156 research outputs found
Author’s Response to Commentary on: Liu Y, Attinger D, De Brabanter K. Automatic classification of bloodstain patterns caused by gunshot and blunt impact at various distances
No full textThe Commentary by A. Keten makes the case for considering evaporation and coagulation in research and applications of the forensic discipline of bloodstain pattern analysis (BPA). The author also mentions two important facts: first, blood stains are often present in crime scenes, and second, they can provide significant information towards crime scene reconstruction.This is a manuscript of a Letter to the Editor published as Attinger, D., Liu, Y. and De Brabanter, K. (2020), Authors’ Response. J Forensic Sci, 65: 1386-1387. https://doi.org/10.1111/1556-4029.14452. © 2020 American Academy of Forensic Sciences. Posted with permission of CSAFE
La " koinonia ", voie et âme de l'Église une
No full textAprès quelques remarques préliminaires sur la communion comme nœud sémantique non univoque, mais complexe et susceptible de multiples significations, l'auteur analyse quelques types particulièrement significatifs du processus d'inculturation de la communion chrétienne : tout d'abord, le rapport continuité/nouveauté face à la culture juive. Puis, avec la diffusion du christianisme et la paix constantinienne se réalise la confrontation avec la culture gréco-latine principalement. Ensuite, l'expérience dominante demeure, surtout en Occident, celle d'une « société chrétienne », engendrant le régime de chrétienté, où se développe la métaphysique classique. L'unité de l'Église implique, alors, une nouvelle inculturation de la koinonia chrétienne. Finalement, la confrontation avec la modernité semble entraîner une éclipse de la communion. Aujourd'hui, la société pluriculturelle ressent l'urgence d'une nouvelle inculturation de la communion.Alberigo Giuseppe, Attinger Daniel. La " koinonia ", voie et âme de l'Église une. In: Revue des Sciences Religieuses, tome 68, fascicule 1, 1994. pp. 47-71
Thermodynamics and historical relevance of a jetting thermometer made of Chinese zisha ceramic
No full textFollowing a recent trend of scientific studies on artwork, we study here the thermodynamics of a thermometer made of zisha ceramic, related to the Chinese tea culture. The thermometer represents a boy who “urinates” shortly after hot water is poured onto his head. Long jetting distance is said to indicate that the water temperature is hot enough to brew tea. Here, a thermodynamic model describes the jetting phenomenon of that pee-pee boy. The study demonstrates how thermal expansion of an interior air pocket causes jetting. A thermodynamic potential is shown to define maximum jetting velocity. Seven optimization criteria to maximize jetting distance are provided, including two dimensionless numbers. Predicted jetting distances, jet durations, and temperatures agree very well with infrared and optical measurements. Specifically, the study confirms that jetting distances are sensitive enough to measure water temperature in the context of tea brewing. Optimization results show that longer jets are produced by large individuals, with low body mass index, with a boyhood of medium size inclined at an angle π/4. The study ends by considering the possibility that ceramic jetting artifacts like the pee-pee boy might have been the first thermometers known to mankind, before Galileo Galilei’s thermoscope.This article is published as Lee, Vincent, and Daniel Attinger. "Thermodynamics and historical relevance of a jetting thermometer made of Chinese zisha ceramic." Scientific reports 6 (2016): 28609. doi:10.1038/srep28609. Posted with permission.</p
Automatic Classification of Bloodstain Patterns Caused by Gunshot and Blunt Impact at Various Distances
No full textThe forensics discipline of bloodstain pattern analysis plays an important role in crime scene analysis and reconstruction. One reconstruction question is whether the blood has been spattered via gunshot or blunt impact such as beating or stabbing. This paper proposes an automated framework to classify bloodstain spatter patterns generated under controlled conditions into either gunshot or blunt impact classes. Classification is performed using machine learning. The study is performed with 94 blood spatter patterns which are available as public data sets, designs a set of features with possible relevance to classification, and uses the random forests method to rank the most useful features and perform classification. The study shows that classification accuracy decreases with the increasing distance between the target surface collecting the stains and the blood source. Based on the data set used in this study, the model achieves 99% accuracy in classifying spatter patterns at distances of 30 cm, 93% accuracy at distances of 60 cm, and 86% accuracy at distances of 120 cm. Results with 10 additional backspatter patterns also show that the presence of muzzle gases can reduce classification accuracy.This is a manuscript of an article published as Liu, Yu, Daniel Attinger, and Kris De Brabanter. "Automatic Classification of Bloodstain Patterns Caused by Gunshot and Blunt Impact at Various Distances." Journal of Forensic Sciences (2019). Posted with permission of CSAFE.</p
Charts based on big data from fluid dynamics simulations provide a simple tool to estimate how far from its source a specific blood stain can be found
No full textThe bloodstain pattern analyst sometimes has to judge if a given stain could originate from a specific location. A wide range of values of the maximum distance that a blood drop can travel have been reported from experiments, ranging from less than one meter to more than 10 meter. Here we formulate the problem in a fluid dynamics and big data framework. The fluid dynamics is solved with Newton’s classical equation of motion coupled with well‐established models for the gravity and drag forces that bend the trajectories of drops. The parameters screened are the drop size, initial velocity and launch angle, as well as the height of a blood source and the ceiling height. Combining a wide range of values of those five parameter commended the performance of more than 4.5 million fluid dynamic simulations. Results of those simulations have been searched and mined for additional parameters directly measurable on a crime scene, such as the stain size and stain ellipticity. The results are presented in simple charts. Those charts are easy to use, and do not require any knowledge of fluid dynamics from the analyst.This manuscript based on presentation of D. Attinger at 1st "IABPA (International Association of Bloodstain Pattern Analysts) Congresso International de Analistas de Patrones de Manchas de Sangre," June 27-28, 2018, in Buenos Aires, Argentina. Presentation entitled "Determinacion de la distancia maxima de viaje de una gota de sangre" Posted with permission.</p
Using the likelihood ratio in bloodstain pattern analysis
No full textThere is an apparent paradox that the likelihood ratio (LR) approach is an appropriate measure of the weight of evidence when forensic findings have to be evaluated in court, while it is typically not used by bloodstain pattern analysis (BPA) experts. This commentary evaluates how the scope and methods of BPA relate to several types of evaluative propositions and methods to which LRs are applicable. As a result of this evaluation, we show how specificities in scope (BPA being about activities rather than source identification), gaps in the underlying science base, and the reliance on a wide range of methods render the use of LRs in BPA more complex than in some other forensic disciplines. Three directions are identified for BPA research and training, which would facilitate and widen the use of LRs: research in the underlying physics; the development of a culture of data sharing; and the development of training material on the required statistical background. An example of how recent fluid dynamics research in BPA can lead to the use of LR is provided. We conclude that an LR framework is fully applicable to BPA, provided methodic efforts and significant developments occur along the three outlined directions.The following is published as Attinger, Daniel, Kris De Brabanter, and Christophe Champod. "Using the likelihood ratio in bloodstain pattern analysis." Journal of forensic sciences 67, no. 1 (2022): 33-43. Posted with permission of CSAFE
In silico design of crop ideotypes under a wide range of water availability
No full textGiven the changing climate and increasing impact of agriculture on global resources, it is important to identify phenotypes which are global and sustainable optima. Here, an in silico framework is constructed by coupling evolutionary optimization with thermodynamically sound crop physiology, and its ability to rationally design phenotypes with maximum productivity is demonstrated, within well‐defined limits on water availability. Results reveal that in mesic environments, such as the North American Midwest, and semi‐arid environments, such as Colorado, phenotypes optimized for maximum productivity and survival under drought are similar to those with maximum productivity under irrigated conditions. In hot and dry environments like California, phenotypes adapted to drought produce 40% lower yields when irrigated compared to those optimized for irrigation. In all three representative environments, the trade‐off between productivity under drought versus that under irrigation was shallow, justifying a successful strategy of breeding crops combining best productivity under irrigation and close to best productivity under drought.This article is published as Jubery, Talukder Z., Baskar Ganapathysubramanian, Matthew E. Gilbert, and Daniel Attinger. "In silico design of crop ideotypes under a wide range of water availability." Food and Energy Security (2019): e167. DOI: 10.1002/fes3.167. Posted with permission.</p
Automated reconstruction of cast-off blood spatter patterns based on Euclidean geometry and statistical likelihood
No full textCast-off spatter patterns exhibit linear trails of elliptical stains. These characteristic patterns occur by centrifugal forces that detach drops from a swinging object covered with blood or other liquid. This manuscript describes a method to reconstruct the motion, or swing, of the object. The method is based on stain inspection and Euclidean geometry. The reconstructed swing is represented as a three-dimensional region of statistical likelihood. The reconstruction uncertainty corresponds to the volume of the reconstructed region, which is specific to the uncertainties of the case at hand. Simple numerical examples show that the reconstruction method is able to reconstruct multiple swings that are either intersecting or adjacent to each other. The robustness, spatial convergence, computing time of the reconstruction method is characterized. For the purpose of this study, about 20 cast-off experiments are produced, with motion of the swinging object documented using video and/or accelerometers. The swings follow circular or arbitrary paths, and are either human- or machine-made. The reconstruction results are compared with the experimentally documented swings. Agreement between measured and reconstructed swings is very good, typically within less than 10 cm. The method used in this study is implemented as a numerical code written in an open source language, provided in an open access repository, for purposes of transparency and access.This is a manuscript of an article published as McCleary, Scott, Eugene Liscio, Kris De Brabanter, and Daniel Attinger. "Automated Reconstruction of Cast-off Blood Spatter Patterns based on Euclidean Geometry and Statistical Likelihood." Forensic Science International (2020): 110628. DOI: 10.1016/j.forsciint.2020.110628. Posted with permission.</p
- …
