Stamenkovic L.J.,University of Belgrade |
Antanasijevic D.Z.,Karnegijeva 4 |
Ristic M..,University of Belgrade |
Peric-Grujic A.A.,University of Belgrade |
Pocajt V.V.,University of Belgrade
Environmental Science and Pollution Research | Year: 2015
Ammonia emissions at the national level are frequently estimated by applying the emission inventory approach, which includes the use of emission factors, which are difficult and expensive to determine. Emission factors are therefore the subject of estimation, and as such they contribute to inherent uncertainties in the estimation of ammonia emissions. This paper presents an alternative approach for the prediction of ammonia emissions at the national level based on artificial neural networks and broadly available sustainability and economical/agricultural indicators as model inputs. The Multilayer Perceptron (MLP) architecture was optimized using a trial-and-error procedure, including the number of hidden neurons, activation function, and a back-propagation algorithm. Principal component analysis (PCA) was applied to reduce mutual correlation between the inputs. The obtained results demonstrate that the MLP model created using the PCA transformed inputs (PCA-MLP) provides a more accurate prediction than the MLP model based on the original inputs. In the validation stage, the MLP and PCA-MLP models were tested for ammonia emission predictions for up to 2 years and compared with a principal component regression model. Among the three models, the PCA-MLP demonstrated the best performance, providing predictions for the USA and the majority of EU countries with a relative error of less than 20 %. © 2015, Springer-Verlag Berlin Heidelberg.
Kostic D.,Karnegijeva 4 |
Vidovic S.,University of Belgrade |
Obradovic B.,University of Belgrade
Journal of Nanoparticle Research | Year: 2016
A stepwise experimental and mathematical modeling approach was used to assess silver release from nanocomposite Ag/alginate microbeads in wet and dried forms into water and into normal saline solution chosen as a simplified model for certain biological fluids (e.g., blood plasma, wound exudates, sweat, etc). Three phenomena were connected and mathematically described: diffusion of silver nanoparticles (AgNPs) within the alginate hydrogel, AgNP oxidation/dissolution and reaction with chloride ions, and diffusion of the resultant silver-chloride species. Mathematical modeling results agreed well with the experimental data with the AgNP diffusion coefficient estimated as 1.3 × 10−18 m2 s−1, while the first-order kinetic rate constant of AgNP oxidation/dissolution and diffusivity of silver-chloride species were shown to be inversely related. In specific, rapid rehydration and swelling of dry Ag/alginate microbeads induced fast AgNP oxidation/dissolution reaction with Cl− and AgCl precipitation within the microbeads with the lowest diffusivity of silver-chloride species compared to wet microbeads in normal saline. The proposed mathematical model provided an insight into the phenomena related to silver release from nanocomposite Ca-alginate hydrogels relevant for use of antimicrobial devices and established, at the same time, a basis for further in-depth studies of AgNP interactions in hydrogels in the presence of chloride ions. © 2016, Springer Science+Business Media Dordrecht.
Deljanin I.,Karnegijeva 4 |
Antanasijevic D.,Karnegijeva 4 |
Urosevic M.A.,University of Belgrade |
Tomasevic M.,University of Belgrade |
And 2 more authors.
Environmental Monitoring and Assessment | Year: 2015
To compare the applicability of the leaves of horse chestnut (Aesculus hippocastanum) and linden (Tilia spp.) as biomonitors of trace element concentrations, a coupled approach of one- and two-dimensional Kohonen networks was applied for the first time. The self-organizing networks (SONs) and the self-organizing maps (SOMs) were applied on the database obtained for the element accumulation (Cr, Fe, Ni, Cu, Zn, Pb, V, As, Cd) and the SOM for the Pb isotopes in the leaves for a multiyear period (2002–2006). A. hippocastanum seems to be a more appropriate biomonitor since it showed more consistent results in the analysis of trace elements and Pb isotopes. The SOM proved to be a suitable and sensitive tool for assessing differences in trace element concentrations and for the Pb isotopic composition in leaves of different species. In addition, the SON provided more clear data on seasonal and temporal accumulation of trace elements in the leaves and could be recommended complementary to the SOM analysis of trace elements in biomonitoring studies. © 2015, Springer International Publishing Switzerland.