Motorcycle helmet type and the risk of head injury and neck injury during motorcycle collisions in California

The use of novelty motorcycle helmets is often prompted by beliefs that wearing a standard helmet can contribute to neck injury during traffic collisions. The goal of this analysis was to examine the association between helmet type and neck injury risk and the association between helmet type and head injury. Data were collected during the investigation of motorcycle collisions of any injury severity by the California Highway Patrol (CHP) and 83 local law enforcement agencies in California between June 2012 and July 2013. We estimated head injury and neck injury risk ratios from data on 7051 collision-involved motorcyclists using log-binomial regression. Helmet type was strongly associated with head injury occurrence but was not associated with the occurrence of neck injury. Rider age, rider alcohol use, and motorcycle speed were strong, positive predictors of both head and neck injury. Interventions to improve motorcycle helmet choice and to counteract misplaced concerns surrounding neck injury risk are likely to lead to reductions in head injury, brain injury, and death.     

Correlation of head injury to vehicle contact points using crash injury research and engineering network data

Head injury is the most common cause of morbidity and mortality in motor vehicle crashes. Efforts to improve vehicle design, which minimize forces exerted to the occupant's head, may lead to a reduction in the frequency and severity of head injury. We therefore set out to identify mechanisms producing severe head injury in motor vehicle crashes (MVC) derived from the crash injury research and engineering network (CIREN) database. CIREN combines crash site analysis, vehicle damage assessment, and occupant kinematics in relation to the occupant's injuries. From the Seattle CIREN database of 101 cases, compiled from 1997 to 1998, we selected those crashes in which the occupant sustained severe head injury (abbreviated injury score, AIS>or=4) for analysis. We examined crash mechanism, energy transfer, point of head contact, vehicle intrusion and resulting injuries.There were 15 cases with severe head injury. These were primarily due to side impacts (n=10) in comparison to front impacts (n=5). The average net change in velocity (delta velocity, DV) was 15 mile/h (range 4-29 mile/h). In cases where the primary point of head contact could be elucidated the B-pillar predominated (4 cases, 33.3%) followed by the striking external object (2 cases, 16.7%), A- (1 case, 8.3%) and C- (1 case, 8.3%) pillars, roof side rail (1 case, 8.3%), windshield header (1 case, 8.3%), windowsill (1 case, 8.3%) and airbag (1 case, 8.3%).In this series the predominant mechanism of head injury was lateral impacts, especially those in which the victims' heads struck the B-pillar. The need for improved head protection from lateral impacts is indicated.     

Underreporting in traffic accident data, bias in parameters and the structure of injury severity models

Injury severities in traffic accidents are usually recorded on ordinal scales, and statistical models have been applied to investigate the effects of driver factors, vehicle characteristics, road geometrics and environmental conditions on injury severity. The unknown parameters in the models are in general estimated assuming random sampling from the population. Traffic accident data however suffer from underreporting effects, especially for lower injury severities. As a result, traffic accident data can be regarded as outcome-based samples with unknown population shares of the injury severities. An outcome-based sample is overrepresented by accidents of higher severities. As a result, outcome-based samples result in biased parameters which skew our inferences on the effect of key safety variables such as safety belt usage. The pseudo-likelihood function for the case with unknown population shares, which is the same as the conditional maximum likelihood for the case with known population shares, is applied in this study to examine the effects of severity underreporting on the parameter estimates. Sequential binary probit models and ordered-response probit models of injury severity are developed and compared in this study. Sequential binary probit models assume that the factors determining the severity change according to the level of the severity itself, while ordered-response probit models assume that the same factors correlate across all levels of severity. Estimation results suggest that the sequential binary probit models outperform the ordered-response probit models, and that the coefficient estimates for lap and shoulder belt use are biased if underreporting is not considered. Mean parameter bias due to underreporting can be significant. The findings show that underreporting on the outcome dimension may induce bias in inferences on a variety of factors. In particular, if underreporting is not accounted for, the marginal impacts of a variety of factors appear to be overestimated. Fixed objects and environmental conditions are overestimated in their impact on injury severity, as is the effect of separate lap and shoulder belt use. Combined lap and shoulder belt usage appears to be unaffected. The parameter bias is most pronounced when underreporting of possible injury accidents in addition to property damage only accidents is taken into account.     

The relationship between visibility aid use and motor vehicle related injuries among bicyclists presenting to emergency departments

Background

Little is known about the effectiveness of visibility aids (VAs; e.g., reflectors, lights, fluorescent clothing) in reducing the risk of a bicyclist–motor-vehicle (MV) collision.

Purpose

To determine if VAs reduce the risk of a bicyclist–MV collision.

Methods

Cases were bicyclists struck by a MV and assessed at Calgary and Edmonton, Alberta, Canada, emergency departments (EDs) from May 2008 to October 2010. Controls were bicyclists with non-MV injuries. Participants were interviewed about their personal and injury characteristics, including use of VAs. Injury information was collected from charts. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for VAs during daylight and dark conditions, and adjusted for confounders using logistic regression. Missing values were imputed using chained equations and adjusted OR estimates from the imputed data were calculated.

Results

There were 2403 injured bicyclists including 278 cases. After adjusting for age, sex, type of bicycling (commuting vs. recreational) and bicyclist speed, white compared with black (OR 0.52; 95% CI 0.28, 0.95), and bicyclist self-reported light compared with dark coloured (OR 0.67; 95% CI 0.49, 0.92) upper body clothing reduced the odds of a MV collision during daylight. After imputing missing values, white compared with black (OR 0.57; 95% CI: 0.32, 0.99) and bicyclist self-reported light compared with dark coloured (OR 0.71; 95% CI 0.52, 0.97) upper body clothing remained protective against MV collision in daylight conditions. During dark conditions, crude estimates indicated that reflective clothing or other items, red/orange/yellow front upper body clothing compared with black, fluorescent clothing, headlights and tail lights were estimated to increase the odds of a MV collision. An imputed adjusted analysis revealed that red/orange/yellow front upper body clothing colour (OR 4.11; 95% CI 1.06, 15.99) and tail lights (OR 2.54; 95% CI: 1.06, 6.07) remained the only significant risk factors for MV collisions. One or more visibility aids reduced the odds of a bicyclist MV collision resulting in hospitalization.

Conclusions

Bicyclist clothing choice may be important in reducing the risk of MV collision. The protective effect of visibility aids varies based on light conditions, and non-bicyclist risk factors also need to be considered.     

Comparison of risk factors for cervical spine,head, serious,and fatal injury in rollover crashes

Previous epidemiological studies of rollover crashes have focused primarily on serious and fatal injuries in general, while rollover crash testing has focused almost exclusively on cervical spine injury. The purpose of this study was to examine and compare the risk factors for cervical spine, head, serious, and fatal injury in real world rollover crashes. Rollover crashes from 1995–2008 in the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) were investigated. A large data set of 6015 raw cases (2.5 million weighted) was generated. Nonparametric univariate analyses, univariate logistic regression, and multivariate logistic regression were conducted. Complete or partial ejection, a lack of seatbelt use, a greater number of roof inversions, and older occupant age significantly increased the risk of all types of injuries studied (p < 0.05). Far side seating position increased the risk of fatal, head, and cervical spine injury (p < 0.05), but not serious injury in general. Higher BMI was associated with an increased risk of fatal, serious, and cervical spine injury (p < 0.05), but not head injury. Greater roof crush was associated with a higher rate of fatal and cervical spine injury (p < 0.05). Vehicle type, occupant height, and occupant gender had inconsistent and generally non-significant effects on injury. This study demonstrates both common and unique risk factors for different types of injuries in rollover crashes.     

Comparison of roadside crash injury metrics using event data recorders

The occupant impact velocity (OIV) and acceleration severity index (ASI) are competing measures of crash severity used to assess occupant injury risk in full-scale crash tests involving roadside safety hardware, e.g. guardrail. Delta-V, or the maximum change in vehicle velocity, is the traditional metric of crash severity for real world crashes. This study compares the ability of the OIV, ASI, and delta-V to discriminate between serious and non-serious occupant injury in real world frontal collisions. Vehicle kinematics data from event data recorders (EDRs) were matched with detailed occupant injury information for 180 real world crashes. Cumulative probability of injury risk curves were generated using binary logistic regression for belted and unbelted data subsets. By comparing the available fit statistics and performing a separate ROC curve analysis, the more computationally intensive OIV and ASI were found to offer no significant predictive advantage over the simpler delta-V.     

Mechanisms and modelling of creep in superalloys

The characteristics of creep deformation of nickel-base superalloys are reviewed and the implications for the micromechanisms controlling the behaviour are considered. The development of a model of the creep deformation that is compatible with the physical mechanisms is traced, first in an isotropic form and later incorporating full crystallographic anisotropy. The validity of the model and its ability to be extrapolated to more complex loading conditions are evaluated against a wide range of experimental measurements. Much of the work described in this review has been funded by the Defence Research Agency and creep data and specimens for examination were supplied by Dr M R Winstone of DRA.     

Relationship between mechanisms and activities at the time of pedestrian injury and activity limitation among school adolescents in Kathmandu, Nepal

This study assessed the relationship between pedestrian activity at the time of injury, the type of vehicle involved and resulting activity limitation among school adolescents in the Kathmandu and Lalitpur districts of Nepal. A cross-sectional study of 1557 students in grades 6–8 across 14 schools was conducted using a self-administered questionnaire from August to September 2003. Twenty-three percent of adolescents reported pedestrian injuries, 38% were from urban and 21% from semi-urban areas. Adolescents were commonly injured by motorcycles and motor vehicles while crossing the road; however, while walking and playing, they were commonly injured by bicycles and motorcycles. Bicycles and motor vehicles were less likely to be involved in injury while crossing the roads and playing, respectively (p < 0.001). Activity was more likely to be limited for a longer period of time (>7 days) with injuries endured while crossing the road (p < 0.001). In urban areas, boys and girls were more likely to be injured while crossing the road and walking, respectively (p < 0.05), and both were commonly injured by motorcycles. In semi-urban areas, boys and girls were commonly injured while walking and were more likely to be injured by motorcycles and bicycles, respectively (p < 0.05). In both areas, more boys than girls were injured while playing. These findings have important implications for pedestrian safety interventions in poor countries.     

Exploring the impacts of factors contributing to tram-involved serious injury crashes on Melbourne tram routes

Previous research is limited regarding factors influencing tram-involved serious injury crashes. The aim of this study is to identify key vehicle, road, environment and driver related factors associated with tram-involved serious injury crashes. Using a binary logistic regression modelling approach, the following factors were identified to be significant in influencing tram-involved fatal crashes in Melbourne: tram floor height, tram age, season, traffic volume, tram lane priority and tram travel speed. Low floor trams, older trams, tram priority lanes and higher tram travelling speeds are more likely to increase tram-involved fatal crashes. Higher traffic volume decreases the likelihood of serious crashes. Fatal crashes are more likely to occur during spring and summer. Findings from this study may offer ideas for future research in the area of tram safety and help to develop countermeasures to prevent specific fatality types from occurring.     

Application of weibull proportional hazards modelling to bad-as-old failure data

In this paper, an analysis is conducted of the equipment failure regime known as bad-as-old. In such a regime, the repair of the machine after an unexpected emergency breakdown does not reset the hazard rate. Only a planned overhaul refreshes the hazard rate. This bad-as-old regime is modelled as a non-homogeneous Poisson process. The structure is comprised of a base-line hazard rate, here assumed to be Weibull, plus a covariate structure, since such (covariate) factors are found to influence equipment failure times. The results are compared to similar results¹ when the underlying failure regime is assumed to be good-as-new. The analysis performed here is also compared to a previous analysis² in which the base-line hazard rate was of a non-parametric form. Several tests are presented as well as an examination of the residuals in order to verify the appropriateness of the model chosen.     

Experimental and mathematical modelling of magnetically labelled mesenchymal stromal cell delivery

A key challenge for stem cell therapies is the delivery of therapeutic cells to the repair site. Magnetic targeting has been proposed as a platform for defining clinical sites of delivery more effectively. In this paper, we use a combined in vitro experimental and mathematical modelling approach to explore the magnetic targeting of mesenchymal stromal cells (MSCs) labelled with magnetic nanoparticles using an external magnet. This study aims to (i) demonstrate the potential of magnetic tagging for MSC delivery, (ii) examine the effect of red blood cells (RBCs) on MSC capture efficacy and (iii) highlight how mathematical models can provide both insight into mechanics of therapy and predictions about cell targeting in vivo. In vitro MSCs are cultured with magnetic nanoparticles and circulated with RBCs over an external magnet. Cell capture efficacy is measured for varying magnetic field strengths and RBC percentages. We use a 2D continuum mathematical model to represent the flow of magnetically tagged MSCs with RBCs. Numerical simulations demonstrate qualitative agreement with experimental results showing better capture with stronger magnetic fields and lower levels of RBCs. We additionally exploit the mathematical model to make hypotheses about the role of extravasation and identify future in vitro experiments to quantify this effect.     

Comparison of the binary logistic and skewed logistic (Scobit) models of injury severity in motor vehicle collisions

The binary logistic model has been extensively used to analyze traffic collision and injury data where the outcome of interest has two categories. However, the assumption of a symmetric distribution may not be a desirable property in some cases, especially when there is a significant imbalance in the two categories of outcome. This study compares the standard binary logistic model with the skewed logistic model in two cases in which the symmetry assumption is violated in one but not the other case. The differences in the estimates, and thus the marginal effects obtained, are significant when the assumption of symmetry is violated.     

Identification of composite uncertain material parameters from experimental modal data

Stochastic analysis of structures using probability methods requires the statistical knowledge of uncertain material parameters. This is often quite easier to identify these statistics indirectly from structure response by solving an inverse stochastic problem. In this paper, a robust and efficient inverse stochastic method based on the non-sampling generalized polynomial chaos method is presented for identifying uncertain elastic parameters from experimental modal data. A data set on natural frequencies is collected from experimental modal analysis for sample orthotropic plates. The Pearson model is used to identify the distribution functions of the measured natural frequencies. This realization is then employed to construct the random orthogonal basis for each vibration mode. The uncertain parameters are represented by polynomial chaos expansions with unknown coefficients and the same random orthogonal basis as the vibration modes. The coefficients are identified via a stochastic inverse problem. The results show good agreement with experimental data.     

Hybrid cadaveric/surrogate model of thoracolumbar spine injury due to simulated fall from height

A fall from high height can cause thoracolumbar spine fracture with retropulsion of endplate fragments into the canal leading to neurological deficit. Our objectives were to develop a hybrid cadaveric/surrogate model for producing thoracolumbar spine injury during simulated fall from height, evaluate the feasibility and performance of the model, and compare injuries with those observed clinically. Our model consisted of a 3-vertebra human lumbar specimen (L3–L4–L5) stabilized with muscle force replication and mounted within an impact dummy. The model was subjected to a fall from height of 2.2 m with impact velocity of 6.6 m/s. Kinetic and kinematic time-history responses were determined using spinal and pelvis load cell data and analyses of high-speed video. Injuries to the L4 vertebra were evaluated by fluoroscopy, radiography, and detailed anatomical dissection. Peak compression forces during the fall from height occurred at 7 ms and reached 44.7 kN at the ground, 9.1 kN at the pelvis, and 4.5 kN at the spine. Pelvis acceleration peaks reached 209.9 g at 8 ms for vertical and 62.8 g at 12 ms for rearward. Tensile load peaks were then observed (spine: 657.0 N at 47 ms; pelvis: 569.4 N at 61 ms). T1/pelvis peak flexion of 68.3° occurred at 38 ms as the upper torso translated forward while the pelvis translated rearward. Complete axial burst fracture of the L4 vertebra was observed including endplate comminution, retropulsion of bony fragments into the canal, loss of vertebral body height, and increased interpedicular distance due to fractures anterior to the pedicles and a vertical split fracture of the left lamina. Our dynamic injury model closely replicated the biomechanics of real-life fall from height and produced realistic, clinically relevant burst fracture of the lumbar spine. Our model may be used for further study of thoracolumbar spine injury mechanisms and injury prevention strategies.     

Head injury prediction capability of the HIC, HIP, SIMon and ULP criteria

The objective of the present study is to synthesize and investigate using the same set of sixty-one real-world accidents the human head injury prediction capability of the head injury criterion (HIC) and the head impact power (HIP) based criterion as well as the injury mechanisms related criteria provided by the simulated injury monitor (SIMon) and the Louis Pasteur University (ULP) finite element head models. Each accident has been classified according to whether neurological injuries, subdural haematoma and skull fractures were reported. Furthermore, the accidents were reconstructed experimentally or numerically in order to provide loading conditions such as acceleration fields of the head or initial head impact conditions. Finally, thanks to this large statistical population of head trauma cases, injury risk curves were computed and the corresponding regression quality estimators permitted to check the correlation of the injury criteria with the injury occurrences. As different kinds of accidents were used, i.e. footballer, motorcyclist and pedestrian cases, the case-independency could also be checked. As a result, FE head modeling provides essential information on the intracranial mechanical behavior and, therefore, better injury criteria can be computed. It is clearly shown that moderate and severe neurological injuries can only be distinguished with a criterion that is computed using intracranial variables and not with the sole global head acceleration.     

Effects of work zone presence on injury and non-injury crashes.

Work zones in the United States have approximately 700 traffic-related fatalities, 24,000 injury crashes, and 52,000 non-injury crashes every year. Due to future highway reconstruction needs, work zones are likely to increase in number, duration, and length. This study focuses on analyzing the effect of work zone duration mainly due to its policy-sensitivity. To do so, we created a unique dataset of California freeway work zones that included crash data (crash frequency and injury severity), road inventory data (average daily traffic (ADT) and urban/rural character), and work zone related data (duration, length, and location). Then, we investigated crash rates and crash frequencies in the pre-work zone and during-work zone periods. For the freeway work zones investigated in this study, the total crash rate in the during-work zone period was 21.5% higher (0.79 crashes per million vehicle kilometer (MVKM)) than the pre-work zone period (0.65 crashes per MVKM). Compared with the pre-work zone period, the increase in non-injury and injury crash rates in the during-work zone period was 23.8% and 17.3%, respectively. Next, crash frequencies were investigated using negative binomial models, which showed that frequencies increased with increasing work zone duration, length, and average daily traffic. The important finding is that after controlling for various factors, longer work zone duration significantly increases both injury and non-injury crash frequencies. The implications of the study findings are discussed in the paper.     

Mixed logit analysis of bicyclist injury severity resulting from motor vehicle crashes at intersection and non-intersection locations

Standard multinomial logit (MNL) and mixed logit (MXL) models are developed to estimate the degree of influence that bicyclist, driver, motor vehicle, geometric, environmental, and crash type characteristics have on bicyclist injury severity, classified as property damage only, possible, nonincapacitating or severe (i.e., incapacitating or fatal) injury. This study is based on 10,029 bicycleinvolved crashes that occurred in the State of Ohio from 2002 to 2008. Results of likelihood ratio tests reveal that some of the factors affecting bicyclist injury severity at intersection and non-intersection locations are substantively different and using a common model to jointly estimate impacts on severity at both types of locations may result in biased or inconsistent estimates. Consequently, separate models are developed to independently assess the impacts of various factors on the degree of bicyclist injury severity resulting from crashes at intersection and non-intersection locations.Several covariates are found to have similar impacts on injury severity at both intersection and non-intersection locations. Conversely, six variables were found to significantly influence injury severity at intersection locations but not non-intersection locations while four variables influenced bicyclist injury severity only at non-intersection locations. In crashes occurring at intersection locations, the likelihood of severe bicyclist injury increases by 14.8 percent if the bicyclist is not wearing a helmet, 82.2 percent if the motorist is under the influence of alcohol, 141.3 percent if the crash-involved motor vehicle is a van, 40.6 percent if the motor vehicle strikes the side of the bicycle, and 182.6 percent if the crash occurs on a horizontal curve with a grade. Results from non-intersection locations show the likelihood of severe injuries increases by 374.5 percent if the bicyclist is under the influence of drugs, 150.1 percent if the motorist is under the influence of alcohol, 53.5 percent if the motor vehicle strikes the side of the bicycle and 99.9 percent if the crash-involved motor vehicle is a heavy-duty truck.     

纸杯机典型机构的运动分析及仿真

纸杯机工作过程主要由曲柄摇杆机构完成,为确保其工作可靠和运动平稳,采用理论推导和数值模拟相结合的方法,对其典型机构进行了运动分析,建立了数学模型.分析了滑块的位移、速度及加速度,计算结果与实测值相吻合,证明了数学模型的正确性.并采用运动分析软件分析了纸杯加工组合机构的运动与动态特性,绘制了速度、加速度曲线,为纸杯机设计与改进提供了重要的数据.     

Construction and evaluation of thoracic injury risk curves for a finite element human body model in frontal car crashes

There is a need to improve the protection to the thorax of occupants in frontal car crashes. Finite element human body models are a more detailed representation of humans than anthropomorphic test devices (ATDs). On the other hand, there is no clear consensus on the injury criteria and the thresholds to use with finite element human body models to predict rib fractures. The objective of this study was to establish a set of injury risk curves to predict rib fractures using a modified Total HUman Model for Safety (THUMS). Injury criteria at the global, structural and material levels were computed with a modified THUMS in matched Post Mortem Human Subjects (PMHSs) tests. Finally, the quality of each injury risk curve was determined. For the included PMHS tests and the modified THUMS, DcTHOR and shear stress were the criteria at the global and material levels that reached an acceptable quality. The injury risk curves at the structural level did not reach an acceptable quality.