Computational modeling and analysis of thoracolumbar spine fractures in frontal crash reconstruction

Abstract

Objective: This study aimed to reconstruct 11 motor vehicle crashes (6 with thoracolumbar fractures and 5 without thoracolumbar fractures) and analyze the fracture mechanism, fracture predictors, and associated parameters affecting thoracolumbar spine response.

Methods: Eleven frontal crashes were reconstructed with a finite element simplified vehicle model (SVM). The SVM was tuned to each case vehicle and the Total HUman Model for Safety (THUMS) Ver. 4.01 was scaled and positioned in a baseline configuration to mimic the documented precrash driver posture. The event data recorder crash pulse was applied as a boundary condition. For the 6 thoracolumbar fracture cases, 120 simulations to quantify uncertainty and response variation were performed using a Latin hypercube design of experiments (DOE) to vary seat track position, seatback angle, steering column angle, steering column position, and D-ring height. Vertebral loads and bending moments were analyzed, and lumbar spine indices (unadjusted and age-adjusted) were developed to quantify the combined loading effect. Maximum principal strain and stress data were collected in the vertebral cortical and trabecular bone. DOE data were fit to regression models to examine occupant positioning and thoracolumbar response correlations.

Results: Of the 11 cases, both the vertebral compression force and bending moment progressively increased from superior to inferior vertebrae. Two thoracic spine fracture cases had higher average compression force and bending moment across all thoracic vertebral levels, compared to 9 cases without thoracic spine fractures (force: 1,200.6 vs. 640.8 N; moment: 13.7 vs. 9.2?Nm). Though there was no apparent difference in bending moment at the L1–L2 vertebrae, lumbar fracture cases exhibited higher vertebral bending moments in L3–L4 (fracture/nonfracture: 45.7 vs. 33.8?Nm). The unadjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 9 of the 11 cases (sensitivity?=?1.0; specificity?=?0.6). The age-adjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 10 of the 11 cases (sensitivity?=?1.0; specificity?=?0.8). The age-adjusted principal stress in the trabecular bone was an excellent indicator of fracture occurrence (sensitivity?=?1.0; specificity?=?1.0). A rearward seat track position and reclined seatback increased the thoracic spine bending moment by 111–329%. A more reclined seatback increased the lumbar force and bending moment by 16–165% and 67–172%, respectively.

Conclusions: This study provided a computational framework for assessing thoracolumbar fractures and also quantified the effect of precrash driver posture on thoracolumbar response. Results aid in the evaluation of motor vehicle crash–induced vertebral fractures and the understanding of factors contributing to fracture risk.     

Relationship between the ATP content of subsurface material and the rate of biodegradation of alkylbenzenes and chlorobenzene

The rate of biotransformation of toluene in unconsolidated subsurface material from sites at Lula, Oklahoma, and Conroe, Texas, was compared to the ATP (adenosine triphosphate) content of these materials. The rate of toluene degradation decreased with decreasing ATP content. When ATP contents were at or less than 0.05 ng g⁻¹, biotransformation of toluene could not be detected (less than 1% of the initial concentration was degraded per week). At intermediate concentrations of ATP, 0.37 and 0.16 ngvg⁻¹, the rates of toluene degradation were 18 ± 4.5% and 25 ± 10% of the initial concentration per week. At ATP concentrations above 1 ng g⁻¹, the rates of toluene degradation exceeded 90% of the initial concentration per week. There was no simple relationship between ATP content and chlorobenzene degradation. Subsurface material that had been exposed to creosote wastes, and which degraded toluene rapidly, also degraded benzene, o-xylene, and m-xylene.     

Golden Eagle fatalities and the continental‐scale consequences of local wind‐energy generation

Renewable energy production is expanding rapidly despite mostly unknown environmental effects on wildlife and habitats. We used genetic and stable isotope data collected from Golden Eagles (Aquila chrysaetos) killed at the Altamont Pass Wind Resource Area (APWRA) in California in demographic models to test hypotheses about the geographic extent and demographic consequences of fatalities caused by renewable energy facilities. Geospatial analyses of δ²H values obtained from feathers showed that ≥25% of these APWRA‐killed eagles were recent immigrants to the population, most from long distances away (>100 km). Data from nuclear genes indicated this subset of immigrant eagles was genetically similar to birds identified as locals from the δ²H data. Demographic models implied that in the face of this mortality, the apparent stability of the local Golden Eagle population was maintained by continental‐scale immigration. These analyses demonstrate that ecosystem management decisions concerning the effects of local‐scale renewable energy can have continental‐scale consequences.     

Echolocation signals of the bat Eptesicus serotinus recorded using a vertical microphone array: effect of flight altitude on searching signals

The acoustic behaviour of Eptesicus serotinus was investigated in the field using a 13.5-m vertical, linear microphone array that allowed for simultaneous recordings at three different heights and for the calculation of flight altitude and distance from the array. Recordings were made at two locations that differed in bat species diversity. E. serotinus hunted on average at an altitude of 10.7 m (±2.7) at one location and 6.8 m (±3.6) at the other location. Search signals were 5–17 ms long depending on flight altitude, and consisted of two to three frequency-modulated harmonics. For bats flying below 8–10 m altitude, signal duration decreased with decreasing flight altitude, whereas signal interval, terminal frequency, peak frequency and frequency range of the first harmonic increased. Above 8–10 m flight altitude, the signal parameters were fairly constant. The –10 dB bandwidth and duty cycle did not change with flight altitude. Source levels were calculated to between 121 and 125 dB peSPL re 20 μPa at 10 cm. For bats flying higher than 9 m, the microphone placed 1.5 m above the ground recorded significantly reduced signal durations and frequency ranges of the first harmonic compared to the same signals recorded with the microphones at heights of 7 or 15 m. We caution the use of ground recordings to fully describe the echolocation signals of high-flying bats. We demonstrate that flight altitude significantly influences the structure of sonar signals from E. serotinus. Received: 17 May 1999 / Received in revised form: 20 September 1999 / Accepted: 25 September 1999     

Nitrous oxide emissions from a Northern Great Plains soil as influenced by nitrogen management and cropping systems

Field measurements of N2O emissions from soils are limited for cropping systems in the semiarid northern Great Plains (NGP). The objectives were to develop N2O emission-time profiles for cropping systems in the semiarid NGP, define important periods of loss, determine the impact of best management practices on N2O losses, and estimate direct N fertilizer-induced emissions (FIE). No-till (NT) wheat (Triticum Aestivum L.)-fallow, wheat-wheat, and wheat-pea (Pisum sativum), and conventional till (CT) wheat-fallow, all with three N regimes (200 and 100 kg N ha(-1) available N, unfertilized control); plus a perennial grass-alfalfa (Medicago sativa L.) system were sampled over 2 yr using vented chambers. Cumulative 2-yr N2O emissions were modest in contrast to reports from more humid regions. Greatest N2O flux activity occurred following urea-N fertilization (10-wk) and during freeze-thaw cycles. Together these periods comprised up to 84% of the 2-yr total. Nitrification was probably the dominant process responsible for N2O emissions during the post-N fertilization period, while denitrification was more important during freeze-thaw cycles. Cumulative 2-yr N2O-N losses from fertilized regimes were greater for wheat-wheat (1.31 kg N ha(-1)) than wheat-fallow (CT and NT) (0.48 kg N ha(-1)), and wheat-pea (0.71 kg N ha(-1)) due to an additional N fertilization event. Cumulative losses from unfertilized cropping systems were not different from perennial grass-alfalfa (0.28 kg N ha(-1)). Tillage did not affect N2O losses for the wheat-fallow systems. Mean FIE level was equivalent to 0.26% of applied N, and considerably below the Intergovernmental Panel on Climate Change mean default value (1.25%).     

First-trimester maternal serum alpha-fetoprotein and human chorionic gonadotropin screening for chromosome defects

The aim of this study was to determine the efficacy of combined maternal serum alpha-fetoprotein (MSAFP) and maternal serum human chorionic gonadotropin (MShCG) screening in detecting chromosome defects in the first trimester of pregnancy. Sera of 492 women (previously assayed for MSAFP) were analysed for MShCG under code without knowledge of cytogenetic results. Overall, 48 of 492 patients (9·8 per cent) had either an MSAFP multiple of the median ⩽0·5 or an MShCG β/a z ratio multiple of the median ⩽ 0·25, eight of whom had a fetus with a serious chromosome defect. A third of fetuses with Down' s syndrome and 83 per cent with trisomy 18 were detected at a potential‘cost’ of providing chorionic villus sampling or amniocentesis in 8·6 percent of women screened.     

Adaptive introgression as a resource for management and genetic conservation in a changing climate

Current rates of climate change require organisms to respond through migration, phenotypic plasticity, or genetic changes via adaptation. We focused on questions regarding species’ and populations’ ability to respond to climate change through adaptation. Specifically, the role adaptive introgression, movement of genetic material from the genome of 1 species into the genome of another through repeated interbreeding, may play in increasing species’ ability to respond to a changing climate. Such interspecific gene flow may mediate extinction risk or consequences of limited adaptive potential that result from standing genetic variation and mutation alone, enabling a quicker demographic recovery in response to changing environments. Despite the near dismissal of the potential benefits of hybridization by conservation practitioners, we examined a number of case studies across different taxa that suggest gene flow between sympatric or parapatric sister species or within species that exhibit strong ecotypic differentiation may represent an underutilized management option to conserve evolutionary potential in a changing environment. This will be particularly true where advanced‐generation hybrids exhibit adaptive traits outside the parental phenotypic range, a phenomenon known as transgressive segregation. The ideas presented in this essay are meant to provoke discussion regarding how we maintain evolutionary potential, the conservation value of natural hybrid zones, and consideration of their important role in adaptation to climate.     

Streamflow Forecasting Using Singular Value Decomposition and Support Vector Machine for the Upper Rio Grande River Basin

The current study improves streamflow forecast lead‐time by coupling climate information in a data‐driven modeling framework. The spatial–temporal correlation between streamflow and oceanic–atmospheric variability represented by sea surface temperature (SST), 500‐mbar geopotential height (Z₅₀₀), 500‐mbar specific humidity (SH₅₀₀), and 500‐mbar east–west wind (U₅₀₀) of the Pacific and the Atlantic Ocean is obtained through singular value decomposition (SVD). SVD significant regions are weighted using a nonparametric method and utilized as input in a support vector machine (SVM) framework. The Upper Rio Grande River Basin (URGRB) is selected to test the applicability of the proposed model for the period of 1965–2014. The April–August streamflow volume is forecasted using previous year climate variability, creating a lagged relationship of 1–13 months. SVD results showed the streamflow variability was better explained by SST and U₅₀₀ as compared to Z₅₀₀ and SH₅₀₀. The SVM model showed satisfactory forecasting ability with best results achieved using a one‐month lead to forecast the following four‐month period. Overall, the SVM results showed excellent predictive ability with average correlation coefficient of 0.89 and Nash–Sutcliffe efficiency of 0.79. This study contributes toward identifying new SVD significant regions and improving streamflow forecast lead‐time of the URGRB.