Search Results (2,943)

Atherosclerosis is a complex, multifactorial disease that progresses through distinct stages: initiation, progression, and complication, ultimately leading to acute coronary syndromes (ACS). Endothelial cells (ECs), vascular smooth muscle cells (VSMCs), and macrophages are central players in this process, influencing plaque stability and vulnerability. Insulin-Like Growth Factor 1 (IGF-1), soluble-Klotho (S-Klotho), and the Growth Hormone Receptor exon 3 deletion polymorphism (GHRd3) have emerged as key modulators of vascular health, impacting these cellular components through various mechanisms. IGF-1 supports endothelial function, enhances VSMC survival and migration, and mitigates inflammation by inhibiting macrophage recruitment and activation, ultimately reducing the risk of plaque destabilization. S-Klotho, an anti-aging protein with potent anti-inflammatory and antioxidant properties, has been linked to vascular protection, with its deficiency associated with endothelial dysfunction, vascular calcification, and impaired VSMC survival. Evidence suggests that IGF-1 may enhance Klotho shedding, indicating a potential synergistic role in maintaining vascular integrity. This narrative review aims to outline the fundamental stages of atherosclerosis progression, consolidate current evidence on the roles of IGF-1 and S-Klotho in modulating key cellular components of atherosclerosis, and shed light on their potential involvement in plaque healing—an area that remains largely unexplored. By integrating established molecular mechanisms, we explore how these factors may contribute to endothelial integrity, VSMC survival, and macrophage activation and polarization, potentially shaping a more stable plaque phenotype and influencing future therapeutic strategies in cardiovascular disease. Full article

Safe and energy-aware navigation is still difficult for unmanned surface vehicles (USVs), especially in cluttered waters where obstacles, smooth motion, and wind or current effects must be considered at the same time. If these issues are handled separately, the path may become longer and the vehicle may turn more often, which raises propulsion effort and hurts stability. To reduce these problems, a hybrid path planning method called ${\theta }^{\ast }$-APF-Q is proposed, and it combines global planning, learning-based decisions, and local adjustment in a three-layer structure. First, an any-angle ${\theta }^{\ast }$ global planner is employed to generate a near-optimal backbone trajectory by line-of-sight pruning, thereby reducing redundant waypoints and limiting detours. Second, an enhanced tabular Q-learning model is executed in an expanded eight-direction action space, and policy learning is guided by a multi-objective reward that jointly encourages distance reduction, alignment with ocean current and wind-induced forces for energy saving, smooth heading variation to suppress excessive steering, and maintenance of a safety margin near obstacles. Third, an adaptive artificial potential field (APF) module is used for real-time local correction, providing repulsion in high-risk regions and assisting trajectory smoothing to reduce unnecessary turning operations. A decision bias strategy further couples instantaneous APF forces with long-term state–action values, while the influence weight is adaptively adjusted according to environmental complexity. The algorithm is validated on the randomly generated marine grid maps and on the real-world satellite map scenario, with comparisons against a conventional four-direction Q-learning baseline. Across randomized tests, average path length, turning frequency, and the composite energy indicator are reduced by 22.3%, 55.6%, and 26.4%, respectively, and the success rate increases by 16%. The results indicate that integrating global guidance, adaptive learning, and local reactive decision making supports practical, energy-aware USV navigation. Full article

This paper presents a systematic experimental comparison of three sliding-mode-based current control strategies—traditional sliding mode control (SMC), fast terminal sliding mode control (FTSMC), and super-twisting sliding mode control (STSMC)—applied to a grid-connected five-level active neutral point clamped flying capacitor (5L-ANPC-FC) inverter. Unlike existing studies that typically investigate a single controller or topology, this work provides a fair, hardware-validated benchmark under identical operating conditions, enabling a clear assessment of convergence speed, harmonic performance, robustness, and implementation complexity. All controllers are designed within a unified framework and their stability is rigorously analyzed using Lyapunov theory. Experimental evaluations are conducted under steady-state operation, step changes in reference current, grid-voltage sag/swell, and DC-link voltage variations. The results demonstrate that while all three controllers ensure robust current tracking and inherent DC-side capacitor voltage balancing without additional control loops, FTSMC achieves the lowest grid-current total harmonic distortion (THD) and fastest convergence. STSMC effectively suppresses chattering, and traditional SMC offers a simple yet reliable baseline solution. The presented findings provide practical design guidelines for selecting appropriate sliding-mode controllers in high-performance multilevel inverter applications. Among the assessed control techniques, FTSMC has the most rapid dynamic response, characterized by a rise time of 0.1 ms and a minimal grid-current THD of 1.95%, indicating exceptional steady-state and transient performance. STSMC markedly diminishes chattering and ripple, attaining a THD of 2.04% with enhanced waveform smoothness relative to traditional SMC. Conversely, traditional SMC offers a more straightforward implementation but demonstrates elevated ripple and THD levels of around 2.29%, along with a peak current inaccuracy of 6–8%. The results underscore the trade-offs between implementation simplicity, dynamic responsiveness, and harmonic performance of the evaluated control techniques. Full article

Sustainable economic development involves reducing heavy reliance on fossil energy resources and their associated environmental impacts. The complexity of this task increases significantly in oil-producing countries, given the hydrocarbons’ role in economic growth, GDP, and exports. In such cases, decoupling economic growth, energy consumption and emissions should be achieved gradually to ensure a smooth transition, which will require the development of a reliable approach. This study aims to develop a strategy to identify potential pathways for economic growth and energy decoupling in the oil industry. Given the characteristics of the transition process, the feasibility of long-term solutions remains uncertain, and special measures are needed to enhance the reliability of decisions. An approach that combines assessing the economic–environment–emissions nexus, developing fuzzy transition scenarios, and applying multi-criteria and probabilistic decision-making methods has been designed to identify reliable pathways for the energy transition and sustainable development in oil-dependent countries. This allows us to create reliable and compromise scenarios that consider social, technological, environmental, economic and political factors. This study employed Azerbaijan as a case study. Analysis of key indicators revealed strong correlations between country GDP, energy production, and emissions. The MCDM calculations of the obtained feasible scenarios show the optimality of the scenario assuming a decrease in oil production while maintaining natural gas as usual, significantly increasing solar, and moderately increasing wind and hydro energy production. Decisions reflect global economic and energy-sector trends, expert opinions, and the current realities of Azerbaijan’s economy. Full article

This study employed near-infrared (NIR) spectroscopy for real-time spectral acquisition of fermentation broth in lab-scale bioreactors, comparing the performance of transflectance and transmission sensors through glucose modeling and prediction while optimizing modeling approaches. The results demonstrated superior adaptability of transflectance sensors in fermentation environments: in conventional fermentation, glucose models exhibited lower errors (RMSEC = 4.087 g/L, RMSEV = 9.829 g/L) compared to transmission sensors (RMSEC = 5.972 g/L, RMSEV = 10.904 g/L), with significantly higher predictive performance (RPD = 3.735 vs. 2.369), indicating enhanced fitting accuracy and stability. In complex natural media containing peptone and yeast extract, transmission sensor performance deteriorated dramatically due to turbidity interference (R²_cal = 0.134), whereas transflectance sensors maintained robust performance (R²_cal = 0.993), confirming their adaptability to complex matrices. Regarding modeling strategies, the 1550–1700 nm spectral region demonstrated optimal feature extraction capability (RMSEC = 3.269 g/L, R²_cal = 0.987). Basic preprocessing methods such as the moving average smoothing method have become the preferred preprocessing methods, as they strike a balance between calibration and prediction performance. Outlier removal analysis revealed that moderate elimination of 12 high-error samples (accounting for 30% of the total 39 samples) reduced RMSEC to 1.441 g/L and improved R²_cv to 0.996, optimizing model performance; however, excessive removal of outlier samples degraded model capability, necessitating judicious sample selection. For fixed total sample sizes, calibration sets comprising 70–80% of samples yielded more reliable predictions. In conclusion, transflectance sensors demonstrate superior compatibility with multicomponent fermentation systems. Combined with wavelength selection, moving average preprocessing, and rational sample removal and partitioning strategies, this approach provides an effective solution for NIR-based online glucose monitoring. Full article

The start-up process of water-lubricated bearings (WLBs) exhibits strong nonlinearity and is highly sensitive to the surface topography of both the bush and the journal. However, due to machining errors and operational wear in practical manufacturing and service, the bush inevitably develops surface waviness and wear, which significantly influence its start-up behavior. This issue is particularly critical in high-speed underwater unmanned vehicles, where lightweight design precludes the use of oil lubrication systems, making WLBs a more economically favorable and reliable alternative. To address this, the present study establishes a start-up tribo-dynamic model that comprehensively incorporates both bush surface waviness and wear to systematically investigate their coupled effects on the tribo-dynamic behavior during WLB start-up. The research findings indicate that axial surface waviness reduces the hydrodynamic effect during the start-up phase. Consequently, a higher rotational speed is needed to generate the necessary hydrodynamic pressure for the WLB to start up successfully. The significance of the influence exerted by circumferential surface waviness on start-up behavior is determined by its frequency number, m. A larger m leads to greater fluctuations in both hydrodynamic pressure and contact pressure. Furthermore, when wear occurs, the amplitude of bush surface waviness mediates the influence of wear depth on start-up performance, thereby modifying the optimal wear depth previously established for smooth bearings. These findings highlight the importance of controlling circumferential waviness frequency during machining and manufacturing processes to optimize WLB start-up reliability and service life. Full article

Urban transportation is a crucial aspect of modern societal development, with bus route optimization playing a central role in urban transit planning. Well-designed bus routes can enhance the efficiency and attractiveness of public transportation, alleviate traffic congestion and pollution, and ultimately contribute to the overall growth of a city. This study investigates the selection of bus stop locations and route optimization from three perspectives: population density, facility distribution, and route length. The main methodological contribution lies not in the Pareto filtering itself, but in the development of a unified pipeline. This pipeline first generates and prunes candidate stops by applying road-network and intersection-safety constraints. It then constructs feasible routes using a constraint-driven heuristic that enforces stop spacing, ensures monotonic progress away from the origin and toward the destination, and maintains route smoothness. Finally, it integrates population-grid and POI indicators into a tri-objective evaluation framework prior to non-dominated sorting. The proposed method for bus stop location and route optimization is universally applicable to urban bus routes and can be validated through case studies in different cities. An empirical analysis is conducted using Route 119 in Kunming City, Yunnan Province, as a case study. Compared with the original bus route, the optimized route demonstrates improvements of 18.26% in route distance, 15.79% in Points of Interest (POI) accessibility, and 10.53% in population coverage. Full article

This study explores the effects of sputtering pressure and power on FeCoNi high-entropy alloy films prepared by DC magnetron sputtering, focusing on microstructure, surface morphology, and static/high-frequency magnetic properties. In situ Lorentz TEM (LZ-TEM) was used to directly observe magnetic domain evolution. Results show that low sputtering pressure (1 mTorr) promotes strong FCC (111) crystallization, and smooth and dense surfaces. Increasing pressure leads to amorphization, higher roughness, and degraded magnetic performance. Under optimized pressure, 100 W sputtering power yields the best crystallinity, the smoothest surface, and optimal soft magnetic properties, including high remanence ratio, low coercivity, and clear ferromagnetic resonance in the 2–7.5 GHz range. The optimal parameters are confirmed as 1 mTorr and 100 W, producing uniform nanocrystalline FeCoNi films. In situ LZ-TEM reveals river-like domain walls, vortex–antivortex structures, and uniform magnetic moment precession, indicating weak domain pinning and excellent high-frequency magnetization consistency. This study provides experimental and theoretical support for the controllable fabrication of high-performance FeCoNi soft magnetic films for high-frequency devices. Full article

Background/Objectives: Hidradenitis suppurativa (HS) is a chronic, immune-mediated inflammatory skin disease characterized by painful nodules, abscesses, sinus tracts, and progressive fibrosis. Vascular activation is becoming increasingly acknowledged as an important factor in HS pathogenesis; however, the effects of tumor necrosis factor alpha (TNF-α) blockade on vascular remodeling in HS remain poorly characterized. This study investigated the impact of TNF-α inhibition by adalimumab (ADA) on endothelial and fibroblast-associated markers in HS lesions. Methods: Formalin-fixed paraffin-embedded skin samples from 71 HS patients were analyzed, including treatment-naive (n = 38) and adalimumab-treated (n = 33) cases. Histopathology and immunofluorescence were performed using antibodies against CD31, von Willebrand factor (vWF), α-smooth muscle actin (αSMA), vimentin, Ki-67 (proliferation), and cleaved Caspase-3 (apoptosis). ImageJ software was used to determine the immunoexpression of selected markers and vascular density. Vascular density, assessed as vessel count per mm², was designated as the primary endpoint. Sex-related differences were analyzed as exploratory endpoints. Results: Adalimumab-treated tissue exhibited significantly reduced vascular density (p < 0.01) compared to the treatment-naive group. Conversely, vimentin immunoexpression was significantly higher (p < 0.01) in the adalimumab-treated group. No significant differences were found in endothelial Ki-67 or cleaved Caspase-3 expression between treatment groups, indicating that the observed reduction in vascular density is not associated with direct effects on endothelial cell proliferation or apoptosis, but rather may occur indirectly through attenuation of the pro-angiogenic inflammatory milieu. Exploratory sex-stratified analysis revealed that treatment-naive males had significantly higher endothelial proliferation (Ki-67; p = 0.031) and vimentin expression (p = 0.017) compared to treatment-naive females. In the ADA-treated group, males exhibited significantly lower vascular density (p = 0.036) and higher endothelial apoptosis (p = 0.039) compared to females, whereas females showed a significant increase in vimentin expression following treatment (p = 0.008), suggesting possible sex-dependent differences in vascular remodeling. Conclusions: TNF-α blockade is associated with reduced vascular density, consistent with indirect anti-angiogenic effects, suggesting that adalimumab exerts disease-modifying effects on the microenvironment beyond inflammatory cytokine suppression. Sex-dependent differences in vascular regression underscore the importance of considering sex as a biological variable in HS pathogenesis and treatment response. These results highlight the significance of vascular interactions in HS and support adalimumab as a disease-modifying treatment. These exploratory findings require confirmation in longitudinal studies with paired biopsies. Full article

High-density polyethylene (HDPE) geomembranes (GMs) in landfill liners experience UV exposure during installation. While tensile strength deterioration after UV aging is known, changes in interfacial shear properties are rarely reported. This study investigates the evolution of interfacial shear behavior at the GM/sand interface by subjecting GM specimens to varying durations of indoor UV aging followed by direct shear tests. Underlying mechanisms were explored through tensile strength, melt flow index, crystallinity, and oxidation induction time (OIT) measurements. Results show that displacement required to reach peak shear strength for smooth geomembrane (GMS)/sand interface decreased with aging time (49.0–70.1% reduction), while no clear trend emerged for textured geomembrane (GMX)/sand interface. Following 80 days of UV exposure, the GMS/sand interfacial shear strength declined, with the peak friction angle dropping 20.6% from 26.2° to 20.8°. For the GMX/sand interface, the peak friction angle dropped to its lowest value of 31.2° after 40 days of exposure (from 34.3°), and then exhibited an increase with further UV aging. The large displacement shear strength followed a trend similar to that of the peak strength. Among the other tested indicators, the variation pattern of OIT with UV exposure exhibited the best correlation with the GMS/sand interface shear strength. Full article

Stock-ranking prediction is an important task in quantitative finance because it directly influences portfolio construction and alpha generation. Recent Graph Neural Network (GNN) models provide a promising way to describe inter-stock dependencies, but many existing methods still have difficulty balancing rapidly changing market interactions with relatively stable structural relationships. They are also easily affected by financial micro-structure noise. To address these issues, this paper proposes USTGCN, a Unified Spatio-Temporal Graph Convolutional Network for stock-ranking prediction. USTGCN adopts a dual-stream temporal encoder based on ALSTM and GRU to capture short-term dynamic patterns and longer-horizon structural information, respectively. We further introduce a rolling-window correlation smoothing strategy to build a more stable dynamic graph, and then integrate the dynamic and structural graph views through a shared fusion layer. Skip connections are used to preserve original temporal information during spatial aggregation. Experiments on the CSI100 and CSI300 benchmark datasets show that USTGCN achieves IC values of 0.141 and 0.154, respectively, and exhibits improved drawdown control during stressed market periods, indicating its practical value for quantitative trading. Full article

Wheeled multifunctional motorized crossing frames represent a new type of crossing equipment for high-voltage transmission line construction. The initial design is too conservative, having a large safety margin and high material redundancy. Therefore, it is necessary to study a lightweight design version. However, as the structure constitutes an assembly consisting of multiple components, it also exhibits relatively high complexity. In a lightweight design, optimizing multi-component and multi-size parameters can lead to structural interference and separation, seriously affecting the smooth progress of design optimization. Therefore, an optimization design method of a multi-parameter complex assembly structure is proposed to solve this problem. Firstly, the typical stress conditions of the wheeled multifunctional motorized crossing frame were analyzed using its structural model. Then, a finite element model of the beam was established in ANSYS 2021 R1 Workbench, and the mechanical characteristics were analyzed. The results show that the arm support is the key load-bearing component and has significant optimization potential. Subsequently, functional mapping relationships were established among the 14 dimension parameters of the arm support, reducing the number of design variables to six and successfully avoiding component separation or interference during optimization. Through global sensitivity analysis, the height, thickness, and length of the arm body were screened out as the core optimization parameters from six initial design variables. Then, 29 groups of sample points were generated via central composite design (CCD), and a response surface model reflecting the relationships among the arm body’s dimensional parameters, total mass, maximum stress, and maximum deformation was established using the Kriging method. Leave-one-out cross-validation (LOOCV) was performed, and the coefficients of determination (R²) for model fitting were all higher than 0.995, indicating extremely high prediction accuracy. Taking mass and deformation minimization as the optimization objectives, the MOGA algorithm was adopted to perform multi-objective optimization and determine the optimal engineering parameters. Simulation verification was conducted on the optimized arm support, and an eigenvalue buckling analysis was performed simultaneously to verify structural stability. Finally, the proposed optimization method was experimentally verified through mechanical performance tests of the full-scale prototype under symmetric and eccentric loads. The results show that the mass of the optimized arm support is reduced from 217.73 kg to 189.8 kg, with a weight reduction rate of 12.8%. Under an eccentric load of 70,000 N, the maximum deformation of the arm support is 8.9763 mm, the maximum equivalent stress is 314.86 MPa, and the buckling load factor is 6.08, all of which meet the requirements for structural stiffness, strength, and buckling stability. The maximum error between the experimental and finite element results is only 4.64%, verifying the accuracy and reliability of the proposed method. The proposed optimization methodology, validated on a wheeled multifunctional motorized crossing frame, serves as a transferable paradigm for the lightweight design of complex assemblies with coupled dimensional constraints, thereby offering a general reference for the structural optimization of multi-component transmission line equipment, construction machinery, and other multi-component engineering systems. Full article

Skin fibrosis is characterized by excessive extracellular matrix (ECM) deposition, leading to tissue dysfunction and scarring. Transforming growth factor (TGF)-β is a central mediator of fibrosis. We previously identified CD109 as a TGF-β co-receptor and negative regulator of TGF-β signaling and fibrotic responses and showed that its epidermal overexpression reduces dermal fibrosis in vivo. However, the effects of CD109 loss in the dermis remain unclear. The current study investigates the impact of CD109 knockout (KO) on skin fibrosis using a bleomycin-induced fibrosis mouse model. Following bleomycin treatment, CD109 KO mice showed increased collagen I deposition and elevated fibronectin, CCN2, and α–smooth muscle actin expression in the skin, indicating enhanced ECM production and myofibroblast differentiation compared with wild-type mice. Additionally, CD109 KO mice displayed enhanced Smad1 and Smad2/3 phosphorylation in the skin, indicating heightened TGF-β signaling. In vitro, CD109 KO fibroblasts exhibited increased TGF-β-induced migration and collagen contraction. These findings suggest that CD109 deficiency exacerbates dermal fibrosis by promoting TGF-β/Smad signaling and myofibroblast activation. Given its dysregulation in fibrotic disorders such as scleroderma, our results identify CD109 as a key regulator of skin homeostasis by modulating ECM production and fibroblast activation, underscoring its potential as a therapeutic target in fibrotic disorders. Full article

Traffic calming measures are widely used to reduce operating speeds and mitigate crash risk in urban corridors; however, the way drivers adapt their control strategy when traversing Berlin speed cushions is still poorly described from a multivariate behavioral perspective. This study proposes a behavior-oriented analysis to identify recurring speed-cushion traversal strategies using driving simulator telemetry. A fixed-base simulator reproduced a real urban corridor, and trajectories were segmented in device-centered spatial windows capturing approach, traversal, and immediate recovery. Each segment was summarized by three indicators describing longitudinal and lateral control: mean speed, peak braking demand, and average lane position deviation. Features were standardized and clustered using k-means. The number of clusters was selected primarily through mean silhouette evaluation, while resampling-based checks and a Gaussian mixture modeling comparison were used as supportive evidence rather than competing decision rules. Three traversal profiles emerged: smooth cautious, reactive cautious, and unmoderated fast. The introduction of speed cushions shifted the distribution of segments towards cautious profiles, while driver-level concentration within a single profile was moderate. Overall, results indicate that speed cushions influence the whole vehicle control strategy, offering a quantitative basis for behavior-oriented evaluation of local traffic calming interventions in smart-city contexts. Full article

Reliable steering regulation under varying road curvature and actuator constraints remains a central challenge in autonomous electric vehicles (AEVs). Many exiting approaches rely on reactive error correction or treat preview information solely as a reference adjustment, limiting anticipation and physical consistency. This study proposes a prediction–preview steering control (PSC) framework in which future curvature information within state propagation and constraint handling enables forward-looking steering decisions while respecting dynamic and actuator limits. The method is evaluated using a lateral-heading vehicle model with real-road geometric variation. Experimental results indicate significant improvement in tracking performance, reducing lateral RMSE from 0.1747 m to 0.0074 m with a maximum deviation of 0.0889 m and limiting heading RMSE to 0.0867° (maximum 1.2046°). Steering angle commands remain bounded within ±8.7°, while steering angle rate is maintained within 40–60°/s, ensuring smooth and dynamically admissible operation. The proposed strategy offers a computationally efficient solution for embedded AEV steering systems and demonstrates improved robustness under practical curvature transitions. Full article