Finite element analysis of protective bicycle helmet & dummy head under dynamic loading

Cycling is a good activities particularly for recreation, exercise, and transportation. However, cycling related to the head injury is a significant contributor to hospitalization and death. Previous literatures indicates that the available helmets have less effective in preventing head injuries among cyclists. Moreover, most of the available helmets have been tested for only a few loading conditions. Therefore, the purpose of this study is to use finite element models to evaluate the protective effect of a helmet against various impact velocities. The head and helmet model has been developed using computational software. This study focus on the explicit dynamic analysis which performed in ANSY-WORKBENCH with loading condition in term of various impact velocity impacted on front and side of the head model. The results indicates the differences between the frontal and side simulations. They have been compared to identify the protective effect of the helmet and head

Magnetorheological landing gear: 2. Validation using experimental data

Aircraft landing gears are subjected to a wide range of excitation conditions with conflicting damping requirements. A novel solution to this problem is to implement semi-active damping using magnetorheological (MR) fluids. In part 1 of this contribution, a methodology was developed that enables the geometry of a flow mode MR valve to be optimized within the constraints of an existing passive landing gear. The device was designed to be optimal in terms of its impact performance, which was demonstrated using numerical simulations of the complete landing gear system. To perform the simulations, assumptions were made regarding some of the parameters used in the MR shock strut model. In particular, the MR fluid's yield stress, viscosity, and bulk modulus properties were not known accurately. Therefore, the present contribution aims to validate these parameters experimentally, via the manufacture and testing of an MR shock strut. The gas exponent, which is used to model the shock strut's nonlinear stiffness, is also investigated. In general, it is shown that MR fluid property data at high shear rates are required in order to accurately predict performance prior to device manufacture. Furthermore, the study illustrates how fluid compressibility can have a significant influence on the device time constant, and hence on potential control strategies

The burden of diabetes mellitus during pregnancy in low- and middle-income countries : a systematic review

Peer reviewedPublisher PD

Strategic Approaches to Increase Course Management System Adoption by Higher Education Faculty

The literature suggests multi-causal reasons for low levels of faculty adoption of course management systems (CMSs), and this paper proposes a strategic approach to increase faculty adoption of CMSs. First, challenges to faculty CMS adoption and how faculty willingness to complete CMS training influences CMS adoption will be discussed. Next, research indicating that faculty perceptions of CMS compatibility with their teaching style affects CMS training completion, and likely has a secondary impact on CMS adoption, will be reviewed. Lastly, recommendations for targeting faculty with teaching styles less compatible with CMS use and improving their compatibility will be given

Deeper Learning Methods and Modalities in Higher Education: A 20-year Review

Deep Learning or Deeper Learning (DL) theory has gained traction as a helpful framework for designing higher education curricula in face-to-face (F2F), hybrid, and online settings. Although many research studies have been published testing DL methods in higher education, it is difficult to apply the results without an overview. This review applies a scientifically-informed search approach to select a sample of 127 peer-reviewed articles (representing 176 experimental groups) published from 1999 through 2019 on the topic of DL in higher education, classifies and extracts data from them, and presents a descriptive analysis of the findings

Does the impact of a plant-based diet during pregnancy on birth weight differ by ethnicity? A dietary pattern analysis from a prospective Canadian birth cohort alliance

Objective: Birth weight is an indicator of newborn health and a strong predictor of health outcomes in later life. Signicant variation in diet during pregnancy between ethnic groups in high-income countries provides an ideal opportunity to investigate the influence of maternal diet on birth weight. Setting: Four multiethnic birth cohorts based in Canada (the NutriGen Alliance). Participants: 3997 full-term mother–infant pairs of diverse ethnic groups who had principal component analysis-derived diet pattern scores—plant-based, Western and health-conscious—and birth weight data. Results: No associations were identified between the Western and health-conscious diet patterns and birth weight; however, the plant-based dietary pattern was inversely associated with birth weight (β=−67.6 g per 1-unit increase; P<0.001), and an interaction with non-white ethnicity and birth weight was observed. Ethnically stratified analyses demonstrated that among white Europeans, maternal consumption of a plant-based diet associated with lower birth weight (β=−65.9 g per 1-unit increase; P<0.001), increased risk of small-for-gestational age (SGA; OR=1.46; 95% CI 1.08 to 1.54;P=0.005) and reduced risk of large-for-gestational age (LGA; OR=0.71; 95% CI 0.53 to 0.95;P=0.02). Among South Asians, maternal consumption of a plant-based diet associated with a higher birth weight (β=+40.5 g per 1-unit increase; P=0.01), partially explained by cooked vegetable consumption. Conclusions: Maternal consumption of a plant-based diet during pregnancy is associated with birth weight. Among white Europeans, a plant-based diet is associated with lower birth weight, reduced odds of an infant born LGA and increased odds of SGA, whereas among South Asians living in Canada, a plant-based diet is associated with increased birth weight