Non-fatal spine injuries resulting from motorcycle crashes

This study aims to determine spinal injury patterns and identify crash factors commonly associated with serious spinal injury as a result of motorcycle crashes. Data was retrospectively collected from motorcyclists sustaining spinal injuries from road crashes treated at Kuala Lumpur Hospital, Malaysia, over the 5-year period from 2005 to 2009. Each patient's injuries were analyzed by reviewing his or her medical records for radiographic imaging and computed tomography scans.A total of 151 patients were included in this study, of which, males accounted for over 87%. The first lower lumbar (L1) was the most commonly injured vertebral level, followed by the adjacent thoracic vertebra (T12). Fracture to the vertebral body without dislocation was found to be the most frequently observed spinal injury pattern. Injury severities for a majority of patients (65%) were measured at Maximum Abbreviated Injury Scale (MAIS) of 2. Serious spinal injury was associated with thorax or upper-extremity injury.Prevalence of lumbar spinal injury in the study reflects a predominantly low-speed crash among the motorcyclist in the region. Motorcyclists are at greater odd to sustain severe spinal injury when directly striking an object compare to striking the ground during the crash event.     

An analysis of weekly out-of-home discretionary activity participation and time-use behavior

Activity-travel behavior research has hitherto focused on the modeling and understanding of daily time use and activity patterns and resulting travel demand. In this particular paper, an analysis and modeling of weekly activity-travel behavior is presented using a unique multi-week activity-travel behavior data set collected in and around Zurich, Switzerland. The paper focuses on six categories of discretionary activity participation to understand the determinants of, and the inter-personal and intra-personal variability in, weekly activity engagement at a detailed level. A panel version of the Mixed Multiple Discrete Continuous Extreme Value model (MMDCEV) that explicitly accounts for the panel (or repeated-observations) nature of the multi-week activity-travel behavior data set is developed and estimated on the data set. The model also controls for individual-level unobserved factors that lead to correlations in activity engagement preferences across different activity types. To our knowledge, this is the first formulation and application of a panel MMDCEV structure in the econometric literature. The analysis suggests the high prevalence of intra-personal variability in discretionary activity engagement over a multi-week period along with inter-personal variability that is typically considered in activity-travel modeling. In addition, the panel MMDCEV model helped identify the observed socio-economic factors and unobserved individual specific factors that contribute to variability in multi-week discretionary activity participation.

Performance evaluation of energy meters under nonlinear loads

Due to rapid advancements in power electronics, the utilization of electronically switched loads and nonlinear loads is increasing gradually in the electrical power system. These loads create problems of measuring instruments, when connected to the power distribution systems. In this paper, an experimental investigation has been carried out to analyze the performance of single-phase watt-hour (induction and electronic types) energy meters that are being used in Pakistan. The accuracy of the energy meters has been tested under different household nonlinear loads, at various power factors and also at different supply voltage levels. Power factor and total harmonic distortion (THD) of different household loads are also recorded in the experimental work. A hardware based experimental setup has been designed to perform the experimental work. The experimental results have been compared to Water and Power Development Authority (WAPDA) standards for energy meters.