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    After reviewing different scholarly journals (must be written within 5 years), the student will select six articles and describe how they support or apply to the techniques you have selected. You should also include your opinion on how this technique is applicable to crime scene investigation. Each student must utilize the Saint Leo library.


    The link to the library is http://slulibrary.saintleo.edu/library_home. You should not need login information to access the library. 




Subject Article Analysis Pages 4 Style APA


Crime Scene Investigations (CSI) Bloodstain Pattern Analysis

                In Crime Scene Investigations (CSI), one of the most random occurrences at a crime scene – the shedding of blood – provides major insightful information that can help investigators to analyze and reconstruct events that led to a crime. As elaborated by Vitiello, Di Nunzio, Garofano, Saliva, Ricci and Acampora (2016), Bloodstain Pattern Analysis (BPA) is one of the specialties in forensic science involving examination, analysis, and interpretation of distribution of bloodstains at a crime scene, with the purpose of drawing conclusion about various details and dynamics of the crime scene. Many scholars around the world have explored the concept and techniques adopted in BPA. This paper seeks to explore the some concepts and techniques adopted in BPA by reviewing and analyzing several literature from prominent scholars, explaining how they support and apply the technique of BPA. Moreover, the paper elaborates my thoughts and opinions on how the same technique is applicable in CSI.

Literature Review

First Article

                In many instances, the dynamics of bloodstain formation appear to be complex and infinitely capricious. However, the patterns leaves a reproducible characteristic, which allows for an unswerving link to be made between their distribution and their formation. This fairly complex phenomenon is explored by Taylor, Laber, Kish, Owens and Osborne (2016) in their masterpiece – The Reliability of Pattern Classification in Bloodstain Pattern Analysis. This study, which involved 27 bloodstain pattern analysts, was an examination of around 400 spatter patterns of bloodstains with an aim to determine the reliability of classification decisions that come along with the analysis. The patterns to be analyzed and classified for the standards required in court as well as the nature of substrate – which are commonly encountered in crime scenes – were varied significantly in order to determine the effect of these variables on the accuracy of the classification.

According to the findings of this study, most spatter patterns were reliably classified with an error rate of 4% for expirated pattern and 19% for impact related patterns. Moreover, the study identifies major causes of the errors, among which are; lack of distinctive features in some blood patterns, some spatter blood sharing characteristics with other pattern types, as well as inadequate contextual information. However, Taylor et al. (2016) concluded that as the rate of incorrectly classified patterns increased, the rate at which the final decision was made by experts decreased – making it clear that they lacked certain information for their decision-making. The study, thus, concluded that there is a higher reliability of data from pattern classification in BPA and in minimizing errors. Moreover, analysts ought to take the effort to minimize the effects of contextual information – which were a major source in their error.

Second Article

                Among the many valuable information that BPA provides in helping to reconstruct a crime in a crime scene, one of the most prevalent, is the determination of the position of victims on the scene. This is achieved through a series of calculation, assumptions, and error correction – thus giving a close estimate of the same. This intricate portent is explored in yet one of the most sophisticated studies in BPA entitled implementation of a fluid dynamic model for position determination of victims, illustrated by Laan, De Bruin, Slenter, Wilhelm, Jermy and Bonn (2015). As Laan et al. (2015) denote, to determine the position of the blood source (which is the position of the victim), experts utilizes a straight-line approximation calculation for the trajectory while ignoring certain factors such as gravity and drag – resulting to an overestimation in height or position of the victim. Therefore, the scholars conducted a study where bloodstain patterns were created and the method of straight-line approximation, measurement considering gravity, as well as measurement considering both gravity and drag were used to determine the distance and position of the victim. The study concluded that the inclusion of both drag and gravity in the trajectory calculation can improve the accuracy of the information from BPA, which is four times more accurate than the straight-line approximation technique that is commonly used. Moreover, the method highlighted in this study enables investigators to determine the position of the victim as well as whether the victim was sitting or standing. Additionally, the method also enables the possibility of connecting the wounds of the body to specific patterns at the crime scene. This, according to the authors, would provide insightful and helpful information in crime scene reconstruction and thus valuable information for the court.

Third Article

                In crime scene reconstruction, blood spatter due to gunshots provide a very hard task for the experts – majorly because they can be both forward spatter (in the direction of the bullet) and back spatter (opposite to the direction of the bullet). To differentiate the two, Comiskey, Yarin and Attinger (2018) constructs a theoretical model of a forward spatter and conducts experiments in regard to the same. In their report – Theoretical and experimental investigation of forward spatter of blood from a gunshot – theoretical predictions incorporating the viscoelasticity of blood and its interaction with air molecules, are corroborated against experimental data acquired from a gunshot experiment they carried out. The models presented, which were in agreement with the actual data from the experiment, were able to predict; the distance from the target at which blood stains appear, the distribution of number of stains, as well as distribution of stain area. In spite of the large number of parameters considered in this study, it is able to produce valuable information including the droplet impact angle as well as its final velocity responsible for the stain area. In doing so, the study offers great knowledge in the determination of data that would greatly aid crime scene reconstruction and investigation.

Fourth Article

                While also constructing on the pattern constructed by gunshots, Radford et al. (2016) examine the biochemical basis for back spatter from a gunshot. This is done through the simulation of the same from cranial gunshot wounds using a pig model. The scholars carried out several experiments with live and dead pigs to create back spatter and analyzed the same. Even though the mechanism involving back spatter is entirely complex, the study was able to reveal that back spatter results from splashing of superficial blood if it is already present in the skin. Moreover, the report noted that back spatter effects from contact shots have been demonstrated from subcutaneous gas effects. Therefore, the models presented in this study provides a deep understanding on the phenomena of back spatter and the mechanisms that it is associated with.

Fifth Article

                In crime scene reconstruction, it is also imperative to comprehend the nature of weapon used to attack a victim as well as its characteristics – enabling better decision making for the investigators. Smith, Buntsma and Brutin (2017) have explored this through BPA in their analysis of the influence of roughness on human blood drop spreading and splashing. Their study elaborated that the two main parameters that influenced post-impact pattern of blood was the roughness of the material used as well as the velocity of impact on the victim. The article elaborates that small circular stains are observed on low impact velocities while a circular spine shape along a large splashing of blood is observed in cases of a high velocity impact. Moreover, experimental observations revealed that smooth surfaces were associated with low deformation while greater deformation in the splash blood was associated with fairly rough surfaces. This study provides insight that is important in the reconstruction and reconstitution of the crime scene events, providing even better evidence with the information obtained from blood spatter.

Sixth Article

                Moreover, since BPA provides data through which a victim’s, witness, or accused claims are either confirmed or refuted, the logistics arising from the analysis ought to be accurate, in order to avoid biased decision-making. In an attempt to improve the accuracy and thus the efficiency of BPA, Joris et al. (2015) developed an automated and virtual approach towards BPA. In their research, synthetic crime scenes were developed and analysed in an effort to evaluate the approach proposed by the scholars. As suggested by Joris et al. (2015), minimum manual work is required due to the adoption of fiducial markers and computer vision algorithms. Results and conclusion inferenced from the experiments demonstrates correct operations and accuracy – resulting to practical advantages over many other techniques of analyzing bloodstain spatter patterns. This, in effect, improves the quality of the outcome of the analysis and influences sound decision-making from reliable evidence.


                In my opinion, crime scene investigation requires a considerable amount of information from the data that occur randomly at the crime scene in order to reconstruct the events leading to the same. It is, therefore, important to adopt techniques that are able to develop a lot of information from very little data. One of such techniques is bloodstain pattern analysis. This method, as discussed above, is able to provide a wide variety of information from blood splash encountered at several crime scenes. It provides valuable information such as position of victim during the crime, the nature of material used in the crime, as well as the force of impact leading to shedding of blood. This is insightful in reconstructing the events of a crime scene, thus being an important and integral part of crime scene analysis.


                In conclusion, it is evident that BPA is imperious in drawing conclusion about the dynamics and details of any crime scene involving the shedding of blood. This paper has analyzed several literary works involving the BPA technique of crime scene investigation. First, the paper has developed the reliability of the data that comes along with BPA which concluded that very minimum errors are developed by experts in the analysis of blood splash patterns. Moreover, articles analyzing the theoretical and practical techniques of identifying information such as position and state of the victim as well as forward and backward spatter of blood from a gunshot, were identified and critically analyzed. The paper also analyzed the bloodstains associated with weapons and characteristics of the weapon based on the nature of the bloodstain developed. Lastly, the paper has considered an automated and virtual approach towards BPA that would minimize errors arising due to human errors. This would ensure a higher accuracy of data obtained from bloodstains at any scene – resulting to more reliable information needed for decision-making and reconstruction of crime scene events.




Comiskey, P. M., Yarin, A. L., & Attinger, D. (2018). Theoretical and experimental investigation of forward spatter of blood from a gunshot. Physical Review Fluids3(6), 063901.

Joris, P., Develter, W., Jenar, E., Suetens, P., Vandermeulen, D., Van de Voorde, W., & Claes, P. (2015). HemoVision: An automated and virtual approach to bloodstain pattern analysis. Forensic science international251, 116-123.

Laan, N., De Bruin, K. G., Slenter, D., Wilhelm, J., Jermy, M., & Bonn, D. (2015). Bloodstain pattern analysis: implementation of a fluid dynamic model for position determination of victims. Scientific reports5, 11461.

Radford, G. E., Taylor, M. C., Kieser, J. A., Waddell, J. N., Walsh, K. A. J., Schofield, J. C., … & Chakravorty, E. (2016). Simulating backspatter of blood from cranial gunshot wounds using pig models. International journal of legal medicine130(4), 985-994.

Smith, F. R., Buntsma, N. C., & Brutin, D. (2017). Roughness influence on human blood drop spreading and splashing. Langmuir34(3), 1143-1150.

Taylor, M. C., Laber, T. L., Kish, P. E., Owens, G., & Osborne, N. K. (2016). The Reliability of Pattern Classification in Bloodstain Pattern Analysis, Part 1: Bloodstain Patterns on Rigid Non‐absorbent Surfaces. Journal of forensic sciences61(4), 922-927.

Vitiello, A., Di Nunzio, C., Garofano, L., Saliva, M., Ricci, P., & Acampora, G. (2016). Bloodstain pattern analysis as optimisation problem. Forensic science international266, e79-e85.













Appendix A:

Communication Plan for an Inpatient Unit to Evaluate the Impact of Transformational Leadership Style Compared to Other Leader Styles such as Bureaucratic and Laissez-Faire Leadership in Nurse Engagement, Retention, and Team Member Satisfaction Over the Course of One Year

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