An investigation on multi-vehicle motorcycle crashes using log-linear models

Motorcyclists are the most crash-prone road-user group in many Asian countries including Singapore; however, factors influencing motorcycle crashes are still not well understood. This study examines the effects of various roadway characteristics, traffic control measures and environmental factors on motorcycle crashes at different location types including expressways and intersections. Using techniques of categorical data analysis, this study has developed a set of log-linear models to investigate multi-vehicle motorcycle crashes in Singapore. Motorcycle crash risks in different circumstances have been calculated after controlling for the exposure estimated by the induced exposure technique. Results show that night-time influence increases crash risks of motorcycles particularly during merging and diverging manoeuvres on expressways, and turning manoeuvres at intersections. Riders appear to exercise more care while riding on wet road surfaces particularly during night. Many hazardous interactions at intersections tend to be related to the failure of drivers to notice a motorcycle as well as to judge correctly the speed/distance of an oncoming motorcycle. Road side conflicts due to stopping/waiting vehicles and interactions with opposing traffic on undivided roads have been found to be as detrimental factors on motorcycle safety along arterial, main and local roads away from intersections. Based on the findings of this study, several targeted countermeasures in the form of legislations, rider training, and safety awareness programmes have been recommended.

Correlation of carotid atheromatous plaque inflammation with biomechanical stress: Utility of USPIO enhanced MR imaging and finite element analysis

Objective: The aim of this study was to explore whether there is a relationship between the degree of MR-defined inflammation using ultra small super-paramagnetic iron oxide (USPIO) particles, and biomechanical stress using finite element analysis (FEA) techniques, in carotid atheromatous plaques. Methods and Results: 18 patients with angiographically proven carotid stenoses underwent multi-sequence MR imaging before and 36 h after USPIO infusion. T2 * weighted images were manually segmented into quadrants and the signal change in each quadrant normalised to adjacent muscle was calculated after USPIO administration. Plaque geometry was obtained from the rest of the multi-sequence dataset and used within a FEA model to predict maximal stress concentration within each slice. Subsequently, a new statistical model was developed to explicitly investigate the form of the relationship between biomechanical stress and signal change. The Spearman's rank correlation coefficient for USPIO enhanced signal change and maximal biomechanical stress was -0.60 (p = 0.009). Conclusions: There is an association between biomechanical stress and USPIO enhanced MR-defined inflammation within carotid atheroma, both known risk factors for plaque vulnerability. This underlines the complex interaction between physiological processes and biomechanical mechanisms in the development of carotid atheroma. However, this is preliminary data that will need validation in a larger cohort of patients.

Assessment of inflammatory burden contralateral to the symptomatic carotid stenosis using high-resolution ultrasmall, superparamagnetic iron oxide-enhanced MRI

BACKGROUND AND PURPOSE It is well known that the vulnerable atheromatous plaque has a thin, fibrous cap and large lipid core with associated inflammation. This inflammation can be detected on MRI with use of a contrast medium, Sinerem, an ultrasmall superparamagnetic iron oxide (USPIO). Although the incidence of macrophage activity in asymptomatic disease appears low, we aimed to explore the incidence of MRI-defined inflammation in asymptomatic plaques in patients with known contralateral symptomatic disease. METHODS Twenty symptomatic patients underwent multisequence MRI before and 36 hours after USPIO infusion. Images were manually segmented into quadrants, and the signal change in each quadrant was calculated after USPIO administration. A mixed mathematical model was developed to compare the mean signal change across all quadrants in the 2 groups. Patients had a mean symptomatic stenosis of 77% compared with 46% on their asymptomatic side, as measured by conventional angiography. RESULTS There were 11 (55%) men, and the median age was 72 years (range, 53 to 84 years). All patients had risk factors consistent with severe atherosclerotic disease. All symptomatic carotid stenoses had inflammation, as evaluated by USPIO-enhanced imaging. On the contralateral sides, inflammatory activity was found in 19 (95%) patients. Contralaterally, there were 163 quadrants (57%) with a signal loss after USPIO when compared with 217 quadrants (71%) on the symptomatic side (P=0.007). CONCLUSIONS - This study adds weight to the argument that atherosclerosis is a truly systemic disease. It suggests that investigation of the contralateral side in patients with symptomatic carotid stenosis can demonstrate inflammation in 95% of plaques, despite a mean stenosis of only 46%. Thus, inflammatory activity may be a significant risk factor in asymptomatic disease in patients who have known contralateral symptomatic disease. Patients with symptomatic carotid disease should have their contralateral carotid artery followed up.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

Determinants of self-reported smoking and misclassification during pregnancy, and analysis of optimal cut-off points for urinary cotinine: a cross-sectional study

10 p.

Avaliação do efeito de duas técnicas de instrumentação na zona de risco de molares inferiores curvos por microtomografia computadorizada e análise de imagens

O objetivo deste estudo foi avaliar a espessura mínima radicular remanescente e o desgaste porcentual do terço cervical em raízes mesiais de molares inferiores, após a instrumentação com as técnicas ProTaper Universal e Lima única F2. Foram obtidos 100 primeiros molares inferiores com raízes completamente separadas. Desse total, foram selecionados e incluídos no estudo somente 22 que possuíam dois canais distintos na raiz mesial, comprimento entre 20 e 22 mm e grau de curvatura da raiz mesial com angulação variando entre 10 e 20. Destes, 8 foram eliminados por possuírem uma anatomia muito discrepante, o que limitava o processamento e análise digital das imagens (PADI). Os dentes foram acessados e a patência apical foi realizada em todos os canais determinando o comprimento de trabalho. Em cada dente, cada canal mesial foi instrumentado por uma técnica diferente. As amostras foram posicionadas em um dispositivo de montagem e digitalizadas através de microtomografia computadorizada antes e depois de serem completamente instrumentadas. O volume de interesse, correspondente à região de zona de risco, com uma grande margem de tolerância, tanto em direção apical quanto em direção cervical, foi determinado por 234 fatias, totalizando um comprimento vertical de 3,5 mm, para avaliação quantitativa comparativa. Através de PADI mediu-se, de forma automática, a espessura mínima radicular nos dois canais mesiais, antes e após a instrumentação, para todas as fatias de todos os dentes. A partir destes dados foi calculado o desgaste porcentual. Após o tratamento estatístico das mais de 6500 medidas obtidas, pôde-se concluir que não existiu diferença no desgaste da zona de risco produzido pelas duas técnicas de instrumentação testadas. Em todos os casos a espessura radicular remanescente permaneceu dentro de uma margem de segurança, não havendo, portanto, nenhum caso de rasgo ou perfuração. Dessa forma, ambas as técnicas estudadas foram consideradas seguras quanto ao desgaste da zona de risco da raiz mesial dos molares inferiores.