LOADING
Vector-borne diseases have since the 17th century been the leading cause of death by disease more than any other causes combined, even preventing development in the tropics (Gubler 1998). Of all insect vectors, Aedes aegypti proves to be the deadliest as it is the primary vector of the four most notorious vector-borne diseases – chikungunya (chik-V), Zika (Zik-V), dengue fever and yellow fever viruses. Control of the spread of Aedesborne diseases is primarily reliant on the control of the vector responsible for their spread. Traditionally, vector control relied on environmental hygiene and the elimination of breeding sites (Gubler 1998), shifting only in the 1980s to the use of synthetic chemicals in the form of carbamate, organochloride, organophosphate and pyrethroid insecticides (Norris, et al. 2015). However, the evolution of Aedes aegypti resistance to synthetic chemicals have made control of the spread of the vector and its diseases increasingly difficult. This led to the exploration of innovative and alternative methods in the control of Aedes aegypti.
Brookhaven National Laboratory delivers discovery science and transformative technology to power and secure the nation’s future. Primarily supported by the U.S. Department of Energy’s (DOE) Office of Science, Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research. The laboratory is open to users from all countries and areas of STEM. The workshop will give an introduction to the capabilities of the laboratory, how to access facilities and collaboration tips for working with BNL scientists.
Lead, a well-known neurotoxin, remains environmentally abundant, arising from many natural and synthetic processes which encourage its environmental accumulation and hence, increased interactions with flora and fauna. Therefore, tremendous research efforts have been invested into developing various methods for its analysis and sequestration, however, affordability, sensitivity and selectivity still remain formidable challenges in this area and hence here is room for further exploration.
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.
by clicking any of the buttons below
