Search Results (9,498)

Background: Quality of life (QoL) after transradial access in diagnostic cerebral angiography may be shaped by procedural demands as well as by the ambulatory setting itself. This study, for the first time, prospectively explored this dimension through follow-up assessments of QoL after the procedure. Methods: In this prospective study, QoL was assessed using the 36-Item Short Form Survey (SF-36), including the Physical and Mental Component Summary (PCS and MCS) as well as eight domain-specific subscales. After right transradial cerebral angiography, the SF-36 questionnaire was administered at baseline (pre-procedure), as well as at 1-month and 3-month follow-up visits. Mean PCS and MCS values were analyzed over time using linear mixed-effects regression models. In post hoc analyses, univariate and multivariable models were used to assess the influence of potential confounders. For subgroup analysis, patients were classified as transient deteriorators if PCS and/or MCS worsened by more than 0.5 SD at 1 month compared with baseline but not at 3 months. Permanent deteriorators were defined as worsening by more than 0.5 SD at both 1 month and 3 months compared with baseline. Results: A total of 35 patients (62.9% female) were recruited over the 12-month study period, with a mean age of 59.1 ± 10.1 years. No significant overall time effect was observed for mean PCS and MCS (p = 0.970 and p = 0.076). MCS showed a significant increase at 1 month compared with baseline (p = 0.046), with a trend toward significance at 3 months (p = 0.053). In post hoc analyses, sex, neurosurgical status, and dose area product were associated with MCS in univariate analyses (p < 0.05), but these associations did not persist after multivariable adjustment. For PCS, only age showed a significant association in univariate analysis (p < 0.05). In subgroup analyses, transient deterioration was more frequent in PCS than in MCS (11.4% [95% CI 3.2–26.7%] vs. 5.7% [95% CI 0.7–19.2%]), and permanent deterioration was also more common in PCS at 1- and 3-month follow-up (14.3% [95% CI 4.8–30.3%] vs. 8.6% [95% CI 1.8–23.1%]). Impairment predominantly involved the bodily pain subscale (88.9% [95% CI 51.8–99.7%]) within PCS and the vitality (80.0% [95% CI 28.4–99.5%]) and mental health sub-scales (80.0% [95% CI 28.4–99.5%]) within MCS. Conclusions: This short-term follow-up assessment demonstrated preserved QoL following transradial diagnostic cerebral angiography. Transient or permanent deterioration occurred in no more than five patients per subgroup (14%). These findings support the notion that a radial-first approach can be safely considered for diagnostic cerebral angiography without compromising patient-reported outcomes. Full article

This study presents an application-oriented CFD–FEM integrated workflow for analyzing chamber-side field non-uniformity and kelp-side thermal response during infrared drying. A three-dimensional steady-state CFD model was first established to reconstruct the chamber temperature, airflow, and incident radiation fields under certain operating conditions. Numerical consistency was checked through residual convergence; monitored variables; and global mass balance, for which the net mass imbalance was 0.004077 kg s⁻¹. The reconstructed mid-plane fields were then processed in MATLAB to extract the mean values, extrema, and coefficients of variation, and a composite objective function was used to screen the tested operating conditions in terms of field uniformity, temperature band compliance, and overheating risk. The thermal loads obtained via CFD were subsequently mapped onto a kelp finite element model to simulate the transient surface temperature evolution. Among the tested cases, case01 yielded the lowest composite objective value (J = 0.4535); its mapped kelp response showed a mean surface temperature of 62.23 °C and a maximum temperature of 63.57 °C at the exported time step. The proposed framework is therefore suitable for thermal response assessment and operating condition screening, although determining the full drying behavior still requires coupling of moisture transfer and improved experimental validation. Full article

Ground source heat pump (GSHP) systems, while energy-efficient, often face persistent soil thermal imbalance in heating-dominated severe cold regions, which undermines their long-term performance and sustainability. This study proposes a TRNSYS-GenOpt framework for the life-cycle cost optimization of hybrid GSHP systems integrating electric boilers and geothermal regulation towers. A transient model for a 5650 m² fire station in Changchun was developed, employing the Hooke–Jeeves algorithm to co-optimize boiler capacity, borehole depth, and geothermal regulation tower airflow under constraints on heating supply temperature and soil thermal balance. Time-of-use electricity pricing was incorporated for realistic operational economics. The optimized configuration (148 m, 864.8 kW, 290,400 m³/h) achieved a minimum 20-year life-cycle cost of CNY 1.13 million. Sensitivity analysis revealed “rigid design, flexible cost” characteristics: optimal parameters remained invariant across discount rate variations (3.5–7.5%) and equipment costs (±20%), while life-cycle cost showed the highest sensitivity to electricity pricing and discount rates. The long-term simulation confirmed compliance with all physical constraints. This methodology demonstrates that thermodynamic constraints supersede economic trade-offs in severe cold climates, providing engineers with a reliable tool for sustainable hybrid geothermal system design. Full article

Background/Objectives: Chronic liver diseases, including metabolic dysfunction-associated steatohepatitis (MASH) and chronic viral hepatitis (CVH), are major global health concerns due to their potential progression to cirrhosis, liver failure, and hepatocellular carcinoma. Because liver biopsy, despite meeting the diagnostic gold standard, is invasive and associated with complications, non-invasive fibrosis assessment tools have been increasingly recommended in clinical practice. This study aimed to compare the diagnostic performance of several non-invasive fibrosis markers (ARR, APRI, FI, FIB-4, API, NFS, BARD) and transient elastography in detecting advanced liver fibrosis (F4) in patients with MASH and CVH. Methods: This retrospective study included 237 adult patients (77 MASH, 160 CVH) who underwent liver biopsy between 2017 and 2025 at the University Clinical Center of Serbia. CVH included chronic hepatitis B (CHB) and C (CHC). Patients were evaluated using serum fibrosis indices and TE, and results were compared to histological staging (F0–F4). ROC analysis assessed diagnostic performance. Results: Cirrhosis (F4) was more common in CVH than MASH (p < 0.001). In MASH, NFS (AUROC 0.931), FIB-4 (0.915), BARD (0.872), and APRI (0.878) showed high diagnostic accuracy for F4. In CHC, APRI (0.931), FIB-4 (0.863), and TE (0.938) had strong performance, while in CHB, TE (0.987) outperformed FIB-4 (0.821). Sensitivity and specificity varied by test and cohort, with TE consistently yielding the best results where available. Conclusions: Non-invasive methods, particularly NFS and FIB-4 for MASH and TE for CVH, effectively identify advanced fibrosis. Their application could significantly reduce the need for biopsy, especially in high-risk groups. TE demonstrated superior accuracy, but access limitations highlight the continued relevance of serum-based scores. Full article

Bearing fault diagnosis is an important task for condition monitoring and predictive maintenance of rotating machinery. Nevertheless, many existing deep learning-based methods have difficulty in jointly modeling multi-scale fault characteristics, adaptively highlighting informative features, and maintaining robustness under noisy measurement conditions. To address these issues, this study presents MDCAD-Net, a multi-dilated convolution attention denoising network that integrates multi-scale temporal feature extraction, attention-based feature refinement, and explicit noise suppression within an end-to-end learning framework. Parallel dilated convolutions with different dilation rates are employed to capture short-duration transient impulses as well as long-range periodic patterns in vibration signals. Channel-wise feature recalibration using squeeze-and-excitation networks and spatial-temporal attention via a convolutional block attention module are combined to enhance informative representations. In addition, a denoising block with gated attention and residual connections is introduced to reduce noise interference while retaining fault-related signal components. Experiments conducted on the Case Western Reserve University bearing dataset show that the proposed method achieves a classification accuracy of 98.93% and yields competitive performance compared with several commonly used deep learning models. Ablation studies and feature visualization results further illustrate the contributions of the individual components and the separability of the learned feature representations under noisy conditions. The results indicate the potential of the proposed framework for practical bearing fault diagnosis under noisy operating conditions. Full article

The increasing integration of nonlinear loads in modern power systems has made harmonic pollution a critical challenge to the operational safety of power cables. This study develops a frequency-dependent high-voltage cable system model using the ATP-EMTP (Alternative Transients Program-Electro Magnetic Transient Program) electromagnetic transient simulation platform, systematically investigating the amplification mechanisms and propagation characteristics of grounding currents under multi-type harmonic disturbances. A frequency-dependent parameter correction model is established by integrating the conductor skin effect and the dielectric relaxation properties of the insulation layers. This model incorporates the multi-structure combination among conductors, insulation, and metallic screen. It effectively overcomes the limitations of conventional lumped-parameter models in higher frequency harmonic analysis. Key findings are as follows: (1) The combined influence of harmonic frequency and amplitude leads to a grounding current amplification of up to 445 times (at 1950 Hz with 30% distortion level). Notably, current-source excitation produces significantly greater amplification than voltage-source excitation. (2) The distributed capacitance of long-distance cables (>8 km) exacerbates resonance risks within specific frequency bands (750–1250 Hz), resulting in a maximum harmonic amplification factor of 34.73 (observed for the 17th harmonic in a 15 km cable). (3) The contribution of voltage-source harmonics diminishes to less than 5% of the total current at high frequencies (≥1250 Hz), indicating a pattern of current-dominated harmonic superposition. Full article

This study aimed to develop and validate a physics-informed neural network (PINN) framework for data-efficient and physically consistent process optimization in the laser powder bed fusion (LPBF) of Inconel 718 (IN718) superalloy. Laser powder bed fusion (LPBF) is widely adopted for fabricating Inconel 718 (IN718) components in aerospace and energy applications; however, navigating its high-dimensional, nonlinear process parameter space remains a central challenge. High-fidelity finite element simulations are computationally prohibitive for extensive parameter sweeps, whereas purely data-driven machine learning (ML) models are limited by data scarcity and unphysical extrapolation behavior. This study presents a physics-informed neural network (PINN) framework that embeds the transient heat conduction equation and Goldak double-ellipsoidal heat source model directly into the neural network training loss, enforcing thermophysical consistency simultaneously with data fidelity. The model was trained on a curated, multi-source dataset of LPBF IN718 parameter combinations drawn from peer-reviewed experimental studies and validated finite element simulation outputs, spanning the laser power (70–400 W), scan speed (200–2000 mm/s), hatch spacing (50–140 µm), and layer thickness (20–50 µm). The PINN predicted the melt pool width, depth, peak temperature, and relative density with mean absolute percentage errors (MAPE) of 3.8%, 4.7%, 3.1%, and 1.9%, respectively, outperforming a baseline artificial neural network (ANN) with an identical architecture. The framework correctly identified the optimal volumetric energy density (VED) window of 55–105 J/mm³, yielding relative densities ≥99.5%, consistent with the published experimental thresholds for IN718. A data efficiency analysis demonstrated that the PINN with 25% training data achieves a performance equivalent to that of the fully trained ANN with 100% data, confirming an approximately four-fold data efficiency improvement attributable to physics-informed regularization, consistent with theoretical predictions. Sensitivity analysis via automatic differentiation confirmed that laser power and scan speed were the dominant parameters (~85% combined variance), which is in agreement with previous studies. This study provides a computationally efficient, interpretable, and physically consistent ML pathway for the accelerated process qualification of IN718 components for aerospace and energy applications. Full article

Harmonic Path Integral Diffusion (H-PID) provides an analytically tractable framework for sampling from a target density $p^{\left(\mathrm{tar}\right)}\left(x\right)\propto exp(-E\left(x\right))$. H-PID can be viewed as a diffusion bridge model solving a stochastic optimal transport problem from a $\delta$-density at $t=0$ to the target density at $t=1$. The dynamics are governed by a controlled stochastic differential equation, and the corresponding variational stochastic optimal transport objective combines a time-dependent quadratic potential, ${\beta }_t{\parallel x_t\parallel }^2/2$, with a kinetic control cost, $\parallel u(t;x_t){\parallel }^2/2$. The focus of this paper is the design of the temporal stiffness protocol ${\beta }_t$, which enables explicit control of intermediate sampling dynamics when the terminal density is fixed. We exploit the central advantage of H-PID—its integrability—which yields an explicit representation of the optimal control in terms of the target density and Green functions of the associated linear forward and backward diffusion-in-a-potential problems. Our main contribution is to convert this integrable structure into a practical methodology for protocol optimization. Specializing to piecewise-constant stiffness schedules and Gaussian-mixture targets, we develop two complementary optimization principles: The first is a deterministic one, relying on explicit evaluation of the dynamic marginals, and exemplified on a velocity-gradient-sensitivity objective, which provides a computationally controlled framework for optimizing transport regularity and stiffness. The second is a stochastic one, implemented via sampling, and exemplified on sharpness-based temporal-memory objective regularized to favor transitions within a prescribed time window that targets the temporal organization of the sampling path. These two objectives illuminate different aspects of the same protocol-design problem. The velocity-gradient-sensitivity objective serves as a clean methodological backbone and supports interpretable optimization and scaling studies. The sharpness-based objective reveals that schedule quality is target-dependent, and that the dependence on $\beta$ is not universal: different target geometries may favor different stiffness regimes and qualitatively different transient organizations. Examples with low- and moderate-dimensional Gaussian mixtures demonstrate that the proposed approach can control not only the terminal sampling accuracy but also the transient evolution of probability mass, while remaining computationally light and theoretically transparent. Full article

In order to protect the high-sensitivity optical lens of the “magnetic field and velocity field imager” in extreme deep space environments, this paper proposes a new type of dual redundant planetary differential lens cover drive mechanism. In view of the critical vulnerability that traditional single-motor direct drive is prone to sudden mechanical jamming and catastrophic single-point failure (SPF) in severe tasks such as Jupiter exploration, this study constructs a “dual input single output (DISO)” rigid decoupling architecture from the perspective of physical topology. Through theoretical analysis and kinematic modeling, the adaptive decoupling mechanism of the two-degree-of-freedom (2-DOF) system under unilateral mechanical stalling is revealed. Dynamic analysis shows that in the nominal dual-motor synergy mode, the system shows a significant “kinematic load-sharing effect”, thus greatly reducing the sliding friction and gear wear rate. In addition, under the severe dynamic fault injection scenario (maximum gravity deviation and sudden jam superposition of a single motor), the cold standby motor is activated and the dynamic takeover is quickly performed. The high-fidelity transient simulation based on ADAMS verifies that although the fault will produce transient global torque spikes and pulsed internal gear contact forces at the moment, all extreme dynamic loads remain well within the structural safety margin. The output successfully achieved a smooth transition, which is characterized by a non-zero-crossing velocity recovery. This research provides an innovative theoretical basis and a practical engineering paradigm for the design of high-reliability fault-tolerant mechanisms in deep space exploration. Full article

Platelet-rich plasma (PRP) and mesenchymal stem cells (MSCs) are promising regenerative treatments for lumbar degenerative disc disease (DDD), but their comparative efficacy is unclear. This systematic review and indirect meta-analysis, conducted according to PRISMA guidelines and the PICOS framework, evaluated their effects on pain, function, and safety. PubMed, Scopus, and Web of Science were systematically searched, yielding 1694 records, of which 21 studies (nine randomized controlled trials [RCTs] and 12 prospective studies) were included. Data were analyzed qualitatively and quantitatively, and risk of bias was assessed using RoB 2 and ROBINS-I. Meta-analyses of randomized controlled trials (RCTs) examined pain and disability at 6 and 12 months using a random-effects model. Indirect comparisons were performed using the Bucher method. Qualitative synthesis showed that PRP consistently reduced pain (often > 50%) and improved function, frequently outperforming corticosteroids. MSCs provided sustained benefits, with follow-up extending up to 72 months in some studies. Quantitative meta-analysis of five RCTs demonstrated that PRP significantly reduced pain at 6 months (mean difference [MD] −16.4 mm) and disability (ODI −12.7), with effects persisting at 12 months in one study. In contrast, MSCs showed a modest but significant reduction in pain (MD −4.3 mm) and minimal functional improvement. Indirect comparisons favored PRP over MSCs at 6 months. Both treatments exhibited favorable safety profiles, with mostly mild and transient adverse events. Overall, PRP appears more effective than MSCs in the short to mid-term, although both therapies are safe. Further high-quality head-to-head RCTs are needed to confirm these findings and define optimal clinical indications. Full article

Transformers serve as crucial hubs for power transmission, but during no-load energization, the nonlinear magnetization of their cores frequently induces extreme magnetizing inrush currents. Current suppression methods encounter challenges regarding transient feature extraction and excessive circuit complexity. To overcome these limitations, this study develops a high-fidelity model of a 100 kVA transformer using MATLAB/Simulink to investigate the interaction between residual flux and the closing angle. Extensive simulations were executed across a closing phase angle range of 0° to 360° and a residual flux domain of −0.8 p.u. to 0.8 p.u. Furthermore, this study utilizes Wavelet and Clarke transforms to extract characteristic parameters and quantitatively analyze the transients within the energy domain, enabling a multi-scale assessment of the mitigation efficacy based on these extracted features. The analytical results demonstrate that an optimal pre-magnetization distribution of −0.8 p.u. for Phase A, 0 p.u. for Phase B, and 0.8 p.u. for Phase C, coupled with a target closing angle of 330°, achieves the best suppression. This strategy strictly clamps the peak inrush current to 1.5 times the rated current, significantly outperforming conventional demagnetization alone. Consequently, this highly pronounced mitigation effect provides robust support for reliable transformer protection and overall power grid security. Full article

The skin–brain axis constitutes a complex, bidirectional network integrating cutaneous sensory, immune, and neuroendocrine systems with central neural circuits involved in emotion regulation, stress responsivity, and social cognition. Advances in psychodermatology and cosmetic science have progressively extended this framework to the emerging field of neurocosmetics, which explores how topical formulations, sensorial properties, and cutaneous neuromodulators may influence psychological well-being, affective states, and perceived stress. The aim of this narrative review is to synthesize current evidence on the biological foundations of the skin–brain axis and to critically examine the implications of these mechanisms for neurocosmetic interventions from a psychological and psychiatric perspective. It describes the biological substrates underlying skin–brain communication, including the cutaneous hypothalamic–pituitary–adrenal axis, neuropeptides, neurotrophins, transient receptor potential channels, and endocannabinoid signaling, and examines how these pathways are targeted by neurocosmetic interventions. Particular attention is devoted to neuroactive compounds, such as peptides, cannabinoids, botanicals, and aromatherapeutic molecules, as well as to sensorial strategies involving texture, temperature, and olfactory cues, which may modulate mood, anxiety, and self-perception through peripheral mechanisms. From a psychological and psychiatric perspective, the review discusses the intersection between stress-related skin conditions, body image disturbances, and emotional dysregulation, highlighting how cosmetic practices may influence subjective well-being beyond purely aesthetic outcomes. Methodological limitations of the existing literature, including the heterogeneity of study designs and outcome measures, as well as ethical considerations related to mood- and stress-related claims in cosmetic products, are critically examined. Finally, future research directions are outlined, and a translational framework is proposed to integrate dermatology, neuroscience, and mental health within next-generation cosmetic science. Full article

In mechanical material evaluation and biomechanical studies, Young’s modulus is commonly used to describe the elastic response of materials. Existing measurement approaches are mainly based on contact loading or large-scale experimental instruments, which may limit excitation controllability and system integration in practical applications. In this work, a Young’s modulus measurement system based on electromagnetic excitation and capacitive sensing is designed and experimentally implemented. The system is composed of an electromagnetic driving unit and a capacitive sensing unit. In the driving unit, a coaxial copper wire coil is arranged with a ring-shaped neodymium–iron–boron permanent magnet assembly. When a square-wave electrical signal is applied, the coil generates a Lorentz force, which produces transient mechanical excitation on the tested sample. The resulting micro-scale deformation of the material surface is monitored using a coaxial passive capacitive sensor. The sensor records the relative capacitance variation (ΔC/C₀) induced by deformation during excitation. Based on the measured capacitance response, a force–capacitance coupling model is established to relate the electrical signal to the mechanical behavior of the material, enabling the inverse calculation of Young’s modulus. Commercial standard hardness blocks were used for system calibration and performance verification. The experimentally obtained Young’s modulus values are consistent with reference data within an acceptable deviation range, indicating that the proposed system can be used for quantitative evaluation of elastic properties. Due to its compact configuration and controllable excitation, the system is suitable for non-invasive surface mechanical characterization of soft materials, including biological tissues. Full article

This study quantified nutrient accumulation and partitioning among the kernel, shell, husk, rachis, and leaves during fruit development in three macadamia cultivars. Racemes and leaves were sampled at biweekly intervals until kernel maturity. The shell and rachis ceased to accumulate biomass earlier in the season than the husk or kernel. Nitrogen (N) and potassium (K) were the dominant nutrients accumulated in the fruit. Despite declining concentrations between 80 and 140 DAF, total kernel nutrient content continued to increase, indicating sustained nutrient import during this critical period. The kernel was the primary sink for N, phosphorus (P), sulfur (S), and magnesium (Mg), with peak accumulation occurring during rapid kernel growth at 80–175 days after flowering (DAF). In contrast, the accumulation of calcium (Ca) and manganese (Mn) into the kernel ceased earlier, suggesting limited late-stage mobility. The husk accumulated more K than the kernel and remained an active sink for K, S, Mg, Ca, and Mn until maturity, while N, P, and boron (B) accumulation slowed after ~107 DAF. The shell contributed minimally to nutrient demand, with N, zinc (Zn), and B accumulation ceasing after shell hardening (90–110 DAF). The cultivars exhibited consistent temporal patterns, differing mainly in magnitude. Nutrient partitioning efficiency among- the fruit components was highest for cv. A38. The rachis acted as a transient sink early in development before declining in mobile nutrients, while leaf nutrient dynamics did not reflect fruit demand. Full article

This paper describes the thermal and energy performance of three roof configurations: a conventional concrete slab, a BIPV system, and a BIPV system equipped with passive aluminum fins. Three-dimensional transient finite element simulations were carried out under field-measured 24 h meteorological boundary conditions characteristic of hot climates. The objective of this study is to quantify the impact of PV integration and passive cooling strategies on heat transfer behavior and building energy performance. The BIPV roof achieved a 38.4% lower residual temperature than the concrete slab at 19:00, indicating superior heat dissipation. The addition of passive fins reduced module temperature by up to 10–12 °C and decreased peak roof temperature by up to 12%. This temperature reduction decreased electrical losses from 13.2% to 10.4%, resulting in a 21% relative reduction in temperature-induced losses. The predicted temperature ranges (≈60–75 °C under peak conditions) are consistent with values reported in experimental and numerical studies of BIPV systems in hot climates, supporting the physical realism of the model. Convective heat transfer was represented using effective coefficients, providing a computationally efficient engineering approximation of air-side heat exchange. Despite construction cost increases of up to 38%, PV integration achieved competitive payback periods of approximately 8.5–9 months under hot climate conditions. This economic assessment is based on a simple payback approach using an incremental cost formulation, where the photovoltaic system replaces the conventional concrete roof, reducing the effective investment. This study introduces a reproducible 3D transient FEM methodology for evaluating BIPV roofs under field-measured climatic boundary conditions. The framework explicitly couples geometry-resolved passive cooling, full-day thermal evolution, and temperature-dependent electrical losses, providing a physically consistent basis for assessing BIPV design alternatives in hot climates. Full article