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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.
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.
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.
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.
Benzylideneanilines, the condensation products of benzaldehyde and aniline derivatives, have enjoyed significant success as optical metal ion sensors due to their ability to form stable metal complexes which exhibit distinct spectral features compared to the unbound compound. However, their use in aqueous media is limited by the hydrolytic susceptibility of the C=N moiety. Hence, an in-depth investigation into the hydrolytic degradation mechanism of a series of 2-aminophenol derived Nbenzylideneanilines was conducted wherein molecular modelling techniques were applied to elucidate the “step-by-step” transformation mechanism of these compounds from a fundamental perspective.
At the inception of automated solar tracking in the 1970’s, geometric architectures with pair(/s) of solid-state photo-sensitive devices were constructed and used to detect the sun’s position. As an alternative in recent years, cameras have been used to capture and process live sky images to detect the sun’s position. When the sky is cloudy however, both approaches are prone to errors and sometimes require human intervention which tend to reduce the trackers’ economic viability [1].
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