Ashabul Hoque

In this paper, we introduce a SEIATR compartmental model to analyze and predict the COVID-19 outbreak in the Top 5 affected countries in the world, namely the USA, India, Brazil, France, and Russia. The officially confirmed cases and death due to COVID-19 from the day of the official confirmation to June 30, 2021 are considered for each country. Primarily, we use the data to make a comparison between the cumulative cases and deaths due to COVID-19 among these five different countries. This analysis allows us to infer the key parameters associated with the dynamics of the disease for these five different countries. For example, the analysis reveals that the infection rate is much higher in the USA, Brazil, and France compared to that of India and Russia, while the recovery rate is found almost the same for these countries. Further, the death rate is measured higher in Brazil as opposed to India, where it is found much lower among the remaining countries. We then use the SEIART compartmental model to characterize the first and second waves of these countries, as well as to investigate and identify the influential model parameters and nature of the virus transmissibility in respective countries. Besides estimating the time-dependent reproduction number (Rt) for these countries, we also use the model to predict the peak size and the time occurring peak in respective countries. The analysis demonstrates that COVID-19 was observed to be much more infectious in the second wave than the first wave in all countries except France. The results also demonstrate that the epidemic took off very quickly in the USA, India, and Brazil compared to two other countries considered in this study. Furthermore, the prediction of the epidemic peak size and time produced by our model provides a very good agreement with the officially confirmed cases data for all countries expect Brazil.

This paper is concerned with the deposition of sediment due to dune forests (Nakatajima dune, Japan) and CC block system on a riverbank (Padma, Bangladesh). Measurements of sediment deposition were carried out at Nakatajima dune, Japan and at Padma riverbank, Rajshahi, Bangladesh using Global Positioning System (GPS). 2442 m3 sediment migrates each year to the East side of Nakatajima dune by wind and the edge of the dune develops about 6-7 m/year due to the existence of forests. Sedimentation rate is also greater in shallower mangrove areas. The trapped sediment height varies from 8.0 to 10.0 cm in the mangrove-lined bank. Mangrove forests help to trap 25% more sedimentation at low tide than at high tide. On the other hand, only for setting up the CC block and groynes along the bank, the sedimentation rate is observed almost twice than that of the previous year. An analysis shows that there is a similarity of sedimentation among dune, beach forests, mangrove forests and CC blocks. Journal of Bangladesh Academy of Sciences, Vol. 43, No. 1, 67-78, 2019

Observations on the 2004 tsunami showed that coastal forest vegetation could reduce the impacts of a tsunami or a storm surge in two ways: (i) the well-known wave attenuation and (ii) the protection of coastal areas from storm damage by stabilizing coastal sediments. In this paper, the wave damping performance of mangrove forest of different forest widths is systematically tested in Twin Wave Flumes (without and with the forest model in 1- and 2-m-wide wave flumes, respectively) for both regular and irregular waves. Results reveal that the dissipation coefficient increases with increasing forest width and is strongly related to the transmission coefficient as the contribution of the forest itself to wave reflection is negligibly small. The results also show that an increasing incident wave height causes the transmission coefficient to decrease due to stronger wave breaking. The wave energy dissipation through mangrove forest is also investigated theoretically and demonstrates a good agreement with the experimental results.