Search Results (5,310)

The increasing penetration of renewable energy into power systems has intensified transient power quality (PQ) disturbances, demanding efficient detection and classification methods to enable timely operational decisions. This paper introduces a hybrid framework combining an Improved Adaptive S-Transform (IAST) with a Random Forest (RF) classifier to address these challenges. The IAST employs a globally adaptive Gaussian window as its kernel function, which automatically adjusts window length and spectral resolution based on real-time frequency characteristics, thereby enhancing time–frequency localization accuracy while reducing algorithmic complexity. To optimize computational efficiency, window parameters are determined through an energy concentration maximization criterion, enabling rapid extraction of discriminative features from diverse PQ disturbances (e.g., voltage sags and transient interruptions). These features are then fed into an RF classifier, which simultaneously mitigates model variance and bias, achieving robust classification. Experimental results show that the proposed IAST–RF method achieves a classification accuracy of 99.73%, demonstrating its potential for real-time PQ monitoring in modern grids with high renewable energy penetration. Full article

In power distribution networks, the growing integration of renewable energy sources (RESs) presents a challenge for the electricity system and its operators, who need to make the energy sector more flexible and resilient. In this context, this paper proposes a novel flexibilization service for the distribution system leveraging the role of renewable energy communities (RECs), an emerging entity with the potential to facilitate the sustainable energy transition through Virtual Islanding operation. The concept of Virtual Islanding is investigated in the paper and a methodology for its validation is developed. Its effectiveness is then assessed using an IEEE-standard 33-node network with significant penetration of RESs, considering the presence of multiple RECs to prove its benefits on electrical distribution networks. The results showcase the advantages of the VI paradigm both from technical and sustainability viewpoint. Full article

Inflammatory arthritis (IA) is a chronic condition marked by joint dysfunction and pain, posing significant challenges for effective drug delivery. This study separated Perilla frutescens leaf-derived exosome-like nanovesicles (PFE) to effectively penetrate the stratum corneum barrier. These nanovesicles and indomethacin (IND) were subsequently developed into a nanogel designed for topical drug delivery systems (PFE-IND-GEL). PFE exhibited a typical vesicular structure with a mean diameter of 98.4 ± 1.3 nm. The hydrodynamic size and zeta potential of PFE-IND-GEL were 129.6 ± 5.9 nm and −17.4 ± 1.9 mV, respectively. Mechanistic investigations in HaCaT keratinocytes showed that PFE significantly downregulated tight junction proteins (ZO-1 and Occludin, p < 0.01) via modulation of the IL-17 signaling pathway, as evidenced by transcriptomic analysis. In a sodium urea crystal-induced rat IA model, the topical application of PFE-IND-GEL significantly reduced joint swelling (p < 0.05) and serum levels of inflammatory cytokines (IL-6, IL-1α, TNF-α) compared to control groups. Histopathological analysis confirmed the marked attenuation of synovial inflammation and cartilage preservation in treated animals. These findings underscore the dual role of PFE as both a topical permeation enhancer and an anti-inflammatory agent, presenting a promising strategy for managing IA. Full article

High penetration of photovoltaic (PV) generation presents new challenges for voltage regulation in distribution networks (DNs), primarily due to output intermittency and constrained reactive power capabilities. This paper introduces a distributed voltage control method leveraging reactive power compensation from PV inverters. Instead of relying on centralized computation, the proposed method allows each inverter to make local decisions using real-time voltage measurements and delayed communication with neighboring PV nodes. To account for practical asynchronous communication and feedback delay, a Distributed Online Primal–Dual Push–Sum (DOPP) algorithm that integrates a fixed-step delay model into the push–sum coordination framework is developed. Through extensive case studies on a modified IEEE 123-bus system, it has been demonstrated that the proposed method maintains robust performance under both static and dynamic scenarios, even in the presence of fixed feedback delays. Specifically, in static scenarios, the proposed strategy rapidly eliminates voltage violations within 50–100 iterations, effectively regulating all nodal voltages into the acceptable range of [0.95, 1.05] p.u. even under feedback delays with a delay step of 10. In dynamic scenarios, the proposed strategy ensures 100% voltage compliance across all nodes, demonstrating superior voltage regulation and reactive power coordination performance over conventional droop and incremental control approaches. Full article

Structural collapses caused by accidents or disasters could create unexpected radiation shielding, resulting in sharp gradients within the radiation field. Traditional radiation mapping methods often fail to accurately capture these complex variations, making the rapid and precise localization of radiation sources a significant challenge in emergency response scenarios. To address this issue, based on standard Gaussian process regression (GPR) models that primarily utilize a single Gaussian kernel to reflect the inverse-square law in free space, a novel multi-kernel Gaussian process regression (MK-GPR) model is proposed for high-fidelity radiation mapping in environments with physical obstructions. MK-GPR integrates two additional kernel functions with adaptive weighting: one models the attenuation characteristics of intervening materials, and the other captures the energy-dependent penetration behavior of radiation. To validate the model, gamma-ray distributions in complex, shielded environments were simulated using GEometry ANd Tracking 4 (Geant4). Compared with conventional methods, including linear interpolation, nearest-neighbor interpolation, and standard GPR, MK-GPR demonstrated substantial improvements in key evaluation metrics, such as MSE, RMSE, and MAE. Notably, the coefficient of determination (R²) increased to 0.937. For practical deployment, the optimized MK-GPR model was deployed to an RK-3588 edge computing platform and integrated into a mobile robot equipped with a NaI(Tl) detector. Field experiments confirmed the system’s ability to accurately map radiation fields and localize gamma sources. When combined with SLAM, the system achieved localization errors of 10 cm for single sources and 15 cm for dual sources. These results highlight the potential of the proposed approach as an effective and deployable solution for radiation source investigation in post-disaster environments. Full article

The increasing demand for noninvasive inspection (NII) of complex civil infrastructures requires overcoming the limitations of traditional ground-penetrating radar (GPR) systems in addressing diverse and large-scale applications. The solution proposed in this study focuses on an initial design that integrates a low-SWaP (Size, Weight, and Power) ultra-wideband (UWB) impulse radar with realistic electromagnetic modeling for deployment on unmanned aerial vehicles (UAVs). The system incorporates ultra-realistic antenna and propagation models, utilizing Finite Difference Time Domain (FDTD) solvers and multilayered media, to replicate realistic airborne sensing geometries. Verification and calibration are performed by comparing simulation outputs with laboratory measurements using varied material samples and target models. Custom signal processing algorithms are developed to extract meaningful features from complex electromagnetic environments and support anomaly detection. Additionally, machine learning (ML) techniques are trained on synthetic data to automate the identification of structural characteristics. The results demonstrate accurate agreement between simulations and measurements, as well as the potential for deploying this design in flight tests within realistic environments featuring complex electromagnetic interference. Full article

Australia has the highest per capita penetration of rooftop solar PV systems in the world. Integration of these systems has led to reverse power flow and associated voltage rise problems in residential low-voltage (LV) distribution networks. Furthermore, random, uncontrolled connection of single-phase solar systems can exacerbate voltage unbalance in these networks. This paper investigates the application of a Static Synchronous Compensator (STATCOM) for the improvement of voltage regulation in four-wire LV distribution feeders through reactive power management as a means of mitigating voltage regulation and unbalance challenges. To demonstrate the performance of the STATCOM with varying loads and PV output, a Q-V droop curve is applied to specify the level of reactive power injection/absorption required to maintain appropriate voltage regulation. A practical four-wire feeder from New South Wales, Australia, has been used as a case study network to analyse improvements in system performance through the use of the STATCOM. The outcomes indicate that the STATCOM has a high degree of efficacy in mitigating voltage regulation and unbalance excursions. In addition, compared to other solutions identified in the existing literature, the STATCOM-based solution requires no sophisticated communication infrastructure. Full article

The large-scale integration of renewable energy into power systems poses significant challenges to reactive power and voltage stability. To enhance system stability, this work proposes a cluster partitioning and distributed control strategy for distribution networks with high-penetration distributed PV integration. Firstly, a comprehensive clustering index system, including electrical distance, voltage sensitivity, and regulation ability, is established. Considering the voltage and reactive power support capability of regional clusters, the distribution network is divided into clusters. Subsequently, based on the results of cluster division, a hierarchical partition optimization model is constructed with voltage and reactive power as the optimization objectives. Finally, a distributed optimization algorithm based on ADMM is proposed to solve the optimization model and maximize the utilization of distribution network control resources. The simulation results based on the IEEE 33-node distribution system verify the effectiveness of the proposed distributed optimization strategy. Full article

Cell-penetrating peptides offer a promising strategy for intracellular delivery; however, non-specific uptake and off-target cytotoxicity limit their clinical utility. To address these limitations, a cold atmospheric plasma-responsive delivery platform was developed in which the membrane activity of a peptide was transiently suppressed upon complexation with a DNA-based nanostructure. Upon localized plasma exposure, DNA masking was disrupted, restoring the biological functions of the peptides. Transmission electron microscopy revealed that the synthesized DNA nanoflower structures were approximately 150–250 nm in size. Structural and functional analyses confirmed that the system remained inert under physiological conditions and was rapidly activated by plasma treatment. Fluorescence recovery, cellular uptake assays, and cytotoxicity measurements demonstrated that the peptide activity could be precisely controlled in both monolayer and three-dimensional spheroid models. This externally activatable nanomaterial-based system enables the spatial and temporal regulation of peptide function without requiring biochemical triggers or permanent chemical modifications. This platform provides a modular strategy for the development of potential peptide therapeutics that require precise control of activation in complex biological environments. Full article

Knowing the superior biochemical defense mechanisms of sessile organisms, it is not hard to believe the cure for any human sickness might be hidden in nature—we “just” have to identify it and make it safely available in the right dose to our organs and cells that are in need. For decades, green tea catechins (GTCs) have been a case in point. Because of their low redox potential and favorable positioning of hydroxyl groups, these flavonoid representatives (namely, catechin—C, epicatechin—EC, epicatechin gallate—ECG, epigallocatechin—EGC, epigallocatechin gallate—EGCG) are among the most potent plant-derived (and not only) antioxidants. The proven anti-inflammatory, neuroprotective, antimicrobial, and anticarcinogenic properties of these phytochemicals further contribute to their favorable pharmacological profile. Doubtlessly, GTCs hold the potential to “cope” with the majority of today‘s socially significant diseases, yet their mass use in clinical practice is still limited. Several factors related to the compounds’ membrane penetrability, chemical stability, and solubility overall determine their low bioavailability. Moreover, the antioxidant-to-pro-oxidant transitioning behavior of GTCs is highly conditional and, to a certain degree, unpredictable. The nanoparticulate delivery systems represent a logical approach to overcoming one or more of these therapeutic challenges. This review particularly focuses on the lipid-based nanotechnologies known to be a leading choice when it comes to drug permeation enhancement and not drug release modification nor drug stabilization solely. It is our goal to present the privileges of encapsulating green tea catechins in either vesicular or particulate lipid carriers with respect to the increasingly popular trends of advanced phytotherapy and functional nutrition. Full article

Androgenetic alopecia (AGA) is the most prevalent form of alopecia areata. Traditional treatment options, including minoxidil, finasteride, and hair transplantation, have their limitations, such as skin irritation, systemic side effects, invasiveness, and high costs. The transdermal drug delivery system (TDDS) offers an innovative approach for treating AGA by administering medications through the skin to achieve localized and efficient delivery while overcoming the skin barrier. This review systematically explores the application of TDDS in AGA treatment, highlighting emerging technologies such as microneedles (MNs), liposomes, ionic liquids (ILs), nanostructured lipid carriers (NLCs), and transporters (TFs). It analyzes the underlying mechanisms that enhance drug penetration through hair follicles. Finally, this review presents a forward-looking perspective on the future use of TDDS in the management of AGA, aiming to provide insights and references for designing effective transdermal drug delivery systems for this condition. Full article

The integration of autonomous vehicles (AVs) into urban transportation systems has significant potential to enhance traffic efficiency and reduce environmental impacts. This study evaluates the impact of different AV penetration scenarios (0%, 10%, 30%, 50%) on traffic performance and carbon emissions along Prince Mohammed bin Salman bin Abdulaziz Road in Riyadh, Saudi Arabia. Using microscopic simulation (SUMO) based on real-world datasets, we assess key performance indicators such as travel time, stop frequency, speed, and CO₂ emissions. Results indicate notable improvements with increasing AV deployment, including up to 25.5% reduced travel time and 14.6% lower emissions at 50% AV penetration. Coordinated AV behavior was approximated using adjusted simulation parameters and Python-based APIs, effectively modeling vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-network (V2N) communications. These findings highlight the benefits of harmonized AV–human vehicle interactions, providing a scalable and data-driven framework applicable to smart urban mobility planning. Full article

Molecular dynamics (MD) simulations have been performed on the energetics, mechanical properties, and irradiation response of seventy-three 3C-SiC symmetric tilt grain boundaries (STGBs) with three tilt axes (<100>, <110> and <111>). The effect of GB characteristics on the STGB properties has been investigated. The GB energy is positively and linearly correlated with the excess volume, but the linearity in SiC is not as good as in metals, which stems from the inhomogeneous structural relaxation near GBs induced by orientation-sensitive covalent bonding. For <110>STGBs, the shear strength exhibits symmetry with respect to the misorientation angle of 90°, which is consistent with ab initio calculations for Al in similar shear orientations. Cascades are performed with 8 keV silicon as the primary knock-on atom (PKA). No direct correlation is found between the sink efficiency of GBs for defects and GB characteristics, which comes from the complexity of the diatomic system during the recovery phase. For GBs with smaller values of Σ, the GBs exhibit a weaker blocking effect on the penetration of irradiated defects, resulting in a lower number of defects in GBs and a higher number of total surviving defects. In particular, it is seen that the percentage decrease in tensile strength after irradiation is positively correlated with the Σ value. Taken together, these results help to elucidate the impact of GB behavior on the mechanical properties of as well as the primary irradiation damage in SiC and provide a reference for creating improved materials through GB engineering. Full article

With the increasing penetration of distributed generation (DG), integrated main-distribution networks (IMDNs) face challenges in rapidly and effectively performing comprehensive operational risk assessments under multiple uncertainties. Thereby, using the traditional hierarchical economic scheduling method makes it difficult to accurately find the optimal scheduling operating point. To address this problem, this paper proposes a multi-objective dispatch decision-making optimization model for the IMDN with static security region (SSR) constraints. Firstly, the non-sequential Monte Carlo sampling is employed to generate diverse operational scenarios, and then the key risk characteristics are extracted to construct the risk assessment index system for the transmission and distribution grid, respectively. Secondly, a hyperplane model of the SSR is developed for the IMDN based on alternating current power flow equations and line current constraints. Thirdly, a risk assessment matrix is constructed through optimal power flow calculations across multiple load levels, with the index weights determined via principal component analysis (PCA). Subsequently, a scheduling optimization model is formulated to minimize both the system generation costs and the comprehensive risk, where the adaptive grid density-improved multi-objective particle swarm optimization (AG-MOPSO) algorithm is employed to efficiently generate Pareto-optimal operating point solutions. A membership matrix of the solution set is then established using fuzzy comprehensive evaluation to identify the optimal compromised operating point for dispatch decision support. Finally, the effectiveness and superiority of the proposed method are validated using an integrated IEEE 9-bus and IEEE 33-bus test system. Full article

The global antimicrobial resistance crisis demands innovative strategies to combat bacterial infections, including those caused by drug-sensitive pathogens that evade treatment through biofilm formation or metabolic adaptations. Here, we demonstrate that Squama Manitis extract (SME)—a traditional Chinese medicine component—exhibits broad-spectrum bactericidal activity against clinically significant pathogens, including both Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) species (MIC = 31.25 mg/mL), achieving significant reduction in bacterial viability within 24 h. Through integrated multi-omics analysis combining scanning electron microscopy and RNA sequencing, we reveal SME’s unprecedented tripartite mechanism of action: (1) direct membrane disruption causing cell envelope collapse, (2) metabolic paralysis through coordinated suppression of TCA cycle and fatty acid degradation pathways, and (3) inhibition of DNA repair systems (SOS response and recombination downregulation). Despite its potent activity, SME shows low cytotoxicity toward mammalian cells (>90% viability) and can penetrate Gram-negative outer membranes. These features highlight SME’s potential to address drug-resistant infections through synthetic lethality across stress response, energy metabolism, and DNA integrity pathways. While advocating for synthetic alternatives to endangered animal products, this study establishes SME as a polypharmacological template for resistance-resilient antimicrobial design, demonstrating how traditional knowledge and modern systems biology can converge to guide sustainable anti-infective development. Full article