Search Results (6,043)

High-voltage electric-vehicle (EV) fast charging requires accurate coordination between the off-board charger and the battery management system during voltage and current negotiation. This study evaluates a Hybrid Particle Swarm Optimization-Whale Optimization Algorithm (HPWOA) schedule for training a dual-output feedforward neural network that directly estimates ChargePower_kW and ChargeCurrent_A. Ten protocol-state and battery-condition variables were used as inputs. The 158-dimensional neural-weight vector was optimized using 75 Particle Swarm Optimization (PSO) iterations, followed by 75 Whale Optimization Algorithm (WOA) iterations. Using the supplied 500-record dataset, a reproducible 30-seed sample-level evaluation was conducted with a common 3775 fitness-function-evaluation budget for PSO, the WOA, the SFSA, and the HPWOA. The Stochastic Fractal Search Algorithm (SFSA), therefore, used 30 iterations because it evaluates five diffusion candidates per individual. The reported HPWOA mean ± standard deviation (SD) was RMSE = 4.658 ± 0.986 kW and R² = 0.843 ± 0.071 for power, and RMSE = 12.686 ± 2.687 A and R² = 0.858 ± 0.059 for current. The HPWOA outperformed the WOA and SFSA, but not standalone PSO. A conventional mini-batch Adam-trained dual-output neural network produced RMSE = 1.704 ± 0.121 kW and 4.946 ± 0.273 A, and R² = 0.980 ± 0.003 and 0.979 ± 0.002, respectively. Charger-grouped five-fold validation gave the HPWOA R² = 0.857 ± 0.045 (power) and 0.873 ± 0.048 (current). An analytical P = V × I reconstruction was physically consistent in construction and did not show a statistically significant power–RMSE difference from direct HPWOA outputs. The results, therefore, position the two-phase schedule as a reproducible comparative baseline rather than as a demonstrated replacement for gradient-based training or a physically constrained reconstruction. Full article

Cross-domain distribution shifts severely degrade the diagnostic performance of rolling bearing models under unseen variable operating scenarios. Single-source domain generalization (SDG) builds fault diagnosis models using only single-source vibration data, which fits the practical limitations of industrial data collection. Existing contrastive learning methods adopt uniform spectral perturbations for data augmentation, which easily corrupt fault harmonic characteristics and require massive, labeled training samples. To tackle these drawbacks, this paper proposes an unsupervised contrastive learning framework named FDACL. An adaptive frequency-domain augmentation (AFA) module equipped with learnable weights is designed to separate fault-critical frequency bands from noise components. Differentiated amplitude perturbations are applied to two categories of spectral signals to generate diverse pseudo-samples while retaining intrinsic fault information. A shared encoder is trained with combined InfoNCE contrast loss and classification loss to learn domain-invariant fault representations. Validations are carried out on three datasets, namely Case Western Reserve University (CWRU), Paderborn University (PU), and the industrial CRRC Qingdao Sifang railway wheelset bearing dataset acquired from physical test benches. FDACL achieves average cross-speed diagnostic accuracies of 92.68% and 77.85% on CWRU and PU, respectively, and maintains competitive performance on the Qingdao Sifang industrial dataset. It outperforms state-of-the-art baselines by 4.23–8.71% across all SDG transfer tasks. Ablation experiments and hyperparameter analysis verify the efficacy of the AFA module and contrastive learning scheme, providing an unsupervised diagnostic approach for railway bearings under unknown working conditions. Full article

Background: Aging is characterized by functional decline in different organs and systems. The present study aimed to evaluate the effects of 6-month low-to moderate intensity supervised Social Dance (SD) program on muscular fitness, and clinical–biochemical and hematological parameters associated with healthy aging. Circulating CD34+ and serum antioxidant potential were assessed as exploratory outcomes. Methods: Seventy-nine elderly (aged > 65 years) were enrolled and randomized. Analyses included 49 participants who provided baseline and follow-up data and were assigned to the SD group (SDG, n = 24) or control group (CG, n = 25). Clinical–biochemical and hematological profiles, oxidative stress markers, circulating CD34+ cells, Physical fitness components and Physical Activity Scale for the Elderly (PASE) and EuroQol five-dimensional (EQ-5D) questionnaires were assessed at T0 and T1 to both groups. Results: Significant group × time interactions favored the SDG for HDL cholesterol ($p=0.003$), Hemoglobin (p = 0.031), and Hematocrit (p = 0.005). A significant increase in BAP (∆% = 33.3; p < 0.001) and PASE (∆%= 79.6 vs. 56.9; p < 0.05) were observed among the SDG; conversely, only a positive trend (∆% = 12.9 SDG vs. −5.1 CG) was observed for EQ-VAS at T1; these findings were not supported by significant group × time interaction. CD34+ cells increased significantly only in the CG. Isometric muscular performance declined in both groups. Conclusions: a 6-month SD program may provide beneficial effects on selected biochemical markers (i.e., a positive impact on HDL, hematological profile, antioxidant defenses) and perceived health outcomes in the elderly. However, it appears insufficient to preserve isometric muscular performance, suggesting that complementary resistance-based strategies may be needed to optimize neuromuscular adaptations. Full article

Power-frequency overexcitation increases the voltage-to-frequency ratio applied to a transformer core and may drive the core into saturation, resulting in substantial distortion of the no-load current. This paper presents a duality-derived electromagnetic model for an on-board traction transformer by combining a sixth-order Foster network identified through vector fitting with a Jiles–Atherton hysteresis operator. The proposed model preserves the physical correspondence between magnetic-flux paths and equivalent-circuit elements while accounting for history-dependent core hysteresis and frequency-dependent core impedance. The model is implemented and numerically evaluated in MATLAB/Simulink R2024a, and experimental validation is performed on a 250 kVA prototype under rated power-frequency excitation and power-frequency overexcitation. Under rated excitation, the RMS relative error and NRMSE of the no-load current are 0.09% and 0.96%, respectively, with a maximum relative error of 2.90%. Under power-frequency overexcitation, the NRMSE is 4.14% and the maximum relative error is 9.37%. The results show that the proposed model accurately reproduces the nonlinear no-load current response associated with core saturation and hysteresis within the investigated power-frequency excitation range. Full article

Background/Objectives: The objectives of this study were to compare emotional well-being, depressive symptoms, and psychiatric medication use between adults with and without diabetes in Spain and to identify sex-specific factors associated with these outcomes among individuals with diabetes. Methods: A population-based matched study was conducted using data from the 2023 Spanish National Health Survey (SNHS 2023). Adults aged ≥35 years with physician-diagnosed diabetes were individually matched (1:1) to controls without diabetes according to sex, exact age, and autonomous community of residence. Low emotional well-being (WHO-5 score < 50), clinically relevant depressive symptoms (PHQ-8 ≥ 10), and psychiatric medication use were assessed. Conditional logistic regression and sex-specific multivariable logistic regression models were fitted. Results: The study included 3710 participants (1855 with diabetes and 1855 matched controls without diabetes). The prevalence of low emotional well-being was significantly higher among participants with diabetes than among matched controls in both men (16.4% vs. 11.6%; p = 0.004) and women (28.8% vs. 21.6%; p < 0.001). Likewise, clinically relevant depressive symptoms were more frequent among individuals with diabetes (men: 32.7% vs. 24.9%, p < 0.001; women: 54.4% vs. 40.2%, p < 0.001), as was psychiatric medication use (men: 20.5% vs. 15.2%, p = 0.005; women: 39.5% vs. 30.2%, p < 0.001). After full adjustment, diabetes remained independently associated with low emotional well-being (men: aOR 1.48, 95% CI 1.03–2.13; women: aOR 1.43, 95% CI 1.14–1.78), depressive symptoms (men: aOR 1.31, 95% CI 1.02–1.69; women: aOR 1.38, 95% CI 1.08–1.77), and psychiatric medication use (men: aOR 1.34, 95% CI 1.02–1.75; women: aOR 1.35, 95% CI 1.06–1.73). Poor social support, physical inactivity, and several chronic comorbidities emerged as the factors most consistently associated with adverse mental health outcomes among individuals with diabetes. Conclusions: Adults with diabetes in Spain experience a substantially greater burden of adverse mental health than matched individuals without diabetes. Integrating routine mental health assessment and psychosocial support into diabetes care may help improve both psychological well-being and disease management. Full article

Architectural heritage interventions often preserve visual form while leaving acoustic memory and everyday sound practices outside the design brief. This article positions soundscape as an architectural material for heritage media architecture and tests it through Sanggar Kungfu Kapasan, a historic Chinese-diaspora kampung in Surabaya, Indonesia. The research combined contextual and soundmark mapping, Pepper’s Ghost prototyping, architectural translation of a semi-transparent virtual layer, and comparative evaluation using 2D visualization and immersive VR. After deduplication, 37 participants evaluated the 2D material, 31 evaluated VR, and 24 completed both modes for within-subject analysis. VR significantly improved perceived physical quality (Δ = +0.46, p = 0.0007, d_z = 0.80), communication quality (Δ = +0.42, p = 0.0218, d_z = 0.50), and overall evaluation (Δ = +0.20, p = 0.0285, d_z = 0.48). Sound-specific VR ratings were positive for place-meaning support (M = 5.87) and scene formation (M = 5.65), and the soundscape design index correlated with communication quality (r = 0.47, p = 0.007). The findings show that soundscape strengthens narrative legibility and architectural fit when deliberately coordinated with visual layering, scene sequencing, and cultural context. The study contributes a soundscape-informed, feng shui-readable workflow for pre-installation evaluation of multisensory heritage interventions. Because the respondent pool was predominantly composed of architecture students, the results are interpreted as a preliminary design-user evaluation rather than community validation. Full article

This paper presents an analytical compact DC current model and a numerical gate capacitance model for p-type cylindrical gate-all-around (GAA) nanowire metal–oxide–semiconductor field-effect transistors (MOSFETs). The models are formulated within the Landauer transport framework, incorporating source-to-drain tunneling (SDT) and quantum statistical charge analysis. The proposed current model is validated against non-equilibrium Green’s function (NEGF) simulations for different channel lengths, nanowire radii, and bias conditions, showing good agreement with the NEGF results in the ballistic limit. The model parameters are separated into physical parameters obtained or calibrated from the NEGF simulations and a single set of global empirical fitting parameters. The latter is extracted once and remains unchanged across the investigated device geometries and bias conditions, allowing its transferability to be evaluated. The compact model is implemented in Verilog-A, and its SPICE compatibility is verified through DC simulations of PMOS inverter circuits. All NEGF comparisons in this work are performed with a zero channel backscattering coefficient corresponding to the ballistic transport limit; validation of the quasi-ballistic regime is left for future work. Full article

Background: Physical fitness is an important marker of health and development during early childhood. However, data describing fitness characteristics of preschool children from Central and Eastern Europe remain limited. This study examined age-related trends, sex differences, and associations with BMI-for-age z-scores (BMI SDS) in selected components of the PREFIT battery in Czech preschool children. Methods: A cross-sectional study was conducted in 40 children aged 3–6 years (19 girls and 21 boys) attending a public kindergarten in the Czech Republic. Physical fitness was assessed using four selected PREFIT components: handgrip strength, standing long jump, 4 × 10 m shuttle run, and one-leg stance. Associations with age, sex, and BMI SDS were analyzed using linear regression models. Results: Physical fitness was significantly associated with age across all assessed components (all p < 0.001). Sex differences were generally small, although boys demonstrated moderately higher handgrip strength than girls. After adjustment for age and sex, higher BMI SDS was associated with lower handgrip strength, poorer standing long-jump performance, and longer shuttle-run times, whereas no significant association was observed for one-leg stance performance. Conclusions: Selected PREFIT components were successfully implemented in a real-world kindergarten setting and were sensitive to age-related differences in physical fitness. Age showed the strongest and most consistent associations with fitness performance, while BMI SDS was independently associated with selected fitness outcomes. Larger multi-site and longitudinal studies are needed to establish population-specific reference values and to clarify the role of early physical fitness in later health and development. Full article

Electrochemical parameter identification is crucial for evaluating the electrochemical processes in proton exchange membrane water electrolysis (PEMWE). Conventional characterization techniques-including polarization-curve fitting, electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and current interruption (CI)-face significant limitations for rapid diagnostics under high-current dynamic operation, arising from constraints in instrument current rating, measurement time, zero-current control, and noise amplification in numerical differentiation. In this study, we present a simple current step (CS) method to accurately identify key electrochemical parameters and perform overpotential breakdown by using a simplified equivalent circuit model with a current source. To address the numerical instability in derivative calculation caused by sampling noise during voltage transient analysis, a physics-informed neural network (PINN) is introduced to enhance signal smoothness while guaranteeing physical consist ency. Compared with standard characterization, the proposed CS-PINN method demonstrates high accuracy, with an error of less than 2% in overpotential breakdown, less than 5.3% in ohmic resistance, and 2.8% in the Tafel slope (at 5 A/cm²). These results confirm that the CS-PINN method provides a fast, accurate, and equipment-friendly route for rapid electrochemical parameter identification in PEMWE. Full article

Accurate parameterization of the photovoltaic single-diode model is usually obtained from complete current–voltage (I-V) measurements. However, full I-V curve tracing is not always available in real monitoring environments, where the most accessible variables are irradiance and module temperature. This paper proposes a hybrid methodology for reconstructing the five parameters of the single-diode model from irradiance and temperature data. The method first estimates the maximum-power point and the remaining remarkable points of the I-V curve as well as the photocurrent ($I_{ph}$) through regression models calibrated on measured data. These predicted points are sufficient to solve the SDM equation. A numerical approach is then used to identify the five SDM parameters while enforcing physical admissibility constraints. The method is validated using NREL outdoor datasets from three locations and several photovoltaic technologies. The results show that the maximum-power current is estimated with very high reliability, with $R^2$ values close to unity in almost all cases. Voltage estimation is less stable and depends more strongly on technology and temperature sensor location. The reconstructed I-V curves are physically admissible for most crystalline silicon, HIT, and CdTe modules, whereas CIGS and amorphous silicon modules exhibit lower admissibility. The proposed method should therefore be understood as an environmental-data-driven reconstruction tool when complete I-V curves are unavailable, rather than as a replacement for direct full-curve fitting techniques such as TSLLS or Reduced Form. Full article

Hydrogenation reactors are critical equipment in the petrochemical industry, yet their material degradation is governed by coupled multi-mechanism damage. Current assessment practices largely neglect this complexity, remaining single-factor oriented and overlooking synergistic interactions and temporal evolution. This paper proposes a regionally differentiated, multi-level framework integrating 5 primary and 17 secondary indicators with a hybrid AHP-EWM weighting strategy that synthesizes expert knowledge and measured data. A multi-factor coupling correction coefficient is introduced to provide a preliminary estimate of the synergistic acceleration effect among damage mechanisms, while a GM(1,1) gray model enables dynamic trend prediction. Applied to a 25-year 2.25Cr-1Mo steel reactor, the method produces regional degradation values of 0.378, 0.607, and 0.533 for the base metal, welds, and cladding layer, respectively, with an overall baseline of 0.453 rising by 11% to 0.503 after coupling correction. Compared with exponential regression, ARIMA, and BP neural networks, GM(1,1) is selected for its balanced performance in small-sample fitting, extrapolation stability, and physical interpretability. Sensitivity analysis confirms stable degradation grading even with ±50% coupling coefficient variations. The proposed approach mitigates the underestimation inherent in conventional single-mechanism assessments and offers a quantitative tool for full-lifecycle risk management and predictive maintenance of hydrogenation reactors. Full article

The generation of aerosols with narrow droplet-size distributions remains a key challenge in liquid atomization technologies used in agricultural, chemical-processing, and environmental applications. This study presents an experimental investigation of spray characteristics produced by an inertial rotary atomizer equipped with an internal hydrodynamic flow-conditioning system. The experiments were conducted using a Box–Behnken experimental design and Response Surface Methodology (RSM). Fifteen experimental runs, including three center-point replicates, were performed to evaluate the combined effects of the operating parameters. Liquid flow rate, rotor rotational speed, and spraying height were selected as independent variables. The response variables included the characteristic droplet diameters (d₁₀, d₅₀ and d₉₀), the Span coefficient, and droplet deposition density (N). Quadratic regression models were fitted to the experimental data to explore the influence of the operating parameters on spray characteristics; however, statistical diagnostics indicated limited predictive capability, and the models were therefore used primarily for exploratory interpretation of response trends within the investigated design space. The experimental results indicated that rotor speed exhibited the strongest tendency to influence droplet-size characteristics within the investigated operating range, while increasing liquid flow rate was associated with larger droplet diameters, consistent with the expected effect of increased liquid-film thickness. Within the investigated atomizer configuration, relatively narrow droplet-size distributions were experimentally observed under selected operating conditions. These observations are consistent with the hypothesis that internal hydrodynamic flow conditioning may contribute to liquid-film destabilization and subsequent breakup. However, its independent contribution cannot be isolated from the present experiments because an otherwise identical baseline atomizer without the flow-conditioning element was not tested. Within the model-predicted favorable operating region (liquid flow rate of 1.0 × 10⁻⁶ m³·s⁻¹, rotor rotational speed of 4600–5100 min⁻¹, and spraying height of 30 cm), the fitted response-surface model predicted a volume median droplet diameter of approximately 64 μm. Separately, the minimum experimentally observed Span coefficient was approximately 0.58, indicating a relatively narrow deposited-droplet-size distribution within the investigated operating range. This model-predicted region was not independently verified by a dedicated confirmation experiment and therefore should not be interpreted as an experimentally validated optimum. The proposed physical interpretation considers hydrodynamic flow conditioning as a plausible additional mechanism contributing to spray uniformity, although its quantitative validation requires dedicated flow diagnostics and CFD analysis. The obtained results characterize the spray behavior of the developed atomizer within the investigated operating domain and provide an experimental basis for future comparative studies aimed at quantifying the independent contribution of the internal flow-conditioning system. These findings provide experimental evidence supporting further investigation of this concept and may contribute to the development of rotary atomizers for precision agricultural spraying and other engineering applications requiring controlled droplet-size distributions. Full article

To address the critical challenge of extracting short-period surface deformation signals induced by extreme floods from InSAR time series, this study focuses on the catastrophic flood that struck the Haihe River Basin in July 2023 (hereinafter referred to as the “23·7” flood, with a total duration of approximately 65 days) and proposes a novel method for transient deformation signal extraction. Using Sentinel-1A satellite data and the PS-InSAR technique, we constructed a multivariate composite fitting function comprising a linear trend term, annual and semi-annual seasonal terms, a step term, and a logarithmic decay term. Through nonlinear least-squares fitting, this approach achieves effective separation of long-term tectonic deformation, seasonal fluctuations, high-frequency noise, and transient flood-related signals. The results show that the W-shaped floodplain east of Xiong’an New Area does not exhibit the expected subsidence induced by water loading but instead features pronounced surface uplift of up to 30 mm. Multi-physics forward modeling reveals the underlying mechanism: the elastic subsidence caused by surface water loading, calculated via the LoadDef spherical loading theory, amounts to only ~2 mm. In contrast, forward modeling based on the GMS three-dimensional groundwater seepage model and the principle of effective stress indicates that the pore water rebound effect can produce surface uplift of up to ~36 mm. The superposition of these two effects is highly consistent with InSAR observations in terms of magnitude, direction, and spatial distribution, confirming that the flood-induced surface deformation is dominated by the pore water rebound effect driven by rapid groundwater recharge, rather than subsidence from water loading. The proposed framework extends the application potential of geodetic techniques for monitoring short-period extreme hydrological events. Full article

Objective: To examine the reliability, construct validity, and discriminative capacity of the Spanish version of the Economic Living Standards Index Short Form (ELSI_SF) in a sample of older adults in Spain. Methods: This analysis was conducted using baseline data from 133 participants (mean age = 66.2 years, SD = 5.6; 53.8% women) recruited from community health and social centers in the provinces of Cuenca, Albacete, and Toledo within the PEPE cohort. Participants completed the ELSI_SF (25 items), sociodemographic measures, the SF-12 Health Survey, and the International Fitness Scale (IFIS). Internal consistency was assessed using Cronbach’s alpha. Convergent validity was examined through correlations between ELSI_SF scores and education, occupation, physical and mental health, and perceived fitness. Discriminative ability for health-related variables was analyzed using ANOVA and partial η². The internal structure was explored using exploratory factor analysis (EFA) and subsequently examined against the original four-factor theoretical model using confirmatory factor analysis (CFA), based on polychoric correlations and estimation methods appropriate for ordinal data. Results: The mean ELSI_SF score was 23.0 ± 3.9, with most participants classified as having comfortable or good living standards. Internal consistency was acceptable for the total scale (α = 0.779), whereas the ownership restrictions (α = 0.441) and self-rating (α = 0.319) subscales showed low reliability. Significant associations were observed between the ELSI_SF total score and selected socioeconomic and health-related measures. Factor-analytic findings provided only partial support for the original four-domain structure. Although CFA showed favorable CFI, TLI, and RMSEA values, the elevated SRMR and instability of the self-rating factor warrant cautious interpretation of the factorial solution. Conclusions: The Spanish ELSI_SF provides preliminary psychometric evidence supporting the use of its total score among relatively socioeconomically advantaged older adults. However, limitations in subscale reliability, factorial stability, and the restricted socioeconomic variability of the sample preclude definitive validation across the full spectrum of material living standards. Further evaluation in larger, independent, and more socioeconomically heterogeneous samples, particularly including older adults experiencing material deprivation, is required. Full article

Background/Objectives: Obesity is a chronic, progressive, and relapsing disease that requires long-term, multidisciplinary management rather than episodic weight-loss treatment. Although novel incretin-based anti-obesity pharmacotherapies, including GLP-1 receptor agonists and dual GIP/GLP-1 receptor agonists, have markedly improved the clinical management of obesity, weight reduction alone does not fully capture treatment success. Body composition, lean mass preservation, physical function, nutritional adequacy, psychological well-being, adherence, and long-term weight-loss maintenance are increasingly recognized as essential therapeutic outcomes. This narrative review critically examines the role of lifestyle medicine as a co-therapeutic strategy during modern anti-obesity pharmacotherapy, with particular attention to physical activity, nutrition, behavioral support, and individualized monitoring. Methods: A narrative literature search was conducted in PubMed up to June 2026. The review included studies addressing adults with overweight or obesity and evidence related to anti-obesity pharmacotherapy, physical activity, nutrition, body composition, functional outcomes, eating behavior, quality of life, treatment tolerability, adherence, weight regain, and long-term maintenance. Results: Current evidence indicates that incretin-based therapies produce substantial and clinically meaningful weight loss, but pharmacological efficacy may be limited by reductions in lean mass, gastrointestinal adverse events, inadequate nutritional intake, treatment discontinuation, and weight regain after drug withdrawal. Physical activity should be considered a therapeutic component rather than only a tool for increasing energy expenditure, as aerobic exercise supports cardiometabolic health and cardiorespiratory fitness, while resistance training helps preserve muscle strength, bone health, and functional capacity. Nutritional strategies are equally important, particularly during appetite suppression, to maintain adequate protein, fiber, fluids, micronutrients, and diet quality. Behavioral factors, including sleep, stress, mood, stigma, self-regulation, and the food environment, may influence adherence and long-term outcomes. Conclusions: Novel anti-obesity drugs should not be viewed as replacements for lifestyle medicine but as powerful tools within an integrated chronic-care model. The goal of treatment should move beyond maximal body-weight reduction to durable improvements in body composition, metabolic health, physical function, nutritional status, quality of life, and weight-loss maintenance. Full article