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The main aim of the current work is to investigate the effect of equal channel angular pressing (ECAP) processing parameters, namely, number of passes, ECAP die angle, route type, and processing temperature on the mechanical and electrical properties of pure copper (Cu). The finite element method was used to simulate the homogeneity of stress and plastic strain distribution during ECAP processing. The response surface methodology (RSM) was used to identify the optimum ECAP processing parameters by analyzing the impact of ECAP conditions on responses. A second-order regression model and analysis of variance were created to analyze the ECAP condition of optimum responses. A genetic algorithm (GA) was also applied to optimize the ECAP condition. Finally, a hybrid RSM–GA was created to improve the optimization of ECAP responses and corresponding conditions evaluated using GA. The developed models were validated and compared with the experimental findings to prove that they are reliable as predictive tools. The optimization findings revealed that route Bc was more effective in improving the hardness, yield stress, ductility, and impact energy whereas route A was more effective in improving the ultimate tensile strength and the electrical conductivity of the Cu billets. Furthermore, the optimum die angle, number of passes, and processing temperature for the mechanical and electrical properties were also identified individually.

Purpose: This study was conducted to release the debate and examine the short-term impact of KT on the quadriceps muscle following arthroscopic surgery for partial meniscectomy. Patients and Methods: As part of a double-blind, randomized controlled trial, 40 people who had an arthroscopic partial meniscectomy (APM) were randomly put into two groups, A and B. Group A received Kinesio tape (KT) for the superficial heads of the quadriceps muscle, while group B received placebo KTk. After 10 minutes of KT application, the peak torque of both groups was measured using a Biodex isokinetic dynamometer. Results: Peak torque showed a significant increase in group A in comparison with group B during angular velocity 60◦/Sec. (F (1, 130) = 58.9, p < 0.001, ƞ2 =0.31) and during angular velocity 180◦/Sec. (F (1, 38) = 25.0, p < 0.001, ƞ2 =0.40). Conclusion: After APM, individuals experienced an immediate and significant improvement in the quadriceps' peak torque following KT application to the Rectus femoris, Vastus medialis, and Vastus lateralis muscles from origin to insertion. [ABSTRACT FROM AUTHOR]

(1) Background: Neck pain intensity, psychosocial factors, and physical function have been identified as potential predictors of neck disability. Machine learning algorithms have shown promise in classifying patients based on their neck disability status. So, the current study was conducted to identify predictors of neck disability in patients with neck pain based on clinical findings using machine learning algorithms. (2) Methods: Ninety participants with chronic neck pain took part in the study. Demographic characteristics in addition to neck pain intensity, the neck disability index, cervical spine contour, and surface electromyographic characteristics of the axioscapular muscles were measured. Participants were categorised into high disability and low disability groups based on the median value (22.2) of their neck disability index scores. Several regression and classification machine learning models were trained and assessed using a 10-fold cross-validation method; also, MANCOVA was used to compare between the two groups. (3) Results: The multilayer perceptron (MLP) revealed the highest adjusted R2 of 0.768, while linear discriminate analysis showed the highest receiver characteristic operator (ROC) area under the curve of 0.91. Pain intensity was the most important feature in both models with the highest effect size of 0.568 with p < 0.001. (4) Conclusions: The study findings provide valuable insights into pain as the most important predictor of neck disability in patients with cervical pain. Tailoring interventions based on pain can improve patient outcomes and potentially prevent or reduce neck disability. [ABSTRACT FROM AUTHOR]

The flow behaviour of AA2060 Al alloy under warm/hot deformation conditions is complicated because of its dependency on strain rates ( ε ˙ ), strain ( ε ), and deformation modes. Thus, it is crucial to reveal and predict the flow behaviours of this alloy at a wide range of temperatures ( T) and ε ˙ using different constitutive models. Firstly, the isothermal tensile tests were carried out via a Gleeble-3800 thermomechanical simulator at a T range of 100, 200, 300, 400, and 500 °C and ε ˙ range of 0.01, 0.1, 1, and 10 s−1 to reveal the warm/hot flow behaviours of AA2060 alloy sheet. Consequently, three phenomenological-based constitutive models (L-MJC, S1-MJC, S2-MJC) and a modified Zerilli–Armstrong (MZA) model representing physically based constitutive models were developed to precisely predict the flow behaviour of AA2060 alloy sheet under a wide range of T and ε ˙ . The predictability of the developed constitutive models was assessed and compared using various statistical parameters, including the correlation coefficient (R), average absolute relative error (AARE), and root mean square error (RMSE). By comparing the results determined from these models and those obtained from experimentations, and confirmed by R, AARE, and RMSE values, it is concluded that the predicted stresses determined from the S2-MJC model align closely with the experimental stresses, demonstrating a remarkable fit compared to the S1-MJC, L-MJC, and MZA models. This is because of the linking impact between softening, the strain rate, and strain hardening in the S2-MJC model. It is widely known that the dislocation process is affected by softening and strain rates. This is attributed to the interactions that occurred between ε and ε ˙ from one side and between ε , ε ˙ , and T from the other side using an extensive set of constants correlating the constitutive components of dynamic recovery and softening mechanisms. [ABSTRACT FROM AUTHOR]

Crashes involving heavy trucks on rural mountainous freeways are known to result in severe injuries and fatalities, particularly under challenging driving conditions. This study aims to develop a robust model to accurately predict fatal and injury crashes involving heavy trucks on rural mountainous freeways. The crash database of Interstate-80 in Wyoming was used to extract a wide range of variables related to environmental, roadway, crash, occupant, and vehicle characteristics. This study employed a state-of-the-art deep neural network architecture named ResNet-50 using transfer learning to develop crash severity prediction models. The numeric crash data were converted to images utilizing DeepInsight to facilitate the application of the proposed deep learning model. Due to the imbalanced nature of the crash severity data, this study employed random undersampling (RUS) and synthetic minority oversampling technique (SMOTE) data balancing techniques and investigated several data sampling ratios. A ratio of 1:2:2 (Fatal: Injury: PDO) combined with both RUS and SMOTE produced the best performance with recall values of 99.7%, 79.7%, and 79.3% for fatal, injury, and PDO crashes, respectively. This study also employed Boruta and extreme gradient boosting (XGBoost) to examine the significance of variables on crash severity. The findings revealed that the deployment of airbags, use of seatbelts, driver distraction, and driver conditions such as inattentiveness and fatigue, vehicle type, vertical grades, weather, and road surface conditions were the most critical variables contributing to the severity of crashes involving heavy trucks. Furthermore, this study developed several reduced truck-involved crash severity prediction models without significantly compromising the prediction performance. The proposed deep neural network model can provide accurate and timely prediction of fatal and injury crashes involving heavy trucks, which is beneficial for ensuring efficient collision management, avoiding secondary pile-up crashes, and facilitating prompt medical assistance. [ABSTRACT FROM AUTHOR]

Objective was to assess static trunk balance after recovery from COVID-19. Patients and Methods: 145 recovered COVID-19 university students between the ages of 19 and 25 participated in this single-blinded, randomized controlled trial study. The participants were divided into a Pilates group and a control group, each of which received a home exercise program. Core muscle endurance was measured using the five basic endurance tests and static balance using the Prokin system with open eyes (OE) and closed eyes (CE) at baseline and after three months of treatment. Results: All measured parameters showed improvement within the groups after treatment. Group comparison revealed a significant increase in the Pilates group in all core endurance tests (P< 0.001). The Prokin system results showed improvement in the Pilates group after treatment, while perimeter with OE, CE, and ellipse area with EC decreased (P< 0.001), but there was no significant difference in ellipse with OE between the groups. Conclusion: Pilates exercises positively improved core muscle endurance and trunk balance in people infected with COVID-19, which will be reflected in their quality of movement patterns and quality of life. [ABSTRACT FROM AUTHOR]

This study investigated the effect of a hemispherical friction stir welding (FSW) tool on the heat generation and mechanical properties of dissimilar butt welded AA5083 and AA7075 alloys. FSW was performed on the dissimilar aluminum alloys AA5083-H111 and AA7075-T6 using welding speeds of 25, 50, and 75 mm/min. The tool rotation rate was kept constant at 500 rpm. An analytical model was developed to calculate heat generation and temperature distribution during the FSW process utilizing a hemispherical tool. The experimental results were compared to the calculated data. The latter confirms the accuracy of the analytical model, demonstrating a high degree of agreement. Sound FSW dissimilar joints were achieved at welding speeds of 50 and 25 mm/min. Meanwhile, joints created at a welding speed of 75 mm/min exhibited a tunnel-like defect, which can be attributed to the minimal heat generated at this particular welding speed. At a lower welding speed of 25 mm/min, a higher tensile strength of the dissimilar FSWed joints AA5083 and AA7075 was achieved with a joint efficiency of over 97%. [ABSTRACT FROM AUTHOR]

Background: Anterior cruciate ligament (ACL) is crucial for knee joint stability, but total failure can impair proprioception. Rehabilitation involves unique regimens, virtual reality VR games being a helpful aid. Purpose: Examining how a Wii Fit rehabilitation program affects knee proprioception following ACL reconstruction. Methods: Thirty patients were assigned randomly to Study group (A), and control group (B). For eight weeks, the study group received the Wii Fit training protocol three times a week, lasting forty minutes each, with a conventional exercise program tailored to the control group. The knee joint's position sense was measured in both groups, before and after activities using a Biodex isokinetic dynamometer. Results: After treatment the joint position error JPE significantly improved for group A and group B. With significant decrease of JPE for the three angles of group A compared to group B (P<0.01). Conclusion: The results revealed that Playing weight shifting VR games on the Wii Fit for eight weeks, with a consistent exercise rehabilitation program, can significantly improve knee joint position sense. [ABSTRACT FROM AUTHOR]

Background: Physiotherapy is crucial for managing gait dysfunctions, but research on Egyptian physiotherapists' knowledge and training in gait assessment is limited. Purpose: The study aims to evaluate the current gait assessment tools and training methods among Egyptian physiotherapists and determine the necessity for a clinically standardized approach. Methods: A survey study in Egypt assessed physiotherapists' gait analysis training, frequency of using standardized tools, and perceived need for gait analysis tools in clinical settings. Results: A survey of 330 physiotherapists revealed that despite 84.8% treating gait disorders, standardized gait assessment tools were not widely used. Only 46.4% had access to a gait laboratory. The survey also highlighted the need for training and national guidance in gait assessment. Conclusion: These results highlight the importance of standardized gait analysis approaches, formal training, and the development of national guidelines to enhance gait assessment practices in Egypt's clinical settings. [ABSTRACT FROM AUTHOR]

Promoting the safety of commercial trucks by identifying countermeasures that eliminate/reduce the effect of factors that increase the severity of truck-related crashes is crucial. Crash causal factors for rural interstate roads, located within the mountain plains, are inherently unique compared to urban interstate roads. This is due to the presence of challenging road geometry coupled with severe weather conditions and high truck traffic volumes. This study investigated Interstate 80 in Wyoming using decision trees, as a data mining approach, and structural equation model (SEM) as a latent factor modeling approach. SEM was employed to clarify the direct and indirect relationships between endogenous and exogenous variables while accounting for the variation and covariation within and between the constructed measurement models. Crash severity data were processed to account for factors affecting single vehicles and multivehicle trucks. The results showed that the interaction with surrounding traffic was the most significant latent variable affecting the crash severity of multivehicle truck crashes, while adverse weather conditions were the most significant latent variable affecting the crash severity of single-truck crashes. The results of this study highlighted the importance of increasing the situational awareness of commercial truck drivers with upcoming hazardous events. This could be performed by communicating information using variable message signs, the 511 application, the commercial vehicle operator portal (CVOP), or the connected vehicle (CV) technologies. [ABSTRACT FROM AUTHOR]