Search Results (3,325)

Background/Objectives: The nutrition transition in low- and middle-income countries has produced a double burden of malnutrition (coexistence of excess weight, undernutrition, and micronutrient deficiencies), with scarce evidence in schoolchildren from vulnerable peri-urban areas of Paraguay. The objective was to characterize, in a multidimensional way, the nutritional status of children and adolescents from Limpio and to explore its associations with anemia and clinical, dietary, and environmental variables, in particular, reported intestinal parasitosis. Methods: Cross-sectional observational study in 90 participants aged 6 to 16 years recruited by convenience at six community settings. Anthropometry, body composition, capillary hemoglobin, dietary patterns, and environment were assessed. Weight status was classified using the WHO 2007 references (z-scores), anemia was described using WHO thresholds, and central obesity was assessed using a waist-to-height ratio > 0.5. Non-parametric tests, Fisher’s exact test, Spearman correlations, and multivariable logistic regression were used. Results: Overweight or obesity affected 39.3% (obesity, 16.7%) and central obesity 22.4%, with no cases of thinness, coexisting with anemia (27.0%), stunting (8.2%), and reported intestinal parasitosis (24.1%). Anemia was more frequent in children with reported intestinal parasitosis (45% versus 20%; adjusted OR 5.44; 95% CI 1.44–20.51). Height-for-age was inversely associated with the number of siblings (ρ = −0.25). Conclusions: This population showed a double burden of malnutrition. The association between reported, non-laboratory-confirmed intestinal parasitosis and capillary-hemoglobin-defined anemia was exploratory and non-causal, given the cross-sectional design. Together with the high burden of anemia, these findings raise the hypothesis of a possible triple burden of malnutrition, which would require confirmation through stool parasitological testing and biomarkers of iron status, inflammation, and other micronutrients. These findings are compatible with integrated community strategies addressing dietary quality, sanitation, and access to safe water; decisions on deworming and micronutrient supplementation should be guided by local parasitological surveillance and biomarker-based assessment rather than by these data alone. Because the study used a convenience sample from a single peri-urban community during one fieldwork period, the findings should not be generalized beyond similar vulnerable settings without further confirmation. Full article

Variational autoencoders (VAEs) are sensitive to spatially heterogeneous noise because corrupted high-frequency components can be propagated into the latent posterior and degrade reconstruction. We propose Learnable Local FFT-VAE, a VAE-oriented localized frequency correction framework that performs windowed Fourier-domain modulation before variational encoding. The proposed Localized Denoising-Correction Module extracts overlapping patches, applies local FFT, predicts patch-conditioned frequency-control parameters $(\alpha ,\sigma ,m)$, and reconstructs corrected inputs through inverse FFT and Hann overlap-add. This design preserves spatial locality while remaining differentiable and jointly trainable with the VAE objective. We evaluate the method on FashionMNIST, CIFAR-10, and PneumoniaMNIST under homogeneous and heterogeneous synthetic noise, and compare it with Direct VAE, AE, Local FFT-AE, best-tuned Fixed FFT-VAE, learnable Global FFT-VAE, BM3D, DnCNN, and FFDNet. The revised experiments demonstrate improvements in PSNR, SSIM, SNR, MSE, HFEN, and gradient-error, with statistical tests over random seeds. Parameter heatmaps and spectral visualizations further show that the learned local correction adapts to spatially varying corruption. PneumoniaMNIST is used only as a lightweight biomedical benchmark, and the method is not intended for clinical diagnosis. Full article

Ore districts are important targets for deep mineral exploration. As exploration depths increase, exploration strategies are shifting from ore-body identification based mainly on existing metallogenic models toward refined characterization of subsurface structures and deep mineralization targets. Owing to its high sensitivity to low-resistivity targets, the long-offset transient electromagnetic method (LOTEM) is an important geophysical tool for mineral exploration. However, complex geological settings and electromagnetic interference in ore districts often reduce interpretation accuracy and increase inversion non-uniqueness. To address these challenges, this study proposes an initial-model-guided 3D LOTEM inversion strategy. Background resistivity trends and structural information are incorporated into initial-model construction to provide a better-informed starting model before inversion. Taking concealed vein-type ore bodies in the deep part of the Zhaoxian ore district, northwestern Jiaodong, as the target, an approximate 3D geoelectrical model was built by integrating geological data, borehole information, profile interpretations, and electrical-property constraints. Based on this model, LOTEM forward-response characteristics, inversion comparisons, recovery behavior, and quantitative target-identification metrics were analyzed. The results show that the layered alteration background modifies the response of low-resistivity vein-type targets and reduces the distinguishability between ore-body anomalies and background structural responses, thereby affecting inversion recovery. The structure-constrained initial model concentrates model updates near the target zone and significantly improves anomaly recovery. Sensitivity tests further indicate that one-dimensional electrical information mainly constrains the approximate position and resistivity level of the low-resistivity anomaly, whereas layer-interface information improves the spatial correspondence between the recovered anomaly, the layered background, and the ore-body extension direction. When both types of prior information are integrated, ore-body recovery is significantly enhanced. Under the synthetic-model conditions considered in this study, the initial-model optimization strategy improves the recovery of concealed vein-type low-resistivity targets in a layered alteration background and may inform subsequent LOTEM survey design and inversion interpretation in the Zhaoxian ore district. Full article

Secondary dengue infections are often linked to more severe clinical outcomes, yet pre-existing antibodies may exert either protective or pathogenic effects. To evaluate the role of acute-phase dengue antibodies in pediatric dengue, we analyzed clinical and laboratory features, viremia, and antibody profiles in children infected with DENV-1. We conducted a retrospective study of patients under 18 years diagnosed with DENV-1 in Salta, Argentina. Viremia was quantified by real-time RT-PCR; acute-phase IgG antibodies (within 7 days from symptom onset) against DENV, DENV-1, and DENV-NS1 were measured by immunoassays, and neutralizing antibodies by plaque reduction neutralization tests. Among 151 patients (median age 12 years), 62% presented dengue with warning signs and one case progressed to severe dengue. Viremia was higher in probable primary infections than in probable secondary infections and did not correlate with disease severity. Probable secondary infections were characterized by acute-phase antibody profiles that did not associate with DENV viremia. Age-stratified analyses revealed that adolescents exhibited higher viremia levels than younger children in probable primary infections, while viremia levels were comparable across age groups in probable secondary infections. Furthermore, children younger than 10 years displayed acute-phase antibody levels similar to those of adolescents. In adolescents with probable secondary infections, anti-DENV and anti-DENV-1 IgG were inversely correlated with platelet counts, whereas neutralizing and anti-DENV-NS1 antibodies showed no association. Collectively, these findings indicate that probable secondary DENV infections in our pediatric cohort were characterized by acute-phase antibodies that were not associated with viremia control, and that in adolescents, anti-DENV and anti-DENV-1 IgG antibodies likely associated with platelet depletion. These results highlight important implications for vaccine design, underscoring the need for vaccines that elicit strong neutralizing responses while minimizing cross-reactivity and the risk of antibody dependent enhancement. Full article

Theswitched reluctance motor (SRM) suffers from torque ripple and speed fluctuations because of its doubly salient structure, magnetic saturation, and discrete commutation. To improve commutation performance and disturbance rejection, this paper proposes a progressive torque ripple suppression strategy. First, a multimodal magnetic co-energy model is developed to describe position-dependent saturation and generate the reference current through model inversion. Then, envelope extraction and frequency identification reveal the commutation-related periodic torque-error characteristic. Based on this feature, an angle-domain binned compensation method combining cycle averaging and linear interpolation is proposed to correct the reference current. A score-based finite-set PI hysteresis current controller is further designed to optimize magnetizing, freewheeling, and demagnetizing states, while a linear active disturbance rejection control (LADRC) speed loop improves load-disturbance rejection. Ablation studies verify the synergistic effect between angle-domain compensation and finite-set current execution. Robustness tests confirm low sensitivity to parameter variations, and theoretical analysis proves ultimate boundedness. Simulation results show that torque ripple is reduced to 2.00%, 2.03%, and 2.18% at 250, 500, and 1000 r/min, respectively. Under load-disturbance conditions, speed fluctuation is reduced by 59.92% and 57.20%, and all normalized parameter sensitivities remain below 0.35. Full article

The recovery of low- and medium-temperature waste heat using Organic Rankine Cycles (ORCs) is increasingly important for improving the efficiency and sustainability of industrial and energy systems. In compact ORC turboexpanders, high specific power output and large pressure ratios often require single- or two-stage turbines operating in transonic or supersonic regimes. Under these conditions, stator blade design is complicated by strong compressible-flow effects and, for organic working fluids, by real-gas thermodynamic behavior. Conventional supersonic stator design methods, such as the method of characteristics, are mainly applicable to the diverging supersonic portion of the blade passage, while the converging region is typically defined using empirical or heuristic prescriptions. This paper presents a physics-informed neural-network-based design method for supersonic turbine stator blades. The proposed framework generates the complete inter-blade passage, including both the converging and diverging regions, starting from a prescribed mean-line geometry and Mach number distribution. The velocity field is obtained by solving the governing equations of steady, inviscid, adiabatic, irrotational compressible flow within a PINN formulation. A hard boundary-condition strategy is used to impose the specified mean-line velocity distribution exactly, while real-fluid thermodynamic effects are incorporated through lookup tables for the speed of sound and density. The blade contours are then reconstructed from stream-function isolines predicted from the computed velocity field. The method is demonstrated for two working fluids: air, treated as a perfect gas, and toluene undergoing transcritical expansion. The resulting blade passages are first validated using inviscid CFD simulations, which show close agreement between the prescribed and computed mean-line Mach number distributions. Turbulent CFD simulations of the final blade cascades confirm smooth acceleration through the inter-blade passage, with no strong internal shocks and only weak fishtail shocks downstream of the trailing edge. For both fluids, the post-expansion ratio is approximately unity and the exit flow angle remains close to the prescribed blade metal angle, indicating well-matched supersonic stator designs. The results demonstrate that the proposed PINN-based design method provides a physically consistent approach for generating supersonic stator blade profiles for both ideal-gas and real-gas turbine applications. Full article

Background: Catheter-associated urinary tract infections (CAUTIs) are a major concern in patients with long-term indwelling urinary catheters, especially those with neurogenic bladder. This study assessed whether proactive cystoscopic removal of bladder debris reduces symptomatic UTI incidence and catheter blockage. Methods: This prospective, self-selected cohort study was conducted between January 2022 and December 2025 at a tertiary center in Taiwan. Enrollment occurred from January 2022 to June 2024, with follow-up completed by December 2025. Patients chose standard CDC-guided care (control, n = 63) or standard care plus flexible cystoscopy every 3 months for gentle low-volume evacuation (<100 mL normal saline) of dependent bladder debris (intervention, n = 141). Inverse probability of treatment weighting (IPTW) was used to address selection bias. Symptomatic UTIs were prospectively recorded using strict criteria. Cumulative incidence was analyzed with Kaplan–Meier methods and multivariable Cox regression. Results: After IPTW, baseline characteristics were well balanced. Median follow-up was 26 months (IQR 18–34). The incidence of catheter blockage was significantly lower in the intervention group (7.8% vs. 22.2%, p = 0.004). In the overall cohort, the reduction in symptomatic UTI incidence did not reach statistical significance (49.2% vs. 36.9%, p = 0.092). In the pre-specified spinal cord injury (SCI) subgroup (n = 71), the intervention was associated with improved UTI-free survival (log-rank p = 0.03; adjusted HR 0.52, 95% CI 0.28–0.96, p = 0.037; treatment × SCI interaction p = 0.042). All adverse events were Clavien–Dindo Grade I. No major complications occurred. Conclusions: Proactive gentle cystoscopic debris removal was associated with reduced catheter blockage. A signal toward lower symptomatic UTI risk was observed in the SCI subgroup, but not in the overall cohort. Due to the self-selected design and residual confounding, these findings are hypothesis-generating. Full article

The bias-dependent capacitance of varactors can introduce harmonic distortion into the circuits where they are utilized. A gate capacitance model valid through inversion–depletion has been presented for GaN HEMT varactors in the drive for their utilization in monolithic GaN ASICs. This work focuses on the circuit and the methodology employed to accurately measure on wafer the harmonic distortion caused by one such device. The circuit is presented and its design considerations and operation trade-offs are discussed, followed by a presentation of the measurements resulting from its use. Second- and third-order harmonic distortion is recorded and presented, with Verilog-A model simulations used to fit the measured data. The model consists of a charge-based expression of the HEMT varactor capacitance, with a minimal number of parameters. The good fit of the model is demonstrated, proving both the suitability of the circuit used for the measurements and the validity of the capacitance model for real-world applications. Full article

Background: Lipedema is a chronic disorder of subcutaneous adipose tissue characterized by symmetrical fat accumulation in the extremities, pain, and orthostatic edema. Objectives: This study aimed to assess whether high-resolution cutaneous ultrasound can detect measurable tissue-level changes in subcutaneous tissue over six months. Methods: A retrospective, single-center, real-world longitudinal observational cohort study was conducted in 60 women with lipedema followed at three timepoints (baseline, 3 months, 6 months). High-resolution ultrasound (18–20 MHz) measured subcutaneous and dermal thickness at standardized anatomical sites. Results: All primary ultrasound parameters decreased significantly over six months of conservative multicomponent management, which included individualized nutritional counseling and physical activity. Medial proximal thigh subcutaneous thickness declined by 18.7% (48.2 to 39.2 mm; p < 0.001). Edema prevalence fell from 100% to 55.0%. Echogenicity improved significantly between 3 and 6 months, suggesting a delayed structural remodelling effect distinct from early volumetric reduction. Ultrasound reductions were inversely correlated with weight loss, suggesting that ultrasound captures tissue-level information not fully reflected by anthropometric measures alone. Conclusions: Standardized cutaneous high-resolution ultrasound detected consistent tissue-level modifications over six months of routine clinical follow-up, capturing changes beyond anthropometric measures and representing a candidate monitoring tool warranting evaluation in controlled study designs. Full article

Cancer remains a major public health challenge among women worldwide, and diet quality may play an important role in cancer prevention. This narrative review synthesized evidence on the association between standardized diet quality indices—the DASH Score, Mediterranean Diet Score, and plant-based diet indices—and the risk of selected cancers in women, focusing on breast, colorectal, and ovarian cancer. English-language publications from 2020 to 2026 were reviewed, supplemented by key earlier methodological and epidemiological sources. The most consistent inverse associations were observed for colorectal cancer in relation to the DASH and Mediterranean dietary patterns, and for breast cancer in relation to healthful plant-based diets assessed using the hPDI. Evidence for ovarian cancer remains limited and inconclusive. Across dietary patterns, the findings indicate that overall diet quality, including the quality and processing level of plant-based foods, may be more relevant than the proportion of plant foods alone. The available evidence is limited mainly by heterogeneity in index definitions, predominance of observational designs, dietary assessment errors, and residual confounding. Overall, high-quality dietary patterns may be relevant to cancer prevention in women, although the strength and consistency of associations vary by cancer site and dietary assessment approach. Full article

Accurate prediction of hydrogen storage properties is needed for accelerating the design of body-centered cubic (BCC)-type V-based alloys, where the composition–property space is too large for trial-and-error experimentation alone. Here we report a stacking ensemble framework that combines XGBoost, Random Forest, Extra Trees, and Gradient Boosting as base learners with linear or ridge meta-learners, with hyperparameters tuned by a genetic algorithm (GA). Three descriptor strategies are compared across seven target properties: composition-only (C), property-only (P), and composition–property fusion (CP). On target-specific subsets containing 95–901 experimental records and 17 alloying elements (the smallest subset, 95 records, corresponds to maximum hydrogen capacity $C_{\max }$, which may limit model stability for that property), the best model for each target gives $R^2$ values from 0.865 to 0.981 (all metrics are from five-fold cross-validation; no independent external test set was employed); the P-type model for desorption plateau pressure reaches $R^2=0.981$. SHapley Additive exPlanations (SHAP) analysis shows that physically derived descriptors, including valence electron concentration, atomic size mismatch, and electronegativity difference, dominate in P and CP models, whereas Ti and Cr contents are the leading compositional features. A Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimizer then ranks 3000 final candidate alloy compositions in six alloy families using four objectives: high predicted retention, high predicted cycle count, high predicted BCC phase ratio, and a low cost proxy; these candidates represent model-based predictions and await experimental synthesis and cycling validation. The V–Ti–Cr–Fe–Mn system contains the largest number of candidates with predicted retention above 99%, while Ti-free V–Cr–Fe–Mn–Al alloys provide low-cost alternatives in the model search space. First-principles calculations on four representative alloys only show that BCC structures are lower in energy than FCC structures by about 0.08–0.13 eV/atom and that hydrogenated structures exhibit clear charge accumulation around H sites, supporting the physical plausibility of the data-driven screening results, though density functional theory (DFT) validation does not replace experimental measurement of PCI curves and cyclic stability. Full article

Artificial intelligence (AI), particularly deep learning (DL), is revolutionizing optical metamaterial design by overcoming the fundamental challenges of multidimensional parameter spaces, nonlinear structure–property relationships, and the intrinsic non-uniqueness of inverse problems. By learning complex mappings between geometric structures and electromagnetic responses, DL enables rapid forward prediction and on-demand inverse design without computationally intensive full-wave simulations. This review provides a comprehensive survey of AI-driven design methodologies across four key metamaterial platforms: localized resonant nanostructures, metasurfaces, periodic and guided-wave photonic structures, and complex scattering systems. For each platform, we systematically examine the neural network architectures employed, the specific design challenges addressed, and the representative achievements attained. These data-driven approaches not only significantly accelerate the discovery of high-performance structures but also offer new opportunities for extracting physical insights into light–matter interactions. We assess the critical challenges of data efficiency, model interpretability, and experimental feasibility, and outline emerging research directions that may address these barriers. This review aims to provide both a comprehensive summary of the current state of the art and forward-looking perspectives for this rapidly evolving interdisciplinary field. Full article

In the context of the global transition towards energy systems with a high share of renewable energy, efficient and large-scale energy storage technologies are essential for improving the stability and flexibility of power grids. Phase change thermal energy storage has attracted considerable attention because of its high energy density and nearly isothermal heat release capability. However, its practical application remains constrained by the intrinsically low thermal conductivity of phase change materials (PCMs). For instance, 0.2–0.3 W/m·K for organic paraffins, 0.15–0.35 W/m·K for fatty acids, and 0.5–1.0 W/m·K for salt hydrates lead to slow charging and discharging rates. Incorporating metal foams into PCMs to form composite PCMs has emerged as a promising strategy, as metal foams can significantly improve effective thermal conductivity and enhance internal heat transfer. This paper systematically reviews recent advances in metal foam-enhanced phase change thermal energy storage, with particular emphasis on numerical modeling and structural optimization. First, the heat transfer enhancement mechanisms of metal foam/PCM composites are analyzed, together with the key performance indicators used to evaluate thermal storage performance. Second, material-level developments are reviewed, including pore structure parameters, interfacial engineering, and advanced fabrication methods. The review then discusses current structural design strategies, such as graded pore structures and partially filled configurations, as well as hybrid enhancement methods that combine passive and active heat transfer enhancement. Particular attention is paid to numerical modeling approaches at both pore and system scales, which are used to predict and optimize thermal behavior. In addition, optimization methods, including topology optimization, machine learning, and genetic algorithms, are examined for their potential to inversely design foam structures with tailored thermal performance. Finally, the key challenges in this field are summarized, and future research directions are proposed. These include multi-scale intelligent design, integration with complementary thermal management technologies, and the development of scalable solutions for engineering applications. This review aims to provide a systematic reference for achieving performance breakthroughs and promoting the practical deployment of phase change thermal energy storage technologies. Full article

This study examines the relationship between social–emotional skills (SES) and perceptions of school violence among primary school students (3rd through 8th grade), considering both associations and heterogeneity in social–emotional profiles. A quantitative, non-experimental, cross-sectional design was used, with a sample of 311 students aged 8 to 15 (M = 10.65, SD = 1.69). SES were assessed across four dimensions (stress management, adaptation, sense of safety, and expectations), while perceptions of school violence included verbal, physical, relational, digital, and teacher-perpetrated acts. The results show that all dimensions of SES have significant inverse associations with perceptions of violence, with moderate magnitudes, suggesting their role as cognitive–emotional resources. Likewise, three distinct SES profiles (high, medium, and low; n = 151, 134, and 26, respectively) were identified, with the profile exhibiting the highest levels generally reporting lower perceptions of school violence. However, differences between profiles do not follow a simple linear pattern, suggesting more complex, non-incremental dynamics. Nevertheless, no differences in the perception of violence were found based on gender, despite evident differences in SES. The results indicate that SES operate as situated functional systems that modulate the interpretation of violence. It is concluded that understanding school violence requires integrating variable- and profile-centred approaches and considering the interaction between individual resources and school contexts. Full article

Background: The Mercer Universal Prosthesis (MUP), designed with a default “neutral” (vertical) socket alignment, was developed to simplify transtibial prosthetic fitting, reduce labor costs, and improve access to prosthetic care in low-resource settings. Methods: This present longitudinal study evaluated biomechanical and functional outcomes at baseline, 6 months, and 12 months in 20 transtibial amputees fitted with the MUP. Results: Functional outcomes, assessed using the SF-36, showed significant improvement in overall health scores at 12 months (p < 0.001), while physical function and energy/fatigue domains remained unchanged (p = 0.686 and p = 0.211, respectively). Biomechanically, sagittal kinematics, measured using inertial motion capture, revealed significant limb × time interactions for hip flexion, knee flexion, and ankle plantarflexion. At 6 months, maximum hip flexion (−7°, p = 0.008) and knee flexion (−11°, p = 0.005) of the prosthetic limb were decreased versus baseline. At 12 months, the only observed difference was increased maximum ankle plantarflexion of the intact limb (+5° vs. baseline, p = 0.016). Muscle effort, quantified via the integral of EMG throughout the gait cycle, did not differ significantly between prosthetic and intact limbs across time points. Gait symmetry index (GSI) scores for hip, knee, and ankle range of motion trended toward gradual improvement but without statistical significance (p > 0.05). Conclusions: The MUP performance was maintained over 12 months, with stable biomechanical performance and meaningful quality-of-life gains. These findings support its potential as a cost-effective solution to expand prosthetic accessibility in low- and middle-income countries. Full article