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Forensic Crime Scene Investigators (FCSIs) are forensic practitioners who are key components to the investigative process within a legal framework. In fact, the criminal justice system considers the scientific evaluation and forensic evidence collection to be the most significant aspect of any criminal investigation and court cases. Despite this, limited literature exists on the psychological effects experienced by FCSIs from processing gruesome crime scenes on a regular basis.
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.
The majority of scientific discoveries remain confined to dissertations and peer review publications where they remain hidden from their possible industrial applications. Given the challenges offered by current global events like environmental pollution, climate change effects, and diseases, the need for more rapid transmission of scientific discoveries from the realm of postgraduate dissertations and research papers to industrial applications is most critical. Hence, the need for a clear road map, allowing the connection of both pure and applied scientific discoveries to their industrial applications is obvious. Of course, for this to be achieved, a clear understanding of the constituent steps of such a process is germane. Hence, this brief workshop aims to map a possible path for achieving the aforementioned central goal, using previous experiences and examples.
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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