Objective: Currently, in Turkey, fault rates in traffic accidents are determined according to the initiative of accident experts (no speed analyses of vehicles just considering accident type) and there are no specific quantitative instructions on fault rates related to procession of accidents which just represents the type of collision (side impact, head to head, rear end, etc.) in No. 2918 Turkish Highway Traffic Act (THTA 1983). The aim of this study is to introduce a scientific and systematic approach for determination of fault rates in most frequent property damage–only (PDO) traffic accidents in Turkey.
Methods: In this study, data (police reports, skid marks, deformation, crush depth, etc.) collected from the most frequent and controversial accident types (4 sample vehicle–vehicle scenarios) that consist of PDO were inserted into a reconstruction software called vCrash. Sample real-world scenarios were simulated on the software to generate different vehicle deformations that also correspond to energy-equivalent speed data just before the crash. These values were used to train a multilayer feedforward artificial neural network (MFANN), function fitting neural network (FITNET, a specialized version of MFANN), and generalized regression neural network (GRNN) models within 10-fold cross-validation to predict fault rates without using software. The performance of the artificial neural network (ANN) prediction models was evaluated using mean square error (MSE) and multiple correlation coefficient (R).
Results: It was shown that the MFANN model performed better for predicting fault rates (i.e., lower MSE and higher R) than FITNET and GRNN models for accident scenarios 1, 2, and 3, whereas FITNET performed the best for scenario 4. The FITNET model showed the second best results for prediction for the first 3 scenarios. Because there is no training phase in GRNN, the GRNN model produced results much faster than MFANN and FITNET models. However, the GRNN model had the worst prediction results. The R values for prediction of fault rates were close to 1 for all folds and scenarios.
Conclusions: This study focuses on exhibiting new aspects and scientific approaches for determining fault rates of involvement in most frequent PDO accidents occurring in Turkey by discussing some deficiencies in THTA and without regard to initiative and/or experience of experts. This study yields judicious decisions to be made especially on forensic investigations and events involving insurance companies. Referring to this approach, injury/fatal and/or pedestrian-related accidents may be analyzed as future work by developing new scientific models. 相似文献
To extend the current understanding of the mercury-mediated cytotoxic effect,five neural cell lines established from different animal species were comparatively analyzed using three different endpoint bioassays:thiazolyl blue tetrazolium bromide,3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay(MTT),neutral red uptake assay(NRU),and Coomassie blue assay(CB).Following a 24-hr exposure to selected concentrations of mercury chloride(HgCl_2) and methylmercury(Ⅱ) chloride(MeHgCl),the cytotoxic effect on test cells was characterized by comparing their 50%inhibition concentration(IC_(50)) values.Experimental results indicated that both these forms of mercury were toxic to all the neural cells,but at very different degrees.The IC_(50)values of MeHgCl among these cell lines ranged from 1.15±0.22 to 10.31 ± 0.70 μmol/L while the IC_(50) values for HgCl_2 were much higher,ranging from 6.44 ± 0.36 to 160.97±19.63 μmol/L,indicating the more toxic nature of MeHgCl.The IC_(50) ratio between HgCl_2and MeHgCl ranged from 1.75 to 96.0,which confirms that organic mercury is much more toxic to these neural cells than inorganic mercury.Among these cell lines,HGST-BR and TriG44 derived from marine sea turtles showed a significantly high tolerance to HgCl_2 as compared to the three mammalian neural cells.Among these neural cells,SK-N-SH represented the most sensitive cells to both chemical forms of mercury. 相似文献
ABSTRACTThe Longmen Shan fault area in southwest China is one of the world’s most active earthquake zones. The epicenters of the two most recent earthquakes, the 2008 Wenchuan earthquake (8.0?Ms) and the 2013 Lushan earthquake (7.0?Ms), both of which caused serious losses, were only 85?km apart. Community-based disaster risk reduction is the foundation of the disaster management system pyramid and is critical to the success of ‘sustainable hazard mitigation’. Based on multiple collaborative stakeholder perspectives, this paper examines public participation in an NGO-oriented Community for Disaster Prevention and Mitigation (N-CDPM) in the period between the two earthquakes as a multi-stage problem; N-CDPM establishment, normal operations, disaster testing, and continuous improvement. Multi-stage field research was conducted in the affected areas in the Longmen Shan fault area to examine the collaboration in each stage, after which the differences were compared across the four stages based on eight key indices; scales, core stakeholders, core network stability, mean number of lines, mean collaborative level, governments, and individual and public organization participation. The government participation, individual participation, and public organization participation are then discussed. This paper provides a novel research approach to CDPM in multiple earthquake regions and gives rich insights into the collaboration between the government and the public for N-CDPM. 相似文献