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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].
Invasive alien species (IAS) are implicated in the extinction or decline of numerous native aquatic species worldwide. Their negative impacts occur through mechanisms including habitat alteration, competition, predation, hybridisation, and the spread of disease (Strayer et al. 2006). Small island ecosystems are most susceptible to the impacts of IAS. Once established, freshwater IAS are difficult to eradicate without negatively impacting native species.
The FORECAST Grand Innovation Challenge 2022 (GIC) is to develop a feasible innovation (prototype/product/concept) that will revolutionize the management, protection, and use of water resources in the Caribbean.
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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