Search Results (1,239)

Background/Objectives: Electrospun polyvinylpyrrolidone (PVP) fibers are highly promising for fast-dissolving drug delivery. Methods: In this study, five PVP grades with molecular weights ranging from 4000 to 1,300,000 Da were investigated over a broad concentration range (10–60 w/w%) to evaluate their electrospinnability and dissolution behavior. Results: A well-defined viscosity window of approximately 150–680 mPa·s was identified for the formation of continuous, bead-free fibers. Deviations from this optimal window resulted in electrospraying or jet instability. Continuous fibers were successfully prepared from all investigated PVP grades, including low-molecular-weight PVP K-12 (Mw 4000), demonstrating that appropriate solution viscoelasticity can compensate for limited chain entanglement. Remarkably, in vitro testing revealed that all fibrous formulations exhibited ultrafast disintegration (0.29–1.33 s) and dissolution (0.39–2.32 s). Statistical analysis confirmed no significant differences attributable to polymer molecular weight or fiber diameter, effectively challenging the common assumption that higher-molecular-weight PVP delays disintegration. Instead, the immediate dissolution originates from rapid wetting and capillary-driven fluid uptake, facilitated by the highly porous nano- and microfibrous network. Conclusions: By highlighting the dominant role of macroscopic structural properties over polymer chain length, these findings provide a practical framework for the development of fast-dissolving electrospun PVP-based drug delivery systems. Full article

In the current manuscript, the hot deformation behavior and the thermal processing map of 6082-T6 rolled aluminum alloy sheet were studied. A series of compression tests were conducted using the Gleeble-3500 thermal simulation machine under the conditions of 200–350 °C and 0.001–1 s⁻¹. In order to tackle the stress errors caused by friction and plastic deformation temperature rise, the friction correction model and the adiabatic temperature rise interpolation method were used, respectively, to correct the flow stress curve. Based on the corrected data, a strain-compensated Arrhenius constitutive equation was constructed. Through the 4th-order polynomial fitting of material parameters and strain, the measured and predicted stresses were compared, with the average relative error reaching 10.50%. The thermal processing map was drawn based on the dynamic material model, and the material instability region was concentrated in the low-temperature high-strain rate zone. Within the investigated temperature and strain rate range, the optimal processing window was 320–350 °C and 0.001–0.031 s⁻¹. Combined with microscopic characterization by Optical microscope and transmission electron microscope, it was found that deformation at low temperature and high strain rate was mainly dynamic recovery, and dynamic recrystallization could fully occur at high-temperature low-strain rate. The research results can provide theoretical support for the optimization of the hot forging and hot stamping processes of this alloy. Full article

Consumers’ risk attitudes shape how they evaluate and trade off product attributes, yet most preference estimation approaches overlook risk attitudes, assuming risk neutrality. The resulting preference structures may fail to capture the heterogeneity essential for effective market segmentation and product strategy. We propose a risk-driven preference learning framework that reconceptualizes risk attitude as an integral factor shaping preference structures. Its core is a risk-contingent value function in which risk attitude determines how attributes are traded off. This function infers risk attitudes through deviations from full compensation among attributes under risk neutrality, endogenizing risk-attitude inference within preference estimation, and yields preference structures from behavioral data. The method also identifies distinct preference subtypes within the same risk-attitude category. Validated on 114,317 vehicle reviews from Edmunds, an automotive e-commerce platform, the approach achieves strong in-sample fit to behavioral data. Results show that risk-averse, risk-neutral, and risk-seeking consumers exhibit different preference structures, and the risk-averse group shows pronounced internal heterogeneity. The proposed framework offers a structurally interpretable tool for intelligent decision support in consumer segmentation and product strategies. Full article

A prescribed time-adaptive event-triggered sliding mode control method is proposed for a second-order aircraft antiskid braking system with unmeasurable longitudinal velocity, subject to unknown actuator faults and external disturbances. Based on the time scale transformation technique, a prescribed-time observer is constructed to estimate the unmeasurable longitudinal velocity. A practical prescribed-time super-twisting observer with a saturated gain is designed to estimate the disturbance. Within the prescribed time convergence framework, an adaptive update law and a nonsingular integral sliding surface are developed to compensate for actuator faults. Building on this, a time-varying dynamic threshold event-triggering mechanism is incorporated into the prescribed time-sliding mode control process, while excluding Zeno behavior and reducing the control update frequency. The aforementioned prescribed-time observers and the event-triggered adaptive sliding mode controller form a strict temporal hierarchical architecture. Based on Lyapunov stability theory, it is proved that the closed-loop system is practically prescribed-time stable and that all closed-loop signals are uniformly ultimately bounded. Comparative simulation results verify the effectiveness of the proposed method. Full article

Unauthorized low-altitude UAVs can challenge conventional fixed-parameter interception algorithms through agile maneuvers. This study develops a three-dimensional one-on-one terminal-interception simulation environment that incorporates protected-zone penetration, a within-step geometric interception criterion, and kinematic constraints. The intruder, denoted as the red UAV, combines six physically interpretable maneuver templates to generate structured evasive penetration behavior. The defender, denoted as the blue UAV, augments blended generalized proportional navigation (B-GPN) with a bounded residual corrective acceleration produced by deep reinforcement learning, thereby forming a hybrid architecture that combines a geometry-based nominal guidance command with reward-driven bounded compensation. In standardized tests on 1000 unseen scenarios, the implemented residual PPO pipeline increased the interception rate from 63.8% for nominal guidance to 94.1% (95% Wilson interval: 92.46–95.40%) and maintained at least 88.0% interception under the tested control-delay, kinematic, and noise perturbations. It also achieved the highest interception rate among the evaluated residual-learning implementations under both the stable-configuration comparison and the auxiliary task-side-controlled check; this result is limited to the reported implementations and is not a general ranking of algorithm families. These findings indicate that bounded residual learning can compensate for structural limitations of conventional guidance under the evaluated conditions. Full article

The first step in the analysis of the contact mechanics and leakage prediction of metallic seals applied to nuclear reactor pressure vessels is the proper characterization of the surface topography. At present, two approaches are used for this characterization. On the one hand, there are non-parametric techniques such as HPD and PSD, which retain all the characteristics of the surfaces that have been measured, but the results are high dimensional; hence, they cannot be analyzed analytically. The other type is parametric fractal methods, where the parameters used are fractal dimension D and characteristic scale G, where the analytical derivations can be made; however, this leads to systematic deviations in the mechanical response due to some idealized assumptions, like isotropy, Gaussian distribution, and infinite self-similarity. In this article, we propose an equivalent fractal parameter inversion model (EFPIM) that does not rely on geometric fitting; instead, it fits the mechanical contact behavior of a physical surface. This inversion procedure reduces three errors simultaneously. Thus, the EFPIM does not use D and G as the geometrical fitting variables but rather redefines them as mechanically equivalent ones, the purpose of which is to minimize the difference between the W-M fractal surface and the real measured surface. To address the problem of constrained inversion, we adopt a genetic algorithm with BFGS. To prove its effectiveness, we carried out experiments on C-ring seal surfaces and found that the deviation in the contact area was reduced by an order of magnitude in comparison to traditional structure-function extraction, and the deviation in the approach and the maximum pressure were less than 2%. Moreover, the equivalent parameters shift systematically away from their geometric counterparts in the direction that compensates for the dominant non-ideal deficit of the W-M surface; when both parameters are free, the equivalent fractal dimension decreases, while the equivalent characteristic scale increases, compensating for the absent non-Gaussian deep valleys of ideal W-M surfaces. Existing models of analytical contact and leakage may be directly implemented using equivalent parameters and with accuracy comparable to that of FFT-based simulations, with the modest cost of the offline computations. Full article

Bacterial colonization and biofilm formation on orthopedic and dental implants remain major clinical complications, while conventional systemic antibiotics are often limited by poor penetration into biofilms and infected bone. These limitations have motivated the development of biomaterials with intrinsic antibacterial activity. Hydroxyapatite (HA), a major inorganic component of bone and teeth, possesses excellent biocompatibility, osteoconductivity, and bone-bonding ability but exhibits limited inherent antibacterial activity. Incorporation of therapeutic metal ions, including Ag⁺, Cu²⁺, Zn²⁺, Ti⁴⁺, Co²⁺, Ga³⁺, Sr²⁺, and Ce³⁺, has therefore emerged as a promising strategy for developing multifunctional HA-based biomaterials. This review critically examines the crystal-chemical basis of metal-ion incorporation into HA and discusses how ionic radius, oxidation state, charge-compensation mechanisms, dopant concentration, and synthesis conditions influence lattice occupancy, physicochemical properties, and biological performance. The antibacterial activity of metal-substituted and metal-modified HA systems generally involves interconnected mechanisms, including bacterial membrane damage, intracellular metabolic disruption, interference with enzymes and nucleic acids, reactive oxygen species (ROS)-mediated oxidative stress, and inhibition of bacterial adhesion and biofilm formation. Ag-, Cu-, Zn-, and Ga-containing HA systems show the most consistently reported antibacterial effects, although their efficacy and cytocompatibility depend strongly on dopant concentration and ion-release kinetics. Co-substituted HA may combine antibacterial activity with angiogenic and osteogenic stimulation, whereas Sr-substituted HA is primarily osteogenic and anti-resorptive, with variable antibacterial performance. Ti-modified HA and TiO₂/HA composites exhibit predominantly photoactive antibacterial behavior, while Ce-substituted HA shows concentration-, oxidation-state-, and synthesis-dependent biological effects. The review also evaluates protein adsorption, osteogenic and angiogenic signaling, macrophage-mediated immunomodulation, biological safety, and representative commercial and translational applications. Overall, metal-substituted HA represents a versatile platform for infection-resistant and regenerative hard-tissue biomaterials, provided that composition, phase structure, ion release, antibacterial efficacy, and cytocompatibility are systematically co-optimized before clinical translation. Full article

Accurate fault diagnosis and protection of series-compensated transmission lines remain challenging due to the nonlinear behavior of series capacitors and associated protective devices, which degrade the performance of conventional protection relays under varying operating conditions. To address these challenges, this paper proposes an intelligent ensemble learning-based protection framework for fault detection, fault classification, fault section identification, and fault location estimation in fixed series-compensated transmission networks. The proposed framework integrates an Artificial Neural Network (ANN) and a random subspace ensemble classifier (RSEC), where the ANN performs fault detection, classification, and location estimation, while the RSEC identifies the faulted section using a majority-weighted voting strategy. In addition, four fault indices are formulated to effectively characterize fault conditions and improve diagnostic performance. The proposed framework is evaluated on a 400 kV, 50 Hz series-compensated transmission system under diverse fault scenarios and varying operating conditions, including different fault types, fault resistances, fault locations, compensation levels, and noisy measurements. The results demonstrate an average fault detection time of 4.05 ms, 100% fault classification accuracy, 98.646% fault section identification efficiency, a mean signed fault location error of −0.02988%, and a mean absolute location error of 0.0791%, indicating negligible systematic bias and high localization accuracy. Furthermore, real-time validation using the OPAL-RT digital real-time simulator confirms the computational feasibility of the proposed framework, demonstrating its potential as a reliable, accurate, and computationally efficient solution for intelligent protection and monitoring of modern smart transmission networks. Full article

In industrialized countries, existing regulations generally require the use of renewable energy to the greatest feasible extent. A major difficulty with renewable sources is the inherent fluctuation in their power output due to the main source character. By now, one of the best technologies capable of providing rapid compensation for these fluctuations is hydroelectric power. Hydropower plants, those equipped with hydraulic turbines with fixed blades (e.g., Francis, propeller) are typically designed to operate close to their best efficiency point (BEP) with acceptable load limits in the vicinity due to vibrations and pressure pulsations. Usually, the swirling flow exiting the runner is tailored for peak overall efficiency, which minimizes energy losses in the draft tube cone. When operating away from the design point, draft tube cone losses increase abruptly, and pronounce flow instabilities arise (e.g., vortex rope). This study proposes a new method to control such instabilities that inject a radial-axial water jet into the draft tube cone. Compared with conventional axial water jet injection, the radial-axial jet requires a lower additional flow rate while still effectively suppressing hydraulic instabilities in the draft tube cone. The carried-out analysis was done numerically by using Ansys Fluent 2023 R2. The performed 3D unsteady numerical simulations were carried out to examine the internal flow behavior and evaluate the effect of the radial-axial water jet injection on the unsteady behavior of the flow unsteadiness. Finally, the paper quantifies the relationship between the draft tube pressure fluctuation amplitude and the auxiliary flow rate needed to mitigate these instabilities. Full article

To improve volume stability and durability of cementitious materials, a composite mineral admixture including ground granulated blast furnace slag, fly ash and silica fume was incorporated at a fixed 12% replacement ratio together with varying dosages of an expansive agent (EA). Results show that the composite admixture delays setting while increasing EA shortens setting time. Mechanical properties first increase and then decrease with EA content. The mixture with 6% EA (A4) achieves the best performance, with a 28-day compressive strength of 51.6 MPa. Expansion behavior continuously increases with EA content, but the expansion coefficient peaks near unity at an optimal EA level and then decreases, which indicates effective shrinkage compensation at moderate EA dosages. Durability properties including sulfate resistance and chloride migration resistance follow a similar non-monotonic trend, enhanced at moderate EA levels but degraded at excessive dosages. The A4 mixture exhibits the highest sulfate resistance coefficient and the lowest chloride diffusion coefficient. Microstructural analyses via XRD, EDS, SEM and MIP reveal differences in hydration products and pore structure characteristics among the mixtures. The composite mineral admixtures contribute to pore refinement through hydration and filler effects, while an appropriate EA dosage provides shrinkage compensation and improves microstructural stability. These combined effects reduce harmful pore content and pore connectivity, thereby improving resistance to sulfate and chloride transport. Excessive EA leads to over-expansion, inducing microstructural defects and disrupting pore structure integrity, which ultimately compromises durability. Therefore, durability enhancement of the composite system is governed by a balance between expansion compensation and pore structure refinement, rather than simply the increase in hydration products. Full article

The severe early-age shrinkage of alkali-activated slag is a primary bottleneck restricting its engineering application. In this work, a novel shrinkage control strategy is proposed, dominated by the physical control of vacuum dehydration and assisted by the chemical compensation of MgO. The synergistic mechanism of this strategy in the AAS system was revealed by multi-scale characterization methods (XRD, FTIR, TG, NMR, BSE, and pore solution analysis). Firstly, vacuum dehydration greatly advances the development window of capillary pressure to the early stage (<6 h) of the material in the significant viscoelastic stage by forcibly removing free water between the interlayer and capillary pores. Most of the shrinkage strain energy can be dissipated through the early creep behavior of the slurry, and the strong negative pressure induces the conversion of mesopores to macropores, thereby effectively reducing the equilibrium capillary cracking driving force. Secondly, the late hydration of an appropriate amount of MgO generates magnesium silicate and hydrotalcite phases, which provide a continuous chemical micro-expansion for the matrix to compensate for residual shrinkage and moderately optimize the local pore defects induced by dehydration. The results show that in the sodium silicate solution and sodium hydroxide activating system, the synergistic effect reduces the total shrinkage rate of 28 days by 37.86% and 29.26%, respectively. Additionally, the compressive strength of hardened samples increases by about 20%. This study provides a new theoretical basis for the design of low-shrinkage and high-performance alkali-activated materials based on the physical–chemical coupling mechanism. Full article

Conventional event-triggered attitude controllers effectively reduce communication frequency but usually employ a zero-order-hold strategy between consecutive triggering instants, resulting in abrupt control torque variations that may degrade actuator performance. To address this issue, this paper proposes a self-learning-based integral event-triggered control strategy for spacecraft attitude stabilization. The proposed method uses stored historical commands and elapsed inter-event time to construct a bounded time-varying compensation signal without increasing the communication or controller-update rate. Lyapunov-based analysis establishes uniform ultimate boundedness under bounded disturbances, actuator faults, and inertia uncertainties, while Zeno behavior is excluded. In the reported comparison, the proposed self-learning integral event-triggered controller achieves lower mean attitude and angular-velocity errors together with reduced error variances, while increasing the average inter-event interval by approximately $43\%$ and reducing the number of triggering events by approximately $30\%$. Full article

Scissor lifts are versatile lifting mechanisms that must satisfy stringent safety and reliability requirements. Therefore, accurate determination of their force and kinematic parameters is essential. An analytical approach for the design calculation of a bottom-driven scissor lift was developed. The proposed approach incorporates extension and compression springs to reduce the required driving force in the lowest platform position and improve the energy efficiency of the mechanism. A force analysis model of the scissor lift was developed, and the support reactions and the required driving force were determined as functions of the platform lifting height. Based on the kinematic analysis, the extreme linear and angular displacements of the scissor mechanism arms were determined. The functional dependences of the upper and lower spring deformations on the inclination angle of the scissor arms were established, characterizing the operating behavior of the load compensation system. The results demonstrate that the proposed spring compensation system reduced the required driving force by 26.5% and the internal forces in the scissor mechanism by 19.8–39.6% compared with the configuration without spring compensation. The developed analytical approach enables the determination of the force and energy characteristics of a bottom-driven scissor lift and the selection of reasonable spring parameters to reduce drive energy consumption. Full article

This paper investigates formation trajectory tracking control for multiple autonomous underwater vehicles (AUVs) subject to actuator saturation and unknown lumped disturbances. An adaptive fixed-time nonsingular terminal sliding mode (AFxTNTSM) control method is proposed to achieve formation tracking under input constraints. First, a fixed-time nonsingular terminal sliding mode (FxTNTSM) surface is constructed to improve the convergence behavior of the position and velocity tracking errors while avoiding the singularity associated with conventional terminal sliding mode control. Second, a fixed-time dynamic auxiliary system (FxTDAS) is designed to compensate for the input deviation caused by actuator saturation. In addition, an adaptive robust compensation law is incorporated to handle unknown lumped disturbances without requiring prior knowledge of their upper bounds. Lyapunov-based analysis proves that the closed-loop tracking errors are practically fixed-time stable, and the settling-time upper bound is independent of the initial conditions. At this stage, validation is limited to numerical simulations, which illustrate that the proposed AFxTNTSM control method maintains the prescribed formation, attenuates time-varying lumped disturbances, and keeps the actual control inputs within the actuator saturation limits. Full article

In this study, the response characteristics of spaceborne electronic equipment under actual mounting boundary conditions were evaluated, and an equivalent contact stiffness-based modeling technique was proposed to compensate for the limitations of conventional boundary-condition-based analysis. Finite element analyses were performed for three configurations: an initial design, a structure with increased contact area, and a structure with added stiffeners. Random vibration tests were then conducted with accelerometers directly attached to the PCBs and housings under actual mounting conditions, and the results were compared with conventional analysis results. The conventional analysis overpredicted the actual responses for all configurations, showing discrepancies in response magnitude, housing bottom-surface behavior, and natural frequency distribution. These discrepancies were attributed to insufficient representation of the bottom-surface contact effect formed under actual mounting conditions. Therefore, an empirical equation for the equivalent contact stiffness was established by incorporating fastening force, effective contact area ratio, bottom-surface thickness, and effective span length, and implemented using CBUSH-element-based contact modeling. The proposed method improved the correlation between test and analysis results for all three configurations, demonstrating its applicability for reliable response prediction and overdesign reduction at the early design stage. Full article