Search Results (22,687)

By integrating cathodic arc evaporation (CAE) with magnetron sputtering (MS) or high-power impulse magnetron sputtering (HiPIMS), hard coatings with diverse multicomponent compositions can be fabricated. Depending on the deposition conditions, the coatings with nano-composite or nano-multilayered microstructures are produced. During the mixing deposition conditions, nano-composite coatings are fabricated, which can be tailored to possess combining properties of super hardness, low friction coefficient, and excellent thermal/chemical stability. For the deposition with larger rotating periods, layer-by-layer deposition was observed. By the nano-multilayered coating design, superior mechanical properties (hardness ≥ 35 GPa), modulated residual stresses, and enhanced high-temperature properties can be obtained. In addition, lubricious elements, low friction (friction coefficient < 0.4), and low wear (<10⁻⁵ mm³/N∙m) both at ambient temperature and high temperature can be realized. Among these coatings, some have been specifically designed to achieve outstanding cutting performance in high-speed cutting applications. Several nitride and oxide hard coatings, such as AlTiN, TiAlN/TiSiN, AlCrN/Cu, and AlCrO, were deposited using a hybrid industrial physical vapor deposition (PVD) coating system. The microstructure, mechanical properties, and cutting performance of these coatings will be discussed. Full article

This study experimentally investigates the wake-induced vibration (WIV) behavior of a bio-inspired harbor seal whisker model subjected to upstream propeller-generated unsteady flows. Vibration amplitudes, frequencies, and wake–whisker interactions were systematically evaluated under various flow conditions. The test matrix included propeller rotational speed N_p = 0~5000 r/min, propeller diameter D_p = 60~100 mm, incoming flow velocity U_∞ = 0~0.2 m/s, and separation distance between the whisker model and the propeller L/D = 10~30 (D = 16 mm, diameter of the whisker model). Results show that inline (IL) and crossflow (CF) vibration amplitudes increase significantly with propeller speed and decrease with increasing separation distance. Under combined inflow and wake excitation, non-monotonic trends emerge. Frequency analysis reveals transitions from periodic to subharmonic and broadband responses, depending on wake structure and coherence. A non-dimensional surface fit using L/D and the advance ratio (J = U_∞/(N_pD_p)) yielded predictive equations for RMS responses with good accuracy. Phase trajectory analysis further distinguishes stable oscillations from chaotic-like dynamics, highlighting changes in system stability. These findings offer new insight into WIV mechanisms and provide a foundation for biomimetic flow sensing and underwater tracking applications. Full article

Most levees are composed of earthen materials, making their structural stability vulnerable under flood conditions, especially in the case of overtopping. This study aims to analyze the relationship between the channel Froude number and the flow behavior on the landward slope of a levee during overtopping, enabling the prediction of landward slope velocity (LSV) in advance. Accurate estimation of flow velocity on the landward slope is crucial for predicting the occurrence and intensity of erosion during overtopping events, and it serves as a critical criterion for designing protective armoring and assessing levee structural stability. Numerical simulations were conducted under various Froude numbers in the channel to estimate the corresponding LSV. Key variables, including channel discharge, velocity, levee height, and overtopping flow depth, were used to establish quantitative correlations between channel flow characteristics and LSV. The proposed model effectively predicts the LSV for channel Froude numbers approximately between 0.05 and 0.60. The findings allow for a simplified estimation of LSV based on changes in Froude number and overtopping flow depth, providing valuable baseline data for planning levee reinforcement and maintenance strategies. Full article

Efficient and accurate acquisition of spatial distribution information for Apocynum venetum L. is highly important for the sustainable development of agriculture in Yuli County, Xinjiang. As an important cash crop, Apocynum relies on specific natural conditions for growth, and its survival environment is currently under severe threat. Therefore, accurately quantifying its spatial distribution information is crucial. This research takes Yuli County in Xinjiang as the study area and proposes an enhanced SegFormer model based on deep learning, aiming to realize the effective identification and extraction of Apocynum. The study indicates the following. (1) The improved SegFormer model adds smaller-scale feature layers in the encoder stage, allowing the improved model’s encoder to extract features at five scales: 1/4, 1/8, 1/16, 1/32, and 1/64; meanwhile, integrating the T2T-ViT backbone network into the encoder significantly enhances the precision and efficiency of Apocynum’s spatial distribution extraction. (2) Compared with Unet, TransUNet, and the original SegFormer, the improved SegFormer model outperforms the other models in terms of the mIoU, OA, and mPA metrics, achieving values of 88.22%, 93.98%, and 89.66%, respectively. (3) Ablation experiments show that the T2T_vit_14 model performs best among all the T2T-ViT configurations, with superior extraction effects on fragmented small plots compared with the other models. Therefore, the T2T_vit_14 model is integrated into the SegFormer model. This work improves the extraction accuracy and efficiency of the spatial distribution of Apocynum via an improved SegFormer model, which has strong stability and robustness and offers scientific evidence for resource protection, restoration planting, and germplasm breeding in Yuli County, Xinjiang. Full article

To improve the tracking accuracy and the adaptability of intelligent vehicles in various road conditions, an adaptive model predictive controller combining reinforcement learning is proposed in this paper. Firstly, to solve the problem of control accuracy decline caused by a fixed prediction time domain, a low-computational-cost adaptive prediction horizon strategy based on a two-dimensional Gaussian function is designed to realize the real-time adjustment of prediction time domain change with vehicle speed and road curvature. Secondly, to address the problem of tracking stability reduction under complex road conditions, the Deep Q-Network (DQN) algorithm is used to adjust the weight matrix of the Model Predictive Control (MPC) algorithm; then, the convergence speed and control effectiveness of the tracking controller are improved. Finally, hardware-in-the-loop tests and real vehicle tests are conducted. The results show that the proposed adaptive predictive horizon controller (DQN-AP-MPC) solves the problem of poor control performance caused by fixed predictive time domain and fixed weight matrix values, significantly improving the tracking accuracy of intelligent vehicles under different road conditions. Especially under variable curvature and high-speed conditions, the proposed controller reduces the maximum lateral error by 76.81% compared to the unimproved MPC controller, and reduces the average absolute error by 64.44%. The proposed controller has a faster convergence speed and better trajectory tracking performance when tested on variable curvature road conditions and double lane roads. Full article

Background/Objectives: The intranasal (IN) route of administration is a promising non-invasive approach for brain targeting, bypassing the blood–brain barrier and enhancing bioavailability. Citalopram hydrobromide (CT), a widely prescribed sparingly water-soluble selective serotonin reuptake inhibitor (SSRI), faces challenges with oral and intravenous administration, including delayed onset, adverse effects, and patient compliance issues. Methods: This study aimed to develop a novel thermoresponsive polymeric micelle (PM) system based on Pluronic^® copolymers (Pluronic F127 and Poloxamer 188) improving CT’s solubility, stability, and nasal permeability for enhanced antidepressant efficacy. A preliminary study was conducted to select the optimized formulation. The preparation process involved using the thin-film hydration method, followed by freeze-drying. Comprehensive evaluations of optimized formulation characteristics included Z-average, polydispersity index (PdI), thermal behavior (lower critical solution temperature, LCST), encapsulation efficiency, X-ray powder diffraction (XRPD), thermodynamic solubility, and biological stability. Additionally, in vitro CT release and CT permeability in nasal conditions were studied. Stability under storage was also evaluated. Results: The optimized CT-PM formulation showed nanoscale micelle size (Z-average of 31.41 ± 0.99 nm), narrow size distribution (polydispersity index = 0.241), and a suitable thermal behavior for intranasal delivery (lower critical solution temperature (LCST) ~31 °C). Encapsulation efficiency reached approximately 90%, with an amorphous structure confirmed via XRPD, leading to a 95-fold increase in CT solubility. The formulation demonstrated appropriate biological and physical stability. In vitro studies showed a 25-fold faster CT release from optimized formulation compared to the initial CT, while CT-PM permeability in nasal conditions increased four-fold. Conclusions: This novel nanoscale thermosensitive formulation is a value-added strategy for nasal drug delivery systems, offering enhanced drug solubility, rapid drug release, stability, and improved permeability. This smart nanosystem represents a promising platform to overcome the limitations of conventional CT administration, improving therapeutic outcomes and patient compliance in depression management. Full article

The harsh environment in Arctic regions presents significant challenges to ship stability, particularly when ice accumulation and hull damage occur simultaneously, potentially increasing the risk of instability. This study addresses this critical issue by proposing a comprehensive stability assessment framework for ships operating in Arctic regions. Utilizing the DTMB-5415 ship model, the evaluation integrates both static and dynamic stability under combined ice accumulation and damage conditions. Firstly, an ice accumulation prediction model was developed to estimate ice accumulation over various durations. Subsequently, the static stability of damaged ships with ice accumulation was evaluated. Computational Fluid Dynamics (CFD) simulations were then conducted to calculate roll damping coefficients and analyze the effects of damage location and ice accumulation on free roll decay behavior. A single-degree-of-freedom (SDOF) roll motion model was constructed, incorporating roll damping coefficients and wave excitation moments to simulate roll responses in random wave environments. Extreme value prediction was employed to estimate the short-term extreme response distribution of roll motions. The results indicate that ship stability decreases significantly when ice accumulation and hull damage occur simultaneously. This integrated framework provides a systematic foundation for evaluating ship stability in the Arctic environment, specifically accounting for the combined effects of ice accretion and hull damage. Full article

During operation, failures in a centrifugal pump’s rotary shaft seal—such as wear, deformation, or thermal cracking—can adversely affect system performance. This study utilizes both theoretical and experimental methods to investigate the vibration characteristics of centrifugal pumps under different rotary-shaft-seal conditions. Vibration signals are collected and processed using empirical mode decomposition (EMD) and autoregressive (AR) modeling to generate an EMD-AR spectrum. The results show that rotary-shaft-seal failure leads to decreases in both the head and efficiency of the centrifugal pump. For improved operation stability, centrifugal pumps should operate at or slightly above their design flow rates (Q_d), while avoiding low-flow conditions. Furthermore, the amplitude of the EMD-AR spectrum increases progressively as rotary-shaft-seal degradation worsens. Therefore, the EMD-AR spectrum provides a reliable diagnostic indicator for detecting rotary-shaft-seal damage. Full article

In an intelligent driving system, the rationality of driving decisions and the trajectory planning scheme directly determines the safety and stability of the system. Existing research mostly relies on high-definition maps and empirical parameters to estimate road adhesion conditions, ignoring the direct impact of real-time road status changes on the dynamic feasible domain of vehicles. This paper proposes an intelligent driving decision-making and trajectory planning method that comprehensively considers the influence factors of vehicle–road interaction. Firstly, real-time estimation of road adhesion coefficients was achieved based on the recursive least squares method, and a dynamic adhesion perception mechanism was constructed to guide the decision-making module to restrict lateral maneuvering behavior under low-adhesion conditions. A multi-objective lane evaluation function was designed for adaptive lane decision-making. Secondly, a longitudinal and lateral coupled trajectory planning framework was constructed based on the traditional lattice method to achieve smooth switching between lateral trajectory planning and longitudinal speed planning. The planned path is tracked based on a model predictive control algorithm and dual PID algorithm. Finally, the proposed method was verified on a co-simulation platform. The results show that this method has good safety, adaptability, and control stability in complex environments and dynamic adhesion conditions. Full article

With the increasing integration of renewable energy sources and power electronic converters, Grid-Forming (GFM) technologies such as Virtual Synchronous Generators (VSGs) have emerged as key enablers of future power systems. However, conventional VSG control strategies with fixed parameters often fail to maintain transient stability under dynamic grid conditions. This paper proposes a novel adaptive GFM control framework based on physics-informed reinforcement learning, targeting transient power angle stability in systems with high renewable penetration. An adaptive controller, termed the 3N-D controller, is developed to periodically update the virtual inertia and damping coefficients of VSGs based on real-time system observations, enabling anticipatory adjustments to evolving operating conditions. The controller leverages a reinforcement learning architecture embedded with physical priors, which captures the high-order differential relationships between rotor angle dynamics and control variables. This approach enhances generalization, reduces data dependency, and mitigates the risk of local optima. Comprehensive simulations on the IEEE-39 bus system with varying VSG penetration levels validate the proposed method’s effectiveness in improving system stability and control flexibility. The results demonstrate that the physics-embedded GFM strategy can significantly enhance the transient stability and adaptability of future power grids. Full article

Magnetically separable TiO₂-based composite photocatalysts have gained significant interest in the past two decades; however, the optimization of their synthesis and the stabilization of the magnetic iron oxide within the composite is still an open challenge. The present study investigates the photocatalytic behavior and recyclability of TiO₂-Fe₃O₄ composites, with emphasis on a possible correlation between pollutant degradation efficiency, recyclability, iron oxide stability, and the phase composition of the chosen TiO₂ base. Magnetite nanoparticles were synthesized under varied temperature and alkaline conditions to identify optimal parameters for achieving the desirable magnetic properties. The magnetic nanoparticles were integrated into composite systems with either commercial TiO₂ (Evonik Aeroxide P25 with anatase–rutile mixed phase) or a hydrothermally synthesized anatase TiO₂. The P25-based composite removed 99% paracetamol from aqueous solutions under UV-A irradiation and demonstrated successful recyclability, maintaining 96% paracetamol degradation efficiency after four uses. In contrast, the anatase TiO₂-based magnetic composite exhibited a lower performance (70%) and a significantly hindered recyclability (45% after four cycles). The difference in performance was attributed to variations in the phase composition of the employed TiO₂ in the composites and, consequently, in their charge separation mechanisms. Full article

Acrobeloides nanus is a cosmopolitan, parthenogenetic soil nematode that is widely distributed across various terrestrial environments, including forests, sand dunes, and agricultural lands. In Korea, this nematode was first isolated from soil collected from a potato farm. It has been used as a biological indicator for monitoring contamination caused by divalent metals such as copper and zinc. In this study, A. nanus was isolated from the soil collected from a cucumber farm, and its identity was confirmed using both morphological and molecular markers. Spray-induced gene silencing using double-stranded RNA (dsRNA) represents a promising new strategy for pest control. Here, we tested a spraying dsRNA that would specifically suppress the target genes in A. nanus. Three genes (Pat-10, Unc-87, and vATPase-B) were targeted, and their expression levels were assessed following treatment with their corresponding dsRNAs. The dsRNAs were sprayed onto the nematode diet. As the concentration of dsRNA increased, the expression levels of the target genes were significantly reduced, leading to notable nematode mortality. However, nematicidal activity varied among the three different dsRNAs. To practically assess these dsRNAs under field conditions, the dsRNAs were applied to the soil containing the nematodes by a drenching application. Significant mortality was observed in treatments with dsRNAs targeting vATPase-B or Pat-10, but not with dsRNA targeting Unc-87. To enhance nematicidal activity in soil, the dsRNAs were formulated with chitosan. This formulation significantly improved the stability of dsRNAs under soil conditions and increased their control efficacy against A. nanus. This study suggests that the drenching technique offers an effective strategy to the control of soil-dwelling nematode pests affecting agricultural crops. Full article

Propsilocerus akamusi (Tokunaga, 1938) larvae serve as key bioindicators for water quality assessment. This study identifies optimal reference genes for RT-qPCR under diverse experimental conditions. Fifteen candidate genes commonly employed in other insect species were selected, candidate genes commonly used in other insect species. Homologous genes were identified in the P. akamusi genome through sequence alignment with their Drosophila melanogaster counterparts. Expression stability across developmental stages, body parts, temperature variations, and deltamethrin/nickel chloride exposures was systematically evaluated using geNorm, NormFinder, BestKeeper, and ΔCt methods. RPL32 exhibited the highest expression stability across different body parts of adults under varying temperature conditions, and RPS11 and RPL8 showed the greatest stability across developmental stages and in larvae exposed to different temperatures. Furthermore, under nickel chloride and deltamethrin treatments, RPS11 and RPL8 maintained the highest expression stability. The results indicated that the expression stability of reference genes varied under different conditions. Among different body parts of adults, RPL32 and RPL4 exhibited the most stable expression. Across different developmental stages, RPS11 and RPL8 performed best in terms of expression stability. Under different temperature treatments, RPL32 and RPL4 remained stable in adults, while RPS11 and RPL8 showed the greatest stability in larvae. Similarly, under nickel chloride and deltamethrin treatments, RPS11 and RPL8 demonstrated the most stable expression in larvae. Through the above research, we can advance ecosystem-impact insights and bolster environmental protection and water quality monitoring. Full article

Structural parameters, such as strain or deflection, were collected by sensors and analyzed to assess the bridge’s structural condition and obtain a reliable reference for bridge maintenance. In the data acquisition and transmission process, sensor data inevitably contains noise and interference, resulting in anomalies, especially data distortion during wireless transmission. These anomalies significantly impact data analysis and structural evaluation. To mitigate the effects of these abnormalities, we conducted the cause analysis. The Sanxia Viaduct was used to design a strain monitoring method as a bridge model. We analyzed vibrating string sensor data collected in the cold environment using the Nair method to eliminate outlier data. The analysis results of strain and temperature trends showed that the data fusion method developed in this study showed high precision and stability and effectively reduced the impact of noise and data anomalies. By monitoring actual bridges, the effectiveness and practicality of the method were validated. The model provides significant information on the development and application of bridge health monitoring technology. Full article

Background/Objectives: Gingival recession poses significant challenges in periodontal therapy, particularly in procedures aimed at achieving predictable root coverage and long-term stability of grafts. Conditioning of the root surface plays a crucial role in improving biomaterial adhesion and facilitating periodontal regeneration. This in vitro study aimed to evaluate the morphological and microroughness alterations of root cementum following different mechanical and chemical conditioning protocols commonly used in mucogingival surgery. Methods: Forty extracted human single-rooted teeth were randomly allocated into eight groups: untreated control, mechanical scaling alone, and scaling combined with ethylenediaminetetraacetic acid (EDTA), citric acid, phosphoric acid, tetracycline, doxycycline, or saline. Surface roughness was measured using contact profilometry, while structural modifications were analyzed via scanning electron microscopy. Results: Statistically significant intergroup differences (p < 0.05) were observed. Baneocin treatment produced the most conservative changes, with limited surface roughness and minimal structural alteration, whereas phosphoric acid, tetracycline, and EDTA caused pronounced demineralization and surface porosity. Citric acid and doxycycline induced moderate alterations, with partial preservation of cementum integrity. The null hypothesis assuming no surface or morphological changes was rejected. Conclusions: These findings indicate that low-aggressiveness agents may achieve an optimal balance between surface decontamination and cementum preservation, which is critical for enhancing graft integration and improving clinical outcomes in root coverage surgery. Full article