Search Results (10,515)

Recent advancements in structural engineering have driven the development of sophisticated damping mechanisms aimed at reducing the detrimental effects of structural vibrations. As a result, accurate numerical modeling and analytical evaluation have become essential for assessing structural stability and enhancing seismic resilience. This study introduces a model-updating framework to develop analytical constitutive models for structural damping systems. The proposed approach employs a genetic algorithm (GA) to calibrate model parameters by minimizing the discrepancy between analytical predictions and experimental responses. Experimental force–displacement hysteresis data and displacement time-history records are used at both the element and system levels for model calibration. The methodology is applied to a rubber isolator, a 10-story structure equipped with Pall friction dampers, and a 6-story structure with friction dampers to evaluate its performance under different dynamic characteristics and damping mechanisms. The results indicate that the proposed approach achieves very high accuracy, with prediction errors reduced to negligible levels for both force and displacement responses in all cases. Consistent performance is observed using both global and local displacement measures in friction-damped systems, indicating the robustness of the proposed method. Overall, the findings indicate that the GA-based model-updating framework provides an efficient and reliable tool for improving the predictive capability of analytical models of structures with nonlinear damping devices and is suitable for practical structural engineering applications. Full article

To address the potential oscillation instability issues of grid-forming (GFM) inverter systems integrated into grids with reactive power compensation devices, an impedance-based model of the grid-connected system is established. The impedance analysis reveals that the compensation capacitors alter the grid impedance characteristics, leading to impedance crossover points with insufficient phase margin in the mid-to-high frequency range, thereby inducing oscillations. To address this, a negative capacitive and virtual resistive loop-based composite control strategy is proposed. The grid-side capacitive effects can be neutralized through the virtual negative capacitance, and the system damping is enhanced by a virtual resistive loop to maintain stable operation under varying short-circuit ratios. Hardware-in-the-loop experiments validate that the proposed scheme maintains stable operation under various capacitance switching and grid strengths, thereby enhancing the robustness of the GFM inverter in complex distribution network environments. Full article

With the continuous increase in the capacity of grid-connected new energy sources such as wind and photovoltaic power, the issues of sub-synchronous oscillation and super-synchronous oscillation caused by the interaction between power electronic devices and the grid have become increasingly prominent. Therefore, accurately localizing online oscillation sources is of great importance for preventing the expansion of accidents. In this paper, a modal parameter identification method is first proposed. By selecting the real part of the synchrophasor as the characteristic quantity, the precise decoupling and identification of Sub/Super-SO modal parameters are realized. On this basis, a physical feature-embedded graph attention network localization method is proposed, in which the high-precision modal parameters obtained from identification are embedded as physical features into graph nodes, and the attention mechanism is used to adaptively learn the oscillation propagation patterns in the grid topology. Finally, simulation verification based on the IEEE 14-bus system demonstrates that the proposed method can effectively achieve accurate localization of oscillation sources. Full article

Against the backdrop of the global energy transition towards clean, low-carbon sources and China’s “carbon peak, carbon neutrality” strategic goals, distributed photovoltaic (PV) power generation is being integrated into distribution networks at large scale and with a high penetration level. This trend profoundly changes the configuration and operational characteristics of traditional distribution networks, posing challenges in system planning, operation control, power quality, and economics. This paper innovatively treats the step-up transformers of multiple distributed PV stations as a “distributed generation collection network” that requires coordinated optimization and constructs an integer linear programming (ILP) model aimed at minimizing the total life-cycle cost. The model deeply integrates engineering practice, incorporates nonlinear construction, installation, operation, and maintenance costs related to cluster size, as well as power transmission costs proportional to distance, and it employs piecewise cost functions to accurately capture economies of scale. This research achieves a system-level coordination framework that moves beyond single-device optimization, reducing system costs for step-up transformer deployment in distributed PV stations under complex terrain conditions. Full article

One of the bottlenecks in realizing all-optical computing is the lack of on-chip all-optical logic devices that combine compactness, low loss, and high robustness. Valley photonic crystals (VPCs) have become an important solution for realizing such devices, relying on the excellent transmission characteristics of topological valley states. However, existing structures still face issues such as limited design flexibility. In this paper, a high-performance topological all-optical logic device based on VPCs consisting of circular ring dielectric columns is designed and demonstrated. By introducing the inner radius as an independent design parameter, we construct a new type of VPC and systematically investigate its influence on the photonic band gap. Based on this, we design a beam splitter with high operational bandwidth and low insertion loss (<0.5 dB) and then realize fundamental OR and XOR logic gates, achieving extinction ratios of 18.9 dB for the OR gate and up to 44 dB for the XOR gate at an operating frequency of 193.5 THz. The platform also supports the NOT gate and, through cascading, can implement more logic functions such as the AND gate. Full article

Reliable detection of small agricultural targets is fundamental to precision crop protection, phenotyping, yield estimation, and robotic intervention. Typical examples include detecting aphids such as Aphis gossypii, whiteflies such as Bemisia tabaci, planthoppers such as Nilaparvata lugens, and other tiny pests on sticky traps or crop canopies for early warning, identifying crop-like weed seedlings for site-specific herbicide spraying, locating early disease lesions for targeted treatment, and detecting young fruits, flowers, or wheat heads for yield estimation and robotic manipulation. Agricultural small-object detection differs from generic small-object detection because target visibility is jointly determined by pixel area, physical size, imaging distance, ground sampling distance, canopy structure, biological similarity, and task-specific intervention requirements. Existing reviews have summarized agricultural object detection or general small-object detection, but they rarely connect agricultural failure modes with detector-level mechanisms and reproducible evaluation practices. This review addresses this gap through a mechanism-oriented synthesis of agricultural small-object detection. First, we revisit the limitations of the COCO-style 32²-pixel threshold and propose an agricultural scale-reporting framework that combines pixel area, physical scale, relative image occupancy, and acquisition geometry. Second, we organize recent methods according to the mechanisms by which they address detail loss, scale shift, occlusion, dense distributions, foreground–background confusion, localization uncertainty, and edge-deployment constraints. Third, we summarize public datasets, quantitative evaluation metrics, reporting checklists, and real-device deployment evidence to support fair and field-oriented comparison. Finally, we identify future directions in multimodal sensing, foundation-model adaptation, label-efficient learning, and hardware-aware optimization. By linking agricultural scene characteristics, detector mechanisms, and evaluation requirements, this review aims to provide a more actionable framework for developing robust small-object detection systems in precision agriculture. Full article

Fish Aggregating Devices (FADs), traditionally used to attract and concentrate fish, can also serve as effective environmental enrichment tools in reservoirs, particularly in those with homogeneous characteristics and scarce refuge habitat, enhancing structural complexity and promoting recreational fishing opportunities. This study aimed to evaluate patterns in the use of prototype fish aggregation devices (FADs) in small size reservoirs. It was conducted at the Nascentes Reservoir (Crato), a small Mediterranean reservoir (ca. 10 ha) located in southern Portugal. These FADs were installed to enhance refuge habitat for fish species of interest to recreational fisheries, particularly largemouth bass (Micropterus salmoides Lacepède, 1802), thereby promoting the occurrence of trophy specimens. Two types of FADs were deployed and tested: (1) bank FADs (TREES), used in shallow waters near the margins; and (2) pelagic FADs (DAPs), suspended in the water column in deeper areas at the center of the reservoir. To monitor movement patterns and habitat use, an acoustic telemetry receiver array was deployed with a design to secure a three-dimensional fine-scale positioning with high accuracy. A total of 20 largemouth bass were tagged with acoustic transmitters equipped with pressure (i.e., depth) sensors. A before–after approach was used with 10 fish tracked before FAD deployment and 10 after. Results of fish behavior analysis provide strong evidence of fish using DAPs, but not TREES. In the presence of FADs, fish reduced their home ranges and movement amplitudes, becoming closely associated with these artificial habitats. Several environmental predictors explained fish behavior in the presence of artificial refuges, namely, diel period, moonlight intensity, and fish depth. The findings of this study are expected to contribute to the development of guidelines for refuge habitat enhancement in small- to medium-sized Mediterranean reservoirs, thereby increasing their recreational fishing attractiveness. Full article

Magnesium-based alloys remain poorly researched, particularly regarding their behavior and resistance under hydrodynamic loading conditions. Interest in these materials is driven by their low density, lower even than that of aluminum alloys, and their excellent pressure die-casting capability, leading to manufacturing components with high geometric accuracy and structural homogeneity. Due to their biodegradability and biocompatibility, recent research has focused on using them in reconstructive surgery devices, similar to Zn-Mg alloys. As the blood circulatory system can, at certain stages, be considered similar to a hydraulic system, it is subjected to hydrodynamic flow regimes, including cavitation erosion. In this context, the current research, conducted on the AM50 magnesium-based alloy, provides new insights into its behavior and structural resistance exposed to shock waves and microjets generated by cavitation. Cavitation tests were performed using a standard 20 kHz vibratory device on three material conditions: one semi-finished (initial) state and two aged, heat-treated states at 200 °C for 12 and 24 h. Analyses of the characteristic erosion curves, cavitation resistance parameters, and macro- and microstructural examinations of the eroded surfaces revealed that, compared with the semi-finished condition, the applied heat-treatment regimes increased the HV₅ hardness by 6.8–17% and the cavitation resistance by 27–61%. Full article

Educational information systems have evolved into highly interconnected digital landscapes that support learning management platforms, student information systems, institutional repositories, and online assessment environments. As these systems increasingly operate across cloud infrastructures and mobile devices, ensuring the confidentiality, integrity, and availability (CIA Triad) of educational data is critical for safeguarding institutional operations and maintaining trust in digital education services. This paper investigates how next-generation security protocols, such as adaptive multi-factor authentication and advanced access control and data protection mechanisms, can reinforce ISO/IEC 27001:2022 requirements within contemporary educational information systems. The analysis maps emerging protocol capabilities to relevant new ISO/IEC 27001:2022 control domains, illustrating how they mitigate threats associated with unauthorized access, data manipulation, and service disruption. The proposed framework is further supported by an implementation-oriented mapping and an illustrative operational architecture that demonstrates the feasibility of translating prioritized security determinants into practical mechanisms. The FAHP analysis identifies access control mechanisms, backup and recovery, and data validation as the three highest-weighted determinants, with aggregate weights of 0.061, 0.059, and 0.057, respectively. These determinants are translated into a determinant-driven Security Operationalization Matrix that connects ISO/IEC 27001:2022 control domains, CIA dimensions, and technology recommendations, and is complemented by implementation feasibility considerations tailored to the budgetary, infrastructural, and resource constraints characteristic of educational institutions. Based on the prioritization results and conceptual operationalization, the proposed integrative approach provides a structured and progressively adoptable foundation for CIA-oriented security governance in digital educational environments. Full article

Background/Objectives: Digital, remote, and ecological tools may complement clinic-based assessment in multiple sclerosis (MS), but the distribution of evidence across fatigue/fatigability, mobility, and real-world functional activity remains unclear. This scoping review mapped tools, metrics, constructs, contexts of use, and reported clinical utility in adults with MS, with attention given to whether the evidence was balanced across domains. Methods: Following Joanna Briggs Institute guidance and PRISMA-ScR/PRISMA-S reporting standards, five databases were searched on 14 March 2026. After deduplication, title/abstract screening, full-text assessment, and manual extraction and verification, the findings were synthesized descriptively without formal critical appraisal. Results: Of 3100 records identified, 1433 unique records were screened and 125 sources were included. Gait was the most frequently assessed domain (105/125), followed by fatigue/fatigability (33/125), physical activity (29/125), and sleep (2/125). The most frequent technologies were wearable devices (60/125), accelerometry (54/125), remote/home-based/telemonitoring modalities (52/125), and inertial measurement units (42/125). Conclusions: The evidence is predominantly gait- and mobility-focused, while fatigue/fatigability and broader real-world functional activity are less consistently represented. Reported clinical utility was usually framed around functional assessment, longitudinal/remote monitoring, rehabilitation planning, patient stratification, and decision support, but these characteristics were extracted as reported and were not independently appraised. Full article

Herein, p-NbSe₂ thin films were deposited onto n-Si substrates to fabricate an n-Si/p-NbSe₂ (SNS) heterojunction for visible light communication (VLC) applications. Structural analysis revealed that the NbSe₂ films possess a trigonal phase and are composed of slightly elongated and irregularly shaped grains with an average size of 0.131 μm. Electrical characterization showed that the SNS heterojunction exhibits pronounced rectifying behavior, with a bias-dependent asymmetry factor reaching 6.6 × ${10}^3$. The photodetection performance of the device was evaluated under illumination from white, blue, red, tungsten, and infrared LEDs. The device exhibited excellent photodetection characteristics across the visible region, achieving a maximum responsivity of 3.79/3.68 AW⁻¹, external quantum efficiency of 1160/809%, noise equivalent power of 4.43 × 10⁻¹⁴ /4.57 × 10⁻¹⁴ WHz^−1/2, and specific detectivity of 3.91 × 10¹²/3.79 × 10¹² Jones under blue/white light illumination, confirming its practical relevance for VLC systems. In addition, frequency-dependent photocurrent measurements under modulated blue and white LED illumination revealed −3 dB bandwidths of approximately 775 Hz and 716 Hz, respectively, supporting the potential of the n-Si/p-NbSe₂ photodiode for low-frequency VLC-related visible-light detection. Compared with previously reported photodiodes used in VLC and IR technologies, the present device demonstrated superior responsivity and EQE%, together with competitive NEP and detectivity. The enhanced performance is attributed to efficient photocarrier generation and collection across the Si/NbSe2 heterojunction. These results confirm that the fabricated SNS photodiode is a promising candidate for high-sensitivity and efficient visible light communication applications. Full article

The large-scale integration of distributed photovoltaics (DPVs) into the distribution network exacerbates voltage fluctuations and substantially increases network losses. To improve the voltage quality and economic efficiency of distribution networks, a Volt/Var optimization (VVO) model is established. Coordinating multiple heterogeneous devices, the model aims to minimize the total voltage deviation, the total network losses, and the regulation cost of discrete equipment simultaneously. Considering multi-constraint coupling characteristics, a quantitative method is proposed to evaluate the reactive power regulation potential of DPVs under intricate operating conditions. Then, the multi-strategy integrated rime optimization algorithm (MSIRIME) is utilized for the model solution. Fuch chaotic mapping generates uniformly distributed and ergodic initial populations. A dual-branch search mechanism combining the snow ablation optimizer with the rime optimization significantly enhances global exploration capabilities. The guided learning strategy balances exploration and exploitation for high-dimensional VVO, preventing local optima. Case tests on a modified IEEE 33-bus system demonstrate that the proposed model exhibits excellent effectiveness and robustness. Moreover, MSIRIME exhibits better optimization performance than some classic and recently proposed strategies, reducing the average network losses and voltage deviation over 30 independent runs by at least 5.87% and 52.22%, respectively, relative to those of the compared methods. Full article

Oscillating water column (OWC) wave energy converters equipped with dielectric elastomer generators (DEGs) represent a promising technology for harnessing ocean wave energy. This study emphasises the critical role of functional specifications in guiding the development of these devices from initial concept to full-scale deployment. A comprehensive analysis of key design parameters that influence the performance and efficiency of flexible OWCs with DEG-based power take-off systems is presented. This investigation focuses on the effects of draft, membrane diameter, deformation characteristics, number of layers, and membrane thickness on power output. Utilising a combination of analytical tools, including Wave Venture software, MATLAB, and Abaqus, detailed simulations and analyses are conducted to optimise these parameters. Our results demonstrate that increasing the DEG diameter significantly enhances power output, with diameters between 5 and 12 m showing optimal efficiency. A critical strain threshold of approximately 32% is identified, beyond which power output efficiency diminishes. Furthermore, the study reveals that multi-layer DEG configurations can substantially increase energy production, with thinner membranes generally yielding higher outputs. These findings provide valuable insights for developing functional specifications that balance performance, manufacturability, and long-term reliability in marine environments. This research advances OWC technology by offering a parameter-screening framework to guide device design towards optimised configurations and to accelerate the path to commercial viability in the wave energy sector. Full article

Accurate representation of the pressure drop–flow rate (Δp–q) relationship of nozzle-type inflow control devices (ICDs) is critical for reliable reservoir–wellbore coupled simulation. Conventional ICD models in reservoir simulators rely primarily on empirical correlations or tabulated data, but commonly used formulations cannot consistently capture the linear behavior in the low-flow regime or the transition between flow regimes, which may reduce physical fidelity and numerical robustness. To overcome this limitation, this study proposes a unified characteristic-curve representation that integrates linear, transitional, and quadratic flow regimes into a single continuous and differentiable function through a physically constrained least-squares formulation, and further develops a physics-informed neural network (PINN) to learn the ICD pressure–flow relationship while enforcing physical consistency. The trained PINN model is embedded into a multi-segment well model within a reservoir–wellbore coupled simulation framework and evaluated using a mechanistic reservoir model containing permeability streaks with varying permeabilities. The results show that the proposed method improves numerical convergence and accurately reproduces ICD pressure–flow behavior across multiple flow regimes, providing a more physically consistent and robust representation of ICD performance for inflow control analysis and reservoir simulation. Full article

This paper presents the design of an inverted-F antenna intended for integration into a smartwatch operating in the 2.4 GHz band. The antenna design addresses spatial constraints imposed by the device’s miniaturized form factor and the proximity of electronic components, including the printed circuit board, display, and battery. The influence of the user’s body on the antenna’s performance characteristics was considered during the design phase through numerical simulations employing the Finite-Difference Time-Domain (FDTD) method with a heterogeneous human body model. Simulation results and measurements of a fabricated prototype antenna are presented, demonstrating satisfactory performance in terms of impedance matching with VSWR below 1.5 in the whole band and gain of −1 dBi. Full article