Applied research using the NIOSH lifting equation to optimize the design of shopping trolley for the elderly.

In the context of an aging society, products for the elderly typically need to meet the criteria of ease of use and reduction of physical fatigue. Focusing on elderly shopping scene, combined with the ergonomic principles and JACK simulation software analysis, a method of mapping NIOSH lifting equation to the product optimization design is proposed to optimize the dimensions and styling design of the elderly shopping trolley as a carrier, to optimize length, depth, and basket height from the ground. When the handle height of the elderly shopping cart is adjustable to three levels: 795 mm, 908 mm, and 1021 mm, it can effectively reduce the pressure on the lower limbs.

Optimization for the Process Parameters of Nickel-Titanium Nitride Composites Fabricated via Jet Pulse Electrodeposition.

The corrosion resistance of nickel-titanium nitride (Ni/TiN) composites is significantly influenced by the operation parameters during the jet pulse electrodeposition (JPE) process. The effect of current density, jet rate, TiN concentration, and duty cycle impact on the anti-corrosion property of Ni/TiN composites were investigated and optimized using the response surface method (RSM). After the optimization of the operation parameters, the corrosion current of Ni/TiN composites decreased from 9.

Kinematics and Flow Field Analysis of Flight.

In recent years, bioinspired insect flight has become a prominent research area, with a particular focus on beetle-inspired aerial vehicles. Studying the unique flight mechanisms and structural characteristics of beetles has significant implications for the optimization of biomimetic flying devices. Among beetles, (rhinoceros beetle) exhibits a distinct wing deployment-flight-retraction sequence, whereby the interaction between the hindwings and protective elytra contributes to lift generation and maintenance.

Dynamic Structure-Aware Modulation Network for Underwater Image Super-Resolution.

Image super-resolution (SR) is a formidable challenge due to the intricacies of the underwater environment such as light absorption, scattering, and color distortion. Plenty of deep learning methods have provided a substantial performance boost for SR. Nevertheless, these methods are not only computationally expensive but also often lack flexibility in adapting to severely degraded image statistics.

Multidimensional Characterization of the Physiological State of Hematococcuspluvialis Using Scanning Structured Illumination Super-Resolution Microscopy.

(HP) is a freshwater alga known for its ability to accumulate the potent antioxidant astaxanthin, which has extensive applications in aquaculture, pharmaceuticals, and cosmetics. Astaxanthin rapidly accumulates under unfavorable environmental conditions. However, the mechanisms of astaxanthin accumulation under various stress conditions remain unclear.

Impact of the sense of power on loneliness among international students in China: the chain mediating role of perceived discrimination and loneliness stigma.

Background: Loneliness is a common emotional experience among international students that can affect their mental health, cultural adaptation, and academic development. Therefore, the present study aimed to explore the relationship between a sense of power and loneliness among international students, and to examine the mediating role of loneliness stigma and perceived discrimination.

Methods: The study used the generalized sense of power scale, experiences with discrimination scale, stigma loneliness scale (SLS), and UCLA loneliness scale-6 (ULS -6) for 529 international students in China.

Synthesis of PVA-assisted MnO-CuO-ZnO-g-CN quaternary nanocomposite for the degradation of methylene blue from industrial wastewater.

The pristine phases SS1(ZnO), SS2(MnO), and SS3 (CuO) photocatalysts and mixed phases of ZnO-based nanocomposites were synthesized by the sol-gel method. Whereas SS4 (g-CN) was prepared through polymerization of urea. The synthesized photocatalysts were characterized using TGA-DTA, XRD, DRS, PL, DLS, FTIR, SEM, TEM, and HRTEM.

Precision autofocus in optical microscopy with liquid lenses controlled by deep reinforcement learning.

Microscopic imaging is a critical tool in scientific research, biomedical studies, and engineering applications, with an urgent need for system miniaturization and rapid, precision autofocus techniques. However, traditional microscopes and autofocus methods face hardware limitations and slow software speeds in achieving this goal. In response, this paper proposes the implementation of an adaptive Liquid Lens Microscope System utilizing Deep Reinforcement Learning-based Autofocus (DRLAF).

Molecular dynamics study on the nanofriction and wear mechanism of transverse grain boundaries in nickel-based alloys.

Context: This study employs molecular dynamics simulations to investigate the nanoscale tribological behavior of a single transverse grain boundary in a nickel-based polycrystalline alloy. A series of simulations were conducted using a repetitive rotational friction method to explore the mechanisms by which different grain boundary positions influence variations in wear depth, friction force, friction coefficient, dislocation, stress, and internal damage during repeated friction processes. The results reveal that the grain boundary structure enhances the strength of the nanoscale nickel-based polycrystalline alloy.

Sensitivity-enhanced potentiometric measurement by incorporating graphitic carbon nitride into the ion-to-electron transducer of potassium ion-selective electrodes.

In recent years, wearable sweat sensors have garnered significant attention for real-time monitoring of human physiological information because of their ability to continuously and non-invasively detect multiple sweat biomarkers. Among these, potentiometric sensors stand out for their low power consumption, low cost, compact design, and real-time monitoring capabilities, making them an ideal alternative for sweat analysis. However, enhancing the sensitivity of ion-selective electrodes (ISEs), a critical parameter of potentiometric sensors, remains a challenging research focus.

Bismuth nanoparticles embedded in carbon fibers as flexible and free-standing anodes for efficient sodium ion batteries.

Metallic bismuth is a promising anode electrode material for sodium ion batteries due to its high theoretical specific capacity. However, the formation of NaBi during the reaction process brings about significant volume changes and structural collapse of the electrode, resulting in the destruction of structures and a decrease in the cycling stability of sodium ion batteries. In this study, bismuth nanoparticles embedded in carbon fibers (Bi/CF) through a facile approach of electrospinning and calcination.

Multimodal monitoring of cerebral perfusion in carotid endarterectomy patients: a computational fluid dynamics study.

Objective: To evaluate postoperative cerebral perfusion changes and their influencing factors in carotid endarterectomy (CEA) patients by integrating multimodal monitoring methods, including cerebral regional oxygen saturation (rSO), carotid ultrasound (CU), computed tomographic angiography (CTA), and computed tomographic perfusion imaging (CTP), with computational fluid dynamics (CFD) assessment.

Methods: We conducted a cohort study on patients with internal carotid artery (ICA) stenosis undergoing CEA at our institution. Pre- and postoperative assessments included CU, CTA, CTP, and rSO monitoring.

Effects of acute-phase COVID-19-related indicators on pulmonary fibrosis and follow-up evaluation.

Background: Post-COVID-19 pulmonary fibrosis is a significant long-term respiratory morbidity affecting patients' respiratory health. This exploratory study aims to investigate the incidence, clinical characteristics, and acute-phase risk factors for pulmonary fibrosis in COVID-19 patients. Additionally, it evaluates pulmonary function and chest CT outcomes to provide clinical evidence for the early identification of high-risk patients and the prevention of post-COVID-19 pulmonary fibrosis.

Effect of bismuth on the microstructural evolution and properties of single-crystal Fe during rolling: a molecular dynamics study.

Context: Bi-containing free-cutting steel has consistently attracted attention in the field of materials processing. The molecular dynamics (MD) simulations were used to investigate the impact of bismuth (Bi) nanoparticles on the internal structural evolution and mechanical properties of single-crystal Fe during the rolling process. The influence of varying rolling depths in the presence of nanoparticles is also examined.

Automated Visual Inspection for Precise Defect Detection and Classification in CBN Inserts.

In the high-stakes domain of precision manufacturing, Cubic Boron Nitride (CBN) inserts are pivotal for their hardness and durability. However, post-production surface defects on these inserts can compromise product integrity and performance. This paper proposes an automated detection and classification system using machine vision to scrutinize these surface defects.

Cognitive Response of Underground Car Driver Observed by Brain EEG Signals.

In auxiliary transportation within mines, accurately assessing the cognitive and response states of drivers is vital for ensuring safety and operational efficiency. This study investigates the effects of various vehicle interaction stimuli on the electroencephalography (EEG) signals of mine transport vehicle drivers, analyzing the cognitive and response states of drivers under different conditions to evaluate their impact on safety performance. Through experimental design, we simulate multiple scenarios encountered in real operations, including interactions with dynamic and static vehicles, personnel, and warning signs.

Corrupted Point Cloud Classification Through Deep Learning with Local Feature Descriptor.

Three-dimensional point cloud recognition is a very fundamental work in fields such as autonomous driving and face recognition. However, in real industrial scenarios, input point cloud data are often accompanied by factors such as occlusion, rotation, and noise. These factors make it challenging to apply existing point cloud classification algorithms in real industrial scenarios.

Node Classification Method Based on Hierarchical Hypergraph Neural Network.

Hypergraph neural networks have gained widespread attention due to their effectiveness in handling graph-structured data with complex relationships and multi-dimensional interactions. However, existing hypergraph neural network models mainly rely on planar message-passing mechanisms, which have limitations: (i) low efficiency in encoding long-distance information; (ii) underutilization of high-order neighborhood features, aggregating information only on the edges of the original graph. This paper proposes an innovative hierarchical hypergraph neural network (HCHG) to address these issues.

Multi-Sensor Fusion for Wheel-Inertial-Visual Systems Using a Fuzzification-Assisted Iterated Error State Kalman Filter.

This paper investigates the odometry drift problem in differential-drive indoor mobile robots and proposes a multi-sensor fusion approach utilizing a Fuzzy Inference System (FIS) within a Wheel-Inertial-Visual Odometry (WIVO) framework to optimize the 6-DoF localization of the robot in unstructured scenes. The structure and principles of the multi-sensor fusion system are developed, incorporating an Iterated Error State Kalman Filter (IESKF) for enhanced accuracy. An FIS is integrated with the IESKF to address the limitations of traditional fixed covariance matrices in process and observation noise, which fail to adapt effectively to complex kinematic characteristics and visual observation challenges such as varying lighting conditions and unstructured scenes in dynamic environments.

Improved Method for the Calculation of the Air Film Thickness of an Air Cushion Belt Conveyor.

The air film thickness is an important parameter of an air cushion belt conveyor, which directly affects the compressed air supply power and operating resistance of the system. Therefore, it is important to calculate the bottom thickness of the gas film accurately in the design stage. A calculation method for the thickness of a conveyor air cushion was derived based on the mathematical model of the air cushion flow field for a multi row uniformly distributed air cushion structure.

Deposition Contribution Rates and Simulation Model Refinement for Polysilicon Films Deposited by Large-Sized Tubular Low-Pressure Chemical Vapor Deposition Reactors.

Tunnel oxide passivating contact cells have become the mainstream form of high-performance photovoltaic cells; however, the key factor restricting the further improvement of tunnel oxide passivating contact cell performance lies in the deposition process technology of high-quality polysilicon films. The experimental optimization cost for the deposition of large-sized polysilicon films in low-pressure chemical vapor deposition reactors is enormous when conducted in the temperature range of 800-950 K; hence, the necessity to develop effective computer simulation models becomes urgent. In recent years, our research group has conducted two-dimensional simulation research on large-sized, low-pressure chemical vapor deposition.

Characterization of Particle Size Effects on Sintering Shrinkage and Porosity in Stainless Steel Metal Injection Molding Using Multi-Physics Simulation.

In this study, three stainless steel materials (17-4PH, 316L, and 304) were experimentally simulated using metal injection molding (MIM) technology to explore the size shrinkage behavior and defect formation mechanism of materials with different particle sizes during sintering. The sintering environment was linearly heated to 1250 °C at a rate of 5 °C/min and kept warm for 90 min. Multi-physics field coupling analysis was performed using ANSYS Workbench software.

Formulation of Epoxy Prepregs, Synthesization Parameters, and Resin Impregnation Approaches-A Comprehensive Review.

Prepregs are resin-impregnated, expensive composites mainly limited to high-end applications within the aeronautical, defense, automotive, and energy sectors. Prepreg technology is mainly protected by trade secrets, resulting in limited studies on prepreg resin matrix development and recent advancements. Three key parameters for epoxy resin matrix development including B-staging, viscosity, and tackiness, and their control strategies are discussed in detail.

Impact Resistance of Aluminum Foam Composites with Filler and Coating Materials.

The main objective of this study is to analyze the impact resistance of aluminum foam composites containing fillers and coatings and to investigate the effect of different thickness ratios of the composites on this capability. We prepared composites using aluminum foam and polyurea and performed impact tests and numerical simulations. A comparison of the results shows that the Abaqus simulation results are in general agreement with the test results.