Search Results (15,081)

The progression of skeletal senescence under mechanical unloading conditions elevates fracture risk, emerging as a critical health challenge for the general population and astronauts during spaceflight. Nevertheless, current therapeutic strategies demonstrate persistent limitations in efficacy and safety, with unresolved challenges in long-term sustainability. Baicalein, a natural flavonoid compound, exhibits favorable anti-aging and anti-inflammatory effects, while its therapeutic potential and underlying mechanism in bone disorders remain unknown. In this study, a hind limb unloading (HLU) rat model was employed as a disuse simulation, after which the HLU rats received baicalein treatment by gavage at 30 mg·kg⁻¹·day⁻¹ for 4 weeks. Our results show that baicalein mitigates disuse-driven skeletal aging by ameliorating trabecular microstructure (Tb. N increased by 38.04%), accelerating bone mineral apposition rate (MAR increased by 42.76%), increasing bone mineral density (1.20-fold vs. model group), improving biomechanical strength (ultimate load +31.64%) and downregulating senescence-associated markers p16, p21, p53 in tibial tissue. Additionally, baicalein alleviated the unloading-induced high bone turnover, as evidenced by reducing serum levels of both osteogenic biomarkers ALP, PINP, BGP and osteoclastic biomarkers TRACP 5b, RANKL, NTX. Moreover, baicalein suppressed the inflammatory response caused by mechanical unloading, attributed to the restriction of pro-inflammatory factors TNF-α, IL-6, IL-8, IFN-γ and the promotion of anti-inflammatory cytokines IL-4, IL-10. Importantly, baicalein ameliorated the unloading-induced gut microbiota disorder through the diminished abundance of Proteobacteria and elevated abundance of Actinobacteria and Firmicutes, which were negatively associated with inflammatory response. Overall, our study provides evidence that baicalein inhibits the inflammatory response through the regulation of gut microbiota balance, which plays a role in preserving bone homeostasis. Full article

This paper investigates maximum power point operation in a large-scale offshore wind energy conversion system equipped with a permanent magnet synchronous generator (PMSG). The study focuses on a 15 MW reference offshore wind turbine and aims to determine the operating conditions required for maximum energy extraction under variable wind speeds. Mathematical models of the wind turbine and the generator are developed using selected parameters derived from the International Energy Agency (IEA) 15 MW Reference Wind Turbine, while the operating characteristics are represented by a simplified analytical model. Based on these models, the turbine and generator power characteristics are derived and the equivalent generator load resistance values corresponding to maximum power point operation are determined. Dynamic simulations are performed for several wind speed profiles to evaluate the evolution of the operating point and the associated stability properties. The analysis reveal two equivalent resistance solutions, with the higher value providing stable operation under wind-speed variations and the lower value defining a potentially unstable operating branch. Furthermore, an energy-based control strategy is proposed to compensate for the influence of the large mechanical inertia and to improve maximum power point tracking performance. The proposed model represents a generic 15 MW offshore wind energy conversion system and focuses on the variable-speed operating region and its associated energetic dynamics. The proposed methodology provides a practical framework for energy-based control and stability assessment of next-generation offshore wind turbines rated above 15 MW. Full article

To improve voltage support at the point of common coupling of renewable energy collection stations connected to weak grids, this paper proposes a synchronous machine-like outer reference generator for a conventional fixed-PQ voltage-source converter (VSC). The proposed versatile static synchronous machine (VSSM) emulates the excitation and reactive power-voltage regulation of a synchronous generator, maps the resulting transient internal electromotive force to an exact reactive power reference, and applies converter capability and ramp rate limits with an equivalent Q-tracking response. A two-stage strategy further uses fast dynamic compensation to clamp voltage and slower static compensation to release bidirectional dynamic reserve. In the WSCC nine-bus benchmark, all controllers use the same 100 MVA VSC, +/−80 Mvar limit, 0.04 s reactive power inner loop, and 10 pu/s ramp limit. After a three-phase fault and line tripping, the minimum post-fault bus 8 voltage is 0.9452 pu with the VSSM, compared with 0.8755 pu for the calibrated PI-SVG and 0.7660 pu for fixed Q; Q-U droop gives 0.9492 pu but requires 0.33 s for sustained recovery above 0.95 pu, compared with 0.23 s for the VSSM. A positive-, negative-, and zero-sequence extension also evaluates a single-line-to-ground fault. Finally, an anonymized actual receiving-end grid model shows an approximately 40 ms improvement in voltage recovery and reduced steady-state loading of dynamic reactive sources. All results are obtained from offline simulations. Full article

Ultra-reliable and low-latency communication (URLLC) services require strong latency and reliability performance under dynamic network conditions. However, achieving robust URLLC performance under single access is challenging due to user mobility, time-varying traffic loads, and fluctuating access availability. Multi-access operation provides an opportunity to enhance service robustness by exploiting heterogeneous connectivity. Access Traffic Steering, Switching, and Splitting (ATSSS), introduced in 3GPP Release 16, enables operator-controlled multi-access traffic management within the fifth-generation (5G) core network. In this paper, we propose the Reliability and Latency-Aware ATSSS Framework (RL-AF) for URLLC services, which incorporates latency and reliability awareness into adaptive traffic steering and redundant transmission decisions. RL-AF formulates the joint control problem as a constrained Markov decision process and employs a primal–dual deep reinforcement learning approach to balance latency–reliability performance and the network usage cost. Trace-driven simulations benchmark RL-AF against Cell-Only, Cost-Min (Wi-Fi-only), Redundant, RTT-Min, and Loss-Min schemes. At a residual RTT threshold of 30 ms and a packet loss constraint setting of ${10}^{-3}$, RL-AF achieves an approximately 94.4% RTT success rate and an empirical packet loss ratio of $1.0\times {10}^{-3}$ with an average network usage cost of 4.14, corresponding to a 17.2% cost reduction relative to always-redundant transmission. Full article

Ibuprofen is a widely used non-steroidal anti-inflammatory drug (NSAID) with antipyretic, analgesic, and anti-inflammatory activity; however, its low aqueous solubility limits its dissolution rate and, consequently, its oral bioavailability. This study aimed to develop and physicochemically characterize an ibuprofen-loaded self-nanoemulsifying drug delivery system (SNEDDS) using a Box–Behnken experimental design. Fifteen formulations were prepared and evaluated based on CQAs: cloud point, robustness to dilution, self-emulsification time, droplet size, zeta potential, and polydispersity index (PDI). The experimental responses were subjected to statistical analysis; robustness to dilution as the only response yielding a statistically valid and predictive model within the studied design space, which was used as the sole optimization criterion. The optimal formulation was evaluated and characterized according to previously established CQAs and subjected to thermodynamic stability testing and stress testing over one month. The optimized formulation exhibited rapid self-emulsification, with a self-emulsification time of 37.02 s, a cloud point of 64.87 °C, and high robustness to dilution across different pH conditions and dilution volumes. Moreover, it exhibited a mean droplet size below 157 nm, a zeta potential of −15.43 ± 0.58 mV, and a PDI of 0.251, suggesting adequate colloidal stability and uniformity of the dispersed system. These physicochemical attributes support the potential of the developed system as a platform for further biopharmaceutical evaluation of ibuprofen oral delivery. Full article

Robotic gait technologies can deliver intensive, repetitive, task-oriented stepping, but multimodal platforms require careful integration before clinical testing. This concept-level technical proof-of-concept describes Li-Walk^®, an investigational fixed robotic gait-training platform combining a treadmill-synchronized lower-limb exoskeleton, dynamic body-weight support, phase-synchronized infrared-A (IR-A) thermal biofeedback, directional acoustic feedback, a semi-immersive display, camera-derived body representation, and artificial intelligence (AI)-supported therapist guidance. The architecture is defined through subsystem interfaces, implementation status, operational states, explicit risk controls, and a staged validation roadmap. No human participants, patient-level data, bench datasets, or statistical analyses were involved; subsystem factory checks did not characterize integrated performance. The installed exoskeleton has four actuated sagittal axes at the hips and knees, with in-series load cells supplying interaction-force inputs for contingent ipsilateral IR-A cueing under reduced guidance. The integrated AI module combines rule constraints with a case-based design, but has no trained statistical model or clinical cohort database; the therapist retains parameter-setting authority. Live video and avatar modes are implemented, whereas independent thermal monitoring and structured recommendation audit trails remain planned. Trigger thresholds, sampling rates, end-to-end latency, exposure limits, and fault responses remain undocumented or unverified. The contribution is a conceptual integration framework that distinguishes implemented functions, declared specifications, and unverified requirements. Independent mechanical, thermal, software, and human-factors validation, followed by appropriately authorized human studies, is required to establish safety, usability, technical reproducibility, and any incremental rehabilitation benefit. The optional thermal branch requires particular safeguards for impaired thermal sensation and cannot be assumed to add clinical value beyond robotic gait training alone. Full article

A large-section tunnel has a large excavation span and high construction difficulty and is prone to roof fall and collapse and other engineering disasters under complex geological conditions. Due to the influence of the size effect, it is difficult for surrounding rock to form an arch and form an effective load-bearing structure. A timely and proactive anchoring support system is required to fully utilize the self-bearing capacity of the surrounding rock. Therefore, this paper studies a case of high-prestressed active support based on a large cross-section tunnel in eastern China, clarifying that high-prestressed active support can effectively control rock stress, plastic zone distribution, and surrounding rock deformation. Based on a prestress conversion test, the support structure and application method that meet the high-prestress application requirements of the tunnel engineering site are clearly defined. An active support field test was carried out, and the influence of prestress on the supporting structure stress and the surrounding rock deformation was analyzed. The results show that compared with a no-prestress support scheme, active support with 100 kN high prestress increased the utilization rate of anchor rod strength by 35.29%, reduced the external load on the arch by 40.9%, and reduced the settlement of the arch crown by 34.9%. This indicates that high-prestressed active support can improve the self-bearing capacity and control effect of the surrounding rock. Full article

Background/Objective: Pain self-efficacy is an important determinant of pain-related disability and recovery in individuals with musculoskeletal disorders. Although the Arabic Pain Self-Efficacy Questionnaire (PSEQ) has demonstrated satisfactory psychometric properties in individuals with chronic low back pain, its measurement properties have not been established in individuals with neck pain. This study evaluated the measurement properties of the Arabic PSEQ in individuals with neck pain. Methods: A prospective cohort study was conducted in 118 Arabic-speaking individuals with neck pain recruited from multiple clinics. The Arabic PSEQ, Neck Disability Index (NDI), RAND-36 Health Survey, and Numeric Pain Rating Scale (NPRS) were completed by the participants. Structural validity was examined using exploratory factor analysis. Internal consistency was assessed using Cronbach’s alpha. Test–retest reliability (intraclass correlation coefficient (ICC_2,1)), measurement error (standard error of measurement (SEM), minimal detectable change (MDC₉₅)), and agreement (Bland–Altman analysis) were also examined. Construct validity was assessed by testing predefined hypotheses regarding correlations with comparator measures. Results: The analysis revealed a dominant one-factor structure explaining 66.4% of the variance and item loadings ranging from 0.72 to 0.89. Cronbach’s alpha of 0.94 suggested excellent internal consistency. Test–retest reliability was good (ICC_2,1 = 0.85), with an SEM of 4.38 and MDC₉₅ of 12.14. Four of five (80%) predefined construct validity hypotheses were confirmed, demonstrating expected correlations with disability, physical functioning, emotional well-being, and pain intensity. Conclusions: The Arabic PSEQ demonstrated a one-factor structure, good test–retest reliability, acceptable measurement error, excellent internal consistency and sufficient construct validity in individuals with neck pain. These findings support its use as a patient-reported outcome measure with good measurement properties for assessing pain self-efficacy in Arabic-speaking individuals with neck pain. Full article

Polymer-based self-sensing composite intelligent materials have become an innovative application in the field of road monitoring. Aiming at the shortcomings of existing models that mostly focus on single-filler systems and rarely consider the dual evolution of tunneling gap and conductive network, this study establishes a strain-resistance response model for micro–nano-structured polymer composite smart materials by analyzing four conductive models and taking the tunneling effect as the core conduction mechanism. Taking CNTs-CB/epoxy composites as the object, it constructs a 3D resistive network model, optimizes the Simmons tunneling current model, and deduces the functional relationships of effective conductive pathways and tunnel gap with tensile strain, thus establishing the strain-resistance change rate model. Validated by experimental data and data from the literature on diverse composite systems, the model shows high fitting accuracy (R² > 0.98). It reveals that the resistance change rate is linear with small strain and grows exponentially with increased strain, failing when the conductive network is damaged. The model is verified for monotonic tensile loading, with a concise analytical form and clear physical meaning of parameters, providing theoretical support for design and optimization of composite strain sensors for road monitoring. Full article

Archived distribution studies are difficult to reuse when source calculations, public asset records, processed outputs, and proprietary model files support different levels of inference. This study develops a claim-specific audit for incomplete distribution network archives. Three evidence gates distinguish documentary consistency, asset attribution, and decision-specific adequacy; four archive stages separate preservation and integrity documentation from executable import and numerical reproduction. The method was applied to three retained operating points of a 13.8 kV feeder in Ambato, Ecuador. Eight roofs associated in the worksheet with T54 (code 21076) yielded 205.364 kWp from 1506 m² under the retained sizing assumptions. A public EEASA GIS record corroborated the code, 125 kVA rating, and 13.8/0.22 kV nominal voltages, while the physical-to-model correspondence remained unverified. In the maximum-PV state labeled 1.5825 MWp, the archived feeder-head export was 0.670 MW, and the archived T54 loading metric was 156.915%, triggering a nameplate-based review without establishing thermal overload. Only T54 satisfied the four-element documentary attribution rule; model execution and numerical reproduction were not tested. This contribution is a domain-specific synthesis of established provenance and reproducibility principles that makes claim boundaries explicit. It remains a single-case demonstration, without empirical evidence of improved analyst agreement or decision quality. Full article

TiN/CrN multilayer coatings with bilayer periods of 20 and 30 nm and TiN:CrN layer thickness ratios of 1:1, 1:2 and 2:1 were deposited on 40Kh steel substrates by pulsed direct current magnetron sputtering (pDCMS). The phase composition (XRD), microstructure (SEM), mechanical (nanoindentation, scratch testing), tribological (dry sliding and boundary lubrication), and corrosion (potentiodynamic polarization in 3.5 wt.% NaCl) characteristics of the coatings were examined. Increasing the TiN volume fraction increased nanohardness and elastic modulus reaching a maximum H³/E² = 0.186 GPa. The Λ30-TiN(20)/CrN(10) coating showed the best adhesion (L_c1 = 14.4 N, L_c2 = 17.7 N, CPR_S = 48 N²) and the lowest wear rate both under dry sliding and under boundary lubrication (1.2×10⁻⁵ mm³/(N·m)). In contrast, CrN dominance (Λ30-TiN(10)/CrN(20)) sharply degraded the tribological behaviour (the wear rate increased by almost an order of magnitude) and caused catastrophic localized pitting in the corrosion tests. At the same time, the best corrosion resistance (E_corr ≈ −0.47 V, the most extended quasi-passive region) was achieved at the smallest bilayer period. A balanced composition, Λ20-TiN(10)/CrN(10), owing to the highest density of interlayer boundaries, effectively blocks through-thickness growth defects. The architectures that are optimal in terms of mechanical/tribological and of corrosion criteria do not coincide, which indicates that the TiN:CrN ratio has to be chosen according to the dominant type of service loading. The results obtained show that varying the thickness ratio of the TiN and CrN layers at bilayer periods of 20 and 30 nm makes it possible to tune the balance of hardness, wear resistance, adhesion and corrosion resistance of multilayer coatings on structural steels. Full article

The increasing penetration of nonlinear industrial loads, distributed renewable generation, and intelligent electrical infrastructures requires active power filters capable of simultaneously providing high-performance harmonic mitigation, reactive power compensation, coordinated operation of multiple converters, and deterministic real-time implementation. Conventional centralized shunt active power filters (SAPFs) exhibit limited scalability, while optimization-based approaches often compromise deterministic execution because of their computational complexity. To address these challenges, this paper proposes a Distributed Quantum Multi-Shunt Active Power Filter (Quantum Multi-SAPF) that combines deterministic-based local current control with asynchronous quantum-assisted supervisory optimization. The proposed architecture employs four distributed SAPF units operating under a hierarchical cyber–physical framework. The lower control layer, implemented on a MATLAB R2026a, includes all fast electrical functions—signal acquisition, SOGI-based synchronization, Clarke transformation, instantaneous $p$–$q$ current reference generation, current regulation, interleaved PWM modulation, and protection—which are executed deterministically at a switching frequency of 15 kHz. The upper supervisory layer operates asynchronously at 20 Hz and formulates converter coordination as a quadratic unconstrained binary optimization (QUBO) problem solved using Quantum Approximate Optimization Algorithm (QAOA) allocation together with Variational Quantum Eigensolver (VQE) predictive correction. This multi-rate architecture separates fast electrical dynamics from slow supervisory optimization, ensuring that uncertain optimization latency does not affect converter stability. The proposed controller is validated through comprehensive switching-level simulations on the MATLAB R2026a platform. Numerical results demonstrate a reduction in source current total harmonic distortion from 24.615% to 0.142%, corresponding to a 99.423% harmonic reduction, while improving the source power factor to 0.99999 and achieving 99.999% reactive power compensation. The distributed four-SAPF synchronization network maintains coherent phase alignment among all converter units throughout the simulation, thereby supporting coordinated compensation and balanced current sharing. This synchronized operation contributes to highly accurate compensation current tracking, with an RMS tracking error of only 0.026 A, while limiting the source current unbalance to 0.026%. These results confirm the effectiveness of the distributed synchronization and local control architecture in maintaining coordinated and balanced operation of the four parallel SAPFs. The proposed interleaved modulation strategy, combined with optimized current sharing, maintains balanced converter utilization while suppressing circulating currents without requiring a dedicated circulating current controller. The proposed Distributed Quantum Multi-SAPF establishes a scalable framework that combines deterministic industrial control with quantum-assisted supervisory optimization. The architecture provides high harmonic compensation capability, near-unity power factor, balanced converter utilization, comprehensive Safe Operating Area supervision, and practical industrial feasibility, making it a promising solution for future smart grids, renewable energy integration, electric vehicle charging infrastructures, and intelligent power quality conditioning systems. Full article

To improve post-fault service restoration and network reconfiguration in distribution networks with distributed generation, this paper proposes a fault recovery and reconfiguration method based on a membrane computing multi-objective optimization algorithm. The proposed method formulates the restoration problem as a multi-objective optimization model that simultaneously considers load-restoration maximization, switching-operation minimization, network-loss reduction, and voltage-deviation minimization, while prioritizing the restoration of critical loads. Within the membrane-computing multi-objective optimization algorithm framework, the hierarchical parallel structure and evolutionary mechanisms of membrane systems are employed to enhance global search capability. Non-dominated sorting and crowding-distance calculation are incorporated to generate a well-distributed Pareto solution set, providing decision-makers with multiple candidate schemes for island partitioning and network reconfiguration. A weighted decision-making strategy is then used to select the optimal restoration scheme from the Pareto solution set. The proposed method is validated on the IEEE 33-bus distribution system. Simulation results show that, under distributed generation integration, the proposed method can effectively partition electrical islands, improve critical-load restoration, reduce network losses and voltage deviations, and support efficient post-fault restoration and reconfiguration of distribution networks. Compared with BWO, the best-performing benchmark method, the proposed method increases the total load-restoration rate from 92.1% to 95.3%, representing an improvement of 3.2 percentage points. It also reduces active power losses from 112.6 kW to 89.4 kW, a reduction of 20.6%, and decreases the maximum voltage deviation from 0.036 p.u. to 0.023 p.u., a reduction of 36.1%. Full article

Cross-dataset network intrusion detection faces challenges arising from distribution shifts, heterogeneous feature fields, changing attack distributions, and unreliable explanations across data sources. To address these problems, this paper proposes a fuzzy-enhanced cost-aware Low-Rank Adaptation (LoRA) inference model with multiple security experts. The model uses Qwen2.5-7B-Instruct as a shared backbone and constructs five lightweight LoRA security experts for normal traffic, volumetric attacks, code execution attacks, web application attacks, and reconnaissance behaviors. A cost-aware router selects the appropriate expert by jointly considering neural adaptability, fuzzy consistency derived from raw traffic features, inference cost, and runtime load. To improve evaluation reliability, the model further integrates a leakage-free data protocol with separate raw and standardized feature streams, as well as a traffic-semantic consistency verification module. Across four experimental corpora derived from three independently collected data sources, the proposed method achieves a Macro-F1 of 0.887 on the pooled test set. Parameters are selected on the validation set subject to a contradiction rate of no more than 0.05 and a low-confidence trigger rate of no more than 0.10, and are then held fixed for testing. The contradiction rate among test outputs meeting the verification score threshold is 0.048. This metric reflects output consistency under the selected conditions and does not constitute an independent assessment of explanation quality. Full article

Specimen-scale fitting can reproduce interlaminar fracture in carbon-fiber-reinforced aluminum laminates (CARALL) but obscures the physical origin of cohesive-zone parameters. We present a multiscale framework integrating molecular dynamics (MD), a representative volume element (RVE), finite element (FE) modeling, and opening-dominated asymmetric double-cantilever-beam (DCB) tests. At modeled high rates, an ideal nonbonded Al/epoxy interface exhibited normal and tangential strengths of 470.09 and 352.93 MPa, respectively. Across 0.001–0.005 Å/fs, normal and tangential peak tractions increased by 5.93% and 5.82%, respectively, whereas traction-separation integrals varied nonmonotonically. These single-atomistic-realization descriptors were transferred to an RVE containing Al/matrix and fiber/matrix interfaces. In this morphology, fiber/matrix debonding preceded Al/matrix damage in all three realizations, and the RVE yielded mean effective normal and tangential strengths of 27.42 ± 0.33 and 39.04 ± 0.65 MPa, together with mean Mode I and Mode II fracture energies of 0.36 ± 0.02 and 0.81 ± 0.04 N/mm, respectively, where the means and standard deviations are taken over the three stochastic fiber realizations. The RVE-derived strengths and fracture energies were assigned directly to the DCB model without fitting the experimental response. The FE peak load was 44.48 N, 5.50% above the four-specimen mean of 42.16 ± 1.22 N, and the predicted damage location was qualitatively consistent with the observed Al/matrix interfacial damage. Because the interface model is idealized and the comparison rests on load–displacement data without synchronized crack-length measurements or independent fracture-resistance data, these results are reported as a configuration-specific assessment of the transfer procedure rather than as a quantitative validation; the transferred parameters are not intended to predict the chemically and structurally complex anodized interface. Full article