Search Results (4,390)

Extensive goat farming is the dominant livestock system in the Mediterranean region, where woody rangelands represent essential forage resources for goats. Understanding how goats move and select vegetation within these heterogeneous landscapes–and how these patterns are shaped by herding decisions-is critical for improving grazing management. This study investigated the spatio-temporal movement behavior of a goat flock in a complex woody rangeland using GPS tracking combined with GIS-based vegetation and land morphology mapping. The influence of seasonal changes in forage availability and the shepherd’s management on movement trajectories and vegetation selection was specifically examined over two consecutive years. Goat movement paths, activity ranges, and speed differed among seasons and years, reflecting changes in resource distribution, physiological stage, and herding decisions. Dense oak woodland and moderate shrubland were consistently the most selected vegetation types, confirming goats’ preference for woody species. The shepherd’s management—particularly decisions on grazing duration, route planning, and provision or withdrawal of supplementary feed—strongly affected movement characteristics and habitat use. Flexibility in adjusting grazing strategies under shifting economic conditions played a crucial role in shaping spatial behavior. The combined use of GPS devices, GIS software, vegetation maps, and direct observation proved to be an effective approach for assessing movement behavior, forage selection and grazing pressure. Such integration of technological and classical methods provides valuable insights into diet composition and resource use and offers strong potential for future applications in precision livestock management. Real-time monitoring and decision support tools based on this approach could help farmers optimize grazing strategies, improve forage utilization, and support sustainable rangeland management. Full article

Integrated energy cyber-physical systems (IECPS) face escalating cyber-attack threats due to their deep cyber-physical coupling, while traditional resilience models relying solely on fixed resources exhibit rigidity and limited adaptability. This review investigates IECPS attack mechanisms through the lens of the confidentiality, integrity, and availability framework, revealing their cross-layer propagation characteristics. We explicitly distinguish between fixed and mobile resources. Fixed resources include energy sources, transmission and distribution network facilities, coupling and conversion devices, fixed energy storage systems, and communication and control infrastructure. Mobile resources are grouped into five categories: mobile electricity resources, mobile gas resources, mobile heat resources, mobile hydrogen resources, and mobile communication resources. Fixed resources provide geographically anchored capacity and structural redundancy, and they offer static operational flexibility. Mobile resources, in contrast, provide spatially reconfigurable and rapidly deployable support for sensing, temporary multi-energy supply, and emergency communications. Building on this distinction, this review proposes a full-cycle resilience enhancement framework that encompasses pre-event prevention, in-progress response, and post-event recovery, with a particular focus on collaborative mechanisms between fixed and mobile resources. Furthermore, this review examines the foundational theories and key supporting technologies for such coordination, including fixed-mobile resource scheduling, intelligent perception and data fusion, communication security, and collaborative scheduling optimization. Key technical gaps and challenges in fixed-mobile resource collaboration are identified. Ultimately, this review aims to provide theoretical insights and practical guidance for developing resilient, adaptive, and secure integrated energy systems in the face of evolving cyber-physical threats. Full article

Demographic trends over the last decades and future projections clearly indicate a steady increase in the proportion of older adults (65+) relative to both the working-age (15–64) and child populations (0–15) across Europe. This demographic shift—driven by rising life expectancy and declining fertility—raises pressing challenges for intergenerational equity and questions the sustainability of the implicit formal and informal “social contract” that links generations through the distribution of rights, responsibilities, and resources. In particular, the two fundamental pillars of European post-industrial societies, namely an extensive welfare state and a liberal–democratic institutional framework, appear to be at risk. To address this issue, the notion of “intergenerational fairness”, recently adopted by social policies in both USA and Europe, appears flexible and fundamentally ambiguous. As a substantial variant of neoliberal austerity policies, it is simply used as a justification for further austerity measures, the withdrawal of entitlements to social and economic rights by citizens and the dismantling of welfare states. A second meaning of “intergenerational fairness” is possible starting from the concept of ambivalence used to describe the mix of conflict and solidarity that characterizes intergenerational relations in contemporary post-industrial societies. In this respect, the two concepts of “successful ageing” and “active ageing”, often considered as overlapping, actually involve very different perspectives: successful ageing adopts a substantially reductionist, individualistic, and static approach to the process of ageing, whereas active ageing is a more comprehensive and dynamic strategy that seeks to overcome all these limitations by a life-course perspective. This recognizes that a person’s path to old age is not predetermined but depends primarily on earlier life experiences and their influence: the ageing process affects people of all ages, not just the elderly. And since the subjectivization of ageing in contemporary societies has challenged the conventional notion of “natural life stages”, the new theoretical concept advanced in the article of “ageing styles” becomes central to understanding the ageing process today. Ageing styles are the outcome of the interplay between the objective and subjective dimensions of the life course, represented, respectively, by life chances (social structure) and life choices (agency). A theoretical framework is proposed for analyzing ageing styles that can be used from a life-course perspective to highlight their complex and dynamic nature. An evidence-based European political strategy aimed at promoting active ageing from a perspective of intergenerational fairness, based on the eight principles indicated, can be flexible enough to ensure that everyone can adopt their preferred ageing style without top-down imposition and contribute to the maintenance of the intergenerational social contract. Full article

With the rapid growth of residential electric vehicles, synchronized charging during peak periods can induce severe load ramping and exceed distribution network capacity limits. To mitigate these issues, governments have promoted a unified build-and-operate community model that enables centralized coordination of community charging and ensures real-time responsiveness to grid dispatch signals. Targeting this emerging operational paradigm, a dual-dimensional compensation mechanism for real-time electric vehicle (EV) demand response is proposed. The mechanism integrates two types of compensation: power regulation compensation, which rewards users for providing controllable power flexibility, and state-of-charge (SoC) loss compensation, which offsets energy deficits resulting from demand response actions. This dual-layer design enhances user willingness and long-term engagement in community-level coordination. Based on the proposed mechanism, a bi-level optimization framework is developed to realize efficient real-time regulation: the upper level maximizes the active response capacity under budget constraints, while the lower level minimizes the aggregator’s total compensation cost subject to user response behavior. Simulation results demonstrate that, compared with conventional fair-share curtailment and single-compensation approaches, the proposed mechanism effectively increases active user participation and reduces incentive expenditures. The study highlights the mechanism’s potential for practical deployment in unified build-and-operate communities and discusses limitations and future research directions. Full article

Coastal monitoring requires a synthesis of accuracy, temporal and context flexibility. Unmanned aerial vehicles (UAVs) equipped with LiDAR (light detection and ranging) sensors are a valuable option, made more widespread by the commercialization of consumer-grade systems, although they often limit user control over data processing. This work quantifies the impact of the base station type (temporary, permanent, or virtual) and its distance from the survey site on UAV-LiDAR direct georeferencing accuracy. The comparison is carried out, in a specific coastal study site, on both the estimated trajectories and the final outputs, using novel QGIS tools (PT2DEM, DEM2DEM, T2T). While temporary base stations are affected by uncertainties of the base coordinates, virtual reference stations are affected by a wider range of errors, compromising the relative model reconstruction. In contrast, permanent stations may avoid base-coordinate uncertainties, but if their distance from the site exceeds the suggested limit (15 km), their use leads to a loss of accuracy in both the relative reconstruction of the model and the absolute georeferencing. Although the use of vertical constraints has proven to be a valuable tool for reducing the vertical bias induced by a suboptimal base station, their distribution may not be adequate for minimizing residual random deviations, and their deployment may be challenging in environmental contexts lacking stable and accessible areas. Full article

Prestressed flexible support systems have become essential in deep excavation engineering, with the load distributive compression anchor (LDCA) widely adopted to enhance load-bearing performance through effective load dispersion among multiple anchoring units. Structural parameters of the anchor, particularly perforation ratio and height-to-diameter ratio, play a critical role in determining the mechanical behavior of the surrounding grout. In this study, grout located 500 mm behind the anchor body was selected as the test specimen. Unconfined compression tests were conducted to evaluate the ultimate load-bearing capacity under varying anchor configurations. Based on experimental measurements, a numerical simulation model was established and calibrated to investigate the internal stress distribution of the grout under different perforation ratios and height-to-diameter ratios. Results indicate that the perforation ratio significantly influences both the magnitude and location of stress peaks within the grout, with higher perforation ratios shifting the x-directional stress peak toward the anchor orifice and gradually reducing ultimate load-bearing capacity. Reducing the height-to-diameter ratio leads to a more uniform stress distribution, mitigating stress concentration while maintaining near-constant load-bearing capacity, although it increases anchor deformation. Optimal perforation ratio ranges were determined as [11%, 23%], [31%, 37%], and [42%, 50%] for anchors 1, 2, and 3, respectively, and the recommended height-to-diameter ratio is [15%, 17%]. The integration of experimental testing and numerical simulation provides quantitative insights into the effects of anchor design on grout performance, offering practical guidance for optimizing LDCA structures in deep excavation projects. Full article

With the large-scale integration of new energy and power electronic devices into power systems, frequency stability has become an increasingly critical concern. To maintain frequency stability while mitigating the high capital expenditure of energy storage systems (ESSs), this paper develops a control framework centered on edge energy management terminals (EEMTs). The design is based on a demonstration project in which distributed energy resources (DERs) and flexible loads collaboratively provide frequency regulation. A monitoring station is implemented to make fast frequency response (FFR) resources dispatchable, detectable, measurable, and tradable. Furthermore, a control strategy tailored for building- and factory-level applications is proposed. This strategy enables real-time optimal scheduling of DERs and flexible loads through coordinated communication between EEMTs and net load units (NLUs). Two field tests further demonstrate the effectiveness and advantages of the proposed approach. In addition, this paper proposes a coordinated scheme in which wind farms and NLUs jointly participate in frequency regulation, aiming to mitigate the response delay of NLUs and the secondary frequency drop observed in wind farms. The feasibility and benefits of this scheme are validated through experimental tests. Full article

The expansion force generated by lithium-ion batteries during charge–discharge cycles is a key indicator of their structural safety and health. Recently, flexible pressure-sensing technologies have emerged as promising solutions for in situ swelling monitoring, owing to their high flexibility, sensitivity and integration capability. This review provides a systematic summary of progress in this field. Firstly, we discuss the mechanisms of battery swelling and the principles of conventional measurement methods. It then compares their accuracy, dynamic response and environmental adaptability. Subsequently, the main flexible pressure-sensing mechanisms are categorized, including piezoresistive, capacitive, piezoelectric and triboelectric types, and their material designs, structural configurations and sensing behaviors are discussed. Building on this, we examine integration strategies for flexible pressure sensors in battery systems. It covers surface-mounted and embedded approaches at the cell level, as well as array-based and distributed schemes at the module level. A comparative analysis highlights the differences in installation constraints and monitoring capabilities between these approaches. Additionally, this section also summarizes the characteristics of swelling signals and recent advances in data processing techniques, including AI-assisted feature extraction, fault detection and health state correlation. Despite their promise, challenges such as long-term material stability and signal interference remain. Future research is expected to focus on high-performance sensing materials, multimodal sensing fusion and intelligent data processing, with the aim of further advancing the integration of flexible sensing technologies into battery management systems and enhancing early warning and safety protection capabilities. Full article

MnCo₂O₄ and CoMn₂O₄ were successfully synthesized on a stainless-steel substrate using the hydrothermal method. The structural and morphological characteristics of the spinel samples were investigated using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The electronic and vibrational properties were studied through X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR). Electrochemical properties were also evaluated using a three-electrode system associated with an electrochemical workstation. The studies revealed that the inversion of Mn and Co cation distribution between the spinel structure sites not only modifies the crystal structure and morphology but also alters specific functional properties. MnCo₂O₄ crystallized in a cubic spinel phase, exhibiting spherical particles, pronounced microstrain, and stronger metal–oxygen bonding. In contrast, CoMn₂O₄ adopted a tetragonal spinel structure with rod-like crystallites, lower microstrain, and more flexible bonding environments. Electrochemical impedance spectroscopy further revealed distinct charge-transfer dynamics, indicating differences in surface redox activity. This comparative analysis elucidates how cation site occupancy governs the performance of the synthesized spinel oxides and underscores their potential as efficient catalysts or catalyst supports for redox and energy-related applications. Full article

To achieve low-carbon collaborative operation of active distribution networks (ADNs) and microgrid clusters, this paper proposes a signal-guided collaborative optimization method. Firstly, a spatiotemporal carbon intensity equilibrium model (STCIEM) is constructed, overcoming the limitations of centralized carbon emission flow models in terms of data privacy and equitable distribution, and enabling distributed and precise carbon emission measurement. Secondly, a dual-market mechanism for carbon and electricity is designed to support peer-to-peer (P2P) carbon quota trading between microgrids and ADN-backed clearing, enhancing market liquidity and flexibility. In terms of scheduling strategy optimization, the multi-agent deep deterministic policy gradient (MADDPG) algorithm is incorporated into the carbon-electricity cooperative game framework, enabling differentiated energy scheduling under constraints. Simulation results demonstrate that the proposed method can effectively coordinate the operation of energy storage, gas turbines, and demand response, reduce system carbon intensity, improve market fairness, and enhance overall economic performance and robustness. The study shows that this framework provides theoretical support and practical reference for future distributed energy consumption and carbon neutrality paths. Full article

We introduce an equal-phase method to design the polarization-insensitive metasurface lens, composed of subwavelength nano-holes etched into a silver film. By calculating the intensity distribution under linearly, circularly, and elliptically polarized light illumination, we demonstrate that the designed metasurface lens can effectively focus incident light with different polarization states. Moreover, we confirm that this polarization-insensitive property of the designed lens maintains stable focus ability across the entire visible light bandwidth, exhibiting a broadband performance. It is important to note that the metasurface lens design based on the equal-phase method is not limited by specific nanostructure units and exhibits considerable flexibility. For some complex application conditions, we also explore the design of polarization-insensitive lenses capable of generating longitudinal and transverse dual focal spots. The metasurface lenses and the design method proposed in this paper may provide a reference for the development and application of polarization-independent components in integrated photonic devices. Full article

This paper develops a robust portfolio optimization framework that integrates Weighted Shannon Entropy (WSE) into the classical mean–variance paradigm, offering a distribution-free approach to diversification suited for volatile and heavy-tailed markets. While traditional variance-based models are highly sensitive to estimation errors and instability in covariance structures—issues that are particularly acute in cryptocurrency markets—entropy provides a structural mechanism for mitigating concentration risk and enhancing resilience under uncertainty. By incorporating informational weights that reflect asset-specific characteristics such as volatility, market capitalization, and liquidity, the WSE model generalizes classical Shannon entropy and allows for more realistic, data-driven diversification profiles. Analytical solutions derived from the maximum entropy principle and Lagrange multipliers yield exponential-form portfolio weights that balance expected return, variance, and diversification. The empirical analysis examines two case studies: a four-asset cryptocurrency portfolio (BTC, ETH, SOL, and BNB) over January–March 2025, and an extended twelve-asset portfolio over April 2024–March 2025 with rolling rebalancing and proportional transaction costs. The results show that WSE portfolios achieve systematically higher entropy scores, more balanced allocations, and improved downside protection relative to both equal-weight and classical mean–variance portfolios. Risk-adjusted metrics confirm these improvements: WSE delivers higher Sharpe ratios and less negative Conditional Value-at-Risk (CVaR), together with reduced overexposure to highly volatile assets. Overall, the findings demonstrate that Weighted Shannon Entropy offers a transparent, flexible, and robust framework for portfolio construction in environments characterized by nonlinear dependencies, structural breaks, and parameter uncertainty. Beyond its empirical performance, the WSE model provides a theoretically grounded bridge between information theory and risk management, with strong potential for applications in algorithmic allocation, index construction, and regulatory settings where diversification and stability are essential. Moreover, the integration of informational weighting schemes highlights the capacity of WSE to incorporate both statistical properties and market microstructure signals, thereby enhancing its practical relevance for real-world investment decision-making. Full article

Aiming to solve the bottlenecks of the traditional Grey Wolf Optimizer (GWO) in UAV three-dimensional path planning—including uneven initial population distribution, slow convergence speed, and proneness to local optima—this paper proposes an improved algorithm (CPS-GWO) that integrates the Kent chaotic map with Particle Swarm Optimization (PSO) to mitigate these limitations. To enhance the diversity of the initial population, the Kent chaotic map is employed, as ergodicity ensures the symmetric distribution of the initial population, expanding search coverage; meanwhile, a nonlinear adaptive strategy is adopted to dynamically adjust the control parameter a, enabling flexible search behaviour. Furthermore, the grey wolf position update rule is optimized by incorporating the inertia weight and social learning mechanism of PSO, which strengthens the algorithm’s ability to balance exploration and exploitation. Additionally, a multi-objective comprehensive cost function is constructed, encompassing path length, collision penalty, height constraints, and path smoothness, to fully align with the practical demands of UAV path planning. To validate the performance of CPS-GWO, a three-dimensional urban simulation environment is established on the MATLAB platform. Comparative experiments with different population sizes are conducted, with the traditional GWO as the benchmark. The results demonstrate that, compared with the original GWO, (1) the average fitness of CPS-GWO is significantly reduced by 31.30–38.53%; (2) the path length is shortened by 15.62–22.12%; (3) path smoothness is improved by 43.44–51.52%; and (4) the fitness variance is only 9.58–12.16% of that of the traditional GWO, indicating notably enhanced robustness. Consequently, the proposed CPS-GWO effectively balances global exploration and local exploitation capabilities, thereby providing a novel technical solution for efficient path planning in UAV logistics and distribution under complex urban environments, which holds important engineering application value. Full article

The advancement of polymeric materials for orthopedic applications has enabled the development of lightweight, adaptable structures that support patient-specific solutions. This study focuses on the design, fabrication, and mechanical characterization of additively manufactured (AM) polymeric polylactic acid (PLA) components produced via Material Extrusion (MEX), commonly known as Fused Filament Fabrication (FFF). By optimizing geometric configurations and process parameters, these structures demonstrate enhanced flexibility, energy absorption, and load distribution, making them well-suited for orthopedic products and assistive devices. A comprehensive mechanical testing campaign was conducted to evaluate the elasticity, ductility, and strength of FFF-fabricated samples under tensile and three-point bending loads. Key process parameters, including nozzle diameter, layer thickness, and printing orientation, were systematically varied, and their influence on mechanical performance was recorded. The results reveal that these parameters affect mechanical properties in a complex, interdependent manner. To better understand these relationships, an automated routine was developed to calculate the experimental mechanical response, specifically, stiffness and strength. This methodology enables an automated evaluation of the output, considering parameter ranges for future applications. The outcome of the analysis of variance (ANOVA) of the experimental investigation reveals that the printing orientation has a strong impact on the mechanical anisotropy in FFF, while layer thickness and nozzle diameter demonstrate moderate-to-weak importance. Thereafter, the experimental findings were applied on an innovative orthopedic wrist splint design to be fabricated by means of FFF. The most suitable mechanical properties were selected to test the mechanical response of the designed components under operational bending loading by means of linear elastic finite element (FE) analysis. The computational results indicated the importance of employing the actual mechanical properties derived from the applied printing process parameters compared to data sheet values. Hereby, an additional parameter to adjust the mechanical response is the product’s design topology. Finally, this framework lays the foundation for future training of neural networks to optimize specific mechanical responses, reducing reliance on conventional trial-and-error processes and improving the balance between orthopedic product quality and manufacturing efficiency. Full article

Banana harvesting relies heavily on manual labor, which is labor-intensive and prone to fruit damage due to insufficient control of contact forces. This paper presents a systematic methodology for the design and optimization of adaptive flexible end-effectors for banana bunch harvesting, focusing on contact behavior and mechanical constraints. By integrating response surface methodology (RSM) with multi-objective genetic algorithm (MOGA) optimization, the relationships between finger geometry parameters and key performance metrics—contact area, contact stress, and radial stiffness—were quantified, and Pareto-optimal structural configurations were identified. Experimental and simulation results demonstrate that the optimized flexible fingers effectively improve handling performance: contact area increased by 13–28%, contact stress reduced by 45–56%, and radial stiffness enhanced by 193%, while the maximum shear stress on the fruit stalk decreased by 90%, ensuring harvesting stability during dynamic loading. The optimization effectively distributes contact pressure, minimizes fruit damage, and enhances grasping reliability. The proposed contact-behavior-constrained design framework enables passive adaptation to fruit morphology without complex sensors, offering a generalizable solution for soft robotic handling of fragile and irregular agricultural products. This work bridges the gap between bio-inspired gripper design and practical agricultural application, providing both theoretical insights and engineering guidance for automated, low-damage fruit harvesting systems. Full article