FATIGUE STRENGTH OF A CHASSIS OF A SEMI-HEAVY TRUCK UNDER DYNAMIC LOADS DUE TO REAL ROAD ROUGHNESS

Evaluation of fatigue life of vehicles by using a real road test is very expensive; therefore, numerical methods such as Finite Element Method (FEM) are nowadays very popular for evaluating fatigue life. In this study, a method based on FEM is proposed for predicting fatigue strength of the chassis when designing and optimizing a semi-heavy truck. An experimental modal analysis has been applied for the validation of the finite element model which has been used in the proposed method. The natural frequencies and mode shapes of the chassis have been obtained from the finite element analysis and compared with the corresponding results of the experimental modal analysis. Also, a method for producing uneven roads in the time domain based on the International Reference Index (IRI) was introduced to simulate road roughness. In addition, different road types (with potholes and kerbs) and different load conditions (braking and cornering) have been considered throughout the simulation. In all of the mentioned conditions, stress time histories have been extracted and investigated. Finally, fatigue damage and strength of the chassis and welded connections have been estimated and described

Developing Non-Laboratory Cardiovascular Risk Assessment Charts and Validating Laboratory and Non-Laboratory-Based Models.

BACKGROUND: Developing simplified risk assessment model based on non-laboratory risk factors that could determine cardiovascular risk as accurately as laboratory-based one can be valuable, particularly in developing countries where there are limited resources. OBJECTIVE: To develop a simplified non-laboratory cardiovascular disease risk assessment chart based on previously reported laboratory-based chart and evaluate internal and external validation, and recalibration of both risk models to assess the performance of risk scoring tools in other population. METHODS: A 10-year non-laboratory-based risk prediction chart was developed for fatal and non-fatal CVD using Cox Proportional Hazard regression. Data from the Isfahan Cohort Study (ICS), a population-based study among 6504 adults aged ≥ 35 years, followed-up for at least ten years was used for the non-laboratory-based model derivation. Participants were followed up until the occurrence of CVD events. Tehran Lipid and Glucose Study (TLGS) data was used to evaluate the external validity of both non-laboratory and laboratory risk assessment models in other populations rather than one used in the model derivation. RESULTS: The discrimination and calibration analysis of the non-laboratory model showed the following values of Harrell's C: 0.73 (95% CI 0.71-0.74), and Nam-D'Agostino χ2:11.01 (p = 0.27), respectively. The non-laboratory model was in agreement and classified high risk and low risk patients as accurately as the laboratory one. Both non-laboratory and laboratory risk prediction models showed good discrimination in the external validation, with Harrell's C of 0.77 (95% CI 0.75-0.78) and 0.78 (95% CI 0.76-0.79), respectively. CONCLUSIONS: Our simplified risk assessment model based on non-laboratory risk factors could determine cardiovascular risk as accurately as laboratory-based one. This approach can provide simple risk assessment tool where laboratory testing is unavailable, inconvenient, and costly

PARS risk charts: A 10-year study of risk assessment for cardiovascular diseases in Eastern Mediterranean Region

This study was designed to develop a risk assessment chart for the clinical management and prevention of the risk of cardiovascular disease (CVD) in Iranian population, which is vital for developing national prevention programs. The Isfahan Cohort Study (ICS) is a popu- lation-based prospective study of 6504 Iranian adults 35 years old, followed-up for ten years, from 2001 to 2010. Behavioral and cardiometabolic risk factors were examined every five years, while biennial follow-ups for the occurrence of the events was performed by phone calls or by verbal autopsy. Among these participants, 5432 (2784 women, 51.3%) were CVD free at baseline examination and had at least one follow-up. Cox proportional hazard regression was used to predict the risk of ischemic CVD events, including sudden cardiac death due to unstable angina, myocardial infarction, and stroke. The model fit statis- tics such as area under the receiver-operating characteristic (AUROC), calibration chi- square and the overall bias were used to assess the model performance. We also tested the Framingham model for comparison. Seven hundred and five CVD events occurred during 49452.8 person-years of follow-up. The event probabilities were calculated and presented color-coded on each gender-specific PARS chart. The AUROC and Harrell’s C indices were 0.74 (95% CI, 0.72–0.76) and 0.73, respectively. In the calibration, the Nam-D’Ago stino ¿ 2 was 10.82 (p = 0.29). The overall bias of the proposed model was 95.60%. PARS model was also internally validated using cross-validation. The Android app and the Web-based risk assessment tool were also developed as to have an impact on public health. In compari- son, the refitted and recalibrated Framingham models, estimated the CVD incidence with the overall bias of 149.60% and 128.23% for men, and 222.70% and 176.07% for women, respectively. In conclusion, the PARS risk assessment chart is a simple, accurate, and well- calibrated tool for predicting a 10-year risk of CVD occurrence in Iranian population and can be used in an attempt to develop national guidelines for the CVD management .Peer ReviewedPostprint (published version

Corrigendum to “A new method of diagnosing athlete's anterior cruciate ligament health status using surface electromyography and deep convolutional neural network” [Biocybern. Biomed. Eng. 40 (1) (2020) 65–76]

International audienc

A new method of diagnosing athlete's anterior cruciate ligament health status using surface electromyography and deep convolutional neural network

International audienc

Muscles Data Compression in Body Sensor Network using the Principal Component Analysis in Wavelet Domain

Introduction: Body sensor network is a key technology that is used for supervising the physiological information from long distance that enables physicians to predict, diagnose effectively the different conditions from long distance. These networks include small sensors with the ability of sensing where there are some limitations in calculating and energy. Methods: In the present research, a new compression method based on the analysis of principal components and wavelet transform is used to increase the coherence. In the present method, the first analysis of the main principles is used to find the principal components of the data in order to increase the coherence for increasing the similarity between the data and compression rate. Then, according to the ability of wavelet transform, data are decomposed to different scales. In restoration process of data only special parts are restored and some parts of the data that include noise are omitted. By noise omission, the quality of the sent data increases and good compression could be obtained. Results: Pilates practices were executed among twelve patients with various dysfunctions. The results show 0.7210, 0.8898, 0.6548, 0.6765, 0.6009, 0.7435, 0.7651, 0.7623, 0.7736, 0.8596, 0.8856 and 0.7102 compression ratio in proposed method and 0.8256, 0.9315, 0.9340, 0.9509, 0.8998, 0.9556, 0.9732, 0.9580, 0.8046, 0.9448, 0.9573 and 0.9440 compression ratio for previous method (Tseng algorithm). Conclusion: Comparing compression rate and prediction errors with the available results shows the exactness of the proposed method

Discriminative sEMG-based features to assess damping ability and interpret activation patterns in lower-limb muscles of ACLR athletes

International audienceObjective: The main goal of the athletes who undergo anterior cruciate ligament reconstruction (ACLR) surgery is a successful return-to-sport. At this stage, identifying muscular deficits becomes important. Hence, in this study, three discriminative features based on surface electromyographic signals (sEMG) acquired in a dynamic protocol are introduced to assess the damping ability and interpret activation patterns in lower-limb muscles of ACLR athletes. Methods: The features include the median frequency of the power spectrum density (PSD), the relative percentage of the equivalent damping or equivalent stiffness derived from the median frequency, and the energy of the signals in the time-frequency plane of the pseudo-Wigner-Ville distribution (PWVD). To evaluate the features, 11 healthy and 11 ACLR athletes (6 months post-reconstruction surgery) were recruited to acquire the sEMG signals from the medial and the lateral parts of the hamstrings, quadriceps, and gastrocnemius muscles in pre- and post-fatigue single-leg landings. Results: A significant damping deficiency is observed in the hamstring muscles of ACLR athletes by evaluating the proposed features. This deficiency indicates that more attention should be paid to this muscle of ACLR athletes in pre-return-to-sport rehabilitations. Conclusion: The quality of electromyography-based pre-return-to-sport assessments on ACLR subjects depends on the sEMG acquisition protocol, as well as the type and nature of the extracted features. Hence, combinatorial application of both energy-based features (derived from the PWVD) and power-based features (derived from the PSD) could facilitate the assessment process by providing additional biomechanical information regarding the behavior of the muscles surrounding the knee

The Comparison of Nailfold Capillaroscopy between Juvenile Systemic Lupus Erythematosus and Healthy Controls: Correlation with Laboratory and Clinical Parameters

Background. Nailfold capillaroscopy is a noninvasive technique to recognize peripheral microangiopathy, which is an important feature in systemic lupus erythematosus (SLE). The aims of the present study were to investigate the prevalence of nailfold capillaroscopy (NFC) changes in juvenile systemic lupus erythematosus (JSLE), find out patterns of these changes, and correlate findings with clinical and laboratory parameters. Methods. Forty-nine patients with SLE, all meeting the 1997 revised ACR criteria for SLE classification, and 30 healthy controls were included. A digital video camera was used to capture nailfold capillary images. Computerized image processing was used for analysis. Results. Different abnormal NFC changes were observed with abnormal morphology, the increased diameter and abnormal loop densities in 55.1%, 93.9%, and 26.5% of the patients, respectively. No statistically significant differences were depicted between capillaroscopy with age, gender, autoantibodies (APLs, anti-ds DNA), antiphospholipid antibody syndrome, thrombotic angiopathy, renal function tests (Bun, Cr), and abnormal urine analysis. However, a significant correlation was found between the branched pattern and the CNS involvement group (P value <0.03). Conclusions. Different abnormal NFC changes are quite common among patients with SLE, and nailfold capillaroscopy is an effective method to monitor such changes. Treatment strategies may change in the branched pattern of nailfold capillaroscopy due to CNS involvement

FATIGUE STRENGTH OF A CHASSIS OF A SEMI-HEAVY TRUCK UNDER DYNAMIC LOADS DUE TO REAL ROAD ROUGHNESS

Evaluation of fatigue life of vehicles by using a real road test is very expensive; therefore, numerical methods such as Finite Element Method (FEM) are nowadays very popular for evaluating fatigue life. In this study, a method based on FEM is proposed for predicting fatigue strength of the chassis when designing and optimizing a semi-heavy truck. An experimental modal analysis has been applied for the validation of the finite element model which has been used in the proposed method. The natural frequencies and mode shapes of the chassis have been obtained from the finite element analysis and compared with the corresponding results of the experimental modal analysis. Also, a method for producing uneven roads in the time domain based on the International Reference Index (IRI) was introduced to simulate road roughness. In addition, different road types (with potholes and kerbs) and different load conditions (braking and cornering) have been considered throughout the simulation. In all of the mentioned conditions, stress time histories have been extracted and investigated. Finally, fatigue damage and strength of the chassis and welded connections have been estimated and described