Browse Articles

Intelligent diagnosis of gearbox in data heterogeneous environments based on federated supervised contrastive learning framework

A novel XbaI multiplex PCR method for rapid typing of Klebsiella pneumoniae strains

Optimization mechanism of laminated ceramic package structure on the regulation of semiconductor cooling performance

Influence of kinematic parameters and rock properties on the cutting process with ODC based on discrete element method

Ptychographic reconstructions performed in real time and offline have equivalent quality

Abstract Ptychography is a burgeoning imaging technique that enables high-resolution, lensless reconstruction of complex samples by analysing overlapping diffraction patterns, making it invaluable in fields like materials science, biology, and nanotechnology. Real-time ptychographic reconstructions are gaining interest in the scientific community as they provide immediate feedback. Yet their potential to replace offline reconstructions remains uncertain, in part due to questions about the quality of the resulting images. This study quantitatively compares real-time and offline reconstructions at different overlap conditions. Offline reconstructions, using all diffraction patterns at once, and real-time reconstructions, where new frames are added to the reconstructions in small chunks as the diffraction patterns are recorded, were indistinguishable and identical in reconstruction quality. These results hold consistently across all tested overlap ratios. This study represents the first quantitative analysis of real-time ptychographic reconstruction using a growing dataset, demonstrating the potential for real-time reconstructions to replace or at least complement offline reconstructions.

Nonlinear oscillations of a lumped system with series spring, piezoelectric device, and feedback controller

Abstract This paper examines the behavior of a mechanical system with a lumped- mass comprising two nonlinear springs arranged in series and combined with a piezoelectric device. External harmonic excitations, as well as linear and nonlinear damping, are considered. The main system employs a negative velocity feedback (NVF) controller to reduce undesired effects vibrations, particularly under resonance conditions, thereby enhancing the system’s efficiency. The system is described by differential and algebraic equations, forming a dynamic model governed by differential-algebraic equations (DAE). A nearly analytical technique is further applied to resolve the initial value problem of the DAE. Applying the Lagrange’s equations (LE), the regulating equations of motion (EOM) are derived. The approximate solutions (AS) to third-order are obtained subsequently in the framework of the multiple-scales method (MSM). The AS’s accuracy is confirmed by comparing it to the numerical solution (NS) obtained via Runge–Kutta fourth-order algorithms (RK- 4). Examining the resonance cases, along with the criteria of solvability, leads to the derivation of the modulation equations (ME). Graphical representations of the solutions’ time histories and frequency response curves are presented using Wolfram Mathematica 9 and MATLAB- 23 software, providing a thorough visualization of the results. In addition, bifurcation diagrams and Poincaré maps (PMs) are graphed to illustrate the different behavioral modes of the system. Conversely, piezoelectric transducers are linked to the dynamic model to transform vibrational motion into electrical energy. This technology represents one of the many energy harvesting (EH) solutions widely utilized across commercial, aerospace, industrial, medical sectors, and automotive. A graphical analysis illustrating the time courses of solutions with and without control is presented. Additionally, resonance frequency curves are plotted to assess stability/instability and evaluate the solutions at steady-state.

Quantitative gamma-ray imaging with coded aperture method

Accurate quantification of cell-free Ceruloplasmin mRNA as a biomarker for early detection of hepatocellular carcinoma

Spinopelvic parameters in the lateral decubitus are different from standing and sitting positions

Visual analysis of deep learning semantic segmentation applied to petrographic thin sections

A hybrid gazelle optimization and reptile search algorithm for optimal clustering in wireless sensor networks

Abstract In our modern societies, the wireless sensor network (WSN) is categorized as a smart motivated technology that can be utilized in many work environments and activities to enhance daily life. However, several challenging concerns have been assigned to WSN. The clustering process is a main complex concern and still an open problem in WSN. To support an efficient clustering process, two crucial requirements must be considered, energy management and network lifetime extension, especially in the development of large-scale WSN. The primary objective of this article is to introduce a new meta-heuristic algorithm, denoted as the hybrid gazelle optimization and reptile search algorithm (HGORSA), which optimizes cluster head selection in WSNs. In the proposed algorithm, the mathematical models for the exploration and exploitation phases of the traditional gazelle optimization algorithm (GOA) are enhanced by integrating the hunting operator, reduction function, and predator cumulative effect operators from the traditional RSA. These modifications improve the balance between diversification and intensification processes, effectively addressing two key clustering requirements mentioned above. At the same time, they also positively impact the overall performance evaluation of the WSN. Various simulation scenarios are designed to evaluate the performance of the proposed HGORSA in different network configurations. First, the main experiment was conducted with 300 sensor nodes (SNs). The experimental results then analyzed to assess the effectiveness of the proposed algorithm under different conditions against six state-of-the-art meta-heuristic algorithms. Based on simulation outputs, HGORSA demonstrated superior performance compared to particle swarm optimization, grey Wolf optimizer, sperm swarm optimization, chernobyl disaster optimizer, gazelle optimization algorithm and reptile search algorithm. Specifically, HGORSA achieved percentage improvements in terms of stability period (37.3%, 49.6%, 46.8%, 55.3%, 19.1%, and 34.4%, respectively), energy consumption (10.8%, 10.5%, 9.6%, 8.6%, 8.3%, and 3.5%, respectively), network lifetime (44.5%, 40.8%, 23.8%, 16.8%, 9.3%, and 7.2%, respectively), reduction in number of dead nodes (30.3%, 29.7%, 28.9%, 24.3%, 18%, and 11.5%, respectively), and network throughput (36.4%, 43.9%, 34.2%, 25%, 20%, 14.4%, respectively). Moreover, a supplementary experiment was conducted to test the efficiency of the HGORSA algorithm in dense and sparse networks, where the number of SNs was set at 50 and 500. The algorithm was evaluated based on the five standard aforementioned performance metrics. Furthermore, the robustness of HGORSA was validated using statistical measures, including standard deviation (Std), average (Avg), worst and best values, and box plots of the fitness function across 20 independent runs. Based on statistical results, HGORSA outperformed the other comparative meta-heuristics.

Optimal vaccination model of airborne infection under variable humidity and demographic heterogeneity for hybrid fractional operator technique

Association between high plasma p-tau181 level and gait changes in patients with mild cognitive impairment

Nanoengineered polyaniline/carbon black VXC 72 hybridized with woven abaca for superior electromagnetic interference shielding

Abstract The growing demand for efficient electromagnetic (EM) shielding materials has driven extensive research into sustainable and functionalized composites for high-frequency applications. This study investigates the electromagnetic (EM) shielding properties of Polyaniline (PAni)-functionalized woven abaca fibers, reinforced with Carbon Black (CB) VXC 72, in the ultrahigh-frequency (UHF) range (500–4500 MHz), as determined using Vector Network Analyzer (VNA). The composite was developed by functionalizing abaca fabric with PAni through in situ chemical oxidative polymerization and depositing CB via a dip-and-dry method. The morphological structure and elemental composition were analyzed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX), while Fourier-transform infrared (FTIR) spectroscopy was used to confirm functional group interactions. Electrical resistivity was determined using the four-point probe method, and EMI shielding effectiveness (SE) was evaluated in the ultrahigh frequency (UHF) range of 500 MHz to 4500 MHz using a Vector Network Analyzer (VNA). Experimental results indicate that PAni/CB functionalization successfully imparted shielding properties to abaca fabric. PAni/1CB/Abaca exhibited the highest shielding effectiveness with an average SE of 5.96 dB, corresponding to 74.34% attenuation of incident electromagnetic waves, and a peak attenuation of 7.45 dB at 4.5 GHz. In contrast, 2CB/Abaca and PAni/2CB/Abaca showed selective EMI shielding, with peak attenuation values of 8.27 dB at 1.67 GHz and 7.98 dB at 1.69 GHz, respectively. The electrical resistivity measurements revealed that PAni/1CB/Abaca had the lowest resistivity at 891 Ω·cm, whereas 1CB/Abaca exhibited the highest at 5238 Ω·cm. The primary shielding mechanism was absorption rather than reflection, making the composite a lightweight, corrosion-resistant alternative to traditional metal-based EMI shields. These findings demonstrate the potential of natural fiber-based conductive composites for flexible EMI shielding applications in telecommunications, healthcare, and aerospace industries.

Survival prediction from imbalanced colorectal cancer dataset using hybrid sampling methods and tree-based classifiers

Spin dependent thermoelectric transport in a multiterminal quantum dot hybrid including a superconductor and ferromagnets

Abstract We investigate the thermoelectric response of a hybrid system consisting of two ferromagnetic electrodes and one superconducting lead coupled to a single-level quantum dot with finite Coulomb repulsion. Using the non-equilibrium Green’s function technique within the Hubbard-I approximation, local and non-local thermoelectric coefficients, along with their spin counterparts, such as electrical and thermal conductance, and the Seebeck coefficient are calculated up to linear order with respect to generalized forces. Here, we present a derivation of spin-dependent thermoelectric coefficients for a three-terminal system, extending the existing theory which allowed to describe only cases independent of spin-bias voltage, i.e. when spin accumulation is irrelevant. In the considered system, four competing processes- single particle tunneling, quasiparticle tunneling, direct and crossed Andreev reflection make the system highly adaptable for tuning charge and heat currents. A full analysis of their impact on thermoelectric effects is provided. Moreover, the output power and efficiency of the system operating as a heat engine are evaluated. The extensive goal of this work is to demonstrate how the presence of an additional terminal modifies the hybrid QD-based device’s performance and under which conditions non-local thermoelectric effects become significant.

Improving spinal alignment through innovative resistance training with outdoor fitness equipment in middle-aged and older adults: a randomized controlled trial

Predicting the uplift capacity of circular anchors in frictional-cohesive soils using Kolmogorov-Arnold networks

The influence of the marker set on inverse kinematics results to inform markerless motion capture annotations

Abstract Markerless motion capture has the potential to enable biomechanical analyses without specialised, high-cost equipment. However, the comparability of many markerless motion capture frameworks with the most used marker-based method is limited. One reason for this is the lack of high-quality, biomechanically-informed datasets that are needed to train markerless models. This study aimed to inform the development of such a dataset by systematically analysing the agreement between a gold-standard marker set and a reduced number of markers to solve inverse kinematics (IK). We analysed the impact of different marker positions on the IK solution using an OpenSim lower body model with real and synthetic data of running, walking and counter movement jumps. We found that one mid-segment marker in addition to two anatomical markers per segment result in the best agreement to a gold-standard marker set. The results for real and synthetic data across all movements were similar, with synthetic data showing slightly better agreement with a reduced number of markers (root mean squared error 1.55–8.27° real data, 1.27–7.79° synthetic data), likely due to limited soft tissue artefacts and missing human error in marker placement. These findings can support the development of a dataset to retrain markerless models incorporating biomechanical knowledge.

Time required to achieve optimum viral load suppression with Ravidasvir/sofosbuvir in chronic hepatitis C patients with or without compensated cirrhosis

Abstract A study indicated that ravidasvir (RDV) has excellent safety and tolerability when used with sofosbuvir (SOF) to treat chronic HCV infection. The aim of this study was to determine the time taken by RDV/SOF to achieve optimum viral load suppression in chronic hepatitis C patients with or without compensated cirrhosis. Data from the open-label, multicentre, single-arm, phase II/III clinical trial (STORM-C-1) were utilized. Time‒to-event analysis via Kaplan–Meier curves was performed to determine the time required to achieve optimum viral load suppression in both the cirrhotic and noncirrhotic groups. Multivariate logistic regression analyses were performed to identify potential predictors of achieving suppression within four and eight weeks. The time to achieve optimum viral load suppression ranged from six to 85 days and from five to 148 days among noncirrhotic and cirrhotic patients, respectively. Among noncirrhotic patients, 80.6% achieved optimum viral load suppression within 4 weeks, and 92.6% achieved this within 8 weeks. Among cirrhotic patients, 76.1% and 90.4% achieved optimum viral load suppression within 4 and 8 weeks, respectively. Notably, optimum viral load suppression differs from sustained virological response (SVR12), which is defined as undetectable HCV RNA 12 weeks after treatment completion. While the study demonstrates promising early viral suppression, it does not evaluate the efficacy of a shortened regimen. Further research is needed to assess whether shorter treatment durations maintain high SVR12 rates without compromising treatment success.