Search Results (3,478)

Electrochemical impedance spectroscopy (EIS) is a powerful, non-destructive tool for evaluating ion-selective electrode (ISE) membrane condition. This work investigated EIS for identifying degradation mechanisms in all-solid-state Pb²⁺-selective electrodes. Graphene-containing PVC membranes deposited on glassy carbon electrodes were exposed to synthetic urine, river water, and seawater (24 h and 1 week) and to mechanical damage (cutting, needle puncture, or both). Degradation was assessed using EIS, potentiometric measurements, contact-angle analysis, profilometry, and SEM. River water and urine exposure decreased hydrophobicity, increased roughness, and produced fouling deposits. Seawater caused only minor morphological and wettability changes, though impedance data showed increased membrane hydration due to high ionic strength. Mechanical damage substantially disrupted membrane integrity, causing pronounced impedance changes, increased potential drift, and reduced analytical performance. Fouling and mechanical damage produced distinct electrochemical signatures: fouling mainly affected surface properties, while mechanical damage altered the membrane–transducer interface, increasing capacitance and reducing resistance. Notably, needle-punctured electrodes retained a near-Nernstian response despite clear impedance changes and reduced long-term stability, showing that EIS detects defects invisible to conventional calibration. These results confirm EIS as a sensitive method for distinguishing fouling from physical damage, useful for early degradation detection and lifetime monitoring of all-solid-state ISEs. Full article

Accurate fault location is essential for improving the reliability and service restoration capability of distribution networks. With the increasing penetration of distributed generation, power electronic devices, and flexible loads, fault transient signals become increasingly nonlinear and nonstationary, posing challenges to conventional impedance-based, traveling-wave-based, and feature-engineering-based methods. To improve transient fault feature representation, this paper proposes a wavelet-embedded residual attention convolutional neural network (CNN) for distribution network fault location. The task is formulated as a multi-class classification problem, in which each predefined line section is treated as a candidate fault location class. The proposed method embeds discrete wavelet decomposition into the convolutional feature extraction process, enabling low-frequency trend components and high-frequency transient components to be jointly represented and fused by subsequent trainable network modules. Residual connections improve deep feature propagation, and an attention mechanism enhances fault-sensitive representations. Simulation studies on the IEEE 33-bus distribution system show that the proposed method outperforms multi-layer perceptron (MLP), support vector machine (SVM), standard CNN, ResNet, and Attention-CNN, achieving 98.27% accuracy and a 98.33% F1-score. The class-wise results and robustness tests under different transition resistances, noise levels, and fault types further verify the effectiveness and adaptability of the proposed method. Full article

In the context of accelerated progress in clean energy development, an increasing number of regions are utilizing photovoltaic modules (PVMs) for the purpose of energy production. Numerous studies have demonstrated that the installation of these PVMs can exert both positive and negative effects on local ecosystems in different regions. However, there is a paucity of studies that have explored the ecological recovery mechanisms following PVM removal from another perspective, which may hinder a comprehensive understanding of PVM ecological impacts and impede the formulation and implementation of ecological management policies. The PVMs installed on Jiaogang Lake, which were to be removed due to policy adjustments, provided a valuable opportunity to address this issue. The taxonomic and functional diversity of waterbird communities in Jiaogang Lake was assessed and compared before and after the removal of PVMs. The results demonstrated that following the removal, there was a significant increase in both waterbird species richness and functional diversity, whilst the functional nestedness patterns between waterbird communities became more pronounced, implying the restoration of lake littoral areas. Subsequent analysis of individual waterbird functional traits revealed a significant trend towards larger body sizes in waterbirds following the removal of PVMs. Although temporal changes in certain traits did not attain statistical significance, the consistent trends observed in numerous traits led to this extrapolation with confidence. The present study thus aims to encourage decisive decision-making, particularly in short-term macroecological research in the local-scale region, avoiding delays in ecological management measures due to an obsession with perfect statistical data and analysis outcomes. Full article

This study acknowledges the role of high-involvement work practices (HIWPs) in promoting proactive behavior among public organization employees, addressing the need to obtain further insights into the mechanisms and identify contingencies (i.e., both conditional and individual factors) that might impede the effectiveness of such practices. This builds on emerging empirical studies in the public management literature by drawing on social exchange theory and social cognitive theory to empirically test the impact of HIWPs on employees’ proactive behavior, using data collected through a two-wave, time-lagged survey design with a one-month interval from Turkish public organizations. The mediating role of public relations values was also examined, along with the moderating roles of role breadth self-efficacy and employees’ use of normative public values. Relying on 554 data obtained from Turkish public organization employees, this study finds that HIWPs positively impact employees’ proactive behavior and public relations values. Public relations values positively impact employees’ proactive behavior and partially mediate the link between HIWPs and employees’ proactive behavior. Role breadth self-efficacy moderates the positive relationship between HIWPs and public relations values, with the relationship being stronger for employees with high role breadth self-efficacy than for those with low. Employees’ use of normative public values moderates the positive link between public relations values and employees’ proactive behavior, with the relationship being stronger for employees with high use of normative public values than for those with low. The main theoretical and practical implications of the study’s outcomes are outlined and discussed, along with important future research directions. The findings highlight the importance of human-centric organizational practices in fostering public value in VUCA-D environments. By enabling proactive behavior, public organizations can enhance adaptability, support value co-creation with citizens, and strengthen trust in public service systems. Full article

Aluminum corrosion in acidic media leads to accelerated material degradation and significant economic losses. This study evaluated the aqueous extract of yerba mate (Ilex paraguariensis) as a green inhibitor for aluminum corrosion in 0.5 M HCl at temperatures (298–323 K) and extract concentrations (1%, 2.5%, and 5% v/v). The extract was characterized by FTIR, and its inhibitory performance was assessed using weight loss measurements, potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), and contact angle analysis. Gravimetric results showed a decrease in corrosion rate with increasing extract concentration, reaching a maximum inhibition efficiency of 94% at 308 K and 5% v/v. The increase in activation energy in the presence of the inhibitor suggested the formation of an energy barrier associated with adsorption on the aluminum surface. Polarization studies indicated that the extract behaves as a mixed-type inhibitor, while EIS revealed an increase in charge transfer resistance and the formation of a protective adsorbed film. SEM images confirmed reduced corrosion damage, and contact angle measurements indicated increased surface hydrophobicity. The inhibition mechanism followed Langmuir adsorption behavior, suggesting adsorption of organic species at the aluminum–solution interface. These findings demonstrate that yerba mate extract is an effective corrosion inhibitor. Full article

Soft robots built from compliant materials and deformable structures are increasingly used in medical intervention, wearable assistance, delicate manipulation, and environmental exploration, where conventional rigid robots are limited by high mechanical impedance and poor morphological adaptability. However, their transition from laboratory prototypes to deployable systems remains constrained by coupled bottlenecks in materials, actuation, sensing, modeling, control, energy supply, and manufacturing. This review summarizes recent advances in soft robotics through an evaluative framework covering actuation and materials, modeling and simulation, control strategies, multimodal sensing, and representative applications. Instead of treating these topics as independent descriptions, we compare the underlying mechanisms, measurable performance indicators, strengths, limitations, and application boundaries. Three conclusions emerge. First, no single actuation strategy can simultaneously maximize output force, response speed, energy efficiency, durability, miniaturization, and untethered operation. Second, high-fidelity continuum models improve physical accuracy but remain difficult to use for real-time control, whereas reduced-order and data-driven models improve efficiency at the cost of generalization, interpretability, or contact fidelity. Third, practical soft robots will depend on system-level integration of embedded sensing, physics-informed learning, robust control, reliable materials, and scalable fabrication. Future progress should therefore prioritize standardized benchmarks, lifecycle reliability, energy-autonomous operation, and task-specific comparisons with rigid robotic systems. Full article

Contemporary zoning-driven planning has been associated with traffic hazards, pollution and noise, loss of human scale and public space, socio-spatial separation, and rigid development patterns that impede incremental renewal. In response, the New Urbanism movement promotes traditional urbanism, with Form-Based Codes (FBCs) that regulate urban form and spatial structure, as a central tool. However, FBC practice remains concentrated in North America, and evidence from other contexts is limited. This study examines whether and how FBCs can be implemented within a hierarchical, centralized planning system. Using an exploratory case study approach, we analyzed an approved urban renewal plan for Ramat Verber in Petah Tikva, Israel. The study combines plan analysis, a conceptual FBC simulation, and expert consultations, with findings derived through an inductive analysis of implementation barriers. The FBC simulation showed that goals could be translated into more effective actionable provisions, whereas the statutory plan diluted objectives between vision and implementation. Identified barriers clustered into (1) legal and institutional constraints, (2) social and professional norms, and (3) management and coordination needs. We conclude that FBCs can be advanced without legislative change through municipal policy-level codes that standardize subsequent statutory local plans, supported by clear conversion protocols and existing urban renewal governance mechanisms. Full article

Self-powered monitoring systems capable of scavenging ambient mechanical energy are a highly desirable solution to eliminate the reliance on batteries and grid power in remote and distributed atmospheric sensing networks. However, the widespread adoption of such systems is severely hindered by the insufficient output power density of current energy harvesters, which struggle to simultaneously drive environmental sensors, data acquisition units, and wireless transmission modules. In this work, we report a highly integrated hybrid power generation system that couples a triboelectric nanogenerator (TENG) and an electromagnetic generator (EMG) to efficiently harvest low-frequency mechanical energy from the surroundings. Through systematic structural optimization and synergistic matching of the two transduction mechanisms, the device achieves an outstanding volumetric power density of 129.9 W·m⁻³, which represents one of the highest values ever reported for hybrid nanogenerators targeting self-powered environmental applications. The output characteristics of both the TENG and EMG units under varying load impedances are thoroughly characterized, revealing the optimal operating points for maximum power extraction. A tailored power management module, consisting of rectification, energy storage, and regulation circuits, is designed to convert the irregular alternating output into a stable direct-current supply. To demonstrate the practical viability of the system, we construct a complete self-powered atmospheric environment monitoring node, which integrates multiple environmental sensors, a data acquisition module, and a wireless transmission module. Driven exclusively by the hybrid TENG–EMG generator under ambient mechanical excitation, the node successfully performs real-time sensing, signal processing, and remote data communication without any external power input. This work not only provides a record-high power density among hybrid generators for environmental monitoring, but also establishes a feasible pathway toward maintenance-free, widely distributed, and truly autonomous atmospheric sensing networks. The presented strategy of maximizing volumetric power density through hybrid design and impedance engineering can be readily extended to other self-powered systems. Full article

In multi-coil, multi-load magnetically coupled resonant wireless power transfer (MCR–WPT) systems, the non-negligible cross-coupling among multiple resonators, including the transmitter (Tx), receiver 1 (Rx1), and receiver 2 (Rx2), introduces complex frequency-splitting behavior through the Tx–Rx1, Tx–Rx2, and Rx1–Rx2 coupling paths, severely constraining transmission efficiency and operational stability. In practical multi-receiver WPT applications, receiver-side cross-coupling is often unavoidable and may shift the maximum-power and maximum-efficiency points away from the designed resonant frequency. Clarifying this mechanism is therefore important for coil arrangement, impedance matching, and stable multi-load power delivery. This paper establishes an equivalent circuit model to derive analytical expressions for input impedance, load power, and efficiency. Based on this framework, the formation mechanism of frequency splitting under concurrent coupling paths is systematically investigated. The results indicate that dominant coupling paths dictate the positions and magnitudes of primary split peaks, while cross-coupling between receivers induces local modal reconfiguration and energy redistribution, leading to secondary or minor characteristic peaks. Both simulation and experimental results demonstrate that the coupling coefficient primarily governs the frequency-splitting trajectory, whereas load resistance predominantly modulates peak amplitudes. For $k=0.520$, the split-frequency peaks in the two-coil benchmark occur at $64.6 \mathrm{kHz}$ and $103.8 \mathrm{kHz}$, showing good agreement with the calculated modal frequencies. In the tri-coil dual-load system, pronounced power peaks around $63 \mathrm{kHz}$ and $112 \mathrm{kHz}$ further confirm the shift of the maximum-power transfer points under asymmetric coupling and loading conditions. Furthermore, under strong-coupling conditions, the maximum power transfer point shifts from the nominal resonant frequency toward the system’s inherent modal frequencies. This study elucidates the evolution of frequency splitting in tri-coil dual-load systems, providing a theoretical foundation for parameter optimization in multi-node WPT networks. Full article

In response to an actual super-synchronous oscillation event in an offshore wind farm, this paper proposes a full-topology real-time simulation (FTRT) scheme based on a self-developed universal link library execution device. The technical challenges of FTRT are systematically analyzed, and a complete modeling and implementation methodology is established. Using this scheme, a hardware-in-the-loop real-time simulation platform incorporating the same type of field controller is built, and the 70 Hz voltage oscillation is accurately reproduced. The analysis reveals that the submarine-cable-based transmission network possesses an inherent resonance point in the super-synchronous frequency band. The system stability boundary is then evaluated by comparing the phase–frequency characteristics of the grid-side and wind-farm impedances. Finally, oscillation suppression measures, including controller parameter unification, impedance reshaping, and SVG (Static Var Generator) deployment, are proposed and verified. The adopted FTRT technology overcomes the accuracy limitations of conventional offline simulations and simplified mechanism analyses, and the results can provide reliable, direct engineering decision support for the planning, design, and operation of offshore wind farms. Full article

Image deraining remains a critical challenge in computer vision, as rain streaks significantly degrade visual quality by introducing complex patterns that overlay scene content, impeding applications from autonomous driving to surveillance systems. Existing methods often struggle to balance global scene understanding with precise removal of rain streaks, resulting in either residual rain artifacts or over-smoothed textures. To address this, we propose MPINet, a Multi-Stage Progressive Illumination-Aware Network that integrates illumination awareness and global-context modeling, which is specifically designed for rain-removal tasks. Our architecture features a novel illumination-aware module that generates illumination maps to enhance robustness in the varying lighting conditions commonly encountered during rainy scenarios. The UniMetaFormer core adaptively incorporates global semantic information through dynamic transformations and attention mechanisms, effectively distinguishing between rain streaks and underlying image content. Inspired by MPRNet’s multi-stage restoration framework, our network employs a hierarchical approach with progressive patch-based processing and deep supervision across three stages, enabling efficient integration of our illumination-aware modules while maintaining reasonable model complexity. Experimental results verify the effectiveness of MPINet for rain-removal tasks, demonstrating superior capability in removing rain streaks of varying densities while preserving original image textures. On average, MPINet outperforms MPRNet by approximately 6.5% in terms of PSNR and 1.3% in terms of SSIM across all datasets. Full article

Fault location in distribution networks is challenged by dynamic topology changes and heterogeneous equipment. This paper proposes a Dynamic and Hierarchical Multi-Head Graph Attention Network (DHMGAT) that overcomes the limitations of static graph assumptions. Unlike methods that treat network structure as fixed or neglect line parameters, DHMGAT employs a hierarchical multi-head attention mechanism to encode topology dynamically. An Edge Feature Encoding Module fuses physical line attributes—impedance and switch states—directly into node embeddings. A Topology-Gated Pooling mechanism adapts to radial structural variations, and a Physics-Constrained Data Augmentation strategy ensures robustness under limited-sample and anomalous-data conditions. Evaluated on the IEEE 33-node and IEEE 123-node systems under comprehensive fault scenarios, DHMGAT achieves localization accuracies of 96.70% and 94.31%, respectively, with near-perfect calibration (ECE = 0.066). It maintains accuracy above 92% under high-noise conditions and N-1 topological reconfiguration, and above 88% under severe feature loss (up to 30% missing data), substantially outperforming conventional graph neural networks. Full article

This study examines the direct effects of R&D transfer and the sufficiency of financing for entrepreneurs on Technological Total Entrepreneurial Activity (TechTEA), as well as the mediating role of financing. The analysis employs a variance-based structural equation modeling approach (PLS-SEM) to explore causal relationships among the variables. Data are drawn from the Global Entrepreneurship Monitor (GEM), specifically the National Expert Survey (NES) and the Adult Population Survey (APS), covering 26 emerging economies. The findings reveal that R&D transfer has a significant positive effect on the sufficiency of financing available to entrepreneurs. However, R&D transfer shows a significant negative direct effect on TechTEA. In contrast, the sufficiency of financing has a positive impact on TechTEA, acting as an inconsistent mediator that neutralizes the negative direct friction of R&D and unlocks its positive indirect potential. The study demonstrates that Resource-Based View (RBV) principles operate in a fundamentally distinct manner within emerging economies. Raw technical knowledge (R&D transfer) and capital injections (sufficiency of financing) are not self-sufficient drivers of high-tech ventures in developing contexts. From a sustainability perspective, this dynamic suggests that institutional and ecosystem frictions can impede the Triple Bottom Line, as technological potential struggles to achieve the economic viability required for long-term societal impact. Consequently, achieving genuine ecosystem sustainability requires policymakers to shift away from isolated, supply-side resource injections. Future strategies must pivot toward comprehensive institutional governance, friction-reduction mechanisms, and cross-sector regulatory coordination to enable technological ventures to successfully scale and survive over time. Full article

In modern precision manufacturing systems, multilayer metal structures are key to achieving high-performance devices. However, during actual processing, they are highly prone to interlayer thermal stress concentration and defects such as interface delamination. To thoroughly elucidate and address this stress evolution issue, this study proposes a two-temperature model based on thermomechanical coupling. A thorough analysis of the thermal–mechanical coupling behavior of copper/aluminum two-layer metal films under femtosecond laser irradiation was conducted, investigating non-equilibrium heat transfer within the two-layer material and the resulting stress evolution. The results indicate that stress waves dynamically modulate the temperature distribution, revealing the critical role of thermo-mechanical coupling in energy transfer. Further studies show that stress waves undergo reflection and transmission at material interfaces, with their phases influenced by the acoustic impedance of the materials. When stress waves propagate from a medium with high acoustic impedance to one with low acoustic impedance, the phase of the transmitted wave remains unchanged, while the phase of the reflected wave reverses. Stress unloading occurs during the phase transition; tensile stress at the interface due to reflection can induce delamination, while horizontal stress tends to initiate cracks. This work contributes to the analysis of stress evolution during laser processing of multilayer metals. Full article

Spinel NiCo₂O₄ has emerged as a promising microwave absorption material due to its unique crystal structure and abundant defect sites. Nevertheless, its low intrinsic electrical conductivity leads to insufficient conductive loss and unsatisfactory high-frequency impedance matching, severely limiting the simultaneous realization of strong electromagnetic attenuation and broad absorption bandwidth. Fe³⁺ doping is an effective modification strategy for NiCo₂O₄ by virtue of its matched ionic radius and dual modulation capability for dielectric and magnetic properties. Herein, pristine and Fe-doped NiCo₂O₄ absorbers with different doping contents (4%, 6%, 8%) were fabricated via a hydrothermal–calcination route, and the correlation between Fe doping concentration, microstructure, electronic structure, electromagnetic properties, and microwave absorption performance was systematically investigated. Benefiting from moderate 6% Fe doping, the optimized F6 sample exhibits a refined porous nano-agglomerate structure, which provides abundant heterogeneous interfaces and pore channels for electromagnetic wave scattering and attenuation. The introduced oxygen vacancies and balanced Ni²⁺/Ni³⁺, Co²⁺/Co³⁺, and Fe²⁺/Fe³⁺ mixed-valence states effectively strengthen interfacial and dipole polarization, while the optimized electrical conductivity and magnetic properties synergistically boost conductive and magnetic losses. Owing to the dual-loss synergism and superior impedance matching (58% proportion of Δ < 0.4), the F6 sample achieves an excellent minimum reflection loss of −62.7 dB at 2.2 mm and a wide effective absorption bandwidth of 4.6 GHz. This work clarifies the intrinsic structure–performance mechanism of Fe-doped NiCo₂O₄, providing a reliable and feasible strategy for the design and preparation of high-performance spinel-type microwave-absorbing materials. Full article