIR) emitters and photodiodes. The proposed approach combines simulation-driven optimization of the optical constellation, a multi-frequency modulation and demodulation scheme enabling parallel source discrimination and robust ambient-light rejection, and a resource-efficient signal acquisition pipeline suitable for embedded implementation. Eye rotations in azimuth and elevation are inferred from differential reflectance patterns of ocular regions (sclera, iris, and pupil) using lightweight regression techniques, including shallow neural networks and Gaussian process regression, selected to balance estimation accuracy with computational and power constraints. System performance is evaluated using a controllable artificial-eye platform under defined geometric and illumination conditions, enabling repeatable assessment of gaze-estimation accuracy and algorithmic behavior. Sub-degree errors are achieved in this controlled setting, demonstrating the feasibility and potential effectiveness of the proposed architecture. Practical considerations for translation to real-world smart eyewear, including human-subject validation, anatomical variability, calibration strategies, and embedded deployment, are discussed and identified as directions for future work. By detailing the optical design methodology, modulation strategy, and algorithmic trade-offs, this work clarifies the distinct contributions of the proposed PSOG system relative to existing frame-integrated and camera-free eye-tracking approaches, and provides a foundation for further development toward wearable and augmented-reality applications. Full article

Advances in regenerative medicine increasingly rely on human-relevant in vitro systems to model the multistage process of wound healing. However, the translation of research into effective therapies remains limited by the inability of traditional 2D cultures and animal models to faithfully replicate the structural and biochemical complexity of human skin. While existing reviews often focus on the structural composition of static skin equivalents, this review addresses a critical knowledge gap: the need for dynamic, time-dependent methodologies that can capture the spatiotemporal evolution of healing, from inflammation to remodeling, in both physiological and pathological conditions. To this end, we critically evaluate next-generation platforms, including 3D bioprinting, organ-on-chip systems, organoids, and iPSC-based models, highlighting their comparative advantages and technical hurdles like vascularization and scalability. The unique contribution of this work lies in providing a forward-looking framework that advocates for the convergence of bioengineering and computational modeling to move beyond “steady-state” snapshots toward predictive, high-resolution dynamic models. We conclude that the future of wound healing research depends on integrating vascular and immune components within these platforms to achieve truly human-relevant, personalized diagnostic and therapeutic tools. Full article

The control of oxygen stoichiometry via topochemical reduction offers a powerful route to manipulate the functional properties of complex oxides. Here, we investigate the chemical and structural evolution of epitaxial BiFeO₃ (BFO) thin films under CaH₂ treatment in a sealed tube, using a representative reduction condition of 365 °C for 2 h and a temperature window of 345 to 380 °C to probe the reduction dependent evolution. The inherent sensitivity of BFO’s multiferroic properties to oxygen vacancy formation and cation valence states makes it an ideal platform to probe reduction pathways. The aim of this work is to elucidate the detailed reduction pathway, including phase stability, valence changes in Bi and Fe, and the morphological consequences of oxygen extraction. Using a combination of spectroscopic, diffraction, and microscopic techniques, it was demonstrated that CaH₂ annealing does not yield a homogeneous oxygen-deficient perovskite. Instead, it triggers a decomposition into Bi₂O₃, metallic Bi, and FeO_x secondary phases, accompanied by severe surface roughening. This chemical reconstruction leads to a strong suppression of the ferromagnetic-like response and a redshift in the optical absorption edge. Full article

Pesticides constitute a critical class of anthropogenic contaminants whose pervasive occurrence in surface waters, groundwater, and drinking water distribution systems poses substantial ecological and public health risks. Their pronounced structural heterogeneity, spanning highly polar herbicides to hydrophobic fungicides, together with their co-occurrence at trace levels, requires analytical methodologies capable of delivering rapid, robust, and high-resolution separations. In this study, a UHPLC-based analytical strategy is presented as a methodological framework for the development and optimization of UHPLC methods targeting multiresidue pesticide mixtures of environmental interest. The framework integrates a two-factor, three-level Design of Experiments, quadratic response surface modeling, and a multicriteria global desirability function to optimize the chromatographic resolution of 27 environmentally relevant pesticides. Statistical modeling revealed significant linear and quadratic effects of flow rate and gradient duration, highlighting the importance of multivariate optimization for complex multiresidue separations. The optimized UHPLC conditions improved simultaneous resolution, particularly for structurally similar analytes prone to coelution under conventional HPLC conditions. Overall, this work provides a statistically supported and transferable methodology for chemometric optimization of UHPLC separations and establishes a basis for extending desirability-driven optimization to additional classes of organic contaminants. Full article

Silicone gel packaging for high-voltage power devices suffers severe insulation degradation under complex conditions involving sustained high voltages and steep pulses. DC superimposed pulse electric fields are the primary cause. However, existing research lacks a systematic quantitative analysis of key influencing factors. Motivated by this inadequacy, this study quantified the effects of four core factors via control variable-based electrical tree experiments and revealed the microscopic mechanism through charge vibration experiments. Results indicate that pulse voltage slew rate is the most critical factor, as the impact of altering the pulse voltage slew rate on the parameters of the electrical tree exceeds 200%, while the impacts of altering the superimposed DC amplitude and duty cycle are 49.92% and 77.56%, respectively. Further discussion demonstrates that pulse voltage slew rate reflects the charge dynamic behaviors, while DC amplitude and duty cycle reflect charge static accumulation, with charge dynamic behaviors posing a more significant effect. This work clarifies key control parameters for silicone gel insulation degradation and the intrinsic influence chain from influencing factors to molecular stress, charge dynamic behaviors, electrical tree growth and silicone gel insulation degradation, providing theoretical support and technical guidance for optimizing the design and enhancing the reliability of silicone gel in power electronic devices packaging insulation. Full article

Volatile organic compounds (VOCs, dominated by xylene, toluene, and benzene) and paint mist emissions from ship painting represent a major environmental and health concern, posing a critical bottleneck to the green transformation of the shipbuilding industry. To tackle this challenge, this study presents an integrated recovery system designed specifically for ship automatic-spraying robots. Guided by the synergistic principle of “air-curtain containment, multi-stage adsorption, and negative-pressure recovery,” the system features a modular design that ensures full compatibility with the robots’ spraying trajectory without operational interference. Core adsorption materials, namely glass fiber filter cotton and honeycomb activated carbon fiber, were selected to suit the high-humidity and high-pollutant-concentration environment typical of ship painting. An appropriately matched axial flow fan maintains stable negative pressure throughout the system. Furthermore, the design integrates an air curtain isolation subsystem and an automated control subsystem, enabling coordinated operation and real-time adjustment. Using ANSYS Fluent, geometric and flow field simulation models were established to analyze airflow distribution and pollutant adsorption behavior, which led to the optimization of key structural and material parameters. Field experiments conducted in shipyard environments demonstrated the system’s superior performance: it achieved a VOC removal efficiency of 88.4% and a paint mist capture efficiency of 85.7% under optimal working conditions, with a maximum simulated paint mist capture efficiency of 86.2%. The system maintained stable performance under complex vertical and overhead spraying conditions, with an efficiency attenuation of less than 1.5%, and its outlet emissions fully complied with the mandatory limits specified in the Emission Standard of Air Pollutants for the Shipbuilding Industry (GB 30981.2-2025). The relative error between experimental data and simulation results is less than 2%, confirming the reliability and practicality of the proposed system. This research provides an efficient and adaptable pollution control solution for green shipbuilding and offers valuable technical insights for the sustainable upgrading of automated painting processes in heavy industries. Full article