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The efficiency of azelastine hydrochloride and fluticasone propionate nasal spray to improve PAP adherence in patients with obstructive sleep apnea
Preparation and ecological risk assessment of porous sewage sludge substrate for ecological restoration
Genomic, socio-environmental, and sequencing capability patterns in the surveillance of SARS-CoV-2 in Latin America and the Caribbean up to 2023
Predictive models and WTAP targeting for idiopathic pulmonary fibrosis (IPF)
Experimental and numerical study of tubular steel columns with/without demountable bolted shear connectors embedded in the concrete
Abstract Three push-out specimens were experimentally tested to investigate the behavior of tubular steel columns (TSC) with and without bolted shear connectors embedded in normal concrete (NC). Each specimen consisted of a tubular steel column (TSC) encased in a 250 × 250 × 200 mm concrete cube The embedment/the prominent height of TSC was 100 mm. Foam was used underneath the TSC to form free space. The study considered variables such as the presence of demountable shear studs and reinforcement. The failure modes, load-slip response, peak load/slip, and shear stiffness of the specimens were analyzed. Furthermore, a finite element model (FEM) was developed using ABAQUS software to simulate the behavior of the tested specimens and validated against the experimental results. The FEM was also employed to conduct further parametric investigations. The results indicate that demountable shear studs significantly improve shear capacity, with specimens exhibiting a 217% higher peak load than those without studs. Reinforcing the concrete block had a negligible effect on peak load but increased peak slip by 37.7% and shear stiffness by 18.7% compared to the unreinforced specimen. Furthermore, increasing the TSC thickness significantly enhances peak load, with a 154.31% increase observed as the thickness increases from one-third of the bolt diameter to the full bolt diameter. Additionally, using TSC thicknesses greater than half the bolt diameter helps prevent bearing failure. Increasing the concrete compressive strength from 25 to 50 MPa leads to a 24.6% increase in peak load, while slip capacity decreases by 19.77%. For applications requiring high ductility, excessively high-strength concrete should be avoided, as it reduces slip capacity. The results also demonstrate that the bolt diameter should not exceed twice the TSC web thickness to prevent bearing failure.
Mineralogical characteristics and color genesis of black quartzite jade from Linwu, Hunan, China
A novel mathematical framework for pedigree-based calculation of Y-STR match probabilities
Abstract Y-chromosomal short tandem repeat (Y-STR) markers are routinely used in forensic casework to identify male donors of biological traces left at crime scenes, particularly in sexual assault cases. However, the evidential value of a match between the Y-STR profile of a trace and a potential donor, usually a crime suspect, is difficult to quantify, and the common albeit inappropriate practise to equate Y-STR match probabilities with Y-STR profile frequencies estimated from population databases has been subject to scientific debate for decades. As a solution to this long-standing problem, we suggest an alternative approach to the calculation of Y-STR match probabilities that involves splitting the group of potential donors other than the suspect into two: (i) his close male relatives (termed his ‘pedigree’) and (ii) all other males. While an upper limit to the match probability is easily calculated for the second group, it is computationally challenging to derive for the first. We therefore developed a mathematical framework that uses importance sampling to reconstruct and evaluate the Y-STR profiles of untyped members of the suspect’s pedigree by way of simulation. Extensive testing with elementary pedigrees of different structure and complexity confirmed that both, the framework and its Python-based software implementation yield match probability estimates that approximate well the correct analytical results, depending upon the number of simulations performed. Our methodology thus facilitates a more appropriate and valid solution to the long-standing problem of interpreting Y-STR profile matches in forensic casework.
Biochemical characterization and activity profiling of recombinant phospholipase A2 from Hemiscorpius lepturus expressed in E. coli with in vivo antibody response
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.