Search Results (346)

Background/Objectives: Cystic fibrosis-associated liver disease (CFLD) is a significant complication in individuals with cystic fibrosis (CF), contributing to morbidity and mortality, with no universally accepted, reliable, non-invasive diagnostic tool for early detection. Current diagnostic methods, including liver biopsy and imaging, remain resource-intensive and invasive. Non-invasive biomarkers like the Fibrosis-4 (FIB-4) index have shown promise in diagnosing liver fibrosis in various chronic liver diseases. This study explores the potential of the FIB-4 index to predict CFLD in an adult CF population and assesses its correlation with transient elastography (TE) as a potential diagnostic tool. The aim of this study is to evaluate the diagnostic performance of the FIB-4 index for CFLD in adults with CF and investigate its relationship with TE-based liver stiffness measurements (LSM). Methods: The study was conducted in a regional cystic fibrosis unit, including 261 adult CF patients. FIB-4 scores were calculated using an online tool (mdcalc.com) based on patient age, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and platelet count. In parallel, 29 patients underwent liver stiffness measurement using TE (Fibroscan^®). Statistical analyses included non-parametric tests for group comparisons and Pearson’s correlation to assess the relationship between FIB-4 scores and TE results. Results: The mean FIB-4 score in patients diagnosed with CFLD was higher (0.99 ± 0.83) compared to those without CFLD (0.64 ± 0.38), although the difference was not statistically significant (p > 0.05). TE results for CFLD patients (5.9 kPa) also did not show a significant difference compared to non-CFLD patients (4.2 ± 1.6 kPa, p > 0.05). However, a positive correlation (r = 0.401, p = 0.031) was found between FIB-4 scores and TE-based LSM, suggesting a potential complementary diagnostic role. Conclusions: The FIB-4 index, while not sufficient as a standalone diagnostic tool for CFLD in adults with CF, demonstrates potential when used in conjunction with other diagnostic methods like TE. This study introduces a novel approach for integrating non-invasive diagnostic markers in CF care, offering a pathway for future clinical practice. The combination of FIB-4 and TE could serve as an accessible, cost-effective alternative to invasive diagnostic techniques, improving early diagnosis and management of CFLD in the CF population. Additionally, future research should explore the integration of these tools with emerging biomarkers and clinical features to refine diagnostic algorithms for CFLD, potentially reducing reliance on liver biopsies and improving patient outcomes. Full article

Internal leakage within the valve body constitutes a severe potential safety hazard in industrial fluid control systems, attributable to its high concealment and the resultant difficulty in detection via conventional methodologies. Acoustic emission (AE) technology, functioning as an efficient non-destructive testing approach, is capable of capturing the transient stress waves induced by leakage, thereby furnishing an effective means for the real-time monitoring and quantitative assessment of internal leakage within the valve body. This paper conducts a systematic review of the theoretical foundations, signal-processing methodologies, and the latest research advancements related to the technology for detecting internal leakage in the valve body based on acoustic emission. Firstly, grounded in Lechlier’s acoustic analogy theory, the generation mechanism of acoustic emission signals arising from valve body leakage is elucidated. Secondly, a detailed analysis is conducted on diverse signal processing techniques and their corresponding optimization strategies, encompassing parameter analysis, time–frequency analysis, nonlinear dynamics methods, and intelligent algorithms. Moreover, this paper recapitulates the current challenges encountered by this technology and delineates future research orientations, such as the fusion of multi-modal sensors, the deployment of lightweight deep learning models, and integration with the Internet of Things. This study provides a systematic reference for the engineering application and theoretical development of the acoustic emission-based technology for detecting internal leakage in valves. Full article

Energy generation from renewable sources has increased exponentially worldwide, particularly wind energy, which is converted into electricity through wind turbines. The growing demand for renewable energy has driven the development of horizontal-axis wind turbines with larger dimensions, as the energy captured is proportional to the area swept by the rotor blades. In this context, the dynamic loads typically observed in wind turbine towers include vibrations caused by rotating blades at the top of the tower, wind pressure, and earthquakes (less common). In offshore wind farms, wind turbine towers are also subjected to dynamic loads from waves and ocean currents. Vortex-induced vibration can be an undesirable phenomenon, as it may lead to significant adverse effects on wind turbine structures. This study presents a two-dimensional transient model for a rigid body anchored by a torsional spring subjected to a constant velocity flow. We applied a coupling of the Fourier pseudospectral method (FPM) and immersed boundary method (IBM), referred to in this study as IMERSPEC, for a two-dimensional, incompressible, and isothermal flow with constant properties—the FPM to solve the Navier–Stokes equations, and IBM to represent the geometries. Computational simulations, solved at an aspect ratio of $\varphi =4.0$, were analyzed, considering Reynolds numbers ranging from $Re=150$ to Re = 1000 when the cylinder is stationary, and $Re=250$ when the cylinder is in motion. In addition to evaluating vortex shedding and Strouhal number, the study focuses on the characterization of space–time symmetry during the galloping response. The results show a spatial symmetry breaking in the flow patterns, while the oscillatory motion of the rigid body preserves temporal symmetry. The numerical accuracy suggested that the IMERSPEC methodology can effectively solve complex problems. Moreover, the proposed IMERSPEC approach demonstrates notable advantages over conventional techniques, particularly in terms of spectral accuracy, low numerical diffusion, and ease of implementation for moving boundaries. These features make the model especially efficient and suitable for capturing intricate fluid–structure interactions, offering a promising tool for analyzing wind turbine dynamics and other similar systems. Full article

Radioactive iodine (RAI) therapy plays a fundamental role in the management of differentiated thyroid cancer (DTC) following appropriate surgical intervention. High levels of TSH are required in order to achieve maximum RAI uptake in residual thyroid tissue or metastatic cells. The two techniques that are most commonly used are thyroid hormone withdrawal (THW), which induces endogenous TSH elevation by creating a hypothyroid state, and exogenous stimulation with recombinant human TSH (rhTSH). This review compares both approaches over a range of DTC risk categories. Extensive evidence demonstrates that rhTSH and THW yield equivalent oncological outcomes, including remnant ablation success, recurrence-free survival, and overall survival, in low-, intermediate-, and high-risk disease. Additionally, rhTSH maintains quality of life by avoiding hypothyroid symptoms. While THW continues to be an excellent option when there is a lack of availability of rhTSH, its disadvantages, particularly the transient hypothyroid state, must be carefully weighed against the demonstrated equivalence in efficacy. In current clinical practice, rhTSH is frequently the preferred option for its convenience, safety, and patient-centered benefits; however, the selection of the optimal approach should be based on individual clinical circumstances and patients’ preferences, as well as resource considerations. Full article

The no-insulation (NI) technique improves the stability and defect-tolerance of high-temperature superconducting (HTS) coils by enabling current redistribution, thereby reducing the risk of quenching. NI–HTS coils are widely applied in DC systems such as high-field magnets and superconducting field coils for electric machines. However, the presence of turn-to-turn contact resistance makes current distribution uneven, rendering traditional simulation methods unsuitable. To address this, a finite element method (FEM) based on the T–A formulation is proposed. This model solves coupled equations for the magnetic vector potential (A) and current vector potential (T), incorporating turn-to-turn contact resistance and anisotropic conductivity. The thin-strip approximation simplifies second-generation HTS materials as one-dimensional conductors, and a homogenization technique further reduces computational time by averaging the properties between turns, although it may limit the resolution of localized inter-turn effects. To verify the model’s accuracy, simulation results are compared against the H formulation, distributed circuit network (DCN) model, and experimental data. The proposed T–A model accurately reproduces key transient characteristics, including magnetic field evolution and radial current distribution, in both circular and racetrack NI coils. These results confirm the model’s potential as an efficient and reliable tool for transient electromagnetic analysis of NI–HTS coils. Full article

As semiconductor technologies continue to scale aggressively, electromigration (EM) has become critical in modern VLSI design. Since traditional EM assessment methods fail to accurately capture the complex behavior of multi-segment interconnects, recent physics-based models have been developed to provide a more accurate representation of EM-induced stress evolution. However, numerical methods for these models result in large-scale systems, which are computationally expensive and impractical for complex interconnect structures. Model order reduction (MOR) has emerged as a key enabler for scalable EM analysis, with moment-matching (MM) techniques offering a favorable balance between efficiency and accuracy. However, conventional Krylov-based approaches often suffer from limited frequency resolution or high computational cost. Although the extended Krylov subspace (EKS) improves frequency coverage, its symmetric structure introduces significant overhead in large-scale scenarios. This work introduces a novel MOR technique based on the asymmetric extended Krylov subspace (AEKS), which improves upon the conventional EKS by incorporating a sparsity-aware and computationally efficient projection strategy. The proposed AEKS-based moment-matching framework dynamically adapts the Krylov subspace construction according to matrix sparsity, significantly reducing runtime without sacrificing accuracy. Experimental evaluation on IBM power grid benchmarks demonstrates the high accuracy of our method in both frequency-domain and transient EM simulations. The proposed approach delivers substantial runtime improvements of up to 15× over full-order simulations and 100× over COMSOL, while maintaining relative errors below 0.5%, even under time-varying current inputs. Full article

For power electronic interfaces, Direct Power Control (DPC) has emerged as a leading control technique, especially in applications such as synchronous motors, induction motors, and other electric drives; renewable energy sources (such as photovoltaic inverters and wind turbines); and converters that are grid-connected, such as Virtual Synchronous Generator (VSG) and Static Compensator (STATCOM) configurations. DPC accomplishes several significant goals by avoiding the inner current control loops and doing away with coordinating transformations. The application of STATCOM based on three- and five-level diode-clamped inverters is covered in this work. The study checks the abilities of DPC during power control adjustments during diverse grid operation scenarios while detailing how multilevel inverters affect system stability and power reliability. Proportional Integral (PI) controllers are used to control active and reactive power levels as part of the control approach. This study shows that combining DPC with Sinusoidal Pulse Width Modulation (SPWM) increases the system’s overall electromagnetic performance and control accuracy. The performance of STATCOM systems in power distribution and transient response under realistic operating conditions is assessed using simulation tools applied to three-level and five-level inverter topologies. In addition to providing improved voltage quality and accurate reactive power control, the five-level inverter structure surpasses other topologies by maintaining a total harmonic distortion (THD) below 5%, according to the main findings. The three-level inverter operates efficiently under typical grid conditions because of its straightforward design, which uses less processing power and computational complexity. Full article

In DC microgrids, optimizing the hybrid energy storage system (HESS) current control to meet the power requirements of the load is generally a difficult and challenging task. This is because the HESS always operates under various load conditions, which are influenced by measurement disturbances and parameter uncertainties. Therefore, in this paper, we propose the H_∞ state feedback control based on the reference modulation to improve the current tracking errors of the battery (Bat) and supercapacitor (SC) in the HESS for power tracking performance. Without altering the system control signal, the reference modulation technique combines the feedforward channel and output feedback signal directly to modulate the required currents of the Bat and SC derived from the required load power. The H_∞ state feedback control based on the required Bat and SC currents modulated by the reference modulation technique is proposed to improve the current tracking errors under the influence of measurement disturbances and parameter uncertainties without a disturbance observer. The ability of the reference modulation technique to attenuate the disturbance without the use of a disturbance observer is one advantage for improving transient performance. The improvement of the HESS’s power tracking performance in DC microgrids is confirmed by study results presented under the influence of measurement disturbances for nominal parameters and parameter uncertainties. Full article

Background/Objectives: Immature platelet fraction (IPF) and reticulated platelets (RPs) are biomarkers reflecting the youngest and most metabolically active platelets in circulation. RPs, a subset of immature platelets, contain residual RNA and have been associated with increased thrombotic potential. Elevated IPF levels indicate enhanced platelet production, commonly observed during elevated platelet turnover, such as in autoimmune reactions, consumption, and thrombotic events. This systematic review aims to evaluate the potential role of IPF and RPs in the context of cerebrovascular events, specifically ischemic and hemorrhagic stroke, as well as transient ischemic attacks (TIAs), and to assess their clinical utility in stroke monitoring and management. Methods: A comprehensive literature search was conducted in PubMed, Scopus, Cochrane Library, and Web of Science for studies published between 2000 and 2024, which focused on IPF and RPs in human subjects with cerebrovascular events. Results: Six studies met the inclusion criteria. Findings suggest that elevated levels of IPF and RP are associated with the acute and chronic phases of ischemic stroke and TIA and may reflect increased platelet turnover and thrombotic activity. Some evidence supports their role in predicting stroke severity, recurrence, and underlying etiology, although results are not yet consistent across all studies. Conclusions: IPF and RPs are emerging biomarkers with potential applications in acute ischemic stroke and risk stratification. While current evidence is promising, further research is needed to standardize measurement techniques and validate their routine use in clinical practice. Full article

This study investigates an aerodynamic optimization framework inspired by marine biological morphology, utilizing the sailfish profile as a basis for airfoil configuration. Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. Parametric studies revealed that pivotal factors including installation angle significantly influenced the fluid dynamic performance metrics of lift generation and pressure drag. Response surface methodology was employed to establish predictive models for these critical performance indicators, effectively reducing computational resource consumption and experimental validation costs. The refined bio-inspired configuration demonstrated multi-objective performance improvements compared to the baseline configuration, validating the computational framework’s effectiveness for hydrodynamic profile optimization studies. Furthermore, a coaxial dual-rotor vertical axis turbine configuration was developed, integrating centrifugal and axial-flow energy conversion mechanisms through a shared drivetrain system. The centrifugal rotor component harnessed tidal current kinetic energy while the axial-flow rotor module captured wave-induced potential energy. Transient numerical simulations employing dynamic mesh techniques and user-defined functions within the Fluent environment were conducted to analyze rotor interactions. Results indicated the centrifugal subsystem demonstrated peak hydrodynamic efficiency at a 25° installation angle, whereas the axial-flow module achieves optimal performance at 35° blade orientation. Parametric optimization revealed maximum energy extraction efficiency for the centrifugal rotor occurs at λ = 1.25 tip-speed ratio under Re = 1.3 × 10⁵ flow conditions, while the axial-flow counterpart attained optimal performance at λ = 1.5 with Re = 5.5 × 10⁴. This synergistic configuration demonstrated complementary operational characteristics under marine energy conversion scenarios. Full article

Photodegradation is a sustainable green technology that has been studied worldwide, especially for wastewater treatment. The calcination temperature has an important impact on the physicochemical properties of the prepared photocatalysts. In this study, a ternary photocatalyst of Cu₂O/WO₃/TiO₂ (CWT) was successfully synthesized using an ultrasonic-assisted hydrothermal technique, and the calcination temperature was varied from 500 to 800 °C. The characterization outcomes proved that the anatase phase titanium dioxide (TiO₂) in the CWT composite transformed to rutile phase TiO₂ when the calcination temperature reached 700 °C and 800 °C. The surface area of the CWT composite decreased from 35.77 to 8.09 m².g⁻¹ and the particle size of the CWT composite increased from 39.11 to 180.25 nm with an increasing calcination temperature from 500 to 800 °C. Photoelectrochemical (PEC) studies showed the charge-transfer resistance of 208.10 Ω, electron lifetime of 32.48 ms, current density of 1.40 mA.cm⁻², transient photovoltage of 0.53 V, and p-n heterojunction properties for CWT-500. Reactive Black 5 (RB5) was used as the model pollutant to examine the photodegradation performance. The photodegradation rate of CWT-500 was the highest (0.70 × 10⁻² min⁻¹) due to its large surface area, effective separation of photoexcited electron-hole pairs, and low photoexcited charge carrier recombination rate. Full article

Introduction: Rotational ankle instability (RAI), involving combined medial and lateral ligament insufficiency, is an increasingly recognized clinical entity. While open surgery has traditionally been the mainstay for treating deltoid ligament injuries, recent developments in arthroscopic techniques offer a minimally invasive alternative. This systematic review aimed to evaluate the current evidence on the arthroscopic management of medial and rotational ankle instability, focusing on surgical techniques, clinical outcomes, and complications. Methods: A systematic literature search was conducted following PRISMA guidelines using the PubMed, Scopus, and Web of Science databases. The search strategy included the following terms: ((rotation instability) OR (deltoid) OR (medial ankle instability)) AND (ankle arthrosc*). Eligible studies included adult patients undergoing arthroscopic repair of medial ankle instability with a mean 26.4 months follow-up and reported clinical outcomes. Ten studies met the inclusion criteria, encompassing 336 patients and 346 ankles. Results: The mean patient age was 32.6 ± 5.0 years, with 80.6% being male. MRI was the primary diagnostic tool across most studies. Ankle sprains were the most common cause of instability. Lateral ligament insufficiency was frequently associated with medial injuries, reported in all studies evaluating this parameter. All patients underwent prior conservative treatment (mean duration: 5.6 months). Surgical management involved all-inside arthroscopic repair using knotless suture anchors. Additional procedures were performed in 90% of studies, including osteophyte resection (33.3%) and microfracture (22.2%). The mean follow-up period was 26.4 months. The mean postoperative AOFAS score was 95.3, with return to sport generally achieved between 3 and 5 months. Complications were minimal, primarily consisting of superficial wound issues and transient nerve irritation; no major complications or revision surgeries were reported. Discussion: Arthroscopic management of medial and rotational ankle instability is associated with excellent functional outcomes, low complication rates, and early return to sport. Compared to open procedures, arthroscopic techniques offer advantages including reduced soft tissue trauma, fewer wound complications, and the ability to address concomitant intra-articular lesions in a single session. Although technically demanding, this approach is particularly beneficial in athletic populations. However, high-quality prospective studies are still needed to validate these findings and establish long-term comparative outcomes with open reconstruction techniques. Full article

Diagnostic systems for drive with AC motors of key importance for machine safety require the use of limitations related to the processing of measurement information. These limitations result in significant difficulties in assessing the technical condition of the object’s components. The article proposes the use of a combination of artificial intelligence techniques in the form of shallow and convolutional structures in the diagnostics of stator winding damage from an induction motor. The proposed approach ensures a high level of defect detection efficiency while using information preserved in samples from three periods of current signals. The research presents the possibility of combining the data classification capabilities of self-organizing maps (SOMs) with the automatic feature extraction of a convolutional neural network (CNN). The system was verified in steady and transient operating states on a test stand with a 1.5 kW motor. Remarkably, this approach achieves a high detection precision of 97.92% using only 600 samples, demonstrating that this reduced data acquisition does not compromise performance. On the contrary, this efficiency facilitates effective fault detection even in transient operating states, a challenge for traditional methods, and surpasses the 97.22% effectiveness of a reference system utilizing a full 6 s signal. Full article

This research presents a voting ensemble classification model to distinguish high impedance faults (HIFs) from other transients in a photovoltaic (PV) integrated microgrid (MG). Due to their low fault current magnitudes, sporadic incidence, and non-linear character, HIFs are difficult to detect with a conventional protective system. A machine learning (ML)-based ensemble classifier is used in this work to classify HIF more accurately. The ensemble classifier improves overall accuracy by combining the strengths of many rule-based models; this decreases the likelihood of overfitting and increases the robustness of classification. The ensemble classifier includes a classification process into two steps. The first phase extracts features from HIFs and other transient signals using the discrete wavelet transform (DWT) technique. A supervised discretisation approach is then used to discretise these attributes. Using discretised features, the rule-based classifiers like decision tree (DT), Java repeated incremental pruning (JRIP), and partial decision tree (PART) are trained in the second phase. In the classification step, the voting ensemble technique applies the rule of an average probability over the output predictions of rule-based classifiers to obtain the final target of classes. Under standard test conditions (STCs) and real-time weather circumstances, the ensemble technique surpasses individual classifiers in accuracy (95%), HIF detection success rate (93.3%), and overall performance metrics. Feature discretisation boosts classification accuracy to 98.75% and HIF detection to 95%. Additionally, the ensemble model’s efficacy is confirmed by classifying HIF from other transients in the IEEE 13-bus standard network. Furthermore, the ensemble model performs well, even with noisy event data. The proposed model provides higher classification accuracy in both PV-connected MG and IEEE 13 bus networks, allowing power systems to have effective protection against faults with improved reliability. Full article

This paper presents a vibration analysis method for detecting typical faults in gears of the drive train of a 2 MW wind turbine. The data were collected over a one-year period from an operating wind turbine with a gearbox composed of one planetary stage and two helical gear stages. Failures in two pairs of helical gears were identified: one involving pitting and wear in the gears connecting the intermediate-speed shaft to the low-speed shaft, and another one involving significant material detachment in the gears connecting the intermediate-speed shaft to the high-speed shaft. The continuous evaluation of time signals, frequency spectra, and amplitude modulations allowed the most sensitive sensors and frequencies for predicting surface damage on gear teeth in this type of turbine to be determined. A steady-state frequency analysis was performed, enabling the detection of the aforementioned surface faults. This approach is simpler compared with more complex transient-state techniques. By tracking vibration signals over time, the importance of analyzing gear mesh frequencies and their harmonics was highlighted. Additionally, it was found that the progression of gear damage was dependent on the power output of the wind turbine. As a result, the most appropriate ranges of power were identified, within which the evolution of the vibration measurement was associated with the damage evolution. Since many turbines currently in operation have similar designs and power output levels, the present findings can serve as a guideline for monitoring an extensive number of units. Full article