A preliminary evaluation of the utility of insects and algae for PMI estimation in confined, still-water environments

Author(s):  
SK. Bray ◽  
XA. Conlan ◽  
ML. Harvey
2021 ◽  
Author(s):  
◽  
Rachel Parkinson

<p>Soil is frequently encountered as trace evidence in forensic science case-work, but because of the limitations of current analytical techniques, this evidence is rarely utilised. A technique has been developed that allows comparisons of soil samples to be made, based on molecular analysis of the bacterial communities living in the soil. This project assesses the practicality of using this technique, known as 16S rDNA T-RFLP community profiling, for forensic soil analysis, by refining the basic methodology and performing a preliminary evaluation of its reproducibility and utility. Initial difficulties associated with generating profiles from soil samples have been overcome through methodology improvement, and the technique has been found to be effective for generating simple, visual profiles that clearly demonstrate differences between soil samples. Soil bacterial community DNA profiling is likely to be a powerful yet simple forensic tool, providing the ability to routinely use soil as associative evidence. The potential for using the same technology to develop a time since death or post mortem interval (PMI) estimation tool was also investigated. This study monitored the changes in the soil bacterial community beneath decomposing human cadavers and pig carcasses and showed that community change is dynamic and progressive. These changes are caused by fluctuations in specific bacterial species populations that are able to utilise organic breakdown products released from the body over time. Release of the body’s natural microflora into the underlying soil may also contribute to an altered bacterial community. This project has demonstrated that the soil microbial community clearly changes over the course of decomposition, and potential exists for development of a PMI estimation tool based on soil bacterial community succession.</p>


2021 ◽  
Author(s):  
◽  
Rachel Parkinson

<p>Soil is frequently encountered as trace evidence in forensic science case-work, but because of the limitations of current analytical techniques, this evidence is rarely utilised. A technique has been developed that allows comparisons of soil samples to be made, based on molecular analysis of the bacterial communities living in the soil. This project assesses the practicality of using this technique, known as 16S rDNA T-RFLP community profiling, for forensic soil analysis, by refining the basic methodology and performing a preliminary evaluation of its reproducibility and utility. Initial difficulties associated with generating profiles from soil samples have been overcome through methodology improvement, and the technique has been found to be effective for generating simple, visual profiles that clearly demonstrate differences between soil samples. Soil bacterial community DNA profiling is likely to be a powerful yet simple forensic tool, providing the ability to routinely use soil as associative evidence. The potential for using the same technology to develop a time since death or post mortem interval (PMI) estimation tool was also investigated. This study monitored the changes in the soil bacterial community beneath decomposing human cadavers and pig carcasses and showed that community change is dynamic and progressive. These changes are caused by fluctuations in specific bacterial species populations that are able to utilise organic breakdown products released from the body over time. Release of the body’s natural microflora into the underlying soil may also contribute to an altered bacterial community. This project has demonstrated that the soil microbial community clearly changes over the course of decomposition, and potential exists for development of a PMI estimation tool based on soil bacterial community succession.</p>


1989 ◽  
Vol 32 (3) ◽  
pp. 681-687 ◽  
Author(s):  
C. Formby ◽  
B. Albritton ◽  
I. M. Rivera

We describe preliminary attempts to fit a mathematical function to the slow-component eye velocity (SCV) over the time course of caloric-induced nystagmus. Initially, we consider a Weibull equation with three parameters. These parameters are estimated by a least-squares procedure to fit digitized SCV data. We present examples of SCV data and fitted curves to show how adjustments in the parameters of the model affect the fitted curve. The best fitting parameters are presented for curves fit to 120 warm caloric responses. The fitting parameters and the efficacy of the fitted curves are compared before and after the SCV data were smoothed to reduce response variability. We also consider a more flexible four-parameter Weibull equation that, for 98% of the smoothed caloric responses, yields fits that describe the data more precisely than a line through the mean. Finally, we consider advantages and problems in fitting the Weibull function to caloric data.


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