Search Results (5,480)

In urban redevelopment, adding basements beneath existing buildings often requires specialized retaining structures, such as existing and newly added double-row piles, yet their complex load-sharing mechanism is not yet fully understood. This study addresses this gap through a series of physical model tests, systematically investigating the influence of two key variables: the row spacing and the newly added/existing pile length ratio. The results reveal that row spacing is a critical factor governing the system’s stability and cooperative behavior. The newly added piles bear the majority of the earth pressure, effectively shielding the existing piles. A distinct, layered pressure distribution was observed in the inter-row soil, a phenomenon that classical earth pressure theories cannot adequately predict. Based on a comprehensive evaluation of structural performance, deformation control, and stability, this study proposes an optimized configuration with a row spacing of 4D and a newly added/existing pile length ratio of 9/6. This configuration achieves an effective balance between structural performance and economic efficiency, offering valuable practical guidance for the design of supplementary retaining systems in basement addition projects. Full article

Polysiloxanes are unique polymers used in medicine and materials science and are ideal for various modifications. Classic functionalization methods involve a covalent approach, but finer tuning of the properties of the final polymers can also be achieved through sub-sequent noncovalent modifications. This study introduces a fundamentally new approach to polysiloxane functionalization by incorporating cooperative noncovalent interaction centers: selenium-based chalcogen bonding donors and polyfluoroaromatic π-hole acceptors into a single polymer platform. We developed an efficient nucleophilic substitution strategy using poly((3-chloropropyl)methylsiloxane) as a platform for introducing Se-containing groups with polyfluoroaromatic substituents. Three synthetic approaches were evaluated; only direct modification of Cl-PMS-2 proved successful, avoiding catalyst poisoning and crosslinking issues. The optimized methodology utilizes mild conditions and achieved high substitution degrees (74–98%) with isolated yields of 60–79%. Comprehensive characterization using ¹H, ¹³C, ¹⁹F, ⁷⁷Se, and ²⁹Si NMR, TGA, and contact angle measurements revealed significantly enhanced properties. Modified polysiloxanes demonstrated improved thermal stability (up to 37 °C higher decomposition temperatures, 50–60 °C shifts in DTG maxima) and increased hydrophobicity (water contact angles from 69° to 102°). These systems potentially enable chalcogen bonding and arene–perfluoroarene interactions, providing foundations for materials with applications in biomedicine, electronics, and protective coatings. This dual-functionality approach opens pathways toward adaptive materials whose properties can be tuned through supramolecular modification while maintaining the inherent advantages of polysiloxane platforms—flexibility, biocompatibility, and chemical inertness. Full article

Mainlobe interference can severely degrade the performance of distributed phased-array radar systems in the presence of strong jamming or low-reflectivity targets. This paper introduces a signal–data dual-domain cooperative antijamming and localization (SDCAL) framework that integrates adaptive complete ensemble empirical mode decomposition with improved blind source separation and wavelet optimization (CEEMDAN-WOBSS) for signal-level denoising and separation. Following source separation, CFAR-based pulse compression is applied for precise range estimation, and multi-node data fusion is then used to achieve three-dimensional target localization. Under low signal-to-noise ratio (SNR) conditions, the adaptive CEEMDAN–WOBSS approach reconstructs the signal covariance matrix to preserve subspace rank, thereby accelerating convergence of the separation matrix. The subsequent pulse compression and CFAR detection steps provide reliable inter-node distance measurements for accurate fusion. The simulation results demonstrate that, compared to conventional blind-source-separation methods, the proposed framework markedly enhances interference suppression, detection probability, and localization accuracy—validating its effectiveness for robust collaborative sensing in challenging jamming scenarios. Full article

The wind–solar–storage–thermal combined power generation system is one of the key measures for China’s energy structure transition, and rational capacity planning of each generation entity within the system is of critical importance. First, this paper addresses the uncertainty of wind and photovoltaic (PV) power outputs through scenario-based analysis. Considering the diversity of generation entities and their complex interest demands, a bi-level capacity optimization framework based on game theory is proposed. In the upper-level framework, a game-theoretic method is designed to analyze the multi-agent decision-making process, and the objective function of capacity allocation for multiple entities is established. In the lower-level framework, multi-objective optimization is performed on utility functions and node voltage deviations. The Nash equilibrium of the non-cooperative game and the Shapley value of the cooperative game are solved to study the differences in the capacity allocation, economic benefits, and power supply stability of the combined power generation system under different game modes. The case study results indicate that under the cooperative game mode, when the four generation entities form a coalition, the overall system achieves the highest supply stability, the lowest carbon emissions at 30,195.29 tons, and the highest renewable energy consumption rate at 53.93%. Moreover, both overall and individual economic and environmental performance are superior to those under the non-cooperative game mode. By investigating the capacity configuration and joint operation strategies of the combined generation system, this study effectively enhances the enthusiasm of each generation entity to participate in the energy market; reduces carbon emissions; and promotes the development of a more efficient, environmentally friendly, and economical power generation model. Full article

Against the backdrop of global agricultural transformation, rural China faces the critical challenge of reconciling economic development with environmental conservation and social well-being. This study, grounded in the rural revitalization strategy, investigates the internal mechanisms, level measurement, and sustainable development paths of rural industrial integration based on the “Triple Integration of Production, Livelihood and Ecology” (PLE) philosophy. Firstly, we discussed the suitability and the mechanisms of this philosophy on China’s rural industrial integration. Secondly, based on a textual corpus extracted from academic journals and policy documents, we employed an LDA topic model to cluster the themes and construct an evaluation indicator system comprising 29 indicators. Then, utilizing data from the China Statistical Yearbook and the China Rural Statistical Yearbook (2013–2022), we measured the level of China’s rural industrial integration using the entropy method. The composite integration index displays a continuous upward trend over 2013–2022, accelerating markedly after the 2015 stimulus policy, yet a temporary erosion of “production–livelihood–ecology” synergy occurred in 2020 owing to an exogenous shock. Lastly, combining the system dynamics model, we simulated over the period 2023–2030 the three sustainable development scenarios: green ecological development priority, livelihood standard development priority and production level development priority. Research has shown that (1) the “Triple Synergy of Production, Livelihood and Ecology” philosophy and China’s rural industrial integration are endogenously unified, and they form a two-way mutual mechanism with the common goal of sustainable development. (2) China’s rural industrial integration under this philosophy is characterized by production-dominated development and driven mainly by processing innovation and service investment, but can be constrained by ecological fragility and external shocks. (3) System dynamics simulations reveal that the production-development priority scenario (Scenario 3) is the most effective pathway, suggesting that the production system is a vital engine driving the sustainable development of China’s rural industrial integration, with digitalization and technological innovation significantly improving integration efficiency. In the future, efforts should focus on transitioning towards a people-centered model by restructuring cooperative equity for farmer ownership, building community-based digital commons to bridge capability gaps, and creating market mechanisms to monetize and reward conservation practices. Full article

To address the overvoltage problem in distribution networks with large-scale photovoltaic (PV) integration, this paper proposes an interactive game-based voltage optimization control strategy based on microgrid cluster partitioning. A multi-agent control architecture is constructed, including a dynamic partitioning layer, a parallel independent optimization layer, and an interactive game optimization layer. In the dynamic partitioning layer, microgrid clusters are formed considering coupling degree, voltage regulation capability, and cluster scale. In the parallel optimization layer, a network reconfiguration-based control model is established for utility-owned microgrids, and a PV active/reactive power regulation model is developed for PV microgrids, enabling independent cluster-level control. In the game optimization layer, a non-cooperative game model is formulated to coordinate voltage regulation among clusters. The effectiveness of the proposed method is demonstrated on an actual 10 kV feeder system. Full article

Energy management in hybrid fuel cell ship systems faces the dual challenges of optimizing hydrogen consumption and ensuring power quality. This study proposes an Improved Weighted Antlion Optimization (IW-ALO) algorithm for multi-objective problems. The method incorporates a dynamic weight adjustment mechanism and an elite-guided strategy, which significantly enhance global search capability and convergence performance. By integrating IW-ALO with the Equivalent Consumption Minimization Strategy (ECMS), an improved weighted ECMS (IW-ECMS) is developed, enabling real-time optimization of the equivalence factor and ensuring efficient energy sharing between the fuel cell and the lithium-ion battery. To validate the proposed strategy, a system simulation model is established in Matlab/Simulink 2017b. Compared with the rule-based state machine control and optimization-based ECMS methods over a representative 300 s ferry operating cycle, the IW-ECMS achieves a hydrogen consumption reduction of 43.4% and 42.6%, respectively, corresponding to a minimum total usage of 166.6 g under the specified load profile, while maintaining real-time system responsiveness. These reductions reflect the scenario tested, characterized by frequent load variations. Nonetheless, the results highlight the potential of IW-ECMS to enhance the economic performance of ship power systems and offer a novel approach for multi-objective cooperative optimization in complex energy systems. Full article

The formation of an emotional bond with young people’s parents is crucial for healthy development and serves as a model for future relationships. Disruptions to this bond can result in neurobiological consequences, manifesting as problematic behaviours and social deficits. Social-educational work in re-education facilities in Slovakia focuses on supporting and rehabilitating young people in conflict with the law, aiming for their reintegration into society. This study presents a qualitative analysis of social workers’ activities across 11 re-education facilities in Slovakia, utilizing semi-structured interviews, document analysis, and field observation. The findings reveal that social workers play an indispensable role in the re-education and resocialization process, providing emotional support, professional counselling, and coordination with multidisciplinary teams. Despite differences in client typology and methodologies among facilities, a shared emphasis exists on restoring social ties and personal development. The effectiveness of social work is influenced by adequate staffing, methodological support, and inter-ministerial cooperation. Implementing targeted recommendations could significantly enhance the effectiveness of the system and improve outcomes for children and young people in institutional care. This study contributes vital insights into how social workers must balance competing interests—such as individual therapeutic needs, institutional constraints, and family and community involvement—to successfully facilitate youth reintegration into society. Full article

Designers working towards social change have often focused on designing discrete solutions to social problems, rather than working within the long-term world-making practices of movements. This paper examines the potential of a more embedded design practice within prefigurative movements, where mutual aid networks, worker cooperatives, and other solidarity economy initiatives are already developing alternative systems in the present. What if we could design everyday tools with these collectives to embody their transformative visions? Yet it can be difficult to design for transformation collaboratively. Collectives include members with diverse visions that can conflict, as well as different ideas about how to create change. To explore these challenges, I discuss a project that guided local prefigurative collectives in articulating and sharing their visions of a future 100 years beyond the fall of capitalism by co-creating an illustrated map. The project achieved the collaborative articulation of transformed futures, and it also initiated a dialogue on how to design for these transformative visions today. Moving forward, the project raises questions about the risks of sharing diverging visions while attempting to build coalitions, as well as the opportunity to clarify where our dreams overlap and diverge, empowering collective members to take non-normative steps with confidence. Full article

Sensors in power systems utilize the detection results of fault signals to guide subsequent fault handling procedures. However, the traditional phase-shift restart strategy exhibits limitations such as power interruptions, reactive power redundancy, and intersystem fault clearance failures when addressing faults in the hybrid AC/DC transmission system. To address these shortcomings, a power compensation-based fault ride-through (FRT) scheme and a protection-control cooperation FRT scheme are proposed, taking into account the operational characteristics of the symmetric monopole LCC-HVDC (SM-LCC-HVDC). The power compensation-based FRT scheme actively compensates for power, mitigating the impact of reactive power redundancy on the AC-side bus during faults. The protection-control cooperation FRT scheme is activated after sufficient AC components are detected on the DC side. It leverages the adjustability of the DC system to proactively activate protection for AC transmission lines. An electromagnetic transient simulation model of the hybrid AC/DC same-tower transmission system was developed in PSCAD/EMTDC. Simulation results validate the effectiveness and superiority of the proposed methods. Full article

Accurate modeling of non-cooperative space targets remains a significant challenge, particularly under complex illumination conditions. A hybrid virtual–real framework is proposed that integrates photometric compensation, 3D reconstruction, and visibility determination to enhance the robustness and accuracy of monocular-based modeling systems. To overcome the breakdown of the classical photometric constancy assumption under varying illumination, a compensation-based photometric model is formulated and implemented. A point cloud–driven virtual space is constructed and refined through Poisson surface reconstruction, enabling per-pixel depth, normal, and visibility information to be efficiently extracted via GPU-accelerated rendering. An illumination-aware visibility model further distinguishes self-occluded and shadowed regions, allowing for selective pixel usage during photometric optimization, while motion parameter estimation is stabilized by analyzing angular velocity precession. Experiments conducted on both Unity3D-based simulations and a semi-physical platform with robotic hardware and a sunlight simulator demonstrate that the proposed method consistently outperforms conventional feature-based and direct SLAM approaches in trajectory accuracy and 3D reconstruction quality. These results highlight the effectiveness and practical significance of incorporating virtual space feedback for non-cooperative space target modeling. Full article

As a critical technological foundation for electric vehicles, power battery state estimation primarily involves estimating the State of Charge (SOC), the State of Health (SOH) and the Remaining Useful Life (RUL). This paper systematically categorizes battery state estimation methods into three distinct generations, tracing the evolutionary progression from single-state to multi-state cooperative estimation approaches. First-generation methods based on equivalent circuit models offer straightforward implementation but accumulate SOC-SOH estimation errors during battery aging, as they fail to account for the evolution of microscopic parameters such as solid electrolyte interphase film growth, lithium inventory loss, and electrode degradation. Second-generation data-driven approaches, which leverage big data and deep learning, can effectively model highly nonlinear relationships between measurements and battery states. However, they often suffer from poor physical interpretability and generalizability due to the “black-box” nature of deep learning. The emerging third-generation technology establishes transmission mechanisms from microscopic electrode interface parameters via electrochemical impedance spectroscopy to macroscopic SOC, SOH, and RUL states, forming a bidirectional closed-loop system integrating estimation, prediction, and optimization that demonstrates potential to enhance both full-operating-condition adaptability and estimation accuracy. This progress supports the development of high-reliability, long-lifetime electric vehicles. Full article

An approximate optimal control issue for modular unmanned systems (MUSs) is presented via a cooperative differential game for solving the trajectory tracking problem. Initially, the modular unmanned system’s dynamic model is built with the joint torque feedback technique. The moment of inertia of the motor rotor has positive symmetry. Each MUS module is deemed as a participant in the cooperative differential game. Then, the MUS trajectory tracking problem is transformed into an approximate optimal control problem by means of adaptive critic design (ACD). The approximate optimal control is obtained by the critic network, approaching the joint performance index function of the system. The stability of the closed-loop system is proved through Lyapunov theory. The feasibility of the proposed control algorithm is verified by an experimental platform. Full article

To address the issue of jitter and oscillation of guidance command during multi-vehicle cooperative engagement with maneuvering platforms, this paper proposes a novel terminal guidance law with prescribed performance constraints for multiple cooperative vehicles, which explicitly considers both transient and steady-state performance. Firstly, based on the vehicle-target relative kinematics, with time and space as the main constraint indicators, a multi-vehicle cooperative guidance model is established in the inertial coordinate system. Secondly, combined with the sliding mode control theory, cooperative guidance laws are designed for both the line-of-sight (LOS) direction and the LOS normal direction, respectively, and the Lyapunov stability proof is given. Furthermore, to counteract the impact of target maneuvers on guidance performance, a non-homogeneous disturbance observer is designed to estimate target maneuver information that is difficult to obtain directly, which ensures that performance constraints are still satisfied under strong target maneuvering conditions. Simulation results demonstrate that the proposed guidance law enables multiple coordinated vehicles to successfully engage the target under different maneuvering modes, while satisfying the terminal time-space constraints. Compared with conventional sliding mode control methods exhibiting inherent chattering, the proposed approach employs a novel PPC-SMC hybrid structure to quantitatively constrain the transient convergence of cooperative errors. This structure enhances the multi-vehicle cooperative guidance performance by effectively eliminating chattering and oscillations in the guidance commands, thereby significantly improving the system’s transient behavior. Full article

Background: Mild cognitive impairment (MCI) affects up to 40% of patients with Parkinson’s disease (PD), yet conventional rehabilitation often lacks engagement. The OPERA project developed a novel Bio-cooperative Robotic Platform (PRoBio), integrating a service robot and a virtual reality-based rehabilitation for personalized cognitive training. This work presents two preliminary user-centred studies aimed to assess PRoBio usability and acceptability. Methods: to gather qualitative feedback on robotic and virtual reality technologies, through ad hoc questionnaires, developed according to participatory design principles and user-centered evaluation literature, Study 1 (Focus group) involved 23 participants: 10 PD patients (F = 6; mean age = 68.9 ± 8.2 years), 5 caregivers (F = 3; mean age = 49.0 ± 15.5), 8 healthcare professionals (F = 6; mean age = 40.0 ± 12.0). Study 2 (Living Lab) tested the final version of PRoBio platform with 6 healthy volunteers (F = 3; mean age = 50.3 ± 11.0) and 8 rehabilitation professionals (F = 3; mean age = 32.8 ± 9.9), assessing usability and acceptability through validated questionnaires. Results: The focus group revealed common priorities across the three groups, including ease of use, emotional engagement, and personalization of exercises. Living Lab unveiled PRoBio as user-friendly, with high usability, hedonic quality, technology acceptance and low workload. No significant differences were found between groups, except for minor concerns on system responsiveness. Discussion: These preliminary findings support the feasibility, usability, and emotional appeal of PRoBio as a cognitive rehabilitation tool. The positive convergence among the groups suggests its potential for clinical integration. Conclusions: These preliminary results support the feasibility and user-centred design of the PRoBio platform for cognitive rehabilitation in PD. The upcoming usability evaluation in a pilot study with patients will provide critical insights into its suitability for clinical implementation and guide further development. Full article