Search Results (790)

Automated surface defect detection in steel manufacturing is pivotal for ensuring product quality, yet it remains an open challenge owing to the extreme heterogeneity of defect morphologies—ranging from hairline cracks and microscopic pores to elongated scratches and shallow dents. Existing approaches, whether classical vision pipelines or recent deep-learning paradigms, struggle to simultaneously satisfy the stringent demands of industrial scenarios: high accuracy on sub-millimeter flaws, insensitivity to texture-rich backgrounds, and real-time throughput on resource-constrained hardware. Although contemporary detectors have narrowed the gap, they still exhibit pronounced sensitivity–robustness trade-offs, particularly in the presence of scale-varying defects and cluttered surfaces. To address these limitations, we introduce MBY (MBDNet-Attention-YOLO), a lightweight yet powerful framework that synergistically couples the MBDNet backbone with the YOLO detection head. Specifically, the backbone embeds three novel components: (1) HGStem, a hierarchical stem block that enriches low-level representations while suppressing redundant activations; (2) Dynamic Align Fusion (DAF), an adaptive cross-scale fusion mechanism that dynamically re-weights feature contributions according to defect saliency; and (3) C2f-DWR, a depth-wise residual variant that progressively expands receptive fields without incurring prohibitive computational costs. Building upon this enriched feature hierarchy, the neck employs our proposed MultiSEAM module—a cascaded squeeze-and-excitation attention mechanism operating at multiple granularities—to harmonize fine-grained and semantic cues, thereby amplifying weak defect signals against complex textures. Finally, we integrate the Inner-SIoU loss, which refines the geometric alignment between predicted and ground-truth boxes by jointly optimizing center distance, aspect ratio consistency, and IoU overlap, leading to faster convergence and tighter localization. Extensive experiments on two publicly available steel-defect benchmarks—NEU-DET and PVEL-AD—demonstrate the superiority of MBY. Without bells and whistles, our model achieves 85.8% mAP@0.5 on NEU-DET and 75.9% mAP@0.5 on PVEL-AD, surpassing the best-reported results by significant margins while maintaining real-time inference on an NVIDIA Jetson Xavier. Ablation studies corroborate the complementary roles of each component, underscoring MBY’s robustness across defect scales and surface conditions. These results suggest that MBY strikes an appealing balance between accuracy, efficiency, and deployability, offering a pragmatic solution for next-generation industrial quality-control systems. Full article

This study explores the transformative potential of blockchain technology in overhauling conventional housing rental systems. It specifically addresses persistent issues, such as information asymmetry, fraudulent listings, weak Rental Agreements, and data breaches. A comprehensive review of ten academic publications highlights the architectural frameworks, underlying technologies, and myriad benefits of decentralized rental platforms. The intrinsic characteristics of blockchain—immutability, transparency, and decentralization—are pivotal in enhancing the credibility of rental information and proactively preventing fraudulent activities. Smart contracts emerge as a key innovation, enabling the automated execution of Rental Agreements, thereby significantly boosting efficiency and minimizing reliance on intermediaries. Furthermore, Decentralized Identity (DID) solutions offer a robust mechanism for securely managing identities, effectively mitigating risks associated with data leakage, and fostering a more trustworthy environment. The suitability of platforms such as Hyperledger Fabric for developing such sophisticated rental systems is also critically evaluated. Blockchain-based systems promise to dramatically increase market transparency, bolster transaction security, and enhance fraud prevention. They also offer streamlined processes for dispute resolution. Despite these significant advantages, the widespread adoption of blockchain in the rental sector faces several challenges. These include inherent technological complexity, adoption barriers, the need for extensive legal and regulatory adaptation, and critical privacy concerns (e.g., ensuring compliance with GDPR). Furthermore, blockchain scalability limitations and the intricate balance between data immutability and the necessity for occasional data corrections present considerable hurdles. Future research should focus on developing user-friendly DID solutions, enhancing blockchain performance and cost-efficiency, strengthening smart contract security, optimizing the overall user experience, and exploring seamless integration with emerging technologies. While current challenges are undeniable, blockchain technology offers a powerful suite of tools for fundamentally improving the rental market’s efficiency, transparency, and security, exhibiting significant potential to reshape the entire rental ecosystem. Full article

For the high-voltage AC port of power electronic transformer (HVAC-PET) with three-phase independent DC buses on the low-voltage side, a decoupling control strategy, concerning the influence of grid voltage imbalance, three-phase active-load imbalance, and high-order harmonic distortion, is proposed in this paper to simultaneously realize the functions of active power control, reactive power compensation, and active power filtering. In the outer power control loop, according to the distribution rule of decoupled average active power components in three phases, stability control for the sum of cluster average active power flows is realized by injecting positive-sequence active current, so as to control the average cluster voltage (i.e., the average of all the DC-link capacitor voltages), and by injecting negative-sequence current, the cluster average active power flows can be controlled individually to balance the three cluster voltages (i.e., the average of the DC-link capacitor voltages in each cluster). The negative-sequence reactive power component is considered to realize the reactive power compensation. In the inner current control loop, the fundamental and high-order harmonic components are uniformly controlled in the positive-sequence dq frame using the PI + VPIs (vector proportional integral) controller, and the harmonic filtering function is realized while the fundamental positive-sequence current is adjusted. Experiments performed on the 380 V/50 kVA laboratory HVAC-PET verify the effectiveness of the proposed control strategy. Full article

As the penetration of intermittent renewable energy sources continues to increase, ensuring reliable power system and frequency stability is of importance. Battery energy storage systems (BESSs) have emerged as an important solution to mitigate these challenges by providing essential grid support services. In this context, a state-of-charge (SOC)-frequency control strategy for grid-forming BESSs is proposed to enhance their role in stabilizing grid frequency and improving overall system performance. In the system, the DC-link capacitor is regulated to maintain the angular frequency through a matching control scheme, emulating the characteristics of the rotor dynamics of a synchronous generator (SG). Thereby, the active power control is implemented in the control of the DC/DC converter to further regulate the grid frequency. More specifically, the relationship between the active power and the frequency is established through the SOC of the battery. In addition, owing to the inevitable presence of differential operators in the control loop, a high-gain observer (HGO) is employed, and the corresponding parameter design of the proposed method is elaborated. The proposed strategy simultaneously achieves frequency regulation and implicit energy management by autonomously balancing power output with available battery capacity, demonstrating a novel dual benefit for sustainable grid operation. To verify the effectiveness of the proposed control strategy, a 0.5-Hz frequency change and a 10% power change are carried out through simulations and also on a hardware-in-the-loop (HIL) platform. Full article

Flexible energy sources such as electric vehicles and the battery energy storage systems of intelligent distribution systems can provide system-wide auxiliary services such as frequency regulation for power systems. This paper proposes an optimal method for operating the local energy community that is based on two-stage scheduling. Firstly, the basic concepts of the local energy community and flexible service are introduced in detail. Taking LEC as the reserve unit of artificial frequency recovery, an energy information interaction model among LEC, balance service providers, and the power grid is established. Then, a two-stage scheduling framework is proposed to ensure the rationality and economy of community energy scheduling. In the first stage, day-ahead scheduling uses the energy community management center to predict the up/down flexibility capacity that LEC can provide by adjusting the BESS control parameters. In the second stage, real-time scheduling aims at maximizing community profits and scheduling LEC based on the allocation and activation of standby flexibility determined in real time. Finally, the correctness of the two-stage scheduling framework is verified through a case study. The results show that the control parameters used in the day-ahead stage can significantly affect the real-time profitability of LEC, and that LEC benefits more in the case of low BESS utilization than in the case of high BESS utilization and non-participation in frequency recovery reserve. Full article

The detection of trace chemicals at low and ultra-low concentrations is critical for applications in environmental monitoring, medical diagnostics, food safety and other fields. Conventional detection techniques often lack the required sensitivity, specificity, or cost-effectiveness, making real-time, in situ analysis challenging. Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical tool, offering improved sensitivity through the enhancement of Raman scattering by plasmonic nanostructures. While noble metals such as Ag and Au are currently the reference choices for SERS substrates, fabrication methods should balance enhancement efficiency, reproducibility and scalability. In this study, we propose a novel approach for SERS substrate fabrication using reactive Aerosol Jet Printing (r-AJP) as an innovative additive manufacturing technique. The r-AJP process enables in-flight Ag seed reduction and nucleation of Ag nanoparticles (NPs) by mixing silver nitrate and ascorbic acid aerosols before deposition, as suggested by computational fluid dynamics (CFD) simulations. The resulting coatings were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses, revealing the formation of nanoporous crystalline Ag agglomerates partially covered by residual matter. The as-prepared SERS substrates exhibited remarkable SERS activity, demonstrating a high enhancement factor (10⁶) for rhodamine (R6G) detection. Our findings highlight the potential of r-AJP as a scalable and cost-effective fabrication strategy for next-generation SERS sensors, paving the way for the development of a new additive manufacturing tool for noble metal material deposition. Full article

The depletion of water resources caused by climate change and human activities is a pressing global issue. Lake Ereen is one of the ten natural landmarks of the Gobi-Altai of western Mongolia is included in the list of “important areas for birds” recognized by the international organization Birdlife. However, the construction of the Taishir Hydroelectric Power Station, aimed at supplying electricity to the western provinces of Mongolia, had a detrimental effect on the flow of the Zavkhan River, resulting in a drying-up and pollution of Lake Ereen, which relies on the river as its water source. This study assesses the pollution levels in Ereen Lake and determines the feasibility of its rehabilitation by redirecting the flow of the Zavkhan River. Field studies included the analysis of water quality, sediment contamination, and the composition of flora. The results show that the concentrations of ammonium, chlorine, fluorine, and sulfate in the lake water exceed the permissible levels set by the Mongolian standard. Analyses of elements from sediments revealed elevated levels of arsenic, chromium, and copper, exceeding international sediment quality guidelines and posing risks to biological organisms. Furthermore, several species of diatoms indicative of polluted water were discovered. Lake Ereen is currently in a eutrophic state and, based on a water quality index (WQI) of 49.4, also in a “polluted” state. Mass balance calculations and box model analysis determined the period of pollutant replacement for two restoration options: drying-up and complete removal of contaminated sediments and plants vs. dilution-flushing without direct interventions in the lake. We recommend the latter being the most efficient, eco-friendly, and cost-effective approach to rehabilitate Lake Ereen. Full article

Isoflavones are the main phenolic compounds of soybean that affect its biological activity. The quantity of these valuable compounds extracted from plant material can significantly vary, influenced by the chosen extraction method and the specific extractants employed. Moreover, in cosmetics and pharmacy, the application of non-toxic, eco-friendly solvents is very important. This study aimed to develop the best mixture of extractants to maximize the recovery of individual isoflavones from soybean seeds by optimization of the proportion of three components: ethanol, water, and propanediol. The design of experiments (DOE) method was strategically employed. The extracts were obtained through accelerated solvent extraction and meticulously analyzed for isoflavone content using advanced electrospray ionization–time of flight–mass spectrometry (ESI-TOF-MS) profiling. The predominant isoflavones were daidzin, genistin, malonylgenistin, malonyldaidzin, and malonylglycitin. Our experiment demonstrated that employing three extractants in a balanced 1:1:1 v/v/v ratio resulted in the highest isolation of isoflavones compared to all other mixtures tested. Nevertheless, a detailed exploration of approximate values and utility profiles revealed a more effective composition for extraction efficiency. This optimal mixture features 32.8% ethanol, 39.2% water, and 27.8% propanediol, maximizing the yield of isoflavones from soybean seeds. The innovative use of mixture design and triangular response surfaces has proven to be a powerful approach for developing this superior three-component extraction mixture. This innovative approach not only enhances extraction efficiency but also paves the way for improved processing methods in the industry. Full article

Background: This study aimed to investigate how barbell type (elastic vs. inelastic) and lifting speed affect postural stability and lower limb muscle activation during the single-leg deadlift (SLDL), a common unilateral exercise in rehabilitation and performance training. Methods: Twenty-seven healthy adults performed SLDLs using both elastic and inelastic barbells under three lifting speeds (normal, fast, and power). Center of pressure (COP) displacement in the anterior–posterior (AP) and medial–lateral (ML) directions and electromyographic (EMG) activity of eight lower limb muscles were measured. Results: COP displacement was significantly lower when using elastic barbells (AP: F = 6.509, p = 0.017, η² = 0.200, ω² = 0.164; ML: F = 9.996, p = 0.004, η² = 0.278, ω² = 0.243). EMG activation was significantly higher for the gluteus medius, biceps femoris, semitendinosus, and gastrocnemius (all p < 0.01), especially under power conditions. Significant interactions between barbell type and speed were found for the gluteus medius (F = 13.737, p < 0.001, η² = 0.346, ω² = 0.176), semitendinosus (F = 6.757, p = 0.002, η² = 0.206, ω² = 0.080), and tibialis anterior (F = 3.617, p = 0.034, η² = 0.122, ω² = 0.029). Conclusions: The findings suggest that elastic barbells improve postural control and enhance neuromuscular activation during the SLDL, particularly at higher speeds. These results support the integration of elastic resistance in dynamic balance and injury prevention programs. Full article

The non-uniform thermal distribution in the active neutral-point clamped (ANPC) topology causes significant thermal gradients during high-power operation, restricting its use in large-capacity power conversion systems like variable-speed pumped storage. This study introduces a novel hybrid fundamental frequency modulation strategy. Through a dynamic allocation mechanism based on a reference signal, this strategy alternates inner and outer power switches at the fundamental frequency, ensuring balanced switching frequency across devices. Consequently, it effectively mitigates the inherent loss imbalance in conventional ANPC topologies. Quantitative analysis using a power device loss model shows that, compared to conventional carrier phase-shift modulation, the proposed method reduces total system losses by 39.98% and improves the loss-balancing index by 18.27% over inner-switch fundamental frequency modulation. A multidimensional validation framework, including an MW-level hardware platform, numerical simulations, and test data, was established. The results confirm the proposed strategy’s effectiveness in improving power device thermal balance. Full article

To address energy shortages and achieve carbon peaking/neutrality, this study develops a distributed renewable-based integrated energy system (IES) for rural active zero-energy buildings (ZEBs). Energy consumption patterns of typical rural houses are analyzed, guiding the design of a resource-tailored IES that balances economy and sustainability. Key equipment capacities are optimized to achieve net-zero/zero energy consumption targets. For typical daily cooling/heating/power loads, equipment output is scheduled using a dual-objective optimization model minimizing operating costs and CO₂ emissions. Results demonstrate that: (1) Net-zero-energy IES outperforms separated production (SP) and full electrification systems (FES) in economic-environmental benefits; (2) Zero-energy IES significantly reduces rural building carbon emissions. The proposed system offers substantial practical value for China’s rural energy transition. Full article

Driven by the rapid advancement of Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) technologies, improving power quality and system stability during charging and discharging has become a research focus. To address this, this paper proposes a Model Predictive Control (MPC) strategy for Active Neutral-Point Voltage Balancing (ANPVB) in a single-phase three-level converter used in on-board V2G chargers. Traditional converters rely on passive balancing using redundant vectors, which cannot ensure neutral-point (NP) voltage stability under sudden load changes or frequent power fluctuations. To solve this issue, an auxiliary leg is introduced into the converter topology to actively regulate the NP voltage. The proposed method avoids complex algorithm design and weighting factor tuning, simplifying control implementation while improving voltage balancing and dynamic response. The results show that the proposed Model Predictive Current Control-based ANPVB (MPCC-ANPVB) and Model Predictive Direct Power Control-based ANPVB (MPDPC-ANPVB) strategies maintain the NP voltage within ±0.7 V, achieve accurate power tracking within 50 ms, and reduce the total harmonic distortion of current (THDi) to below 1.89%. The proposed strategies are tested in both V2G and G2V modes, confirming improved power quality, better voltage balance, and enhanced dynamic response. Full article

Under the guidance of carbon peaking and carbon neutrality goals, the power industry is transitioning toward environmentally friendly practices. With the increasing integration of intermittent renewable energy sources (RES) and the enhanced self-regulation capabilities of grids, traditional distribution networks (DNs) are transitioning into active distribution networks (ADNs). To fully exploit the synergistic optimization potential of the “source-grid-load-storage” system in electricity-carbon coupling scenarios, leverage user-side flexibility resources, and facilitate low-carbon DN development, this paper proposes a low-carbon optimal scheduling strategy for ADN incorporating demand response (DR) priority. Building upon a bi-directional feedback mechanism between carbon potential and load, a two-layer distributed robust scheduling model for DN is introduced, which is solved through hierarchical iteration using column and constraint generation (C&CG) algorithm. Case study demonstrates that the model proposed in this paper can effectively measure the priority of demand response for different loads. Under the proposed strategy, the photovoltaic (PV) consumption rate reaches 99.76%. Demand response costs were reduced by 6.57%, and system carbon emissions were further reduced by 8.93%. While accounting for PV uncertainty, it balances the economic efficiency and robustness of DN, thereby effectively improving system operational safety and reliability, and promoting the smooth evolution of DN toward a low-carbon and efficient operational mode. Full article

Plant secondary metabolites possess significant antioxidant and anti-inflammatory properties, but their complex polypharmacological mechanisms remain poorly understood. Network pharmacology has emerged as a powerful systems-level approach for investigating multi-target interactions of natural products. This review systematically analyzes network pharmacology applications in elucidating the antioxidant and anti-inflammatory mechanisms of plant metabolites, evaluating concordance between computational predictions and experimental validation. A comprehensive literature search was conducted across major databases (2015–2025), focusing on network pharmacology studies with experimental validation. Analysis revealed remarkable convergence toward common molecular mechanisms, despite diverse chemical structures. For antioxidant activities, the Nrf2/KEAP1/ARE pathway emerged as the most frequently validated mechanism, along with PI3K/AKT, MAPK, and NF-κB signaling. Anti-inflammatory mechanisms consistently involved NF-κB, MAPK, and PI3K/AKT pathways. Key targets, including AKT1, TNF-α, COX-2, NFKB1, and RELA, were repeatedly identified. Flavonoids, phenolic acids, and terpenoids dominated as bioactive compounds. Molecular docking studies supported predicted interactions, with experimental validation showing good concordance for pathway modulation and cytokine regulation. Network pharmacology provides a valuable framework for investigating the complex bioactivities of plant metabolites. The convergence toward common regulatory hubs suggests that natural compounds achieve protective effects by modulating central nodes that integrate redox balance and inflammatory responses. Despite limitations, including database dependency, integrating network pharmacology with experimental validation accelerates mechanistic understanding in natural-product drug discovery. Full article

High permeability distributed photovoltaic (PV) access to the distribution network makes it easy to cause frequent overvoltage of the system. However, the traditional centralized optimization scheduling method is difficult to meet the real-time voltage regulation requirements due to high communication costs. In this regard, this paper proposes a distributed fast voltage regulation method for energy storage systems (ESSs) in distribution networks. Firstly, to reduce the communication burden, the distribution network cluster is divided according to the electrical distance modularity index. Secondly, the distributed control model of active distribution network with the goal of voltage recovery and ESS power balance is established, and a distributed controller is designed. The feedback-control gains are optimized to improve the convergence rate. Finally, the IEEE33 bus system and IEEE69 bus system are applied for simulation. The results show that the proposed distributed optimal control method can effectively improve the voltage level of the distribution network under the condition of ensuring the ESS power balance. Full article