Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.     

Periphyton Developed on Artificial Substrates: Effect of Substrate Type and Incubation Depth

The aim of this study was to assess the effect of substrate type and incubation depth on periphyton that had developed on artificial substrates. Uniform rectangular tiles made out of artificial substrates: glass, ceramic, willow tree and yew tree, were fixed on a floating buoy and deployed at three different depths in a photic zone of the Sava Lake (Belgrade, Serbia). Non-taxonomic attributes in the developed biofilm were estimated week-by-week from the start of the experiment in July, until its end in September 2014. Through assessment of substrate type and depth of incubation effect we concluded that these parameters for the fact influence periphyton development and composition. Glass was preferred by autotrophic component over ceramic and wooden substrates. In general, substrate type effect was diminished by increasing incubation depth. When non-taxonomic parameters are to be used in biomonitoring studies, our results suggest that glass substrate and shallow layer of water column (up to 50 cm) for incubation should be preferred.     

The assessment and prediction of temporal variations in surface water quality—a case study

In order to optimize the processes of sampling, monitoring, and management, the initial aim of this paper was to develop a model for the definition and prediction of temporal changes of water quality. In the case of the Morava River Basin (Serbia), the patterns of temporal changes have been recognized by applying different multivariate statistical techniques. The results of the conducted cluster analysis are the indicators of the existence of the three monitoring periods: the low-water, transitional, and high-water periods, which is in accordance with changes in the water flow in the analyzed river basin. A possibility of reducing the initial data set and recognizing the main pollution sources was examined by carrying out the principal component/factor analysis. The results indicate that the natural factor has a dominant influence in temporal groups. In order to recognize the discriminatory water quality parameters, a discriminant analysis (DA) was carried out. Conducting the DA enabled a significant reduction in the data set by the extraction of two parameters (the water temperature and electrical conductivity). Furthermore, the artificial neural network technique was used for testing the possibility of predicting changes in the values of the discriminant factors in the monitoring periods. The reliability of this method for the prediction of temporal variations of both extracted parameters within all temporal clusters has been proven.     

Malondialdehyde concentrations in the intestine and gills of Vardar chub (Squalius vardarensis Karaman) as indicator of lipid peroxidation

Environmental Science and Pollution Research - A lipid peroxidation product, malondialdehyde (MDA), was studied in Vardar chub (Squalius vardarensis Karaman) as an indicator of oxidative stress,...     

Water reclamation during drinking water treatments using polyamide nanofiltration membranes on a pilot scale

The aim of this study was to investigate the performances of polyamide nanofiltration membranes during water reclamation. The study was conducted using nanofiltration concentrates obtained from two different nanofiltration drinking water treatment plants placed in the northern part of Serbia (Kikinda and Zrenjanin). Used nanofiltration concentrates contained high concentrations of arsenic (45 and 451 μg/L) and natural organic matter (43.1 and 224.40 mgKMnO₄/L). Performances of polyamide nanofiltration membranes during water reclamation were investigated under various fluxes and transmembrane pressures in order to obtain drinking water from nanofiltration concentrates and, therefore, reduce the amount of produced concentrates and minimize the waste that has to be discharged in the environment. Applied polyamide nanofiltration membranes showed better removal efficiency during water reclamation when the concentrate with higher content of arsenic and natural organic matter was used while the obtained permeates were in accordance with European regulations. This study showed that total concentrate yield can be reduced to ~5 % of the optimum flux value, in both experiments. The obtained result for concentrate yield under the optimum flux presents considerable amount of reclaimed drinking water and valuable reduced quantity of produced wastewater.