Mauricio Chase*, Sarah Fieldhouse, Stephen Bleay and Neil Lamont
This review synthesizes current knowledge on the use of Acid Dyes (ADs) Acid Black 1 (AB1), Acid Yellow 7 (AY7), and Acid Violet 17 (AV17) identified by the UK home office as common enhancement agents for blood-contaminated fingermark impressions. Various factors which can influence AD bloodmark enhancement are reported in scientific literature, including sequence of application, time and temperature, dye formulation, substrate features, processing times and bloodmark volume, contaminants, fingermark age, deposition pressure and donor variation. While these dyes have demonstrated excellent capability on porous (excluding AY7) and non-porous substrates, this review has identified several gaps in understanding and application. Firstly, the effect of blood volume on the fixing and staining times of these dyes, particularly for marks associated with high volumes of blood, requires exploration. Additionally, factors such as air-to-surface temperature, substrate colour, composition, coating and degree of porosity need a comprehensive study to improve practitioner awareness and best practice capabilities. Research into the effects of temperature on AD staining times should also be probed to evaluate the performance and suitability of different dye formulations under operational conditions and their response to temperature fluctuations. Furthermore, examining the effect of proteinaceous and non-proteinaceous contaminants on blood mark visualisation substances is encouraged. Accurate modelling and regulation of deposition pressures and contact durations are also suggested to understand blood matrix responses and their influence on enhancement due to the likely impact on operational marks. Addressing these knowledge gaps will provide valuable insights, optimizing the selection and proficiency of AB1, AY7 and AV17 for blood mark application, thereby benefiting practitioners and researchers alike.
Dejen Fantaw*, SN Jadhav and Alemayehu Shiferaw
Background: Stature refers to a person's height from crown to heel length. Every person is identified by different biometric criteria such as face recognition, fingerprints, Iris patterns, etc., but identification in a dead body can rely on different identification features such as age, sex, stature and other identification marks, with stature being the most distinguishing feature of identification. Identifying an individual from mutilated, decomposed and amputated body fragments has become increasingly important in recent years as a result of natural disasters (such as earthquakes, tsunamis, cyclones and floods) and man-made disasters (such as terror attacks, bomb blasts, wars and plane crashes). Objective: To predict stature from arm and forearm length in the age group of 18 to 25 years of Addis Ababa population, Addis Ababa, Ethiopia.
Materials and methods: A descriptive, cross-sectional, prospective study was conducted to estimate stature from arm and forearm length in the age group of 18 to 25 years of Addis Ababa population. Participants were selected randomly. Data was entered and analyzed with SPSS version 23. A simple linear regression model was computed to estimate stature from arm and forearm length.
Result: A total of 300 individuals with equal male-to-female proportion, 150 males and 150 females were taken as participants in this study. Height ranged from a minimum of 147.5 cm to a maximum of 188 cm, with a mean and standard deviation of 165.26 ± 7.36. For the total participants, the equations derived from arm length were: Stature=23.144 ± 4.212 (right arm length), R-value of 0.884, stature=22.104 ± 4.238 (left arm length), R-value of 0.886. For male, stature=42.352 ± 3.693 (right arm length), R-value of 0.827 and stature=42.224 ± 3.693 (left arm length), R-value of 0.830. For female, stature=55.705 ± 3.182 (right arm length), R-value of 0.790 and stature=54.040 ± 3.228 (left arm length), R-value of 0.796. Using forearm length, for total participants, stature=5.407 ± 5.862 (right forearm length), R-value of 0.884 and stature=6.175 ± 5.825 (left forearm length), R-value of 0.877. For male, stature=27.426 ± 5.112 (right forearm length), R-value of 0.839 and stature=28.521 ± 5.068 (left forearm length), R-value of 0.840. For female, stature=39.698 ± 4.533(right forearm length), R-value of 0.737 and stature=44.214 ± 4.353 (left forearm length), R-value of 0.717.
Conclusion: There is a notable and statistically significant correlation between stature and both arm and forearm lengths across genders and on both sides of the body
Vidhi Soni
A disaster or catastrophe is an impulsive devastating event that utterly disrupts the functioning of a community, a society comprising of widespread human, material, economic or environmental losses and impacts, which exceeds the ability of the affected community or society to cope using its own resources. The death of a loved one leaves an indelible mark on the survivors, and unfortunately, because of the lack of information, the families of the deceased suffer additional harm due to the inadequate ways in which the bodies of the deceased are handled. These secondary injuries are unacceptable, particularly when they are under the consequences of direct authorization or action on the part of the authorities or those responsible for humanitarian assistance. The most serious aspect is that these measures are being carried out without respecting identification procedures or preserving the individuality and dignity of the deceased. Disaster victim identification (DVI) is an intensive and arduous task which needs the contribution of specialists from various disciplines. Here in these exotic situations, forensic facial recognition may act as a boon for revealing the identity of the victims. A lot of face recognition algorithms, along with their modifications, have been developed during the past decades. This paper seeks to present a review of the existing literature in this domain and discuss several aspects, significance and requirements for forensic face recognition systems particularly focusing the various advances and trends of facial imaging which may provide a great beneficiary value in face recognition mechanism of victims in the case of different fatalities.
Journal of Forensic Medicine received 165 citations as per Google Scholar report
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