Search Results (6,136)

This study examines pre-service teachers’ self-efficacy in teaching real-world problems and mathematical modelling. Using a quantitative design, it investigates variation in self-efficacy between primary and special education pre-service teachers across different competence facets. The findings reveal a differentiated, domain-specific pattern of self-efficacy rather than uniform differences between groups. Special education pre-service teachers reported higher self-efficacy in pedagogical content knowledge and task design and differentiation, whereas no significant differences emerged for situation-specific skills and instructional design and enactment. The study contributes to a more differentiated understanding of modelling-related self-efficacy by showing that domain specificity may also operate within a specific area of mathematics teaching. It highlights the relevance of considering different competence facets in teacher education for inclusive mathematics classrooms. Full article

The use of ultra-high magnetic fields, such as 11.74 T in magnetic resonance imaging (MRI), offers great potential for achieving superior image quality and enabling advanced imaging applications. The development of new field-strength systems requires an investigation into the performance of radiofrequency transmitters and receivers. Loop coils are a popular choice for MRI scanners up to 7 T, with better performance exhibited at 3 T, whereas volume coils such as birdcage coils are preferred for 1.5 T scanners. On this basis, the field strength of 11.74 T raises the question of which resonator design will provide superior performance. Dipole antennas have been proposed for many applications involving different field strengths and target organs. One of the limitations of dipole antennas is the relationship between the resonance and the length. At 11.74 T, the dipole frequency of operation is 500 MHz, which provides a dipole antenna length of approximately 28 cm, which is acceptable for an MRI scanner. This study analyzed the transmission and reception performances of dipole arrays with different radii in terms of field intensity, uniformity, SAR, effectiveness, g-factor, and field optimization. Full article

Reliable multisensor perception is a key requirement for practical waste sorting, yet many low-cost sensor configurations cannot rely on hardware synchronization or carefully controlled acquisition. We present a pilot-scale multisensor waste-sorting testbed that combines an unsynchronized RGB camera with a long-wave infrared (LWIR) camera for object classification on a continuously moving conveyor, and introduce ThermalRGBTrash, a new paired RGB–LWIR video dataset for this task. To enable fusion under asynchronous acquisition, we develop a fully software-based registration pipeline that combines SuperPoint–SuperGlue matching with an adaptive sliding-window strategy designed to recover from long-wave infrared sensor artifacts, including non-uniformity correction events. Across 281,439 matched frame pairs from 19 paired videos, the registration pipeline achieves a mean spatial alignment error of 2.27 pixels and matches 99.98% of attempted frame pairs. We then detect and segment objects with Mask R-CNN, track them across the conveyor, and classify each tracklet using frozen DINOv2 self-supervised Vision Transformer (ViT-L/14) features with a lightweight multilayer perceptron head. RGB and LWIR representations are combined through late fusion. On 550 tracklets under video-disjoint 10-fold cross-validation, the fused pipeline reaches a macro F1 score of 0.924, outperforming RGB alone (0.886) and LWIR alone (0.856). On a mixed-class test set of 351 tracklets reserved exclusively for final evaluation, fusion reaches a macro F1 score of 0.947. The fusion advantage persists across multiple backbone and pretraining choices, while ablation studies support the chosen temporal sampling and pooling design. These results show that accurate RGB–LWIR object classification is achievable without synchronization hardware, and establish ThermalRGBTrash as a benchmark for future work on practical multisensor perception in conveyor-based waste sorting. Full article

Carbon fiber-reinforced polymer (CFRP) composites are increasingly used in aerospace, rail transportation, and energy engineering owing to their high specific strength and corrosion resistance. However, their complex and interacting damage mechanisms, including delamination and matrix cracking, present significant challenges for reliable structural health monitoring. Fiber Bragg grating (FBG) sensors offer distinct advantages for monitoring composite structures because of their compact size, immunity to electromagnetic interference, embeddability, and capability for distributed strain measurement. Nevertheless, the effectiveness of an FBG sensing network depends strongly on the spatial distribution of the sensing points. This study proposes a finite-element-assisted framework for evaluating and improving FBG sensor layouts for strain-field reconstruction and structural feature characterization of composite plates. The framework first reconstructs the spatial strain field from limited sensing data using interpolation and least-squares fitting methods, and then evaluates the performance of existing and candidate sensor layouts based on reconstruction errors and spatial coverage of structurally important regions. A strain-gradient-informed heuristic strategy is subsequently developed to improve sensor placement by combining high-gradient region identification, spatially uniform coverage, minimum-distance constraints, and predefined support-region monitoring requirements. The Fourier least-squares fitting method provides the lowest reconstruction error among the investigated approaches and is therefore adopted for subsequent layout evaluation and improvement. Finite-element simulations and experimental measurements are used to assess the reconstruction performance and identify the advantages and limitations of different sensor layouts under static and dynamic loading conditions. The results demonstrate that the proposed framework can effectively evaluate existing FBG layouts and provide a systematic basis for their improvement, while also revealing the trade-off between local strain-gradient resolution and global spatial coverage. The proposed framework provides practical guidance for the performance-oriented design and improvement of FBG sensor networks for structural health monitoring of composite structures. Full article

Blending hydrogen into existing natural-gas pipeline networks provides a practicable route toward future low-carbon applications. A Venturi-type mixer is a classical high-efficiency static gas-mixing device, and clarifying the effects of its structural parameters is important for efficient transport and downstream combustion stability. In this study, numerical simulations were performed in ANSYS Fluent 2024 R1. The contraction angle, throat length, and diffuser angle were selected as representative structural variables. First, the independent effects of these variables on the mixing process were examined through single-factor simulations. Then, three key levels of the three structural parameters were selected to establish a Box–Behnken experimental matrix for response-surface modeling. Based on the numerical results, entropy weighting and a genetic algorithm were used for multi-objective optimization, and the final solution was verified using the TOPSIS method. The results show that the optimized Venturi-type mixing device with optimized parameters of a contraction angle of 20.7°, a throat length of 60 mm, and a diffuser angle of 5° can reduce flow energy loss while maintaining high mixing uniformity. The diffuser angle is the dominant geometric parameter affecting both energy loss and mixing behavior. Compared with the reference central-point structure design, the overall TOPSIS score of the optimized structure increased from 0.41 to 0.82; the pressure loss decreased from 258.94 Pa to 206 Pa, corresponding to a reduction of approximately 20%; and the final-section mixing uniformity decreased only slightly, from 97.85% to 97.43%. Full article

Spray pretreatment is a key step in short-process textile cleaning, and spray deposition uniformity on the target plane directly determines the quality consistency of subsequent dyeing and finishing, with nozzle layout exerting a direct influence on this uniformity. However, the existing non-submerged free jet model suffers from physical distortions in planar flow projection, namely multi-valued flow at the origin and non-convergent far-field flow. To address this, the proportionality coefficient of the Gaussian distribution is redefined to establish a corrected planar flow distribution function with a unique origin flow and natural far-field convergence. Treating continuous fabric motion as equivalent nozzle translation, a cumulative flow superposition model for moving planes is constructed, and a collaborative optimization model for nozzle spacing, mounting height, and attitude angle is established using the Particle Swarm Optimization (PSO) algorithm, with adjacent nozzle pairs as the periodic unit. Experimental calibration shows that relative errors between theoretical and measured flow rates remain within 10%. Nozzle rotation about the local z-axis is identified as the most effective attitude variable for uniformity tuning; a 0.1 m increase in nozzle spacing reduces peak overlap flow by about 30% and overlap width by about 40%. For a dual-nozzle system on a 0.66 m-wide target plane, numerical simulation results show that the calculated cumulative flow variance decreases from 5.9193 to 1.1588, corresponding to an 80.4% reduction in the numerical uniformity index. This numerical optimization framework provides a quantitative reference for nozzle layout design in textile spraying processes. Full article

Virtual reality (VR) survival horror is often discussed in terms of heightened fear and immersion, yet less attention has been paid to how fear is organized across different atmospheric conditions and how this organization differs from non-VR gameplay. This study approaches immersive fear as a process emerging from the interaction among atmospheric configuration, embodied regulation, and post-play interpretation. A sequential mixed-methods design was employed using Resident Evil Village as the empirical context. Study 1 combined scene-based observation, synchronized gameplay recordings, and post-play interviews with eight participants to examine how fear was enacted across three contrasted atmospheric configurations: combat pressure, psychological ambiguity, and spatial disorientation. Study 2 extended this analysis through a within-subject experiment with 30 participants who completed both VR and non-VR versions of the same gameplay content under standardized conditions. The findings show that immersive fear is not a uniform increase in emotional intensity. In Study 1, different atmospheric configurations elicited distinct modes of embodied regulation, including defensive retreat, hesitant exposure, and cautious reorientation, while behavioral responses and retrospective accounts often diverged in systematic ways. In Study 2, paired-samples tests showed that VR produced lower valence, higher arousal, reduced perceived control, higher fear ratings, stronger immersion, and greater motion sickness than non-VR gameplay. Although VR increased fear ratings across all scenes, the display mode × scene interaction was not significant; descriptively, psychologically ambiguous environments produced the highest absolute fear ratings under VR. Across both studies, prior VR and genre experience appeared to shape how players interpreted and narrated threat, while short-term residual effects suggested that fear may extend beyond gameplay. These results suggest that VR modifies not only the intensity but also the organization of fear, while the scene-level and experience-related patterns should be interpreted cautiously. More broadly, the study reframes immersive fear as a temporally distributed process linking atmospheric configuration, embodied regulation, and post-play interpretation in survival horror gameplay. Full article

How the diffusion of green innovation technologies translates into regional landscape sustainability is still poorly resolved, in part because most studies rely on a single data source that cannot separate an adoption signal from confounding climatic and terrain influences. To make progress on this identification problem, an empirical framework is assembled that fuses openly licensed observations, Landsat and Sentinel-2 imagery, OpenStreetMap layers, NPP-VIIRS nighttime lights, and public statistical yearbooks, and embeds them in a spatial econometric design, so that the adoption–pattern–service–sustainability chain can be traced across 72 county-level units spanning Ningxia, eastern Gansu, and northern Shaanxi over 2013–2022. Pixel- and object-level integration, entropy weighting, and principal component reduction jointly deliver a fused representation whose coefficient of determination against held-out reference data exceeds 0.85 while the reconstruction error falls by roughly a third relative to single-source baselines. A spatial Durbin specification then decomposes adoption’s association with sustainability into a dominant direct component and a smaller, distance-bounded spillover, and roughly one-quarter of the total travels through landscape reconfiguration; the result survives the placebo, subsample, and variable-substitution checks, and is strongly conditioned by the terrain and local economic capacity. These findings favour a spatially coordinated, capacity-targeted transition policy rather than uniform deployment. Two caveats should be read alongside them: adoption is measured through proxies whose validity, though corroborated against county-level green-patent and installed-capacity records, is not perfect, and external validation across contrasting landscapes remains outstanding. Full article

Micro-fabrication and structural engineering of an ultrasensitive photoelectrochemical (PEC) micro-sensing platform have been developed, based on ZnO inverse opal electrodes with signal amplification enhanced by AgCuS nanocrystals, specifically designed for the detection of anti-LGI1 antibodies. The delayed light effect inherent in the ZnO inverse opal structure enhances photoelectrochemical efficiency by extending the effective optical path. Incorporation of AgCuS nanocrystals significantly augments the photoelectric sensitivity of the ZnO inverse opal, maximizing visible light utilization, accelerating charge transfer kinetics, and substantially enhancing photocurrent generation. Leveraging the uniform porous architecture of the ZnO inverse opal, the ZnO/AgCuS film provides an expansive surface area for biomolecule immobilization and facilitates enhanced electron transport. The ZnO/AgCuS heterogeneous film was innovatively implemented as a PEC bioassay platform. Under optimized conditions, the biosensor exhibited a linear detection range of 0.01–500 ng/mL and a detection limit of 13 pg/mL for Anti-LGI1. Furthermore, the fabricated PEC biosensor demonstrated robust performance in human serum sample analyses, characterized by high repeatability, long-term stability, and excellent specificity. This work proposes a micro-manufacturing strategy for high-performance PEC biodevices, promoting the development of intelligent diagnostic platforms for autoimmune encephalitis. Full article

This paper addresses adaptive fuzzy tracking control for fractional-order nonlinear systems (FONSs) subject to asymmetric state constraints without imposing separate feasibility conditions on intermediate virtual controllers. Fuzzy logic systems are used to approximate the unknown nonlinear functions. By exploiting the boundedness of the hyperbolic tangent function, a coordinate transformation and an asymmetric fractional barrier Lyapunov function (AFBLF) are developed to construct bounded virtual control signals. Within a backstepping framework, an adaptive fuzzy controller is designed. Fractional-order Lyapunov analysis establishes semi-global uniform ultimate boundedness of all closed-loop signals and preservation of the prescribed asymmetric constraints. Comparative and benchmark simulations demonstrate constraint satisfaction, moderate control effort, and suppression of high-frequency chattering-like oscillations. Full article

Conventional low-frequency antennas face a trade-off between miniaturization and radiation efficiency due to wavelength limitations. Although magnetoelectric (ME) antennas can overcome the electrical size constraint, existing designs lack structural tunability and performance enhancement. This paper proposes a Bézier curve-based (BCB) ME antenna that features a variable cross-section, introducing a shape tuning factor for precise geometric configuration. Using the lumped-mass method, the functional relationship between resonant frequency and the shape tuning factor is derived, establishing the theoretical basis for frequency tuning. A nonlinear multi-field coupled numerical simulation model is established for performance prediction. The BCB structure modifies internal stress distribution, enabling spatial reconstruction of magnetization modulation. The proposed design is validated by comparing the analytical model with our simulation results and literature-reported experimental data. Results show that the BCB design reduces resonant frequency and enhances converse ME (CME) coupling and far-field radiation without increasing material volume. Under clamped and free boundary conditions, the minimum resonant frequencies reach 7.2 kHz and 11.1 kHz, respectively, with CME coupling improved by 124% and 140%. When the shape tuning factor proposed in this work is set to 1/2, the proposed design degenerates into a traditional antenna with uniform cross-sections, which verifies the consistency of the established model. Full article

Air-void distribution is an important internal characteristic of asphalt mixtures, as it affects compaction quality, moisture susceptibility, permeability, and long-term pavement durability. Conventional air-void testing methods generally provide only an average volumetric parameter and cannot effectively describe the spatial distribution of air voids within cylindrical specimens. To address this limitation, this study proposes a capacitance-based method for characterizing the vertical and radial air-void distribution of asphalt mixtures using a saturated reference field. An annular capacitive sensor was designed for cylindrical asphalt mixture specimens, and its structural dimensions were optimized using capacitance sensitivity and sensitivity-field distribution uniformity as evaluation indicators. Asphalt mixture specimens with different gradations and compaction conditions were prepared and tested under a saturated reference-field measurement scheme. Dielectric indicators derived from capacitance measurements were used to characterize the variation in air-void distribution along the specimen height and across radial regions. Layer-wise air-void measurements were further conducted to validate the vertical distribution results, while radial partition-based indicators were introduced to quantitatively describe the air-void distribution characteristics from the center to the edge of the specimen. In addition, rotation-angle and saturated-condition stability tests were performed to evaluate the robustness of the proposed method. The results indicate that the saturated reference-field capacitance method can effectively reflect the spatial variation in air voids in asphalt mixtures and provides a low-cost, rapid, and non-destructive approach for evaluating air-void distribution characteristics in laboratory-compacted specimens. Full article

Asphalt pavements at high-altitude airports endure prolonged extreme low temperatures and large diurnal swings, imposing stringent demands on crack sealants, whose multi-scale adhesion failure mechanism remains unclear. Three SBS and crumb-rubber-composite-modified sealants, designated A, B and C, were characterized through surface free energy tests, pull-off and shear tests, fluorescence microscopy, FTIR and molecular dynamics simulations. Cross-scale correlation analysis and CRITIC-TOPSIS were applied to link and rank the sealants across scales. Work of cohesion, work of adhesion, pull-off strength and shear strength all rose monotonically with modifier content, and sealant C exhibited a 38.5% higher work of cohesion and a 52.4% lower CV_φ than sealant A. Molecular dynamics simulations showed that electrostatic forces drove sealant–aggregate adhesion while van der Waals forces governed sealant–asphalt adhesion, with a simulation–experiment deviation of only 2.88–5.74%. A level-by-level transmission linked phase-morphology uniformity, intermolecular interaction, interfacial energy and macroscopic mechanical performance. Sealant C achieved a CRITIC-TOPSIS index of 1.000, far above 0.271 for B and 0.000 for A, and is recommended as the preferred material for crack sealing of high-altitude airport asphalt pavements. Full article

Tight oil reservoirs are characterized by poor petrophysical properties, ultra-low permeability, and limited pressure-transmission capacity. After hydraulic fracturing, retained fracturing fluid can accumulate near the fracture–matrix interface and form a water shield, which restricts carbon dioxide (CO₂) seepage, CO₂–oil contact, and crude-oil mobilization during CO₂ huff-n-puff. To clarify the control mechanism of a fracture-adjacent water shield on pressure dynamics and pore-scale oil mobilization in tight reservoirs, three stepwise core experiments were designed: a non-fractured core without a water shield (#E1), a single-fracture core without a water shield (#E2), and a single-fracture core with a MnCl₂-induced water shield (#E3). Pressure monitoring, cumulative nuclear magnetic resonance (NMR) T₂ spectra, and NMR imaging were integrated to compare the matrix, fracture, and water-shield effects. The results show that the water shield does not act as a constant resistance during cyclic CO₂ huff-n-puff. In Cycle 1, the water shield restricts CO₂–oil contact, and the relative pressure-decline amplitude of #E3 is approximately 10% lower than that of #E2. In Cycle 2, the relative pressure-decline amplitude of #E3 increases to 18.4%, approximately 1.8 times that of #E2, indicating a local water-shield transition rather than uniform matrix sweeping. The T₂-derived recovery degrees of #E3 are 7.24%, 15.34%, 7.96%, and 4.07% from Cycles 1 to 4, respectively, and its cumulative recovery after four cycles is 34.61%, which is 7.32 percentage points lower than that of #E2. NMR imaging further shows that the swept region in #E3 is mainly concentrated near the fracture after Cycle 2, while matrix regions away from the fracture retain strong oil signals. These results indicate that the water shield first acts as a fracture-adjacent water-phase barrier and then undergoes a local transition into a preferential pressure-dissipation pathway. The findings provide a basis for interpreting pressure decline together with NMR evidence and for optimizing CO₂ huff-n-puff operations in tight reservoirs affected by retained fracturing fluid. Full article

The influence of pleat angle on the pressure drop of H14 HEPA filters was investigated through a mathematical model that represents the filter as a system of converging–diverging channels coupled with porous filtration media. The analysis was conducted for pleat angles ranging from 1° to 20° under a constant laminar airflow rate of 0.167 m³/s and 0.45 m/s velocity. The model combines Darcy–Forchheimer flow through the filtration media with laminar channel flow theory, enabling the total pressure drop to be expressed as a function of pleat geometry and subsequently optimised through analytical differentiation. The results show that the pressure drop contribution of the filtration media increases with the pleat angle, from 10.57 Pa at 1° to 213.49 Pa at 20°, whereas channel losses decrease sharply from 1121.71 Pa to 2.75 Pa over the same interval. The competing behaviour of these two mechanisms generates a minimum total pressure drop of 94.56 Pa at a pleat angle of approximately 6°, compared with 120 Pa for the current industrial configuration operating at 3.73°. This represents a pressure drop reduction of approximately 21.2%, implying a corresponding decrease in fan energy consumption without compromising filtration performance. The analysis further demonstrates that very small pleat angles (1–2°) are highly unfavourable, producing total pressure drops between 301 and 1132 Pa due to severe channel constriction, while for angles above 13–14°, the channel contribution becomes negligible, and the overall pressure drop is governed almost entirely by the filtration media. These findings provide quantitative design criteria for optimising HEPA, EPA, and ULPA filter geometries, highlighting pleat angle as a critical parameter for improving aerodynamic performance, flow uniformity, and energy efficiency in high-purity environments. The proposed model was further assessed using a commercially available H14 HEPA filter with 188 pleats, an effective filtration area of 10.618 m², and a nominal airflow rate of 600 m³/h, demonstrating its applicability to real industrial filter configurations. Full article