Search Results (21,661)

Wastewater-based epidemiology (WBE) has emerged as a powerful approach for population-level monitoring of chemical exposure, health status, and disease transmission by analysing wastewater. Although chromatographic and molecular techniques remain the gold standard in WBE, their high cost, infrastructural demands, and limited suitability for decentralized and real-time monitoring motivate the development of complementary sensing technologies. In this context, optical (bio)sensors, particularly fluorescence-based platforms, have attracted increasing attention due to their high sensitivity, rapid response, and potential for on-site monitoring. This review discusses recent advances in fluorescent optical (bio)sensors for WBE, with a particular focus on carbon dots (CDs), including waste- and biomass-derived CDs produced via green synthesis as well as CDs obtained from commercial chemicals. The applicability of CD-based sensors to wastewater-relevant analytes is evaluated, highlighting current achievements, as well as existing limitations and challenges related to real-sample validation and the translation of these platforms into robust, field-deployable systems for their implementation in sustainable wastewater monitoring and public health surveillance. Full article

The stochastic and intermittent characteristics of renewable energy pose significant challenges to energy utilization and power system stability. The reversible solid oxide cell (RSOC), as an emerging multi-energy conversion technology, exhibits high efficiency in both electrolysis and power generation modes, offering a promising solution to renewable energy integration and energy supply issues. However, RSOC performance degrades over time, and its average efficiency decay rate directly influences capacity investment decisions and day-ahead scheduling strategies. To address this, a comprehensive energy system model considering RSOC capacity is developed, with a detailed representation of each subsystem. A bi-level optimization framework is then proposed, where the upper level minimizes system investment and operation costs, and the lower level optimizes day-ahead scheduling costs. The model explicitly accounts for RSOC efficiency degradation and lifetime attenuation. Particle swarm optimization is applied to determine the optimal capacity configuration. Case studies demonstrate that the proposed model enhances system economics, promotes multi-energy complementarity, and prolongs RSOC lifetime, providing theoretical and technical support for the planning and operation of integrated energy systems with RSOC. Full article

This paper presents a compact output-stage current-limiting architecture intended for reliable overcurrent protection in CMOS analog and mixed-signal circuits. In modern integrated systems, the output stages of blocks such as operational amplifiers, drivers, buffers, and reference circuits may be exposed to overload conditions, low-impedance loads, or short circuits that can lead to excessive power dissipation and device degradation. The proposed architecture employs scaled replicas of the output transistors together with local negative feedback to sense the delivered load current and independently limit both sinking and sourcing currents. The circuit is demonstrated by integration into a two-stage folded-cascode operational amplifier with a class-AB output stage and evaluated through circuit-level simulations in 130 nm CMOS technology. The results confirm a well-defined current limit across the supply and temperature corners that are relevant to high-reliability applications, spanning 2 V and 5 V supplies and a temperature range from −55 °C to 175 °C. The proposed current-limiting scheme constrains both pull-down and pull-up currents to approximately 9–12 mA across the investigated operating domain. Monte Carlo analysis further shows bounded dispersion and symmetric single-mode distributions, indicating predictable operation under device mismatch. These results demonstrate that the proposed architecture provides a compact and scalable solution for deterministic current limiting in reliability-critical CMOS systems. Full article

To systematically review the research progress, methodological frameworks, and application characteristics of energy management technologies for All-Electric Ships (AES), this review provides a comprehensive and critical survey of studies published over the past two decades, following the technical trajectory of multi-energy coupling–multi-objective optimization–engineering-oriented operation. Based on a structured analysis of representative literature, the review first elucidates the overall architecture and operational characteristics of AES energy systems from a system-level perspective, highlighting their core advantages as “mobile microgrids” in terms of multi-energy coordination and dispatch flexibility. On this basis, a structured classification framework for energy management strategies is established, and the theoretical foundations, applicable scenarios, and engineering feasibility of rule-based, optimization-based, uncertainty-aware, and intelligent/data-driven approaches are comparatively reviewed and discussed. Furthermore, focusing on key research themes—including multi-energy system optimization, ship–port–microgrid coordinated operation, battery safety and lifetime-oriented management, and real-time energy management strategies—the review synthesizes the main findings and engineering validation progress reported in recent studies. The analysis indicates that, with the integration of fuel cells, renewable energy sources, and Hybrid Energy Storage Systems (HESS), energy management for AES has evolved from a single power allocation problem into a system-level optimization challenge involving multiple time scales, multiple objectives, and diverse sources of uncertainty. Optimization-based and Model Predictive Control (MPC) methods have shown promising performance in many simulation and pilot-scale studies for improving energy efficiency and emission performance, while robust optimization and data-driven approaches offer useful support for enhancing operational resilience, prediction capability, and decision quality under complex and uncertain conditions. These advances collectively contribute to the environmental, economic, and operational sustainability of maritime transport by reducing greenhouse gas emissions, extending equipment lifetime, and enabling efficient integration of renewable energy sources. At the same time, the current literature still reveals important limitations related to model fidelity, data availability, validation maturity, and the gap between methodological sophistication and practical deployment. Overall, an increasingly structured but still evolving research framework has emerged in this field. Future research should further strengthen ship–port–microgrid coordinated energy management frameworks, develop system-level optimization methods that integrate safety constraints and uncertainty, and advance intelligent Energy Management Systems (EMS) oriented toward sustainable zero-carbon shipping objectives. Full article

High-power-density LEDs can achieve many functions that are difficult for traditional light sources and conventional LEDs to realize, pushing the semiconductor lighting technology chain to a new level. Increasing the number of chips is an effective approach to improving the light output capability of LED devices. In this study, five high-power-density LED devices with different chip numbers (4, 9, 16, 25, and 64 chips) were fabricated using the same blue LED chips, and the effects of chip number on the light output capability, spatial light distribution characteristics, and spatially correlated color temperature distribution characteristics of high-power-density LED devices were systematically investigated. The temperature distribution characteristics of the internal chips were further analyzed in combination with infrared thermal imaging results. The results show that increasing the chip number significantly enhances the total light output capability of the device; however, due to the influence of thermal coupling among chips, the saturation current and saturated luminous intensity of devices with different chip numbers are not proportional to the chip number. Increasing the number of chips in the device does not alter the intrinsic spatial emission pattern. Under optical saturation conditions, the luminous intensity distribution curves of all five devices exhibit Lambertian spatial light distribution characteristics. In terms of correlated color temperature, the CCT of all devices increases with increasing current per chip, and devices with more chips exhibit higher CCT values and a faster increasing trend. The spatial CCT distribution results show that the correlated color temperature of the device reaches its maximum in the normal direction, decreases with increasing testing angle, and exhibits good spatial symmetry. The thermal imaging results show that devices with more chips exhibit higher average chip temperatures and a relatively more uniform temperature distribution, which improves the spatial CCT uniformity of the device to some extent. Full article

Polyolefin bonding technologies with metal foils are extensively employed in various sectors, particularly in automotive, electronics, and aerospace industries. This research examined the innovative electromagnetic joining of polyolefins to aluminum by evaluating the behavior of hot-melt adhesives derived from polyolefins containing metallic particles. The study aimed at establishing the specific absorption rate (SAR, expressed in W/kg) via electromagnetic simulation using CST Studio Suite software. It was observed that, regardless of particle size, Al was the most efficient particle, while the distribution of particles has a negligible impact on Total SAR values. The most significant beneficial effect of the inserts on the absorption capacity of the hot-melt material is primarily observed with a particle size of 1 μm. When connecting polyolefins to aluminum, the power loss density and SAR values exceed those for bonding polyolefins to polyolefins by at least 10 times, owing to aluminum’s conductive properties, which influence the absorption of additional energy in the hot melt mass, likely due to the Salisbury screen effect generated by the bonding arrangement. For hot melts made from polyethylene, a higher frequency of 5.8 GHz is suggested, which is a newly approved frequency used in advanced industrial applications. This positively impacts the effectiveness and viability of the bonding process of polyolefins to aluminum, resulting in reduced exposure times and/or decreased microwave exposure power. It was observed that the hot melts derived from HDPE and PP yielded greater SAR values. Conversely, the SAR values increase when aluminum is attached to HDPE. As a result, the strongest bond of polyolefins to Al occurs when connecting HDPE to Al using HDPE-based hot melts. The proposed simulation methodology may offer considerable improvement in evaluating the efficacy of bonding technology for dissimilar materials subjected to electromagnetic energy Full article

This paper presents a comprehensive life-cycle analysis of distribution transformers, based on realized measurements of the increased power losses as a result of their long-term service under real-world conditions. The study is based on aggregated measured data from extensive fleets of oil-immersed distribution transformers characterized by diverse designs, manufacturing vintages, and service lives. The evolution of no-load losses and short-circuit losses is analyzed as a function of operational duration, structural characteristics, and the specific technologies employed for windings and magnetic core construction. Statistical models describing the variation in these losses are presented, highlighting the limitations of the static assumptions commonly utilized in power distribution network planning. On this basis, an approximation of the time evolution of the transformer’s total power and energy losses is proposed as appropriate for implementation in a life-cycle analysis model. Furthermore, the impacts of thermal loading and abnormal operating conditions—such as unbalanced loads, frequent short circuits, and repeated overheating of the transformer oil—are analyzed as drivers of accelerated transformer aging. These effects are integrated into a unified life-cycle framework, enabling the quantitative assessment of loss variations and their associated operational expenditures (OPEX). A numerical example is provided to evaluate the cost-effectiveness of “repair vs. replacement” scenarios, utilizing a discounted cash flow analysis that incorporates a carbon component. The findings establish a methodological foundation for a broader assessment of technical condition and energy performance, identifying the optimal intervention point for repair or replacement to support decision-making for Distribution System Operators (DSOs) amidst increasing requirements for efficiency and decarbonization. Full article

Partial discharge detection is a key technology for maintaining the normal operation of industrial power equipment. Oil-impregnated paper bushings are crucial components connecting transformers to the power grid. Insulation degradation leads to partial discharge, posing a significant threat to power system operation. Developing on-line diagnostics for partial discharge in transformer bushings and automatic identification of insulation defects can effectively protect system and personnel safety. Due to limitations of small sample sizes and lightweight networks, this study combines interpolation techniques with a lightweight convolutional neural network to improve identification accuracy. This network uses interpolation to maintain the undistorted sample signal from the initial input and reduces training defects from a small sample size. The neural network extracts partial discharge features to determine the defect type and its cause. This study uses a publicly available dataset with discharge signals from generators. Although from a different source from the discharge signals generated by oil-impregnated paper bushings, the signal distribution is similar, allowing for a fair analysis and providing a reference for evaluating discharge signals obtained from oil-impregnated paper bushings or other discharge devices. The experimental results show that the accuracy of this network improved from 97% to over 99% while maintaining low computational complexity and excellent real-time performance. Furthermore, this network was implemented and validated on existing industrial equipment. Full article

Optical-fibre daylighting systems (OFDS) harvest solar energy as a renewable lighting resource by delivering sunlight deep into green buildings. This emerging technology for sustainable infrastructure reduces electric-lighting demand; however, reported performance is difficult to compare across heterogeneous designs, metrics, and validation practices. Therefore, a PRISMA 2020–reported systematic literature review (SLR) of OFDS studies from three databases (Google Scholar, Scopus, and Web of Science; 2000–2025) was conducted, synthesising primary research that quantifies system- or component-level performance, with a focus on (i) plastic optical fibre (POF) transmission characteristics; and (ii) POF-based illuminance model validation. After de-duplication and screening, 106 primary studies were included, and two meta-analyses were performed where data were harmonised from 29 studies in total. Across reported POF configurations, attenuation ranged from 150 to 800 dB/km with a pooled mean of 332.8 dB/km, corresponding to a mean 1 m transmission of 92.7% and median design length scales of ∼3.7 m for 80% transmission and ∼11.6 m to half-power. Across illuminance validation datasets, models showed high linear agreement with experimental measurements (coefficient of determination ($R^2$) = 0.99; slope = 0.99) but typically underpredicted illuminance (geometric mean ratio = 1.16; mean absolute error (MAE) = 27.3 lux; mean absolute percentage error (MAPE) = 17.6%). These findings underscore the need for a standardised evaluation framework, including consistent metric definitions, robust uncertainty reporting, and reusable validation datasets to enable variance-weighted synthesis, while also identifying short-run POF routing as a key lever for improving system efficiency. In addition to providing the OFDS research agenda, this study serves as a roadmap for the industrial development of daylighting systems for green buildings based on harvesting solar energy, with its novelty lying in the PRISMA-guided evidence synthesis and quantitative meta-analytic consolidation of POF transmission and illuminance-validation performance. Full article

The prehistoric and historic Greek populations have a long and glorious history and could teach us significant lessons relevant to water resources and their management. Most Greek civilizations lived in harmony with the environment, with a profound understanding of environmental sustainability. The Minoan era, considered as Pax Minoica (or Minoan peace), was a time when palaces and other living places did not have defensive walls; in that time, human rights and power without a military aristocracy developed. During that time, hydro-structures with a high degree of security, which remained in operation for millennia, were developed, most of them established in predominantly arid areas for reasons of security, protection, and public health. The study presents important elements of the development and progress of these technological achievements provided by ancient civilizations throughout the prehistoric to modern period, in the context of revealing and highlighting potential lessons to understand and address current critical issues in the management of water resources. Furthermore, the methodology used and the technological structural advancement of water works, their infrastructure durability, and early water law principles are considered. Many modern systems are designed for operational lifespans of 50–100 years, whereas several ancient Greek hydraulic structures remained functional for centuries by relying on renewable natural resources—reflecting a fundamentally different design philosophy centered on longevity and robustness. Thus, terms such as “sustainability” and “water security/safety”, first taught by ancient civilizations, need to be reconsidered and adopted again nowadays to inspire policies, strategies, and actions against the increasing challenges. Full article

The detection of sulfur hexafluoride (SF₆) decomposition products is critical for diagnosing insulation faults in gas-insulated switchgear (GIS). In this study, a vanadium-doping strategy was incorporated into the graphene/MoS₂ (GM) heterojunction to design a vanadium-doped graphene/MoS₂ (GMV) heterojunction material. Leveraging first-principles density functional theory (DFT), the adsorption behaviors of five characteristic SF₆ and its decomposition gases (H₂S, SO₂, SOF₂, SO₂F₂) on intrinsic GM and GMV were systematically investigated to evaluate their potential for gas sensing applications. Computational results reveal that intrinsic GM exhibits only weak physical adsorption toward all target molecules, with low adsorption energies and negligible charge transfer, which fails to meet practical application requirements. In contrast, GMV demonstrates significantly enhanced adsorption energies for H₂S, SO₂, and SOF₂ at vanadium sites (with a maximum value of −0.388 eV for SO₂) and shorter adsorption distances, while SO₂F₂ and SF₆ preferentially adsorb near electron-deficient carbon regions. Intrinsic GMV displays semimetallic properties, with a Fermi level at 0.126 eV and a band gap of 0.0017 eV. Upon adsorption of H₂S, SOF₂, SO₂F₂, or SF₆, the Fermi level undergoes a moderate shift (ranging from −1.083 eV to +0.349 eV), with minimal changes in the band gap. Conversely, SO₂ adsorption induces a substantial downward shift of the Fermi level to −1.732 eV, accompanied by the emergence of a sharp partial density of states (PDOS) peak near the Fermi level (0–1.5 eV), indicating strong orbital coupling and significant charge transfer. Furthermore, recovery times calculated using classical formulas show that at room temperature and a frequency of 1 × 10⁶ Hz, the recovery time of GMV for SO₂ is 2.43 s, outperforming the other four gases and satisfying practical gas sensing requirements. Through comprehensive analysis of adsorption distances, electronic structure changes, and recovery times, GMV exhibits higher selectivity toward SO₂. Thus, GMV can serve as a sensing material for detecting GIS insulation faults associated with elevated SO₂ concentrations, offering a viable strategy for advancing online monitoring technologies in power systems. Full article

The increasing integration of renewable energy sources increases the variability and uncertainty of power systems, requiring advanced prediction-based control strategies. This paper proposes an integrated AutoML–MPC framework for a hybrid renewable energy system (HRES) combining solar and wind generation, biomass, battery energy storage, and a hydrogen chain (electrolyzer and fuel cell). Short-term load and generation forecasts are made using H2O AutoML models, and the energy flow allocation is optimized using model-based control (MPC) formalized in the form of mixed-integer linear programming (MILP). The objective function minimizes electricity imports from the grid and the associated ${\mathrm{C}\mathrm{O}}_2$ emissions, subject to technological constraints. The results obtained showed a clear distribution of short-term (battery) and long-term (hydrogen) storage functions in time: during periods of excess generation, the electrolyzer operated close to nominal mode, and in the deficit phase, the fuel cell was activated, reducing the need for grid imports. The battery ensured fast short-term balancing, while the hydrogen system compensated for the longer-term energy shortage. The forecast models were characterized by high accuracy ($R^2>0.98$), which allowed for reliable planning of energy flows over the MPC horizon. The proposed methodology allows for effective coordination of storage technologies of different time scales, maximum use of renewable generation and reducing the system’s dependence on the external grid. Full article

Fuel cell technologies are increasingly investigated as alternatives to conventional auxiliary diesel generators in order to enhance shipboard energy efficiency and reduce greenhouse gas emissions. This study presents a unified and uncertainty-driven system-level assessment of solid oxide fuel cell (SOFC) and proton exchange membrane fuel cell (PEMFC) systems operating as auxiliary power sources on a 200 m bulk carrier. Both technologies are evaluated under identical vessel characteristics, operating profiles, auxiliary load levels (360–600 kW), and cost assumptions, and are benchmarked directly against a conventional three–diesel-generator configuration. A modular numerical framework is developed to model propulsion–auxiliary interactions for ship speeds between 10 and 14 knots. SOFC systems are assessed using grey, bio-derived, and green natural gas pathways, while PEMFC systems are examined under grey, blue, and green hydrogen supply routes. Performance indicators include annual fuel consumption, carbon dioxide (CO₂) emission reduction, net present value (NPV), internal rate of return (IRR), payback period (PBP), and marginal abatement cost (MAC). Economic uncertainty is explicitly embedded in the framework through Monte Carlo simulation, where fuel prices (±20%) and capital costs are sampled across defined ranges, generating probabilistic distributions rather than single deterministic estimates. This uncertainty-centred approach enables assessment of robustness, downside risk, and probability of profitability. Results show that replacing a single operating 600 kW diesel generator with fuel cell systems reduces auxiliary fuel energy demand by 25–35% for SOFC and approximately 15–25% for PEMFC relative to the diesel benchmark. Annual CO₂ reductions range from 1.1 to 1.3 kt for SOFC systems and 1.8–2.8 kt for PEMFC configurations. Under grey fuel pathways, median NPVs reach approximately 2–4.5 M$ for SOFC and 9–17 M$ for PEMFC as load increases, with IRRs exceeding 15% and 30%, respectively. Transitional pathways exhibit narrower margins, while renewable pathways remain more sensitive to fuel price variability. The findings demonstrate that fuel pathway cost dominates lifecycle outcomes under uncertainty and that hydrogen-based PEMFC systems exhibit the strongest economic resilience within the examined market ranges. The framework provides structured, uncertainty-aware decision support and establishes a foundation for integration into model-based systems engineering (MBSE) environments for early stage ship energy system design. Full article

The current literature on electrical system maintenance highlights three technology domains—Building Information Modeling (BIM), Digital Twin (DT), and extended reality (XR)—that have independently demonstrated strong potential for improving lifecycle information management, predictive analytics, and operational support. However, their convergence remains largely underexplored, particularly in electrical system maintenance. This paper provides a structured review of BIM–DT–XR convergence in electrical system lifecycle management, examining their roles across lifecycle phases and their integration through literature synthesis and cross-domain implementation evidence. BIM is analyzed as a basis for modeling and integrating facility management with electrical asset lifecycles; DT as a framework for dynamic system representation and applications in electrical and power systems; and XR as a means of visualizing and interacting with BIM-DT environments. Cross-domain implementation evidence from an industrial electrical facility and a tertiary smart-building pilot shows that BIM–DT–XR integration is technically feasible at pilot scale. However, the analysis identifies five structural integration gaps: semantic misalignment between building-oriented IFC and grid-oriented CIM ontologies; fragmented standard adoption; inconsistent data governance and naming practices; validation approaches focused on syntactic rather than dynamic model fidelity; and the separation of XR visualization from predictive DT capabilities. The implementation evidence further indicates that real-world deployment remains constrained by data quality limitations, integration complexity, cost factors, and interoperability with legacy systems. The review concludes that, despite the maturity of individual technologies, their effective application depends on advances in semantic alignment, lifecycle data governance, validation of dynamic models, and scalable integration frameworks, enabling the transition toward integrated, interoperable, and lifecycle-aware infrastructures for electrical system maintenance. Full article

The use of solar photovoltaic technology is among the most promising approaches to achieving SDG7—Affordable and Clean Energy—which seeks to provide modern, reliable, sustainable, and efficient energy for everyone globally, especially in developing areas with high irradiation, where both energy access and decarbonization are major challenges. South Khorasan Province, Iran, is one of the most highly irradiated regions in the world. However, despite the abundance of solar resources, most previous research in Iran on solar potential has focused on technical potential, with little emphasis on actual energy consumption patterns and economic viability. To the best of our knowledge, this is the first demand-driven assessment at the county level and the first national-scale implementation of the MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution) method for selecting solar energy sites in Iran. A spatially explicit integrated framework based on GIS-MARCOS was established for each of the eleven counties of South Khorasan Province, and five benefits were used as criteria (solar irradiance, population, per capita electrical consumption in residential, industrial, and agricultural sectors). Objective weights were calculated using Shannon’s Entropy. The analysis indicates that residential electricity demand emerges as the most influential factor in the prioritization process. Therefore, the counties of Birjand, Qaenat, and Tabas were identified as top priority counties, while counties with high irradiation levels but low demand (for example, Boshruyeh) received the least priority. These results clearly indicate the need to transition from irradiation-based to demand-based planning to minimize transmission losses and maximize the ability to integrate solar-generated electricity into the electric power grid. This proposed methodology provides a transferable decision-support tool for other high-irradiation, demand-heterogeneous regions around the globe. Full article