Search Results (8,623)

Background/Objectives: Growing evidence suggests that erythrocyte membrane lipids are subject to changes during their lifespan. Factors such as the type of dietary intake and its composition contribute to the changes in red blood cell (RBC) membranes. Due to the high antioxidant content of beer, we aimed to investigate the effect of moderate beer consumption on the lipid composition of RBCs membranes from healthy overweight individuals. Methods: We conducted a four-weeks, prospective two-arm longitudinal crossed-over study, where participants (n = 36) were randomly assigned to alcohol-free beer group or traditional beer group. The lipids of RBCs membranes were assessed at the beginning and the end of the intervention by thin-layer chromatography. Results: Four-weeks of alcohol-free beer promoted changes in fatty acids (FA), free cholesterol (FC), phosphatidylethanolamine (PE) and phosphatidylcholine (PC) (p < 0.05). Meanwhile, traditional beer intake led to changes in FA, FC, phospholipids (PL), PE and PC (p < 0.05). The observed alterations in membrane lipids were found to be independent of sex and BMI as influencing factors. Conclusions: The lipid composition of erythrocyte membranes is distinctly but mildly influenced by the consumption of both non-alcoholic and conventional beer, with no effects on RBC membrane fluidity. Full article

As gestures play an important role in human communication, there have been a number of service robots equipped with a pair of human-like arms for gesture-based human–robot interactions. However, the arms of most human companion robots are limited to slow and simple gestures due to the low maximum velocity of the arm actuators. In this work, we present the JF-2 robot, a mobile home service robot equipped with a pair of torque-controlled anthropomorphic arms. Thanks to the low inertia design of the arm, responsive Quasi-Direct Drive (QDD) actuators, and active compliant control of the joints, the robot can replicate fast human dance motions while being safe in the environment. In addition to the JF-2 robot, we also present the JF-mini robot, a scaled-down, low-cost version of the JF-2 robot mainly targeted for commercial use at kindergarten and childcare facilities. The suggested system is validated by performing three experiments, a safety test, teaching children how to dance along to the music, and bringing a requested item to a human subject. Full article

A novel vernier effect filter is designed utilizing two cascaded Mach–Zehnder interferometers (MZIs). Integrating the filter into an erbium-doped fiber laser (EDFL), the tunability of laser wavelength is achieved. Each MZI comprises two sequentially interconnected 3 dB optical couplers (OCs), where the incoming light is initially split into two arms at the first OC and subsequently recombined at the second OC. Interference occurs due to the optical path difference between these two beams. Notably, the two MZIs exhibit closely matched free spectral ranges (FSRs), leading to the formation of a broadened envelope in the superimposed spectrum. By delicately adjusting the optical path difference between the two arms of one MZI, a little drift of the interference spectrum is induced. This small amount of drift, in turn, triggers a significant movement of the envelope, giving rise to the so-called vernier effect. Integrating the vernier effect filter into an EDFL, the wavelength of the fiber laser can be tuned from 1542.56 nm to 1556.62 nm, with a tuning range of 14.06 nm. Furthermore, by employing a high-precision stepper motor, a remarkable tuning accuracy of 0.01 nm is attainable. The side mode suppression ratio of all wavelengths is above 55 dB. In comparison to reported tunable fiber lasers utilizing MZI filters, the proposed fiber laser in this study offers enhanced precision and a more user-friendly tuning process. Full article

(1) Background: The advancement of technologies has made morphological assessment rapid and reliable. A combination of 3D body scanning (3D-BS) and bioelectrical impedance (BIA) could be essential in monitoring the morphological status of athletes and the general population and their symmetries for coaches, researchers and medical professionals. (2) Methods: The current study presents the use of Inbody-720 BIA and 3D-BS NX-16 for analyzing the asymmetry profile of an athlete in 2 min on a sample of 106 male judo competitors from the following age categories: older boys—U14 (N = 24), younger cadets—U16 (N = 31), cadets—U18 (N = 17), juniors—U21 (N = 19) and seniors (N = 15). Variables observed were arm lean mass, upper arm, elbow, forearm and wrist girth, leg lean mass, thigh length, thigh, knee and calf girth. The paired sample t-test, asymmetry index (AI) and Kruskal–Wallis analysis were used at p ≤ 0.05; (3) Results: Morphological asymmetries were detected in all age categories: seniors—three, U21—four, U18—three, U16—five and U14—four. The most common asymmetrical variable in all categories was the forearm girth, while thigh length, knee girth and upper arm girth presented symmetrical variables in all age categories. AI showed that the size of the asymmetries did not differentiate between the age groups. (4) Conclusions: The current study demonstrated great potential for combining BIA and 3D-BS for rapid asymmetry detection that would allow for monitoring and quick adjustments to the training process in youth to senior age categories. Full article

As humans’ additional arms or legs, supernumerary robotic limbs (SRLs) have gained great application prospects in many fields. However, current SRLs lack both rigidity/flexibility adaptability and arm/leg function conversion. Inspired by the muscular hydrostat characteristics of octopus tentacles, fiber-reinforced actuators (FRAs) were employed to develop SRLs simultaneously realizing flexible operation and stable support. In this paper, an SRL with FRAs was designed and implemented. The analytic model of the FRA was established to formulate the movement trajectory and stiffness profile of the SRL. A hierarchical hidden Markov model (HHMM) was proposed to recognize the wearer’s motion intention and control the SRL to complete the specific working mode and motion type. Experiments were conducted to exhibit the feasibility and superiority of the proposed robot. Full article

Introduction: Poor outcomes following IVF treatments are speculated to be due to the transfer of aneuploid embryos that cannot be identified based on morphological evaluation alone. This leads to patients requiring numerous embryo transfers and, consequently, a prolonged time interval before live birth. Embryo selection following preimplantation genetic testing for aneuploidy (PGT-A) with next-generation sequencing (NGS) has been suggested as an intervention to shorten time to pregnancy in women undergoing in vitro fertilisation (IVF). Past studies assessing the clinical efficacy of PGT-A in improving clinical outcomes have been conflicting and the associated clinical pregnancy rates and live birth rates following the transfer of a mosaic embryos have yet to be determined. None of the existing studies solely included women of advanced reproductive age (ARA). The pilot study and proposed RCT will determine if, compared to morphological evaluation alone, the use of PGT-A through NGS is a more clinically effective, safer, and more cost-effective way to provide IVF treatment in women of advanced reproductive age. Method and Analysis: The proposed pilot study will aim to randomise 100 patients within a single-centre study to evaluate recruitment, randomisation, and adherence to study protocol and allocated trail arms by participating patients. The results of the pilot study will enable us to determine the sample size for a larger study to establish the effectiveness of PGT-A in ARA women. Ethics and Dissemination: The study (Integrated Research Application System Number 236067) received approval from the Health Research Authority and Health and Care Research Wales (HCRW) and the East Midlands—Leicester South Research Ethics Committee (20/EM/0290). The results will be made available to patients, the funders, the Reproductive Medicine societies, and other researchers. Trial registration: ClinicalTrials.gov Identifier: NCT05009745, n. Full article

To increase productivity, more sophisticated cluster tools are developed. To achieve this, one of the ways is to increase the number of spaces in a process module (PM) and the number of fingers on a robot arm as well, leading to a cluster tool with multi-space PMs and a multi-finger-arm robot. This paper discusses the scheduling problem of cluster tools with four-space PMs and a four-finger-arm robot, a typical tool with multi-space PMs and a multi-finger-arm robot adopted in modern fabs. With two arms in such a tool, one is used as a clean one, while the other is used as a dirty one. In this way, wafer quality can be improved. However, scheduling such cluster tools to ensure the residency time constraints is very challenging, and there is no research report on this issue. This article conducts an in-depth analysis of the steady-state scheduling for this type of cluster tools to explore the effect of different scheduling strategies. Based on the properties, four robot task sequences are presented as scheduling strategies. With them, four linear programming models are developed to optimize the cycle time of the system and find feasible schedules. The performance of these strategies is dependent on the activity parameters. Experiments are carried out to test the effect of different parameters on the performance of different strategies. It shows that, given a group of parameters, one can apply all the strategies and choose the best result obtained by one of the strategies. Full article

Aiming at the problems of small stems and irregular contours of bitter gourd, which lead to difficult and inaccurate location of picking points in the picking process of mechanical arms, this paper proposes an improved YOLOv5-seg instance segmentation algorithm with a coordinate attention (CA) mechanism module, and combines it with a refinement algorithm to identify and locate the picking points of bitter gourd. Firstly, the improved algorithm model was used to identify and segment bitter gourd and melon stems. Secondly, the melon stem mask was extracted, and the thinning algorithm was used to refine the skeleton of the extracted melon stem mask image. Finally, a skeleton refinement graph of bitter gourd stem was traversed, and the midpoint of the largest connected region was selected as the picking point of bitter gourd. The experimental results show that the prediction precision (P), precision (R) and mean average precision (mAP) of the improved YOLOv5-seg model in object recognition were 98.04%, 97.79% and 98.15%, respectively. Compared with YOLOv5-seg, the P, R and mA values were increased by 2.91%, 4.30% and 1.39%, respectively. In terms of object segmentation, mask precision (P(M)) was 99.91%, mask recall (R(M)) 99.89%, and mask mean average precision (mAP(M)) 99.29%. Compared with YOLOv5-seg, the P(M), R(M), and mAP(M) values were increased by 6.22%, 7.81%, and 5.12%, respectively. After testing, the positioning error of the three-dimensional coordinate recognition of bitter gourd picking points was X-axis = 7.025 mm, Y-axis =5.6135 mm, and Z-axis = 11.535 mm, and the maximum allowable error of the cutting mechanism at the end of the picking manipulator was X-axis = 30 mm, Y-axis = 24.3 mm, and Z-axis = 50 mm. Therefore, this results of study meet the positioning accuracy requirements of the cutting mechanism at the end of the manipulator. The experimental data show that the research method in this paper has certain reference significance for the accurate identification and location of bitter gourd picking points. Full article

Lower back pain (LBP) has been the leading cause of disability since 1990. Objectives: The main objective of this observational case–control study was to evaluate, using ultrasound, whether there were differences in the onset and ratio of core muscle contraction between subjects with non-specific chronic lower back pain and healthy subjects. Methods: A total of 60 participants (52% women), split between those with non-specific chronic lower back pain (n = 26) and healthy (n = 34) subjects, were recruited. Initial muscle contraction of the lateral abdominal wall, pelvic floor, lumbar multifidus, and respiratory diaphragm was measured using ultrasound. The abdominal drawing-in maneuver, contralateral arm elevation, the Valsalva maneuver, and voluntary contraction of the pelvic floor in seated and standing positions were performed. The muscle thickness of the lateral abdominal wall and lumbar multifidus and excursion of the pelvic floor and diaphragm at rest and during testing were also analyzed. Results: No differences were found between the groups in the initial contraction. Statistically significant differences were found in the following variables: diaphragm excursion (p = 0.032, r = 0.277) and lumbar multifidus ratio (p = 0.010, r = 0.333) in the standing–abdominal retraction maneuver; pelvic floor excursion (p = 0.012, r = 0.325) in the standing–contralateral arm raise; and transverse abdominis ratio (p = 0.033, r = 0.275) in the sitting–contralateral arm raise. A statistically significant interaction between the groups and body mass index was observed in resting diaphragm excursion (p = 0.018, partial eta squared = 0.096) during sitting–voluntary pelvic floor contraction. Conclusions: It cannot be concluded that there is a specific pattern of core activation in any of the groups. However, statistically significant differences were found in the contraction indexes of the lumbopelvic musculature. Full article

Background/Objectives: Arteriovenous (AV) graft is a procedure for hemodialysis performed in the arm. Optimizing AV graft design is vital to enhance haemodialytic efficiency in patients with kidney disease. Despite being a standard procedure, making it work optimally is still difficult due to various graft diameters and anastomosis configurations, which have limited studies. This research aims to find the ideal AV graft tube diameter on blood flow and pressure gradients and the ideal body site for AV graft implantation and to study their angles for dialysate flow. Methods: Nine models were designed in Autodesk Fusion 360 with 40°, 50°, and 60° angles each having 2 mm, 5.1 mm, and 14.5 mm diameters, all following specific equations on continuity, momentum (Navier-Stokes Equation)), and the Reynolds Stress Model (RSM). The CFD simulation of these models was performed in ANSYS Fluent with an established parameter of 0.3 m/s inlet velocity and stiff/no-slip graft and artery wall boundary condition. Results: As a result, the design with a diameter of 14.5 mm and a 40° angle was overall the most ideal in terms of minimal wall shear stress and turbulence. Conclusions: Thus the brachiocephalic area or the forearm is calculated to be the most optimal implantation site. Additionally, varying angles do affect dialysate flow, as smaller values cause less stress. Full article

This study explores the automation enhancement in the assembly process of wiring harnesses for automotive applications, focusing on manually inserting fuses and relays into boxes—a task known for quality and efficiency challenges. This research aimed to address these challenges by implementing a robotic arm integrated with API technology for digital twin. The methods used included the development of a digital twin model to simulate and monitor the assembly process, supported by real-time adjustments and optimizations. The results showed that the robotic system significantly improved the accuracy and speed of fuse insertion, reducing the insertion errors typically seen in manual operations. The conclusions drawn from the research confirm the feasibility of using robotic automation supported by digital twin technology to enhance assembly processes in automotive manufacturing, promising substantial improvements in production efficiency and quality control. Full article

Future humanoid robots will be widely deployed in our daily lives. Motion planning and control in an unstructured, confined, and human-centered environment utilizing dexterity and a cooperative ability of dual-arm robots is still an open issue. We propose a globally guided dual-arm reactive motion controller (GGDRC) that combines the strengths of global planning and reactive methods. In this framework, a global planner module with a prospective task horizon provides feasible guidance in a Cartesian space, and a local reactive controller module addresses real-time collision avoidance and coordinated task constraints through the exploitation of dual-arm redundancy. GGDRC extends the start-of-the-art optimization-based reactive method for motion-restricted dynamic scenarios requiring dual-arm cooperation. We design a pick–handover–place task to compare the performances of these two methods. Results demonstrate that GGDRC exhibits accurate collision avoidance precision (5 mm) and a high success rate ($84.5\%$). Full article

Space gravitational wave detection primarily focuses on the rich wave sources corresponding to the millihertz frequency band, which provide key information for studying the fundamental physics of cosmology and astrophysics. However, gravitational wave signals are extremely weak, and any noise during the detection process could potentially overwhelm the gravitational wave signals. Therefore, data pre-processing is necessary to suppress the main noise sources. Among the various noise sources, laser phase noise is dominant, approximately seven orders of magnitude larger in strength than typical gravitational wave signals, and requires suppression using time-delay interferometry (TDI) techniques, which involve combining raw data with time delays. This paper will be based on the basic principles of TDI to present methods for obtaining multi-type TDI combinations, including algebraic methods for solving indeterminate equations and geometric methods for symbolic search. Furthermore, the applicability of TDI under actual operating conditions will be considered, such as the arm locking in conjunction with the TDI algorithm. Finally, the sensitivity functions for different types of TDI combinations will be provided, which can be used to evaluate the signal-to-noise ratio (SNRs) of different TDI combinations. Full article

Frozen shoulder (FS) is a common shoulder condition accompanied by shoulder pain and a loss of shoulder range of motion (ROM). The typical clinical assessment tools such as questionnaires and ROM measurement are susceptible to subjectivity and individual bias. To provide an objective evaluation for clinical assessment, this study proposes an inertial measurement unit (IMU)-based identification system to automatically identify shoulder tasks whether performed by healthy subjects or FS patients. Two groups of features (time-domain statistical features and kinematic features), seven machine learning (ML) techniques, and two deep learning (DL) models are applied in the proposed identification system. For the experiments, 24 FS patients and 20 healthy subjects were recruited to perform five daily shoulder tasks with two IMUs attached to the arm and the wrist. The results demonstrate that the proposed system using deep learning presented the best identification performance using all features. The convolutional neural network achieved the best identification accuracy of 88.26%, and the multilayer perceptron obtained the best F1 score of 89.23%. Further analysis revealed that the identification performance based on wrist features had a higher accuracy compared to that based on arm features. The system’s performance using time-domain statistical features has better discriminability in terms of identifying FS compared to using kinematic features. We demonstrate that the implementation of the IMU-based identification system using ML is feasible for FS assessment in clinical practice. Full article

Earthwork operations are critical to construction projects, with their safety and efficiency influenced by factors such as operator skill and working hours. Pre-construction simulation of these operations is essential for optimizing outcomes, providing key training for operators and improving safety awareness and operational efficiency. This study introduces a hierarchical cumulative reward mechanism that decomposes complex operational behaviors into simple, fundamental actions. The mechanism prioritizes reward function design elements, including order, size, and form, thus simplifying excavator operation simulation using reinforcement learning (RL) and enhancing policy network reusability. A 3D model of a hydraulic excavator was constructed with six degrees of freedom—comprising the boom, arm, bucket, base, and left/right tracks. The Proximal Policy Optimization (PPO) algorithm was applied to train four basic behaviors: scraping, digging, throwing, and turning back. Motion simulation was successfully achieved using diggable terrain resources. Results demonstrate that the simulated excavator, powered by RL neural networks, can perform coordinated actions and maintain smooth operational performance. This research offers practical implications by rapidly illustrating the full operational process before construction, delivering immersive movies, and enhancing worker safety and operational efficiency. Full article