Assessment of heavy metals concentration in water and Tengra fish (Mystus vittatus) of Surma River in Sylhet region of Bangladesh

The study was carried out to assess the concentration of heavy metals in water and Tengra fish (Mystus vittatus) of the Surma River, the largest water basin ecosystem covering the north-eastern parts of Bangladesh. Water and Tengra fish (M. vittatus) samples were collected from a total of six sampling stations in which three sampling stations were in Sylhet district and the rest three were in Sunamganj district. Samples were collected from February 2017 to June 2017 on a monthly basis. Water and Tengra fish (M. vittatus) samples were analyzed for the detection of heavy metals viz., lead (Pb), chromium (Cr) and cadmium (Cd) concentrations. Atomic absorption spectrophotometry was used for the detection of heavy metals after digestion of the samples. Pb and Cr were detected from both water and Tengra fish (M. vittatus) samples collected from all the six sampling stations of Sylhet and Sunamganj district. But, Cd was not found both in water and Tengra fish (M. vittatus) during the study period. This study concluded that the detected concentrations of metals (Pb and Cr) in the studied Tengra fish (M. vittatus) muscles were accepted by the international legislation limits and are safe for human consumption. But in water, Pb is the only metal that potentially poses the ecological risk to the water body as it exceeds the acceptance level recommended by World Health Organization (WHO). Consequently, close monitoring of metals pollution of the Surma River is recommended with a view to minimizing the health risk of the population that depend on the river for their water and fish supply

An Experience Oriented-Convergence Improved Gravitational Search Algorithm for Minimum Variance Distortionless Response Beamforming Optimum

<div><p>An experience oriented-convergence improved gravitational search algorithm (ECGSA) based on two new modifications, searching through the best experiments and using of a dynamic gravitational damping coefficient (<i>α</i>), is introduced in this paper. ECGSA saves its best fitness function evaluations and uses those as the agents’ positions in searching process. In this way, the optimal found trajectories are retained and the search starts from these trajectories, which allow the algorithm to avoid the local optimums. Also, the agents can move faster in search space to obtain better exploration during the first stage of the searching process and they can converge rapidly to the optimal solution at the final stage of the search process by means of the proposed dynamic gravitational damping coefficient. The performance of ECGSA has been evaluated by applying it to eight standard benchmark functions along with six complicated composite test functions. It is also applied to adaptive beamforming problem as a practical issue to improve the weight vectors computed by minimum variance distortionless response (MVDR) beamforming technique. The results of implementation of the proposed algorithm are compared with some well-known heuristic methods and verified the proposed method in both reaching to optimal solutions and robustness.</p></div

Comparison of weight vectors for conventional MVDR, PSO-MVDR, GSA-MVDR, SLGSA-MVDR [28] and ECGSA-MVDR for user at 0° and interferences at 30°and 50°.

<p>Comparison of weight vectors for conventional MVDR, PSO-MVDR, GSA-MVDR, SLGSA-MVDR [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156749#pone.0156749.ref028" target="_blank">28</a>] and ECGSA-MVDR for user at 0° and interferences at 30°and 50°.</p

The variations of the proposed <i>α(t)</i> along with <i>G(t)</i>.

<p>The variations of the proposed <i>α(t)</i> along with <i>G(t)</i>.</p

Multimodal benchmark functions.

<p>Multimodal benchmark functions.</p

The simplified flowchart of ECGSA beamforming.

<p>The simplified flowchart of ECGSA beamforming.</p

Comparison of <i>SINR</i> calculation for conventional MVDR, PSO-MVDR, GSA-MVDR, SLGSA-MVDR [28] and ECGSA-MVDR for user at 0° and interference at 30°.

<p>Comparison of <i>SINR</i> calculation for conventional MVDR, PSO-MVDR, GSA-MVDR, SLGSA-MVDR [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156749#pone.0156749.ref028" target="_blank">28</a>] and ECGSA-MVDR for user at 0° and interference at 30°.</p

Comparison of performance of power response with 100 iterations for user at 0°with two interferences at 30° and 50°.

<p>(a) MVDR, (b) PSO-MVDR, (c) GSA-MVDR, (d) SLGSA-MVDR [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156749#pone.0156749.ref028" target="_blank">28</a>] and (e) ECGAS-MVDR.</p

Composition tests functions.

<p>Composition tests functions.</p