The unusual situation that arose due to the COVID-19 pandemic and the 65-day fishing ban (national policy to boost depleted fish stocks) affected the lower-income fishing communities in coastal Bangladesh. Shocks and stresses were posed, and community people adopted strategies to adapt to the changes. In the process of adaptation, social-ecological systems resilience at different levels plays a crucial role. Though resilience is acknowledged as multilevel feature, studies on the interaction between the levels while understanding communities’ responses to shock and stress are limited. Thus, in this study, we explored the shocks and stresses the fishing community faced and their views on the resilience feature at different levels (i.e., individual, household, and community level) in coastal Bangladesh during the COVID-19 pandemic and 65-day fishing ban period. The study found that the most resilience promoting features (e.g., diversified livelihood, friendship, and network of supports) were adopted at the individual and household levels. However, positive and negative interactions were explored between resilience features at all levels. Low community-level resilience was not translated into a lack of household-level resilience, and strong individual-level resilience did not mean high household-level resilience. It was noted that the increased resilience of a particular individual or household could negatively affect community resilience. Resilience features showed inconsistent interactions within or among the three levels’ resilience features. The study also revealed that multilevel resilience features stressed the importance of combining persistence (i.e., keeping fishing as the main livelihood) and adaptation process (e.g., livelihood diversification). The study showcases the importance of considering multilevel resilience that offers insight into crucial resilience factors which would not be evident if only one level were studied. The overall finding of this study will contribute to framing governance strategies to ensure sustainable coastal management even in the time of any abrupt or expected changes, such as the COVID-19 pandemic and the fishing ban policy.

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In microalgae based biofuel technology, the light is one of the important factors for the proper growth of microalgae cells as microalgae is a photosynthetic microorganism. For a large scale outdoor culture the irradiance of sunlight and associated temperature is also need to consider. In this study aims to present computational model of microalgae growth taking effect of solar irradiance and corresponding temperature in a tubular photo bioreactor for an outdoor culture system. We consider the transient behavior of temperature inside the photo bioreactor for a microalgae culture. The optimum range of temperature for outdoor cultivation of microalgae is about 22˚C -27˚C and out of this range the microalgae cell growth inhibits. Many correlations have already been established to investigate the algal productivity based on the dynamic conditions of temperature in case of full scale outdoor cultivation. However, none of them are validated yet numerically considering the model as a function of weather conditions, operational behavior and design criteria. A tubular photobioreactor (PBR) with length 20.5 m and radius 0.05 m has taken account as a simulation model. The PBR is horizontally placed as temperature variations can be observed with greater accuracy. As the solar irradiance varies at any geographic latitude for a year and so thus temperature, equations and parameters are established relating the irradiance with the temperature to simulate the effect. We observed some significant effects of temperature on the growth of microalgae. Moreover, for the maximum growth of the cells we should control the surrounding temperature.

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Identifying the relationship between demographical factors with COVID-19 infection could demonstrate some prevention strategies of “possible super-spreaders”.To evaluate the correlation between recovery and demographic characteristics of COVID-19-infected patientsA descriptive type of study to demonstrate the 200 COVID-19 infections with various demographical variables by using a questionnaire. The survey consisted of 64-close ended queries, including a short summary of the study background, purpose, procedures, privacy contract, and knowledgeable consent form.For statistical analysis Independent T-test or ANOVA test and SPSS version 25 (IBM, USA) and STATA 15 were used.The male-female ratio of COVID-19 infected patients is 115:100. 50% of patients have never attended social gatherings before getting COVID-19 infection. Social events were visited by 44% of the participants. 47.24% need hospitalization during the positive period, whereas 52.76% recovered at home. Respondents older than 40 years required oxygen support for recovery (p< 0.05). The most common symptoms were loss of smell and taste (53%), headache (48%) body pain (38%), and, fever (33%) in the first-time infection however, these symptoms decreased by Second- and third-time re-infection. Similarly, 20% of patients need oxygen support the first time of infection; it decreased by 10% the second time and 4% the third time. There is a statistically significant difference in the mean recovery time between the people from different professions (p< 0.05). The recovery time of COVID-19 infections is associated with age, profession, and the number of COVID-19 infection times.

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