Search Results (15,090)

(1) Background: Low back pain (LBP) is the most prevalent cause of disability worldwide, yet current assessment relies mainly on subjective questionnaires, underscoring the need for objective and interpretable biomarkers. Bioelectrical impedance parameter (BIP), quantified by resistance (R), impedance magnitude (Z), and phase angle (PA), reflects tissue hydration and cellular integrity and may provide physiological correlates of pain; (2) Methods: This cross-sectional study used lumbar BIP and demographic characteristics from 83 participants (38 with lumbar BIP and 45 normal controls). We applied Extreme Gradient Boosting (XGBoost), a regularized tree-based machine learning (ML) algorithm, with stratified five-fold cross-validation. Model interpretability was ensured using SHapley Additive exPlanations (SHAP), which provide global importance rankings and local feature attributions. Outcomes included classification of LBP versus healthy status and regression-based prediction of pain scales: the Visual Analog Scale (VAS), Oswestry Disability Index (ODI), and Roland–Morris Disability Questionnaire (RMDQ); (3) Results: The classifier achieved high discrimination (ROC–AUC = 0.996 ± 0.009, sensitivity = 0.950 ± 0.068, specificity = 0.977 ± 0.049). Pain prediction showed best performance for VAS (R² = 0.70 ± 0.14; mean absolute error = 1.23 ± 0.27), with weaker performance for ODI and RMDQ; (4) Conclusions: These findings suggest that explainable ML models applied to BIP could discriminate between LBP and healthy groups and could estimate pain intensity, providing an objective complement to subjective assessments. Full article

Background/Objectives: Diamine oxidase (DAO) enzyme metabolizes dietary histamine in the gastrointestinal tract. DAO deficiency can lead to histamine intolerance (HIT), manifesting as migraines, gastrointestinal disturbances, and allergic reactions. DAO supplementation has been shown to enhance histamine breakdown, alleviating these symptoms. This randomized, double-blind, single ascending dose (SAD) Phase I clinical trial aimed to evaluate the safety and tolerability of escalating doses of DAO supplementation in healthy volunteers. Methods: Thirty participants were randomly assigned to receive single doses of 42 mg, 84 mg, or 210 mg of DAO extract (adiDAO^® Veg) or placebo under fasting conditions. Vital signs, laboratory parameters, and adverse events (AEs) were monitored. Results: No serious adverse events or clinically significant changes in vital signs, ECGs, or laboratory parameters were observed. Conclusions: This trial confirms the safety and tolerability of high-dose DAO supplementation. Future studies are recommended to explore the effects of chronic high-dose administration and alternative dosage forms to improve convenience. Full article

This paper proposes a novel method for locating single-phase grounding faults in generator stator windings with high resistance, which are typically challenging to locate due to weak fault characteristics. The method utilizes an active voltage injection technique combined with traveling wave reflection analysis, singular value decomposition (SVD) denoising, and discrete wavelet transform (DWT). A DC voltage signal is then injected into the stator winding, and the voltage and current signals at both terminals are collected. These signals undergo denoising using SVD, followed by DWT, to identify the arrival time of the traveling waves. Fault location is determined based on the reflection and refraction of these waves within the winding. Simulation results demonstrate that this method achieves high accuracy in fault location, even with fault resistances up to 5000 Ω. The method offers a reliable and effective solution for locating high-resistance faults in generator stator windings without requiring winding parameters, demonstrating strong potential for practical applications. Full article

This paper introduces Exponentiated Inverse Exponential Distribution (EIED), a novel probability model developed within the power inverse exponential distribution framework. A distinctive feature of EIED is its highly flexible hazard rate function, which can exhibit increasing, decreasing, and reverse bathtub (upside-down bathtub) shapes, making it suitable for modeling diverse lifetime phenomena in reliability engineering, survival analysis, and risk assessment. We derived comprehensive statistical properties of the distribution, including the reliability and hazard functions, moments, characteristic and quantile functions, moment generating function, mean deviations, Lorenz and Bonferroni curves, and various entropy measures. The identifiability of the model parameters was rigorously established, and maximum likelihood estimation was employed for parameter inference. Through extensive simulation studies, we demonstrate the robustness of the estimation procedure across different parameter configurations. The practical utility of EIED was validated through applications to real-world datasets, where it showed superior performance compared to existing distributions. The proposed model offers enhanced flexibility for modeling complex lifetime data with varying hazard patterns, particularly in scenarios involving early failure periods, wear-in phases, and wear-out behaviors. Full article

This paper presents a comprehensive study on automated defect detection in complex structures using phased array ultrasonic testing data, focusing on both traditional signal processing and advanced deep learning methods. As a non-AI baseline, the well-known signal-to-noise ratio algorithm was improved by introducing automatic depth gate calculation using derivative analysis and eliminated the need for manual parameter tuning. Even though this method demonstrates robust flaw indication, it faces difficulties for automatic defect detection in highly noisy data or in cases with large pore zones. Considering this, multiple DL architectures—including fully connected networks, convolutional neural networks, and a novel Convolutional Attention Temporal Transformer for Sequences—are developed and trained on diverse datasets comprising simulated CIVA data and real-world data files from welded and composite specimens. Experimental results show that while the FCN architecture is limited in its ability to model dependencies, the CNN achieves a strong performance with a test accuracy of 94.9%, effectively capturing local features from PAUT signals. The CATT-S model, which integrates a convolutional feature extractor with a self-attention mechanism, consistently outperforms the other baselines by effectively modeling both fine-grained signal morphology and long-range inter-beam dependencies. Achieving a remarkable accuracy of 99.4% and a strong F1-score of 0.905 on experimental data, this integrated approach demonstrates significant practical potential for improving the reliability and efficiency of NDT in complex, heterogeneous materials. Full article

This study presents a qualitative analysis of the fractional coupled nonlinear Schrödinger equation (FCNSE) to obtain its complete set of solutions. An appropriate wave transformation is applied to reduce the FCNSE to a fourth-order dynamical system. Due to its non-Hamiltonian nature, this system poses significant analytical challenges. To overcome this complexity, the dynamical behavior is examined within a specific phase–space subspace, where the system simplifies to a two-dimensional, single-degree-of-freedom Hamiltonian system. The qualitative theory of planar dynamical systems is then employed to characterize the corresponding phase portraits. Bifurcation analysis identifies the physical parameter conditions that give rise to super-periodic, periodic, and solitary wave solutions. These solutions are derived analytically and illustrated graphically to highlight the influence of the fractional derivative order on their spatial and temporal evolution. Furthermore, when an external generalized periodic force is introduced, the model exhibits quasi-periodic behavior followed by chaotic dynamics. Both configurations are depicted through 3D and 2D phase portraits in addition to the time-series graphs. The presence of chaos is quantitatively verified by calculating the Lyapunov exponents. Numerical simulations demonstrate that the system’s behavior is highly sensitive to variations in the frequency and amplitude of the external force. Full article

The present study examines the effect of viruses on forest insects depending on the virus dose. Two model approaches are used to quantify the effect of viruses on insect survival. Both approaches describe the processes of virus exposure to insects within the framework of the second-order phase transition model, which is well known in theoretical physics. The first approach examines the temporal dynamics of larval survival at a given dose of virus exposure. This dependence is characterized by the time–effect curve. In this case, the lethal time of exposure LT100 is the time required for the death of all larvae in the experiment at a given dose D of exposure. The second approach describes the relationship between the proportion q_r of larvae that survived a fixed time T_c after the start of the experiment and the dose D of virus exposure. This dependence is characterized by the dose–effect curve. The experiments tested the effect of two different viruses—nucleopolyhedrovirus (NPV) and cypovirus (CPV)—on such insect species as Lymantria dispar L., Manduca sexta L. and Loxostege sticticalis L. It was shown that the proposed models of second-order phase transitions very accurately (with coefficients of determination of the models close to R² = 0.95) describe experiments on studying the effect of different virus strains on insect survival. The proposed models turned out to be useful for assessing the effectiveness of different virus strains against insect pests. Since the parameters of the second-order “dose–time” and “dose–effect” phase transition models are related to each other, it is possible to reduce the number of measurements of virus–insect interaction due to the relationship between these parameters, and instead of n observations of insect dynamics over time depending on the dose of exposure, the basic parameters characterizing the “virus–insect” interactions can be accurately estimated using only one measurement. It appears that the proposed model can be used to calculate the effect of toxic agents on the population of victims for a wide variety of toxicant species and populations. A sharp reduction in the labor intensity of experiments to assess the toxicity of certain toxicants on animal populations will simplify and reduce the cost of testing the response of living objects to toxicants. Full article

Electromagnetic Railguns Face Severe Ablation and Melting Risks Due to Extremely High Transient Thermal Loads During High-Speed Launching, Directly Impacting Launch Reliability and Service Life. To address this thermal management challenge, this study proposes and validates the effectiveness of spray cooling technology. Leveraging its high heat transfer coefficient, exceptional critical heat flux (CHF) carrying capacity, and strong transient cooling characteristics, it is particularly suitable for the unsteady thermal control during the initial launch phase. An experimental platform was established, and a three-dimensional numerical model was developed to systematically analyze the dynamic influence mechanisms of nozzle inlet pressure, flow rate, spray angle, and spray distance on cooling performance. Experimental results indicate that the system achieves maximum critical heat flux (CHF) and rail temperature drop at an inlet pressure of 0.5 MPa and a spray angle of 0°. Numerical simulations further reveal that a 45° spray cone angle simultaneously achieves the maximum temperature drop and optimal wall temperature uniformity. Key parameter sensitivity analysis demonstrates that while increasing spray distance leads to larger droplet diameters, the minimal droplet velocity decay combined with a significant increase in overall momentum markedly enhances convective heat transfer efficiency. Concurrently, increasing spray distance effectively improves rail surface temperature uniformity by optimizing the spatial distribution of droplet size and velocity. Full article

Background: Bioelectrical impedance analysis (BIA) is a widely used field technique for assessing body composition in football. However, its reliance on population-specific regression equations limits its accuracy. Objective: This scoping review aimed to map the scientific literature on BIA applications in professional and semi-professional football, highlighting uses, limitations, and research opportunities. Methods: A comprehensive search was conducted in the scientific databases PubMed, EMBASE, Web of Science, and SPORTDiscus. Identified studies involved the use of BIA in professional and semi-professional football players (≥16 years) in the context of routine training and competition. Results: From 14,624 records, 39 studies met the inclusion criteria and were included. Three main applications were identified: (1) quantitative body composition assessment, (2) qualitative/semi-quantitative analysis (e.g., bioelectrical impedance vector analysis (BIVA)), and (3) muscle health and injury monitoring. Seven specific research areas emerged, including hydration monitoring, cross-method validation of body composition analyses, development of predictive models, sport phenotype identification, tracking training adaptations, performance/load assessment via phase angle, and localized BIA for injury diagnosis and recovery. Conclusions: While quantitative BIA estimates may lack individual-level precision, raw parameter analyses may offer valuable insights into hydration, cellular integrity, and muscle injury status, yet further research is needed to fully realize these applications. Full article

Background: Intensive Care Unit (ICU) readmission and in-hospital mortality are critical indicators of patient outcomes following ICU discharge. Patients readmitted to the ICU often face worse prognosis, higher healthcare costs, and prolonged hospital stays. Identifying high-risk patients is essential for optimizing post-ICU care and resource allocation. Methods: This two-phase study included the following: (1) a retrospective analysis of ICU survivors in a mixed medical–surgical ICU to identify risk factors associated with ICU readmission and in-hospital mortality, and (2) a prospective validation of a newly developed predictive model: the Worse Outcome Score (WOScore). Data collected included demographics, ICU admission characteristics, severity scores (SAPS II, SAPS III, APACHE II, SOFA), interventions, complications and discharge parameters. Results: Among 1.190 ICU survivors, 126 (10.6%) were readmitted to the ICU, and 192 (16.1%) died in hospital after ICU discharge. Key risk factors for ICU readmission included Diabetes Mellitus, SAPS III on admission, and ICU-acquired infections (Ventilator-Associated Pneumonia (VAP) and Catheter-Related Bloodstream Infection, (CRBSI)). Predictors of in-hospital mortality were identified: medical admission, high SAPS III score, high lactate level on ICU admission, tracheostomy, reduced GCS at discharge, blood transfusion, CRBSI, and Acute Kidney Injury (AKI) during ICU stay. The WOScore, developed based on the results above, demonstrated strong predictive ability (AUC: 0.845 derivation, 0.886 validation). A cut-off of 20 distinguished high-risk patients (sensitivity: 88.1%, specificity: 73.0%). Conclusions: ICU readmission and in-hospital mortality are influenced by patient severity, underlying comorbidities, and ICU-related complications. The WOScore provides an effective, easy-to-use risk stratification tool that can guide clinicians in identifying high-risk patients at ICU discharge and guide post-ICU interventions, potentially improving patients’ outcomes and optimizing resource allocation. Further multi-center studies are necessary to validate the model in diverse healthcare settings. Full article

The bioavailability of a drug is closely linked to its solubility, making its early determination essential in drug development. The saturation shake-flask (SSF) method is the gold standard protocol for this, which includes a phase separation step—either by sedimentation, filtration, or centrifugation. This step is critical, as it can directly influence the accuracy of the results. This study investigated the impact of centrifugation parameters—time and rotation speed—on solubility measurements. Additionally, we compared two sample preparation protocols: continuous stirring for 24 h versus 6 h of stirring followed by 18 h of sedimentation before centrifugation. Four model compounds were tested at three pH values using Britton–Robinson buffers. Centrifugation was conducted for 5, 10, or 20 min at either 5000 or 10,000 rpm. Results showed that pre-sedimented samples yielded solubility values closer to sedimentation-only references, while continuous stirring often led to overestimated values, particularly at higher speeds and longer durations. One such example was papaverine hydrochloride, that showed solubility values 60–70% higher than the reference after centrifugation at 10,000 rpm for 20 min without prior sedimentation. Lower standard deviations were observed with shorter, slower centrifugation, with 5 min and 5000 rpm yielding results closest to the reference values. Full article

Wave propagation in periodic media is governed by energy–momentum relations and geometric phases characterizing band topology, such as Zak phase in one-dimensional lattices. We demonstrate that, in the off-diagonal trimer lattices, Zak phase carries quantized screw-type dislocations winding around degeneracies in parameter space. If the lattice evolves in time periodically, as in adiabatic Thouless pumps, the corresponding closed trajectory in parameter space is characterized by a Chern number equal to the negative total winding number of Zak phase dislocations enclosed by the trajectory. We discuss the correspondence between bulk Chern numbers and the edge states in a finite system evolving along various pumping cycles. Full article

This paper investigates soliton solutions of the time-fractional Biswas–Arshed (BA) equation using the Extended Simplest Equation Method (ESEM). The model is analyzed under two distinct fractional derivative operators: the $\beta$-derivative and the M-truncated derivative. These approaches yield diverse solution types, including kink, singular, and periodic-singular forms. Also, in this work, a nonlinear second-order differential equation is reconstructed as a planar dynamical system in order to study its bifurcation structure. The stability and nature of equilibrium points are established using a conserved Hamiltonian and phase space analysis. A bifurcation parameter that determines the change from center to saddle-type behaviors is identified in the study. The findings provide insight into the fundamental dynamics of nonlinear wave propagation by showing how changes in model parameters induce qualitative changes in the phase portrait. The derived solutions are depicted via contour plots, along with two-dimensional (2D) and three-dimensional (3D) representations, utilizing Mathematica for computational validation and graphical illustration. This study is motivated by the growing role of fractional calculus in modeling nonlinear wave phenomena where memory and hereditary effects cannot be captured by classical integer-order approaches. The time-fractional Biswas–Arshed (BA) equation is investigated to obtain diverse soliton solutions using the Extended Simplest Equation Method (ESEM) under the $\beta$-derivative and M-truncated derivative operators. Beyond solution construction, a nonlinear second-order equation is reformulated as a planar dynamical system to analyze its bifurcation and stability properties. This dual approach highlights how parameter variations affect equilibrium structures and soliton behaviors, offering both theoretical insights and potential applications in physics and engineering. Full article

Objectives: To determine the frequency of development of hypogammaglobulinemia in rheumatoid arthritis (RA) patients receiving rituximab (RTX) and to examine the relation between the development of hypogammaglobulinemia and RTX treatment response. Methods: The data of 165 RA patients who applied to our outpatient clinic between January 2010 and June 2021, and who received at least 2 courses of RTX with an interval of 6 months, were retrospectively evaluated. The demographic, clinical, and laboratory data, as well as treatment characteristics, were collected. Results: Of 165 patients, 35 (21.2%) developed hypogammaglobulinemia. In the multivariable analysis examining the risk factors for the development of hypogammaglobulinemia in RA patients receiving RTX, it was determined that having pre-treatment IgG value below 10.5 g/l (OR= 4.24 (95% CI 1.69–10.66) and the increase in the number of RTX courses (OR= 1.1 (95% CI 1.01–1.22) were independently associated risk factors. During their follow-up, patients who developed hypogammaglobulinemia and those who did not were compared. No difference was observed between DAS28-ESR levels, but CRP levels were significantly lower in the group that developed hypogammaglobulinemia. Conclusions: In this study, there was no difference in DAS28-ESR levels between patients with and without hypogammaglobulinemia, although a difference was observed in acute phase reactants, which are more objective parameters. This may be due to subjective parameters in DAS28-ESR scoring or other concomitant conditions such as fibromyalgia. Therefore, additional objective findings or methods may guide the evaluation of treatment response. Full article

Bi₂Sr₂CaCu₂O_8+x (Bi2212) high-temperature superconductor exhibits broad application prospects in strong magnetic fields, superconducting magnets, and power transmission due to its exceptional electrical properties. However, during practical applications, Bi2212 superconducting round wires are prone to mechanical loading effects, leading to crack propagation and degradation of superconducting performance, which severely compromises their reliability and service life. To elucidate the damage mechanisms under mechanical loading and their impact on critical current, this study establishes a two-dimensional model with existing cracks based on phase field fracture theory, simulating crack propagation behaviors under varying conditions. The results demonstrate that crack nucleation and propagation paths are predominantly governed by stress concentration zones. The transition zone width of cracks is controlled by the phase field length scale parameter. By incorporating electric fields into the phase field model, coupled mechanical-electrical simulations reveal that post-crack penetration causes significant current shunting, resulting in a marked decline in current density. The research quantitatively explains the mechanism of critical current degradation in Bi2212 round wires under tensile strain from a mechanical perspective. Full article