Environment, Environmental Crimes, Environmental Forensic Medicine, Environmental Risk Management and Environmental Criminology.

Forensic medicine has always held the human environment, either seen as a source for pathological agents or the background of judicial events, in great consideration. The concept of the environment has evolved through time, expanding itself to include all the physical and virtual sub-spaces in which we exist. We can nowadays talk of technoenvironmental reality; virtual spaces exploded because of the COVID-19 pandemic making us come to terms with the fact that those are the places where we work, where we socialize and, even, where we meet our doctors and can be cured. Artificial Intelligence (AI) has contributed to shaping new virtual realities that have got their own rules yet to be discovered, carved and respected. We already fight a daily battle to save our natural environment: along with the danger of green crimes, comes the need for environmental justice and environmental forensic medicine that will probably develop a forensic branch and an experimental branch, to implement our technical culture leading to definition of the real dimension of the risk itself to improve the role of legal medicine in the Environmental Risk Management. While green criminology addresses widespread green crimes, a virtual environment criminology will also develop, maybe with a contribution of AI in the justice field. For a sustainable life, the environmental revolution must rapidly take place, and there is the need for a new justice, a new forensic medicine and a new criminology too.

The pathological diagnosis of the height of fatal falls: A mathematical approach.

The authors analyzed the injury pattern of 385 victims of fall from a height which underwent a complete autopsy, with the objective to investigate whether it was possible to construct a mathematical model to be used for height of the fall diagnosis. The cases were selected and enrolled according to a balanced stratification of the heights of the fall, allowing a subdivision into seven classes consisting of 55 subjects each: 6m or less, 9m, 12m, 15m, 18m, 21m, 24m or more (maximum 36m). For each case anthropologic and necroscopic data was collected and analyzed to obtain a standardized description of the injury pattern was obtained, dividing the body into 4 major anatomical areas (Head, Thorax, Abdomen, Skeleton), each of them further divided in 5 major organs. Every organ was finally divided into 5 objective degrees of injury. Statistical analysis was performed on all the available data using IBM SPSS Statistics 20, to test the performance of the "injury pattern assessment table" in the diagnosis of the height of the fall and to develop a related mathematical model. Our findings confirm that the height of the fall is significantly associated with age, weight of the body and the injury pattern. An Injury Pattern Assessment Table and two mathematical models which correlates the height of the fall with analyzed variables are presented.