Search Results (5,256)

Squall lines are some of the most common types of mesoscale cloud systems in tropical and subtropical regions. Thunderstorms associated with these systems are among the major causes of weather-related disasters and socio-economic losses in many regions across the world. This study investigates the capability of the Weather Research and Forecasting (WRF) model in simulating squall line features over the South African Highveld region. Two squall line cases were selected based on the availability of South African Weather Service (SAWS) weather radar data: 21 October 2017 (early austral summer) and 31 January–1 February 2018 (late austral summer). The European Centre for Medium-Range Weather Forecasts ERA5 datasets were used as observational proxies to analyze squall line features and compare them with WRF simulations. Mid-tropospheric perturbations were observed along westerly waves in both cases. These perturbations were coupled with surface troughs over central interior together with the high-pressure systems to the south and southeast of the country creating strong pressure gradients over the plateau, which also transports relative humidity onshore and extending to the Highveld region. The 2018 case also had a zonal structured ridging High, which was responsible for driving moisture from the southwest Indian Ocean towards the eastern parts of South Africa. Both ERA5 and WRF captured onshore near surface (800 hPa) winds and high-moisture contents over the eastern parts of the Highveld. A well-defined dryline was observed and well simulated for the 2017 event, while both ERA5 and WRF did not show any dryline for the 2018 case that was triggered by orography. While WRF successfully reproduced the synoptic-scale processes of these extreme weather events, the simulated rainfall over the area of interest exhibited a broader spatial distribution, with large-scale precipitation overestimated and convective rainfall underestimated. Our study shows that models are able to capture these systems but with some shortcomings, highlighting the need for further improvement in forecasts. Full article

Reliable multiscale models of thrombosis require platelet-scale fidelity at organ-scale cost, a gap that scientific machine learning has the potential to narrow. We trained a DeepONet surrogate on platelet dynamics generated with LAMMPS for platelets spanning ten elastic moduli and capillary numbers (0.07–0.77). The network takes as input the wall shear stress, bond stiffness, time, and initial particle coordinates and returns the full three-dimensional deformation of the membrane. Mean-squared-error minimization with Adam and adaptive learning-rate decay yields a median displacement error below 1%, a 90th percentile below 3%, and a worst case below 4% over the entire calibrated range while accelerating computation by four to five orders of magnitude. Leave-extremes-out retraining shows acceptable extrapolation: the held-out stiffest and most compliant platelets retain sub-3% median error and an 8% maximum. Error peaks coincide with transient membrane self-contact, suggesting improvements via graph neural trunks and physics-informed torque regularization. These results represent a first demonstration of how the surrogate has the potential for coupling with continuum CFD, enabling future platelet-resolved hemodynamic simulations in patient-specific geometries and opening new avenues for predictive thrombosis modeling. Full article

Resonant acoustic technology utilizes low-frequency vertical harmonic vibrations to induce full-field mixing effects in processed materials, and it is regarded as a “disruptive technology in the field of energetic materials”. Although numerous scholars have investigated the mechanisms of resonant acoustic mixing, there remains a lack of parameter selection methods for improving product quality and production efficiency in engineering practice. To address this issue, this study employs phase-field modeling and fluid–structure coupling methods to numerically simulate the transport process of glycerol during resonant acoustic mixing. The research reveals the mass transfer mechanism within the flow field, establishes a liquid-phase distribution index for quantitatively characterizing mixing effectiveness, and clarifies the enhancement effect of fluid transport on solid particle mixing through particle tracking methods. Furthermore, parameter studies on vibration frequency and amplitude were conducted, yielding a critical curve for guiding parameter selection in engineering applications. The results demonstrate that Faraday instability first occurs at the fluid surface, generating Faraday waves that drive large-scale vortices for global mass transfer, followed by localized mixing through small-scale vortices. The transport process of glycerol during resonant acoustic mixing comprises three distinct stages: stable Faraday wave oscillation, rapid mass transfer during flow field destabilization, and localized mixing upon stabilization. Additionally, increasing either vibration frequency or amplitude effectively enhances both the rate and effectiveness of mass transfer. These findings offer theoretical guidance for optimizing process parameters in resonant acoustic mixing applications. Full article

Antibody–drug conjugates (ADCs) are a rapidly advancing class of targeted cancer therapeutics that couple the antigen specificity of monoclonal antibodies (mAbs) with the potent cytotoxicity of small-molecule drugs. In their core design, a tumor-targeting antibody is covalently linked to a cytotoxic payload via a chemical linker, enabling the selective delivery of highly potent agents to malignant cells while sparing normal tissues, thereby improving the therapeutic index. Humanized and fully human immunoglobulin G1(IgG1) antibodies are the most common ADC backbones due to their stability in systemic circulation, robust Fcγ receptor engagement for immune effector functions, and reduced immunogenicity. Antibody selection requires balancing tumor specificity, internalization rate, and binding affinity to avoid barriers to tissue penetration, such as the binding-site barrier effect, while emerging designs exploit tumor-specific antigen variants or unique post-translational modifications to further enhance selectivity. Advances in antibody engineering, linker chemistry, and payload innovation have reinforced the clinical success of ADCs, with more than a dozen agents FDA approved for hematologic malignancies and solid tumors and over 200 in active clinical trials. This review critically examines established and emerging conjugation strategies, including lysine- and cysteine-based chemistries, enzymatic tagging, glycan remodeling, non-canonical amino acid incorporation, and affinity peptide-mediated methods, and discusses how conjugation site, drug-to-antibody ratio (DAR) control, and linker stability influence pharmacokinetics, efficacy, and safety. Innovations in site-specific conjugation have improved ADC homogeneity, stability, and clinical predictability, though challenges in large-scale manufacturing and regulatory harmonization remain. Furthermore, novel ADC architectures such as bispecific ADCs, conditionally active (probody) ADCs, immune-stimulating ADCs, protein-degrader ADCs, and dual-payload designs are being developed to address tumor heterogeneity, drug resistance, and off-target toxicity. By integrating mechanistic insights, preclinical and clinical data, and recent technological advances, this work highlights current progress and future directions for next-generation ADCs aimed at achieving superior efficacy, safety, and patient outcomes, especially in treating refractory cancers. Full article

High penetration of distributed photovoltaics (DPV) in distribution networks can lead to voltage violations, increased network losses, and renewable energy curtailment, posing significant challenges to both economic efficiency and operational stability. To address these issues, this study develops a coordinated planning framework for DPV and energy-storage systems (ESS) that simultaneously achieves cost minimization and operational reliability. The proposed method employs a cluster partitioning strategy that integrates electrical modularity, active and reactive power balance, and node affiliation metrics, enhanced by a net-power-constrained Fast-Newman Algorithm to ensure strong intra-cluster coupling and rational scale distribution. On this basis, a dual layer optimization model is developed, where the upper layer minimizes annualized costs through optimal siting and sizing of DPV and ESS, and the lower layer simultaneously suppresses voltage deviations, reduces network losses, and maximizes PV utilization by employing an adaptive-grid multi-objective particle-swarm optimization approach. The framework is validated on the IEEE 33-node test system using typical PV generation and load profiles. The simulation results indicate that, compared with a hybrid second-order cone programming method, the proposed approach reduces annual costs by 6.6%, decreases peak–valley load difference by 22.6%, and improves PV utilization by 28.9%, while maintaining voltage deviations below 6.3%. These findings demonstrate that the proposed framework offers an efficient and scalable solution for enhancing renewable hosting capacity, and provides both theoretical foundations and practical guidance for the coordinated integration of DPV and ESS in active distribution networks. Full article

Closing resistors in ultra-high-voltage (UHV) gas-insulated circuit breakers (GCBs) are critical components designed to suppress inrush currents and transient overvoltages during switching operations. However, in practical service, these resistors are subjected to repeated mechanical impacts and transient electrical stresses, leading to degradation of their electrical contact interfaces, fluctuating resistance values, and potential failure of the entire breaker assembly. Existing studies mostly simplify the closing resistor as a constant resistance element, neglecting the coupled electro-thermal–mechanical effects that occur during transient events. In this work, a comprehensive modeling framework is developed to investigate the dynamic electrical contact characteristics of a 750 kV GCB closing resistor under transient closing impacts. First, an electromagnetic transient model is built to calculate the combined inrush and power-frequency currents flowing through the resistor during its pre-insertion period. A full-scale mechanical test platform is then used to capture acceleration signals representing the mechanical shock imparted to the resistor stack. These measured signals are fed into a finite element model incorporating the Cooper–Mikic–Yovanovich (CMY) electrical contact correlation to simulate stress evolution, current density distribution, and temperature rise at the resistor interface. The simulation reveals pronounced skin effect and current crowding at resistor edges, leading to localized heating, while transient mechanical impacts cause contact pressure to fluctuate dynamically—resulting in a temporary decrease and subsequent recovery of contact resistance. These findings provide insight into the real-time behavior of closing resistors under operational conditions and offer a theoretical basis for design optimization and lifetime assessment of UHV GCBs. Full article

An innovative multi-absorber 1 MW wave energy converter (WEC), Nankun, is proposed for efficient wave energy extraction. It comprises a semi-submersible floating platform, a wave energy capture mechanism, a hydraulic energy conversion system, and a mooring system. The WEC operates by converting fluctuating wave power into stable electrical output through a unique sharp eagle-shaped wave absorber coupled with a hydraulic energy conversion module. Scaled model experiments (1:25) demonstrated energy-capture efficiency ranges predominantly between 30% and 50% across 0.8–1.4 s wave periods, with a peak of 56.17%. Analysis of the wave direction effect revealed that the device achieved significantly a higher energy capture at 180 deg compared with 0 deg wave headings, with a relative efficiency ratio of approximately 1.0:0.6~0.8. A full-scale prototype with 10 absorbers was deployed in the South China Sea, achieving grid connection in November 2023. Operational data confirmed viability and generation capacity, with the peak daily output reaching 9850 kWh and a cumulative production of 89,852 kWh over 20 days. Full article

While size effects in composite structures have been widely studied under quasi-static uniaxial loading, their influence under fatigue conditions, particularly in the presence of multiaxial stress states and elevated temperatures, remains insufficiently understood. This study investigates the fatigue behaviour of thick-walled $\pm {45}^{\circ }$ braided glass fibre-reinforced polyurethane composite box structures under varying temperature and loading conditions. A combined experimental approach is adopted, coupling quasi-static and fatigue tests on large-scale structures with reference data from standardised coupon specimens. The influence of temperature (23–80 °C) and multiaxial shear–compression loading is systematically evaluated. The results demonstrate a significant temperature-dependent decrease in compressive strength and fatigue life, with a linear degradation trend that aligns closely between the box structure and coupon data. Under moderate multiaxial conditions, the fatigue life of box structures is not significantly impaired compared to uniaxial test coupon specimens. Complementary non-destructive testing using air-coupled ultrasound confirms these trends, demonstrating that guided-wave phase-velocity measurements capture the evolution of anisotropic damage and are therefore suitable for in situ structural health monitoring applications. Furthermore, these findings highlight that (i) the temperature-dependent fatigue behaviour of thick-walled composites can be predicted using small-scale coupon data and (ii) small shear components have a limited impact on fatigue life within the studied loading regime. Full article

Background and Objectives: This study aimed to evaluate the association between relationship dynamics as measured by dyadic adjustment and factors such as erectile function and lower urinary tract symptoms, adjusting for relevant clinical characteristics. Materials and Methods: This cross-sectional study collected data from 94 males in relationships of at least 6 months and with a prostate volume equal to or higher than 30 cc. Lower urinary tract symptoms, erectile function, and relationship dynamics were assessed with the International Prostate Symptom Score (I-PSS), International Index of Erectile Function (IIEF), Dyadic Adjustment Scale (DAS). Results: We found significant positive correlations between DAS affective expressions (AEs) and erectile dysfunction duration; between IIEF general satisfaction and DAS dyadic adjustment (DA), dyadic consensus (DC), and dyadic cohesion (DH); and between prostate width and DAS DA and DC (all ρ ≈ 0.2–0.3, p < 0.05). Further multiple regression analyses adjusting for age, prostate width, and comorbidities showed that the associations between IIEF general satisfaction and DAS DA (p = 0.013) and DH (p = 0.008) remained significant, while the relationship with DAS DC (p = 0.051) was borderline. Conclusions: Our findings highlight that general sexual satisfaction, as measured with the IIEF, had a small but independent association with higher affective expressions, dyadic cohesion, and dyadic consensus in couples, which are key domains of dyadic adjustment, regardless of relationship duration, prostate width, and comorbidities. These results emphasize the importance of considering sexual satisfaction in the context of relationship quality and, therefore, involving the female partner in the assessment and treatment of erectile dysfunction. Full article

This study addresses the problems of poor dynamic stability, high vibration coupling, and inefficient energy use in large-farm manure handling machines. A profiling wheel-based multi-disciplinary approach is proposed in the study. With the rocker arm prototype, double-ball heads, and a hydraulic damping system, a parametric design is built that includes vibration and energy consumption. The simulation results in EDEM2022 and ANSYS2022 prove the structure viability and motion compensation capability, while NSGA-II optimizes the damping parameters (k₁ = 380 kN/m, C = 1200 Ns/m). The results show a 14.7% σ_Fc reduction, 14.3% α_RMS decrease, resonance avoidance (14–18 Hz), Δx (horizontal offset of the frame) < 5 mm, 18% power loss to 12.5%, and 62% stability improvement. The new research includes constructing a dynamic model by combining the Hertz contact theory with the modal decoupling method, while interacting with an automatic algorithm of adaptive damping and a mechanical-hydraulic-control-oriented optimization platform. Future work could integrate lightweight materials and multi-machine collaboration for smarter, greener manure cleaning. Full article

To address the challenges of complex harmonic characteristics, multi-source coupling, and strong time variability in aggregated loads downstream of high-voltage substations, this paper proposes an Adaptive Multi-Task Gaussian Process Regression (AMT-GPR) method for harmonic modeling. First, field measurements from the medium-voltage side of a 500 kV substation are denoised and analyzed using Fourier transform to reveal the dynamic patterns and interdependencies of harmonic current magnitudes. Then, a multi-task GPR framework is constructed, incorporating task correlation modeling and adaptive kernel functions to capture inter-task coupling and differences in feature scales. Finally, a probabilistic harmonic model is developed based on multiple sets of measured data, and the modeling performance of AMT-GPR is compared with single-task GPR, conventional MT-GPR, and mainstream machine learning approaches including RBF, LS-SVM, and LSTM. Simulation results demonstrate that traditional harmonic modeling methods are insufficient to capture the dynamic behavior and uncertainty of aggregated loads and AMT-GPR maintains strong robustness under small-sample conditions, significantly reduces prediction errors, and yields narrower uncertainty intervals, outperforming the baseline models. These findings validate the effectiveness of the proposed method in modeling harmonics of aggregated loads in high-voltage substations and provide theoretical support for subsequent harmonic assessment and mitigation strategies. Full article

With the increasing intensity of resource development in alpine regions, numerous geotechnical engineering problems in cold regions have become increasingly prominent. In order to explore the damage and deterioration laws of rocks caused by freeze–thaw action, this paper takes the biotite granulite on the eastern slope of Yanshan Iron Mine as the research object. By analyzing the changes in mechanical and acoustic emission parameters of rock samples after freeze–thaw, and combining with existing freeze–thaw damage theories, the suitable freeze–thaw damage mechanism for this rock is further explored, and a freeze–thaw damage model for biotite granulite with low and high freeze–thaw cycles is established. The results of this study demonstrate that biotite granulite subjected to a lower number of freeze–thaw cycles exhibits significantly greater reductions in peak strength, elastic modulus, acoustic emission (AE) hit counts, cumulative ringing counts, and cumulative energy compared with specimens exposed to a higher number of cycles. As the freeze–thaw cycles increase, the formation of newly generated large-scale fractures during failure becomes progressively less pronounced, leading to a diminished resistance to deformation and a gradual increase in plastic deformation during loading. A coupled damage variable relationship was established for biotite granulite under both low and high freeze–thaw regimes based on cumulative AE ringing counts. In the early three stress stages, specimens subjected to fewer cycles exhibited fewer microcracks, with no clear spatial correlation between their distribution and the eventual fracture coalescence zones, whereas specimens exposed to a higher number of cycles showed a distinct sequential relationship between microcrack initiation sites and subsequent crack coalescence. Building upon existing freeze–thaw damage theories, the freeze–thaw damage mechanism specific to biotite granulite was further elucidated. Accordingly, a freeze–thaw damage model for low- and high-cycle conditions was developed and preliminarily validated. Full article

This study aims to analyse the effect of partially clogged inlets on the behaviour of urban drainage systems at the city scale, particularly regarding intercepted volumes and flood depths. The main challenges were to represent the inlet network in detail at a rather large scale and to avoid the effect of sewer network surcharging on the draining capacity of inlets. This goal has been achieved through a 1D/2D coupled hydraulic model of the whole urban drainage system in La Almunia de Doña Godina (Zaragoza, Spain). The model focuses on the interaction between grated drain inlets and the sewer network under partial clogging conditions. The model is fed with data obtained on field surveys. These surveys identified 948 inlets, classified into 43 types based on geometry and grouped into 7 categories for modelling purposes. Clogging patterns were derived from field observations or estimated using progressive clogging trends. The hydrological model combines a semi-distributed approach for micro-catchments (buildings and courtyards) and a distributed “rain-on-grid” approach for public spaces (streets, squares). The model assesses the impact of inlet clogging on network performance and surface flooding during four rainfall scenarios. Results include inlet interception volumes, flooded surface areas, and flow hydrographs intercepted by single inlets. Specifically, the reduction in intercepted volume ranged from approximately 7% under a mild inlet clogging condition to nearly 50% under severe clogging conditions. Also, the model results show the significant influence of the 2D mesh detail on flood depths. For instance, a mesh with high resolution and break lines representing streets curbs showed a 38% increase in urban areas with flood depths above 1 cm compared to a scenario with a lower-resolution 2D mesh and no curbs. The findings highlight how inlet clogging significantly affects the efficiency of urban drainage systems and increases the surface flood hazard. Further novelties of this work are the extent of the analysis (city scale) and the approach to improve the 2D mesh to assess flood depth. Full article

Supercritical CO₂ (ScCO₂) injection has emerged as a promising method to enhance shale gas recovery while simultaneously achieving CO₂ sequestration. This research investigates how ScCO₂ interacts with water and shale rock, altering the pore structure characteristics of shale reservoirs. The study examines shale samples from three marine shale formations in southern China under varying thermal and pressure regimes simulating burial conditions at 1000 m (45 °C and 10 MPa) and 2000 m (80 °C and 20 MPa). The research employs multiple analytical techniques including XRD for mineral composition analysis, MICP, N₂GA, and CO₂GA for comprehensive pore characterization, FE–SEM for visual observation of mineral and pore changes, and multifractal theory to analyze pore structure heterogeneity and connectivity. Key findings indicate that ScCO₂–water–shale interactions lead to dissolution of minerals such as kaolinite, calcite, dolomite, and chlorite, and as the reaction proceeds, substantial secondary mineral precipitation occurs, with these changes being more pronounced under 2000 m simulation conditions. Mineral dissolution and precipitation cause changes in pore structure parameters of different pore sizes, with macropores showing increased PV and decreased SSA, mesopores showing decreased PV and SSA, and micropores showing insignificant changes. Moreover, mineral precipitation effects are stronger than dissolution effects. These changes in pore structure parameters lead to alterations in multifractal parameters, with mineral precipitation reducing pore connectivity and consequently enhancing pore heterogeneity. Correlation analysis further revealed that H and D₋₁₀–D₁₀ exhibit a significant negative correlation, confirming that reduced connectivity corresponds to stronger heterogeneity, while mineral composition strongly controls the multifractal responses of macropores and mesopores, with micropores mainly undergoing morphological changes. However, these changes in micropores are mainly manifested as modifications of internal space. Siliceous shale samples exhibit stronger structural stability compared to argillaceous shale, which is attributed to the mechanical strength of the quartz framework. By integrating multifractal theory with multi–scale pore characterization, this study achieves a unified quantification of shale pore heterogeneity and connectivity under ScCO₂–water interactions at reservoir–representative pressure–temperature conditions. This novelty not only advances the methodological framework but also provides critical support for understanding CO₂–enhanced shale gas recovery mechanisms and CO₂ geological sequestration in depleted shale gas reservoirs, highlighting the complex coupling between geochemical reactions and pore structure evolution. Full article

Market gardening plays a crucial role in ensuring food security and reducing poverty in Africa’s rapidly urbanizing regions. However, urban agricultural systems are increasingly threatened by climatic shocks such as floods, droughts, and heat waves. This study uses an integrated approach to analyze the multidimensional factors of climatic vulnerability among urban market gardeners in the Grand Nokoué region of Benin. Based on socio–economic, technico–agronomic, and perceptual data collected from 369 growers, multiple correspondence analysis (MCA) coupled with ascending hierarchical analysis (AHA) was performed to identify vulnerability profiles. K–means partitioning was used to confirm the optimal number of groups, thereby guaranteeing the robustness and internal consistency of the typology. Three distinct vulnerability groups were identified, each characterized by specific socioeconomic, technical, and territorial characteristics, as well as varying exposure to the risks of flooding, drought, and dry spells. The results show that the most vulnerable farmers tend to be young women with low incomes, limited access to land, and a reliance on manual irrigation in flood–prone areas. These findings emphasize the uneven distribution of adaptive capacities and the pressing requirement for tailored public policies to enhance resilience, especially among small–scale, low–income, and land–insecure urban farmers, who are vulnerable to various climate–related risks. Full article