In this study, the concentrations of metals (As, Cd, Co, Cr, Cu, Hg, Ni, Pb, and Zn) were deter-mined in two freshwater fish species. The same fish were also used to determine the content of fatty acids (FA), including saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA). We investigated the species-specific relationship between bioaccumulation of metals and the content of FA. Roach and white bream were caught at two different sites in the Serbian part of the Danube. The measured metal concentrations were below the standard concentrations recommended in the guidelines of the EU and the Republic of Ser-bia. Among the non-essential metals, Ni had the highest concentration, ranging from 0.158 to 0.591 µg g-1. The muscle of the two fish species contained high concentrations of SFA, ranging from 36.31 to 51.79%, and MUFA, ranging from 33.56 to 43.70%. Polyunsaturated fatty acids were represented with the lowest percentage (5.32 - 27.18). Four of the nine metals studied (As, Hg, Ni and Pb) in one fish species and five of the nine metals studied (A, Cu, Ni, Pb and Zn) in the other fish species showed correlations with fatty acid content. These results help to reveal potential biomarkers of metal stress in lipid composition.

Of all the renewable energy sources, solar photovoltaic (PV) power is estimated to be a popular source due to several advantages such as its free availability, absence of rotating parts, integration to building such as rooftops, and less maintenance cost. The nonlinear current-voltage (I–V) characteristics and power generated from a PV array primarily depend on solar insolation/irradiation and panel temperature. The extracted PV output power is influenced by the accuracy with which the nonlinear power–voltage (P–V) characteristic curve is traced by the maximum power point tracking (MPPT) controller. In this paper, a bio-inspired roach infestation optimization (RIO) algorithm is proposed to extract the maximum power from the PV system (PVS). To validate the usefulness of the RIO MPPT algorithm, MATLAB/Simulink simulations are performed under varying environmental conditions, for example, step changes in solar irradiance, and partial shading of the PV array. Furthermore, the search performance of the RIO algorithm is examined on different unconstrained benchmark functions, and it is that realized that the RIO algorithm has improved convergence characteristics in terms of finding the optimal solution than Particle swarm optimization (PSO). The results demonstrated that the RIO-based MPPT performs remarkably in tracking with high accuracy as the PSO-based MPPT.