Search Results (27,116)

This paper presents a hardware-in-the-loop (HIL) simulation case study on the application of High-Order Sliding Mode Control (HOSMC) to a flexible-link robotic arm. The developed HIL platform combines physical hardware components with a simulated plant model, enabling real-time testing of control algorithms under realistic operating conditions without requiring a full-scale prototype. HOSMC, an advanced nonlinear control strategy, mitigates the chattering effects inherent in conventional sliding mode control by driving the system to a reduced-order sliding manifold within a finite time, resulting in smoother actuator commands and reduced mechanical stress. Flexible-link arms, while lightweight and energy-efficient, are inherently nonlinear and prone to vibration, posing significant control challenges. In this case study, the experimental HIL environment is used to evaluate HOSMC performance, demonstrating improved trajectory tracking, reduced overshoot, and minimized steady-state error. The results confirm that HIL simulation offers an effective bridge between theoretical control design and practical implementation for advanced robotic systems. Full article

Molecular quantum-dot cellular automata (QCA) are attracting much attention as an alternative that can improve the problems of digital circuit design technology represented by existing CMOS technology. In particular, they are well suited to the upcoming nanoquantum environment era with their small size, fast switching speed, and low power consumption. In this study, we propose a 5 × 5 × 1 ultra-slim vertical panel type multi-layer 2-to-1 multiplexer (Mux) using molecular QCA, departing from conventional multi-layer formats, and show its expansion to 4-to-1 Mux and application to vertical panel type D-latch and RAM cells. In addition, the polarization phenomenon of cells is physically proven using the potential energy, distance among electrons, and the relative positions of cells, and the secure RAM design takes noise elimination and polarization of the output signal into consideration. The circuits are simulated in terms of operation and performance using QCADesigner 2.0.3 and QCADesignerE, and the proposed multi-layer 2-to-1 Mux shows a significant improvement of at least 1473% and 277% in two representative standard design costs compared to the state-of-the-art multi-layer Muxes. Full article

In the task of integrated circuit micrograph acquisition, image super-resolution reconstruction technology can significantly enhance acquisition efficiency. With the advancement of deep learning techniques, the performance of image super-resolution reconstruction networks has improved markedly, but their demand for inference device memory has also increased substantially, greatly limiting their practical application in engineering and deployment on resource-constrained devices. Against this backdrop, we designed image super-resolution reconstruction networks based on feature reuse and structural reparameterization techniques, ensuring that the networks maintain reconstruction performance while being more suitable for deployment in resource-limited environments. Traditional image super-resolution reconstruction networks often redundantly compute similar features through standard convolution operations, leading to significant computational resource wastage. By employing low-cost operations, we replaced some redundant features with those generated from the inherent characteristics of the image and designed a reparameterization layer using structural reparameterization techniques. Building upon local feature fusion and local residual learning, we developed two efficient deep feature extraction modules, and forming the image super-resolution reconstruction networks. Compared to performance-oriented image super-resolution reconstruction networks (e.g., DRCT), our network reduces algorithm parameters by 84.5% and shortens inference time by 49.8%. In comparison with lightweight image reconstruction algorithms, our method improves the mean structural similarity index by 3.24%. Experimental results demonstrate that the image super-resolution reconstruction network based on feature reuse and structural reparameterization achieves an excellent balance between network performance and complexity. Full article

Prenatal maternal stress (PNMS) predicts risk for autism spectrum disorders (ASD), although the mechanisms are unknown. Because ASD and autistic-like traits have been associated with both prenatal stress and DNA methylation differences, it is important to examine whether epigenetic mechanisms mediate the pathway from PNMS to later autistic-like outcomes. This study aimed to determine the extent to which DNA methylation mediates the association between PNMS from a natural disaster and autistic-like traits in offspring assessed during adolescence. Five months following the 1998 ice storm in Quebec, we recruited women who had been pregnant during the crisis and assessed their PNMS: objective hardship, subjective distress, and cognitive appraisal. At age 13, their children provided blood samples for DNA. At ages 15, 16 and 19, the youth self-reported their own autistic-like traits using the Broad Autism Phenotype Questionnaire. This longitudinal design allowed us to track the developmental pathway from prenatal exposure, through adolescent DNA methylation, to later behavioral outcomes. Analyses included youth with data on PNMS, DNA methylation, and the BAPQ (n = 27 at age 15; 22 at age 16; and 13 at age 19). Results showed that mothers’ disaster-related objective hardship and their negative cognitive appraisal of the disaster were associated with DNA methylation at age 13, which then were associated with the severity of their children’s Aloof Personality and Pragmatic Language Deficits, but not Rigid Personality, at ages 15, 16 and 19. Mediation was significant particularly through genes within the PI3K/AKT/mTOR pathway, which has been implicated in various neurodevelopmental disorders, including ASD. Interestingly, while greater PNMS predicted more severe ASD traits, the epigenetics effects were for less severe traits. Although other interpretations are possible, these results could suggest that DNA methylation, assessed in early adolescence, may protect against ASD traits at later ages, particularly when there is a mismatch between the prenatal environment (disaster) and the postnatal environment (absence of disaster). The interpretation of these findings benefits from the longitudinal design and is discussed in the context of fetal programming and the predictive adaptive response. Full article

Following the significant disruption of traditional teaching by the COVID-19 pandemic, gamified education—an approach integrating technology and cognitive strategies—has gained widespread attention and use among educators and learners. This study explores how game-based learning, supported by situated learning theory and game design elements, can boost learner motivation and knowledge construction. Using 20,293 user comments from the Chinese video platform Bilibili, the study applies sentiment analysis and LDA to uncover users’ sentimental tendencies and cognitive themes. The analysis identifies four core themes: (1) The application of contextual strategies in language learning, (2) Autonomous exploration and active participation in gamified learning, (3) Progressive enhancement of logical thinking in gamified environments, and (4) Teaching innovation in promoting knowledge construction and deepening. Building on these findings, the study further develops a cognitive scaffolding model integrating “contextualization–procedural logic–active construction” to explain the mechanisms of motivation–cognition interaction in gamified learning. Methodologically, this study innovatively combines LDA topic modeling with sentiment analysis, offering a new approach for multidimensional measurement of learner attitudes in gamified education. Theoretically, it extends the application of situated learning theory to digital education, providing systematic support for instructional design and meaning-making. Findings enrich empirical research on gamified learning and offer practical insights for optimizing educational platforms and personalized learning support. Full article

Computational fluid dynamics and machine learning (ML) models are employed to investigate the relationships between scaffold topology and key flow parameters, including permeability (k), average wall shear stress ($WS{S}_a$), and the 25th and 75th percentiles of WSS. Statistical analysis showed that $WS{S}_a$ values are consistent with those found in common scaffold architectures, while percentile-based WSS properties provided insight into shear environments relevant for bone and cartilage differentiation. No significant effect of pore shape was observed on k and $WS{S}_a$. Correlation analysis revealed that k was positively associated with topological features of the scaffold, whereas $WSS$ metrics were negatively correlated with these properties. ML models trained on six topological and flow inputs achieved a performance of $R^2$ above 0.9 for predicting k and $WS{S}_a$, demonstrating strong predictive capability based on the topology. Their performance decreased for $WS{S}_{25\%}$ and $WS{S}_{75\%}$, reflecting the difficulty in capturing more specific shear events. These findings highlight the potential of ML to guide scaffold design by linking topology to flow conditions critical for osteogenesis. Full article

Inspired by the free-flight capabilities of the gannet in both aerial and underwater environments, a foldable-wing air–water cross-medium vehicle was designed. To enhance its propulsive performance and transition stability across these two media, aero-hydrodynamic performance analyses were conducted under three representative operating states: aerial flight, underwater navigation, and water entry. Numerical simulations were performed in ANSYS Fluent (Version 2022R2) to quantify lift, drag, lift-to-drag ratio (L/D), and tri-axial moment responses in both air and water. The transient multiphase flow characteristics during water entry were captured using the Volume of Fluid (VOF) method. The results indicate that: (1) in the aerial state, the lift coefficient increases almost linearly with the angle of attack, and the L/D ratio peaks within the range of 4–6°; (2) in the folded (underwater) configuration, the fuselage still generates effective lift, with a maximum L/D ratio of approximately 2.67 at a 10° angle of attack; (3) transient water entry exhibits a characteristic two-stage force history (“initial impact” followed by “steady release”), with the peak vertical load increasing significantly with water entry angle and velocity. The maximum vertical force reaches 353.42 N under the 60°, 5 m/s condition, while the recommended compromise scheme of 60°, 3 m/s effectively reduces peak load and improves attitude stability. This study establishes a closed-loop analysis framework from biomimetic design to aero-hydrodynamic modeling and water entry analysis, providing the physical basis and parameter support for subsequent cross-medium attitude control, path planning, and intelligent control system development. Full article

To address the challenges of radar multi-target detection in marine environments, this paper proposes an information geometry (IG)-based, two-stage track-before-detect (TBD) framework. Specifically, multi-target measurements are first modeled on the manifold, leveraging its geometric properties for enhanced detection. The designed scoring function incorporates both the feature dissimilarity between targets and clutter, as well as the precise inter-target path associations. Consequently, a novel merit function combining feature dissimilarity and transition cost is derived to mitigate the mutual interference between adjacent targets. Subsequently, to overcome the integrated merit function expansion phenomenon, a two-stage integration strategy combining dynamic programming (DP) and greedy integration (GI) algorithms was adopted. To tackle the challenges of unknown target numbers and computationally infeasible multi-hypothesis testing, a target cancellation detection scheme is proposed. Furthermore, by exploiting the independence of multi-target motions, an efficient implementation method for the detector is developed. Experimental results demonstrate that the proposed algorithm inherits the superior clutter discrimination capability of IG detectors in sea clutter environments while effectively resolving track mismatches between neighboring targets. Finally, the effectiveness of the proposed method was validated using real-recorded sea clutter data, showing significant improvements over conventional approaches, and the signal-to-clutter ratio was improved by at least 2 dB. Full article

In multi-agent systems (MAS), autonomy is a fundamental characteristic that enables agents to operate independently and adaptively within complex environments. However, such characteristics may cause the system to fall into undesirable situations. On the one hand, purely autonomous agents are difficult to predict. On the other hand, fully controlled agents lose many of their abilities. Therefore, control frameworks have been designed in the form of organizational architectures to help address the need for balance between purely autonomous and fully controlled agents. This paper investigates the impact of organization on the autonomy of the agents. To measure this impact, we propose a set of seven metrics (Behavioral Wealth (BW), Service Wealth (SW), Frequency of Service Searches per Time (FoSST), Frequency of Service Searches per Behavior (FoSSB), Number of Service Searches (NoSS), Number of Service Demands per Behavior (NoSDB), and Number of Provided Services per Demand (NoPSD)) and apply them to a case study implemented in two configurations: with and without organizational aspects. To model organizational aspects, we adopt the Agent–Group–Role (AGR) model, chosen for its structured approach to defining agent responsibilities and interactions. The findings of this study show that the organizational aspects reduce the communication load and enhance the effectiveness of agents. Full article

The increasing integration of artificial intelligence agents (AIAs) based on large language models (LLMs) is transforming many spheres of society. These agents act as human assistants, forming Distributed Intelligent Systems (DISs) and engaging in opinion formation, consensus-building, and collective decision-making. However, complex DIS network topologies introduce significant uncertainty into these processes. We propose a quantum-inspired graph signal processing framework to model collective behavior in a DIS interacting with an external environment represented by an influence matrix (IM). System topology is captured using scale-free and Watts–Strogatz graphs. Two contrasting interaction regimes are considered. In the first case, the internal structure fully aligns with the external influence, as expressed by the commutativity between the adjacency matrix and the IM. Here, a renormalization-group-based scaling approach reveals minimal reservoir influence, characterized by full phase synchronization and coherent dynamics. In the second case, the IM includes heterogeneous negative (antagonistic) couplings that do not commute with the network, producing partial or complete spectral disorder. This disrupts phase coherence and may fragment opinions, except for the dominant collective (Perron) mode, which remains robust. Spectral entropy quantifies disorder and external influence. The proposed framework offers insights into designing LLM-participated DISs that can maintain coherence under environmental perturbations. Full article

This paper presents the design, development, and experimental evaluation of a hybrid wheel–leg guide robot intended to assist blind and elderly people with mobility tasks indoors and outdoors. The design requirements are derived from an analysis of safety, usability, and affordability needs for assisting devices. The resulting design consists of a compact platform with two front leg–wheel assemblies and three additional wheels, two of which are motorized, arranged in a triangular configuration that provides stable support and reliable traction. The proposed locomotion system is innovative because existing guide robots typically rely exclusively on either wheels or legs. In contrast, this hybrid configuration combines the energy efficiency of wheeled locomotion with the capability of leg-assisted stepping, enabling improved terrain adaptability. Experiments with a prototype were carried out in indoor environments, including straight-line motion, turning, and obstacle-overcoming tests. The prototype, with a total weight of 1.9 kg and a material cost of 255 euros, maintained stable movement and achieved a 100% success rate for obstacles up to 30 mm, with partial success up to 40 mm. Additional test results indicate an average cruising speed of 0.1 m/s, and a practical endurance of 4.5–5 h. The proposed design aims to contribute to the development of more inclusive, efficient, and user-centered robotic solutions, promoting greater autonomy and quality of life for blind and elderly people. Full article

The low-altitude economy represents an important facet of emerging productive forces, and flying cars serve as key vehicles driving its development. This paper proposes an aerodynamic design for the aerial vehicle module of split-type flying cars, which meets the functional requirements for vertical takeoff, climb, and cruising, and provides a reference solution for urban air mobility. A multidisciplinary constraint-based approach was employed to define the design requirements of the aerial vehicle module, ensuring its capability to operate in various complex environments. Through theoretical analysis and Computer-Aided Design (CAD) methods, key geometric, aerodynamic, and stability parameters were developed and evaluated. After finalizing the design concept of the aerial vehicle module, aerodynamic analysis was conducted, and aerodynamic coefficients were assessed using Computational Fluid Dynamics (CFD) simulations across angles of attack ranging from −5° to 20°. The results indicated that the aerial vehicle module achieved a maximum lift-to-drag ratio of 13.40 at an angle of attack of 2°, and entered a stall condition at 13°. The aerodynamic design enhances the module’s stability under various operating conditions, thereby improving handling performance. Overall, the aerial vehicle module demonstrates favorable aerodynamic characteristics during low-altitude flight and low-speed cruising, satisfying the design requirements and constraints. Full article

This study employs first-principles calculations combined with the Special Quasirandom Structure (SQS) technique to investigate the impact of three interstitial elements C, N, and O, on the mechanical properties and stacking fault energy (SFE) of NiCoCr medium-entropy alloys. The results indicate that non-metallic O, C, and N tend to occupy octahedral interstitial sites, which can effectively release stress concentration and enhance the strength and deformability of the material. Differential charge density analysis shows that the dissolution of C, N, and O significantly alters the surrounding electronic environment, strengthening the interaction between solute atoms and metal atoms, thereby hindering dislocation glide and increasing the strength and hardness of the material. Elastic property analysis indicates that NiCoCr alloys doped with C, N, and O exhibit good ductility and anisotropic characteristics. Furthermore, the study of stacking fault energy reveals that the doping with C, N, and O can significantly increase the stacking fault energy of NiCoCr alloys, thereby optimizing their mechanical properties. These findings provide theoretical evidence for the design of advanced high-entropy alloys that combine high strength with good ductility. Full article

Unbonded flexible risers, which can experience large bending deformation, are key equipment in advancing deep-sea exploration for marine resources. However, the riser experiences coupled loading effects from ocean environment. This results in complex response characteristics, leading to potential damage or even destruction. By presenting an analytical–numerical framework, this study uncovers the mechanism underlying the coupled failure of the pressure- and tensile-armor layers, furnishes a new tension–pressure coupled failure boundary for the ultimate-limit-state design of deep-water risers, and supplies the corresponding theoretical verification. Firstly, based on the axisymmetric load assumption, a theoretical model is proposed based on principle of functionality; afterwards, the failure model is defined by considering the material elastoplasticity. Secondly, a full-layered numerical model with detailed geometric properties is established; meanwhile, a simplified 7-layer model without a carcass layer is constructed for comparison. Finally, after verified through experimental data and interactive verification of theoretical and numerical methods, the simplified numerical model is proved to have calculation accuracy and validity. The characteristics are studied by the proposed methods. The comparison results show that the pre-applied internal pressure has limited influence on the axial stiffness of unbonded flexible rise. The initial axial tension would enhance the anti-burst failure ability of unbonded flexible riser, the failure pressure increases by 35% when the tensile force is 500 kN. Full article

This paper investigates the influence of groundwater level fluctuations on the vibration response and isolation performance of saturated soil foundations under moving loads. A coupled model consisting of an overlying elastic layer and a saturated half-space is established, with water level variation simulated by adjusting the elastic layer thickness. Using Biot’s theory and Fourier transforms, the dynamic response is solved analytically and validated numerically via COMSOL6.0 simulations with perfectly matched layers. Results indicate that the groundwater level significantly affects wave propagation: deeper water levels lead to responses resembling an elastic half-space, while rising water levels amplify surface displacement due to wave reflection at the saturation interface. As water levels approach the surface, behavior converges to that of a fully saturated foundation. P-wave resonance at certain water levels reduces isolation effectiveness. Furthermore, isolation performance is sensitive to load frequency, soil permeability, and trench dimensions. These findings offer valuable insights for designing vibration mitigation measures in environments with variable groundwater conditions. Full article