Search Results (15,798)

This paper addresses the critical challenge of selecting suitable pile foundations in port engineering by systematically investigating the axial bearing behavior of large-diameter steel pipe piles and prestressed high-strength concrete (PHC) piles. The study integrates both numerical simulations and field tests within the context of the Yancheng Dafeng Port Security Facilities Project. A self-balanced static load numerical model for PHC piles was developed using Plaxis 3D, enabling the simulation of load-displacement responses, axial force transfer, and side resistance distribution. The accuracy of the model was verified through a comparison with field static load test data. With the verified model parameters, the internal force distribution of steel pipe piles was analysed by modifying material properties and adjusting boundary conditions. A comparative analysis of the two pile types was conducted under identical working conditions. The results reveal that the ultimate bearing capacities of the 1# steel pipe pile and the 2# PHC pile are 6734 kN and 6788 kN, respectively. Despite the PHC pile having a 20% larger diameter, its ultimate bearing capacity is comparable to that of the steel pipe pile, suggesting a more efficient utilisation of material strength in the latter. Further numerical simulations indicate that, under the same working conditions, the ultimate bearing capacity of the steel pipe pile exceeds that of the PHC pile by 18.43%. Additionally, the axial force distribution along the steel pipe pile shaft is more uniform, and side resistance is mobilised more effectively. The reduction in side resistance caused by construction disturbances, combined with the slenderness ratio (L/D = 41.7) of the PHC pile, results in 33.87% of the pile’s total bearing capacity being attributed to tip resistance. The findings of this study provide crucial insights into the selection of optimal pile types for terminal foundations, considering factors such as bearing capacity, environmental conditions, and economic viability. Full article

The cornea, the transparent anterior window of the eye, critically refracts light and protects intraocular structures. Corneal pathologies, including trauma, infection, chemical injury, metabolic diseases, genetic conditions, and age-related degeneration, can lead to significant visual impairment. While penetrating keratoplasty or full-thickness corneal transplantation remains a standard and effective intervention for severe corneal dysfunction, limitations in donor tissue availability and the risk of immunogenic graft rejection necessitate alternative therapeutic strategies. Furthermore, for cases of isolated epithelial disfunction, a full-thickness cornea graft may not be required or effective. This review examines the potential of corneal epithelial constructs derived from autologous stem cells with functional barrier properties for corneal reconstruction and in vitro pharmacotoxicity testing. In this review, we delineate the current limitations of corneal transplantation, the advantages of stem cell-based approaches, and recent advances in generating engineered corneal epithelium. Finally, we address remaining technical challenges and propose future research directions aimed at clinical translation. Full article

Land use/land cover (LULC) change constitutes a critical driver influencing regional carbon cycling processes. Optimizing LULC structures represents a significant pathway toward the realization of carbon neutrality. This study takes Liaoning Province as a case area to analyze LULC changes from 2000 to 2020 and to assess their impacts on land use carbon emissions (LUCE) and ecosystem carbon storage (ECS). To accelerate the achievement of carbon neutrality, four development scenarios are established: natural development (ND), low-carbon emission (LCE), high-carbon storage (HCS), and carbon neutrality (CN). For each scenario, corresponding optimization objectives and constraint conditions are defined, and a multi-objective LULC optimization coupling model is formulated to optimize both the quantity structure and spatial pattern of LULC. On this basis, the model quantifies ECS and LUCE under the four scenarios and evaluates the economic value of each scenario and its contribution to the carbon neutrality target. Results indicate the following: (1) From 2000 to 2020, the extensive expansion of construction land resulted in a reduction in ECS by 12.72 × 10⁶ t and an increase in LUCE by 150.44 × 10⁶ t; (2) Compared to the ND scenario, the LCE scenario exhibited the most significant performance in controlling carbon emissions, while the HCS scenario achieved the highest increase in carbon sequestration. The CN scenario showed significant advantages in reducing LUCE, enhancing ECS, and promoting economic growth, achieving a reduction of 0.18 × 10⁶ t in LUCE, an increase of 118.84 × 10⁶ t in ECS, and an economic value gain of 3386.21 × 10⁶ yuan. This study optimizes the LULC structure from the perspective of balancing economic development, LUCE reduction, and ECS enhancement. It addresses the inherent conflict between regional economic growth and ecological conservation, providing scientific evidence and policy insights for promoting LULC optimization and advancing carbon neutrality in similar regions. Full article

Powdery mildew, caused by Erysiphe quercicola, is one of the primary diseases responsible for the reduction in natural rubber production in China. This disease is a typical airborne pathogen, characterized by its ability to spread via air currents and rapidly escalate into an epidemic under favorable environmental conditions. Accurate prediction and determination of the prevention and control period represent both a critical challenge and key focus area in managing rubber-tree powdery mildew. This study investigates the effects of spore concentration, environmental factors, and infection time on the progression of powdery mildew in rubber trees. By employing six distinct machine learning model construction methods, with the disease index of powdery mildew in rubber trees as the response variable and spore concentration, temperature, humidity, and infection time as predictive variables, a preliminary predictive model for the disease index of rubber-tree powdery mildew was developed. Results from indoor inoculation experiments indicate that spore concentration directly influences disease progression and severity. Higher spore concentrations lead to faster disease development and increased severity. The optimal relative humidity for powdery mildew development in rubber trees is 80% RH. At varying temperatures, the influence of humidity on the disease index differs across spore concentration, exhibiting distinct trends. Each model effectively simulates the progression of powdery mildew in rubber trees, with predicted values closely aligning with observed data. Among the models, the Kernel Ridge Regression (KRR) model demonstrates the highest accuracy, the R² values for the training set and test set were 0.978 and 0.964, respectively, while the RMSE values were 4.037 and 4.926, respectively. This research provides a robust technical foundation for reducing the labor intensity of traditional prediction methods and offers valuable insights for forecasting airborne forest diseases. Full article

(1) Background: Polyploid fish are highly important in increasing fish production, improving fish quality, and breeding new varieties. The loach (Misgurnus anguillicaudatus), as a naturally polyploid fish, serves as an ideal biological model for investigating the mechanisms of chromosome doubling; (2) Methods: In this study, tetraploidization in diploid loach was induced by heat shock treatment, and, for the first time, the role of the key cell cycle gene cdk1 (cyclin-dependent kinase 1) in chromosome doubling was investigated; (3) Results: The experimental results show that when eggs are fertilized for 20 min and then subjected to a 4 min heat shock treatment at 39–40 °C, this represents the optimal induction condition, resulting in a tetraploid rate of 44%. Meanwhile, the results of the cdk1 knockout model (2n cdk1^−/−) constructed using CRISPR/Cas9 showed that the absence of cdk1 significantly increased the chromosome doubling efficiency of the loach. The qPCR analysis revealed that knockout of cdk1 significantly upregulated cyclin genes (ccnb3,ccnc, and ccne1), while inhibiting expression of the separase gene espl1 (p < 0.05); (4) Conclusions: During chromosome doubling in diploid loaches induced by heat shock, knocking out the cdk1 gene can increase the tetraploid induction rate. This effect may occur through downregulation of the espl1 gene. This study offers novel insights into optimizing the induced breeding technology of polyploid fish and deciphering its molecular mechanism, while highlighting the potential application of integrating gene editing with physical induction. Full article

As a core device in low-voltage distribution networks, the distribution zone transformer (DZT) is influenced by short circuits, overloads, and unbalanced loads, which cause thermal aging, mechanical stress, and eventually deformation of the winding, resulting in parameter deviations from nameplate values and impairing system operation. However, existing identification methods typically require synchronized high- and low-voltage data and are limited to symmetric three-phase conditions, which limits their application in practical distribution systems. To address these challenges, this paper proposes a parameter identification method for DZTs under three-phase unbalanced conditions. Firstly, based on the transformer’s T-equivalent circuit considering the load, the power flow equations are derived without involving the synchronization issue of high-voltage and low-voltage side data, and the sum of the impedances on both sides is treated as an independent parameter. Then, a novel power flow equation under three-phase unbalanced conditions is established, and an adaptive recursive least squares (ARLS) solution method is constructed using the measurement data sequence provided by the smart meter of the intelligent transformer terminal unit (TTU) to achieve online identification of the transformer winding parameters. The effectiveness and robustness of the method are verified through practical case studies. Full article

Based on the principle of symmetry, we propose a variable step-size FxLMS algorithm with double nonlinear functions cooperative coupling (DNVSS-FxLMS), aiming to optimize the contradiction between convergence rate and steady-state error in the active pressure pulsation control system of hydraulic systems. The algorithm innovatively couples two types of nonlinear mechanisms (rational-fractional and exponential-function-based), constructing a refined error-step mapping relationship to achieve a balance between rapid convergence and low steady-state error. Simulation experiments were conducted considering the complex time-varying operating environment of a simulation-based hydraulic system. The results demonstrate that, when the system undergoes unstable random changes, the DNVSS-FxLMS algorithm converges at least twice as fast as traditional and existing variable step size algorithms, while reducing steady-state error by 2–5 dB. The proposed DNVSS-FxLMS algorithm exhibits significant advantages in convergence rate, steady-state error reduction, and tracking capability, providing a highly efficient and robust solution for real-time active control of hydraulic system pressure pulsation under complex operating conditions. Full article

This study investigates the effectiveness of passive design in low-rise residential buildings located in arid desert climates, using the Dubai Solar Decathlon Middle East (SDME) competition as a case study. This full-scale experiment offers a unique opportunity to evaluate design solutions under controlled, realistic conditions; prescriptive, modeled performance; and monitored performance assessments. The prescriptive assessment reviews geometry, orientation, envelope thermal properties, and shading. Most houses adopt compact forms, with envelope-to-volume and envelope-to-floor area ratios averaging 1 and 3.7, respectively, and window-to-wall ratios of approximately 17%, favoring north-facing openings to optimize daylight while reducing heat gain. Shading is strategically applied, horizontal on south façades and vertical on east and west. The thermal properties significantly exceed the local code requirements, with wall performance up to 80% better than that mandated. The modeled assessment uses Building Energy Models (BEMs) to simulate the impact of prescriptive measures on energy performance. Three variations are applied: assigning minimum local code requirements to all the houses to isolate the geometry (baseline); removing shading; and applying actual envelope properties. Geometry alone accounts for up to 60% of the variation in cooling intensity; shading reduces loads by 6.5%, and enhanced envelopes lower demand by 14%. The monitored assessment uses contest-period data. Indoor temperatures remain stable (22–25 °C) despite outdoor fluctuations. Energy use confirms that houses with good designs and airtightness have lower cooling loads. Airtightness varies widely (avg. 14.5 m³/h/m²), with some well-designed houses underperforming due to construction flaws. These findings highlight the critical role of passive design as the first layer for improving the energy performance of the built environment and advancing toward net-zero targets, specifically in arid desert climates. Full article

The aim of this work is to study a class of nabla fractional difference equations with anti-periodic conditions. First, we construct the related Green’s function. After deducing some of its useful properties, we obtain an upper bound for its sum. Then, using this bound, we are able to obtain three existence results based on the Banach contraction principle, Brouwer’s fixed point theorem, and Leray–Schauder’s nonlinear alternative, respectively. Then, we show some non-existence results for the studied problem, and existence results are also provided for a system of two equations of the considered type. Finally, we outline some particular examples in order to demonstrate the theoretical findings. Full article

High-viscosity stratified strata, characterized by complex geotechnical properties such as strong cohesion, low permeability, and pronounced layered structures, exhibit significant lateral friction resistance and high-end resistance during steel sheet pile installation. These factors substantially increase construction difficulty and may even cause structural damage. This study addresses two critical mechanical challenges during vibratory pile driving in Fujian Province’s hydraulic engineering project: prolonged high-frequency driving durations, and severe U-shaped steel sheet pile head damage in high-viscosity stratified soils. Employing the Coupled Eulerian–Lagrangian (CEL) numerical method, a systematic investigation was conducted into the penetration resistance, stress distribution, and damage patterns during vibratory pile driving under varying conditions of cohesive soil layer thickness, predrilled hole spacing, and aperture dimensions. The correlation between pile stress and penetration depth was established, with the influence mechanisms of key factors on driving-induced damage in high-viscosity stratified strata under multi-factor coupling effects elucidated. Finally, the feasibility of predrilling techniques for resistance reduction was explored. This study applies the damage prediction model based on the CEL method to U-shaped sheet piles in high-viscosity stratified formations, solving the problem of mesh distortion in traditional finite element methods. The findings provide scientific guidance for steel sheet pile construction in high-viscosity stratified formations, offering significant implications for enhancing construction efficiency, ensuring operational safety, and reducing costs in such challenging geological conditions. Full article

To improve collision risk prediction in high-traffic coastal waters and support real-time decision-making in maritime navigation, this study proposes a regional collision risk prediction system integrating the Computed Distance at Collision (CDC) method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Unlike Distance at Closest Point of Approach (DCPA), which depends on the position of Global Positioning System (GPS) antennas, Computed Distance at Collision (CDC) directly reflects the actual hull shape and potential collision point. This enables a more realistic assessment of collision risk by accounting for the hull geometry and boundary conditions specific to different ship types. The system was designed and validated using ship motion simulations involving bulk and container ships across varying speeds and crossing angles. The CDC method was used to define collision, almost-collision, and near-collision situations based on geometric and hydrodynamic criteria. Subsequently, the FIS–CDC model was constructed using the ANFIS by learning patterns in collision time and distance under each condition. A total of four input variables—ship speed, crossing angle, remaining time, and remaining distance—were used to infer the collision risk index (CRI), allowing for a more nuanced and vessel-specific assessment than traditional CPA-based indicators. Simulation results show that the time to collision decreases with higher speeds and increases with wider crossing angles. The bulk carrier exhibited a wider collision-prone angle range and a greater sensitivity to speed changes than the container ship, highlighting differences in maneuverability and risk response. The proposed system demonstrated real-time applicability and accurate risk differentiation across scenarios. This research contributes to enhancing situational awareness and proactive risk mitigation in Maritime Autonomous Surface Ship (MASS) and Vessel Traffic System (VTS) environments. Future work will focus on real-time CDC optimization and extending the model to accommodate diverse ship types and encounter geometries. Full article

The force ripple of a permanent magnet synchronous linear motor (PMSLM) caused by multi-source disturbances in practical applications seriously restricts its high-precision motion control performance. The traditional single-mechanism model has difficulty fully characterizing the nonlinear disturbance factors, while the data-driven method has real-time limitations. Therefore, this paper proposes a hybrid modeling framework that integrates the physical mechanism and measured data and realizes the dynamic compensation of the force ripple by constructing a collaborative suppression algorithm. At the mechanistic level, based on electromagnetic field theory and the virtual displacement principle, an analytical model of the core disturbance terms such as the cogging effect and the end effect is established. At the data level, the acceleration sensor is used to collect the dynamic response signal in real time, and the data-driven ripple residual model is constructed by combining frequency domain analysis and parameter fitting. In order to verify the effectiveness of the algorithm, a hardware and software experimental platform including a multi-core processor, high-precision current loop controller, real-time data acquisition module, and motion control unit is built to realize the online calculation and closed-loop injection of the hybrid compensation current. Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions. Full article

As an efficient clean energy technology, water electrolysis for hydrogen production has its efficiency limited by the sluggish oxygen evolution reaction (OER) kinetics, which drives the demand for the development of high-performance anode OER catalysts. This work constructs bimetallic (Al, Mn) co-doped nanoporous spinel CoFe₂O₄ (np-CFO) with a tunable structure and composition as an OER catalyst through a simple two-step dealloying strategy. The as-formed np-CFO (Al and Mn) features a hierarchical flaky configuration; that is, there are a large number of fine nanosheets attached to the surface of a regular micron-sized flake, which not only increases the number of active sites but also enhances mass transport efficiency. Consequently, the optimized catalyst exhibits a low OER overpotential of only 320 mV at a current density of 10 mA cm⁻², a minimal Tafel slope of 45.09 mV dec⁻¹, and exceptional durability. Even under industrial conditions (6 M KOH, 60 °C), it only needs 1.83 V to achieve a current density of 500 mA cm⁻² and can maintain good stability for approximately 100 h at this high current density. Theoretical simulations indicate that Al and Mn co-doping could indeed optimize the electronic structure of CFO and thus decrease the energy barrier of OER to 1.35 eV. This work offers a practical approach towards synthesizing efficient and stable OER catalysts. Full article

This paper investigates the tracking consensus of nonlinear multi-agent systems under undirected topology, considering asynchronous switching caused by delays between communication topology switching and controller switching. First, by using the properties of undirected topology graphs, the controller design process is simplified. Then, to address asynchronous delays during topology switching, the system operation is divided into synchronized and delayed modes based on the status of the controller and topology. Every operating mode has a corresponding control strategy. To alleviate the burden of communication and computation, an event-triggered mechanism (ETM) is introduced to reduce the number of controller updates. By constructing an augmented Lyapunov function that incorporates both matching and mismatching periods, sufficient conditions ensuring system stability are established. The required controller based on the dynamic ETM is obtained by solving Linear Matrix Inequalities (LMIs). Finally, a simulation example is conducted to verify its effectiveness. Full article

Wearable pressure sensors have emerged as vital tools in personalized monitoring, promising transformative advances in patient care and diagnostics. Nevertheless, conventional devices frequently suffer from limited sensitivity, inadequate flexibility, and concerns regarding biocompatibility. Herein, we introduce silk fibroin, a naturally occurring protein extracted from silkworm cocoons, as a promising material platform for next-generation wearable sensors. Owing to its remarkable biocompatibility, mechanical robustness, and structural tunability, silk fibroin serves as an ideal substrate for constructing capacitive pressure sensors tailored to medical applications. We engineered silk-derived capacitive architecture and evaluated its performance in real-time human motion and physiological signal detection. The resulting sensor exhibits a high sensitivity of 18.68 kPa⁻¹ over a broad operational range of 0 to 2.4 kPa, enabling accurate tracking of subtle pressures associated with pulse, respiration, and joint articulation. Under extreme loading conditions, our silk fibroin sensor demonstrated superior stability and accuracy compared to a commercial resistive counterpart (FlexiForce™ A401). These findings establish silk fibroin as a versatile, practical candidate for wearable pressure sensing and pave the way for advanced biocompatible devices in healthcare monitoring. Full article