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Poster Session (in Gather.Town)
In parallel and distributed computing environments, task scheduling, where the basic idea is minimizing time loss and maximizing performance, is an absolutely critical component. Scheduling in these environments is NP-hard, so it is important that we continue to search and find the most efficient and effective ways of mapping tasks to processors. One such effective approach is known as Ant Colony Optimization (ACO). This popular optimization technique is inspired by the foraging behavior of ants in their colonies to find the shortest paths between their nests and food sources.
Numerous organic chemicals, either directly manufactured or formed as byproducts of other processes, are released into the environment. Once there, many cause adverse effects on environmental and human systems. Of particular concern are long-lasting impacts from those organic pollutants that remain in the environment for long periods of time. The development of appropriate management strategies to address this problem requires knowledge of the environmental distributions of these pollutants.
The malaria epidemic was responsible for about 241 million infectious cases and 627,000 deaths worldwide in 2020.[1] This infectious disease, transmitted by the female Anopheles mosquito, is caused by parasites of the genus Plasmodium namely P. falciparum, P. vivax, P. malariae, P. knowlesi, P. ovale curtisi and P. ovale wallikeri.[2,3] Also, malaria is found predominantly in the highlands of Africa which accounts for more than 90% of infections worldwide. While there has been some success in the treatment of malaria, its eradication has been negatively impacted by insecticide and drug resistance. With emergence of thiosemicarbazone as antimalarial agents, the combination of pyridine and amide or thioamide moieties into one scaffold makes for an interesting target.[4]
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