Assessment of heavy metals contamination in soils around a mining site in Marrakech region, Morocco.

Mining sites are a permanent toxicological problem for the surrounding ecosystems and human health. In the present study we investigate the accumulation of heavy metals in agricultural soils collected from the surrounding area of a mining site of Marrakech (Morocco). The occurrence of heavy metals in field soils was, in a decreasing order, Zn > Cu > Pb and Cd. Concentrations of the heavy metals were higher in the studied soils compared to the control soil. Based on the geoaccumulation index (GeoI) and the contamination factor (CF), the contamination degree can be defined as slightly contaminated for Pb and Zn, highly contaminated for Cd and moderately contaminated for Cu. With respect to the pollution load index (PLI) the metal levels exceed local and regional background concentrations indicating contamination sufficiently high to attract attention and to pose risk to the ecosystem. Heavy metals are persistent in the environment and are subject to bioaccumulation in food chains and therefore pose substantial health risks for human and animal.

A model for considering effects of extremely low frequency electromagnetic fields on quail embryonic cells

Previous experiments have shown that extremely low frequency electromagnetic fields could cause serious effects on the evolution of cells. We propose a mathematical model which confirms those results. In our model, electromagnetic waves could cause the motions of ions and charges and the emergence of some currents around and in the interior of cells. These currents produce some waves which interact with the DNAs and remove or attach some repressors. Consequently, some genes could be turned on or off, and cells could obtain some properties or lose them. The frequency of the external waves should be close to the frequency of the exchanged waves between the repressors and DNAs or even bigger than them. We test this idea and did some experiments on quail embryonic cells. We connected a sample of these cells to a battery and considered their evolution. We observed that after connecting the battery and the production of electrical current, some rings around the quail embryonic cells emerged. Maybe, these rings are the response of the cells to changes in electromagnetic waves and electrical currents

Meta-heuristic optimization methods applied to renewable distributed generation planning: A review

Due to its proven efficiency and computational speed, the most recent developed meta-heuristic optimization methods are widely used to better integrate renewable distributed generation (RDG) into the electricity grid. The main objective of this paper is to obtain a better knowledge of current trends in meta-heuristics applied to optimally integrate RDGs to the distribution network. This is a review of well known meta-heuristic approaches, used to solve the problem of optimal renewable distributed generation allocation planning (ORDGAP). In this context, some research gaps were mentioned, and recommendations were proposed to expand the scope of research in this field

Power efficiency improvement in reactive power dispatch under load uncertainty

Nowadays, there is a significant rise in electricity demand, posing challenges for power grid operators due to inaccurate forecasting, leading to excessive power losses and voltage instability. This paper addresses these issues by focusing on solving optimal reactive power dispatch (ORPD) while considering load demand uncertainty. The main objective of solving ORPD is to reduce power losses by adjusting generator voltage ratings, transformer tap ratio, and shunt capacitors' reactive power. Monte Carlo simulation (MCS) is employed to generate load scenarios using the normal probability density function, while a reduction-based technique is implemented to decrease the number of those scenarios. The improved gray wolf optimization (I-GWO) algorithm is introduced for the first time to address the stochastic ORPD problem. Experimentation is conducted on an IEEE-30 bus system when results are contrasted with conventional gray wolf optimization (GWO) and five other algorithms as stated in the literature. The I-GWO algorithm's performance is assessed with and without considering load demand uncertainty. Through Friedman's statistical tests, a significant decrease of 20.96% in active power losses and 63.06% in the summation of expected power losses is observed. The I-GWO algorithm's results on the ORPD problem demonstrate its effectiveness and robustness

Nanocomposite Fiber Based on Natural Material for Water Disinfection under Visible Light Irradiation

In the last decade, pathogenic bacteria and organic micropollutants have become a major issue in the water purification process. Heterogeneous photocatalysis is a low-cost and an ecofriendly process, which provides a sustainable solution for water treatment and its utilization in rural areas. In this context, we studied the generation and the surface engineering of polyacrylonitrile (PAN)/goethite composite nanofibers for photocatalytic water remediation under visible-light illumination. The photocatalytic activity was evaluated for dye (methylene blue) degradation and bacteria inactivation, as contaminant models, of the composite nanofibers. The PAN/goethite nanofibers were elaborated by an electrospinning technique, and the morphology and the composition, before and after spin coating, were investigated by Scanning Electron Microscopy (SEM) and Energy Dispersive X-Ray (EDX). The results showed partially intercalated structures of the PAN/goethite Composite-nano-fiber (CNF) were identified by SEM and EDX analysis. The composite nanofibers exhibited high photoefficiency upon dye bleaching (only 10% left after 5 h of illumination) and bacterial deactivation Escherichia coli and Clostridium perfringens (4.4- and 3.5-fold, respectively, in less than 5 h). The steadiness and pliancy of the generated nanofibers provide a promising application in the continuous flow system