In this paper, the authors are exploring emerging trends in data utilising longitudinal analysis.Longitudinal studies are typically observational studies wherein a participant's outcomes, and possible treatments or exposures, are collected at multiple times on the same individual. These studies have no limit on the timespan and as such, can last up to several decades. Though shorter time frames are not recommended, the key is for the study to extend beyond a singular time point, ideally three or more[1]. Conducting longitudinal studies are beneficial as it allows one to follow subjects in real time, which allows researchers to have a better understanding of the sequence of events[1].
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.
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.
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