This paper presents an optimization approach to the design of simply supported, post-tensioned, prestressed concrete I-girder bridges. The objective is to minimize the total cost of the structure, considering cost of materials, fabrication, and installation. For a particular girder span and bridge width, the design variables considered for cost minimization of the bridge system are girder spacing, various crosssectional dimensions of the girder, number of strands per tendon, number of tendons, tendon layout and configuration, slab thickness, slab rebar, and shear rebar for the girder. Explicit constraints on the design variables are developed on the basis of geometric requirements, practical conditions for construction, and code restrictions. Implicit constraints for design are formulated as per the American Association of State Highway and Transportation Officials (AASHTO) Standard Specifications. The optimization problem is characterized by having a combination of continuous, discrete, and integer sets of design variables and multiple local minima. An optimization algorithm, evolutionary operation (EVOP), is used that is capable of locating directly with high probability the global minimum without requiring information on gradient or subgradient of the objective function. The present optimization approach is used for a real-life bridge project, leading to a feasible and acceptable design resulting in around 35% savings in cost per square meter of the deck area. Computational time required for optimization of the present problem is only a few seconds. Because constant design parameters have influence on the optimum design, this cost minimization procedure is performed for a range of such parameters.
BackgroundNumerous studies on knowledge, attitude, and practice (KAP) about the prevention of COVID-19 infections are available in Bangladeshi contexts, with results that vary significantly. However, no earlier attempt has been made to analyze the available COVID-19 KAP studies in Bangladesh, which is incorporated in this meta-analysis for the first time.MethodsFollowing the PRISMA guidelines, articles relevant to COVID-19 KAP that were conducted among the Bangladeshi population were found in databases such as PubMed, Scopus, CINAHL, Google Scholar, and ResearchGate. Random-effect meta-analysis was used to generate a pooled prevalence of knowledge, attitude, and practice level toward the prevention of COVID-19 infection.ResultsThis review included 18 articles that were published between March 2020 and November 2021. Overall, 89.87% (95% CI: 67.71–97.40) understood about COVID-19 symptoms, 92.09% (95% CI: 84.32–96.18) knew about how it spreads, and 79.51% (95% CI: 59.38–91.15) knew about how to treat it. The public's perception of controlling COVID-19 is mixed, with only 44.16% (95% CI: 35.74–52.93) and 60.28% (95% CI: 49.22–70.38) believing the country would win the struggle against the pandemic and the infection will be successfully controlled, respectively. Although overall COVID-19 preventative practice was good, subgroup analysis found that men had a poor practice toward controlling the infection. The practice of avoiding crowded places (70.15%) and maintaining social distance (77.17%) was found to be satisfactory in institution-based studies.ConclusionThe findings of this study revealed that the Bangladeshi population had a good awareness of COVID-19 symptoms, treatment, attitudes, and behaviors. The findings of this study are likely to aid Bangladeshi governments and policymakers in putting evidence into action by identifying gaps and emphasizing the importance of educating the less informed public about COVID-19 transmission.
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