First contribution of mites (Acari) to the forensic analysis of hanged corpses: a case study from Spain

This case study from North Spain, highlights the importance of the collection of mites in addition to insects, from crime scenes or corpses subjected to environmental constraints that reduce or minimise insect activity, such as hanged corpses. In addition, this analysis highlights the relevance of arthropods’ collection in the field, even after the corpse has been moved away for autopsy. Four species of mites, phoretic on carrion (Silphidae) and rove (Staphylinidae) beetles, complemented and reinforced the autopsy analysis as well as the scarce information provided by insect activity. Poecilochirus carabi Canestrini & Canestrini, 1882 and Poecilochirus (Physoparasitus) davydovae Hyatt, 1980 (Mesostigmata: Parasitidae) were found in association with two Silphidae, Nicrophorus Fabricius, 1775 and Necrodes Leach, 1815, only when sampled in the autopsy room; this is suggestive of host-switching of mites and was likely due to the lack of availability of specific carriers in the field. The interpretation of the activity of Parasitidae mites both in the field and the autopsy room allows a better understanding of the timing and circumstances of decomposition. Phoretic deutonymphs of Pelzneria Scheucher 1957 (Astigmata: Histiostomatidae) were highly abundant, mostly P. crenulata Oudemans, 1909 and are reported for the first time on a Staphylinidae rove beetle, Creophilus maxillosus (L., 1758). Surprisingly, in this case study no Pelzneria were associated with the Silphidae found, which are their most common hosts, such as Necrodes littoralis (L., 1758) and Nicrophorus interruptus (Stephens, 1830). All histiostomatids were removed from the staphylinid (rove beetle) collected from the soil, at the scene of death, suggesting a recent arrival of the beetle. The occurrence of Staphylinidae beetles and their associated mites, such as Parasitidae and Pelzneria, and the information they provided would have been easily overlooked or lost if only the autopsy sampling would have been considered in the analysis of the case. The four mite species are reported for the first time for the Iberian Peninsula.

Sex/gender differences and autism: setting the scene for future research

Objective The relationship between sex/gender differences and autism has attracted a variety of research ranging from clinical, neurobiological to etiological, stimulated by the male bias in autism prevalence. Findings are complex and do not always relate to each other in a straightforward manner. Distinct but interlinked questions on the relationship between sex/gender differences and autism remain under addressed. To better understand the implications from existing research and to help design future studies, we propose a four-level conceptual framework to clarify the embedded themes. Method We searched PubMed for publications before September 2014 using search terms “‘sex OR gender OR females’ AND autism.” 1,906 citations were screened for relevance, along with publications identified via additional literature reviews, resulting in 329 reports that were reviewed. Results Level 1 “Nosological and diagnostic challenges” concerns the question “How should autism be defined and diagnosed in males and females?” Level 2 “Sex/gender-independent and sex/gender-dependent characteristics” addresses the question “What are the similarities and differences between males and females with autism?” Level 3 “General models of etiology: liability and threshold” asks the question “How is the liability for developing autism linked to sex/gender?” Level 4 “Specific etiological-developmental mechanisms” focuses on the question “What etiological-developmental mechanisms of autism are implicated by sex/gender and/or sexual/gender differentiation?” Conclusions Using this conceptual framework, findings can be more clearly summarized, and the implications of the links between findings from different levels can become clearer. Based on this four-level framework, we suggest future research directions, methodology, and specific topics in sex/gender differences and autism.

Scene understanding for auto-calibration of surveillance cameras

In the last decade, several research results have presented formulations for the auto-calibration problem. Most of these have relied on the evaluation of vanishing points to extract the camera parameters. Normally vanishing points are evaluated using pedestrians or the Manhattan World assumption i.e. it is assumed that the scene is necessarily composed of orthogonal planar surfaces. In this work, we present a robust framework for auto-calibration, with improved results and generalisability for real-life situations. This framework is capable of handling problems such as occlusions and the presence of unexpected objects in the scene. In our tests, we compare our formulation with the state-of-the-art in auto-calibration using pedestrians and Manhattan World-based assumptions. This paper reports on the experiments conducted using publicly available datasets; the results have shown that our formulation represents an improvement over the state-of-the-art.

Chaotic synchronization in general network topology for scene segmentation

Chaotic synchronization has been discovered to be an important property of neural activities, which in turn has encouraged many researchers to develop chaotic neural networks for scene and data analysis. In this paper, we study the synchronization role of coupled chaotic oscillators in networks of general topology. Specifically, a rigorous proof is presented to show that a large number of oscillators with arbitrary geometrical connections can be synchronized by providing a sufficiently strong coupling strength. Moreover, the results presented in this paper not only are valid to a wide class of chaotic oscillators, but also cover the parameter mismatch case. Finally, we show how the obtained result can be applied to construct an oscillatory network for scene segmentation.

Chaotic synchronization in 2D lattice for scene segmentation

Synchronization and chaos play important roles in neural activities and have been applied in oscillatory correlation modeling for scene and data analysis. Although it is an extensively studied topic, there are still few results regarding synchrony in locally coupled systems. In this paper we give a rigorous proof to show that large numbers of coupled chaotic oscillators with parameter mismatch in a 2D lattice can be synchronized by providing a sufficiently large coupling strength. We demonstrate how the obtained result can be applied to construct an oscillatory network for scene segmentation. (C) 2007 Elsevier B.V. All rights reserved.

Novel Application of 2D and 3D-Similarity Searches To Identify Substrates among Cytochrome P450 2C9, 2D6, and 3A4

Cytochrome P450 (CYP450) is a class of enzymes where the substrate identification is particularly important to know. It would help medicinal chemists to design drugs with lower side effects due to drug-drug interactions and to extensive genetic polymorphism. Herein, we discuss the application of the 2D and 3D-similarity searches in identifying reference Structures with higher capacity to retrieve Substrates of three important CYP enzymes (CYP2C9, CYP2D6, and CYP3A4). On the basis of the complementarities of multiple reference structures selected by different similarity search methods, we proposed the fusion of their individual Tanimoto scores into a consensus Tanimoto score (T(consensus)). Using this new score, true positive rates of 63% (CYP2C9) and 81% (CYP2D6) were achieved with false positive rates of 4% for the CYP2C9-CYP2D6 data Set. Extended similarity searches were carried out oil a validation data set, and the results showed that by using the T(consensus) score, not only the area of a ROC graph increased, but also more substrates were recovered at the beginning of a ranked list.

A scenario-driven decision support system for serious crime investigation

Consideration of a wide range of plausible crime scenarios during any crime investigation is important to seek convincing evidence and hence to minimize the likelihood of miscarriages of justice. It is equally important for crime investigators to be able to employ effective and efficient evidence-collection strategies that are likely to produce the most conclusive information under limited available resources. An intelligent decision support system that can assist human investigators by automatically constructing plausible scenarios, and reasoning with the likely best investigating actions will clearly be very helpful in addressing these challenging problems. This paper presents a system for creating scenario spaces from given evidence, based on an integrated application of techniques for compositional modelling and Bayesian network-based evidence evaluation. Methods of analysis are also provided by the use of entropy to exploit the synthesized scenario spaces in order to prioritize investigating actions and hypotheses. These theoretical developments are illustrated by realistic examples of serious crime investigation.

Knowledge based crime scenario modelling

A crucial concern in the evaluation of evidence related to a major crime is the formulation of sufficient alternative plausible scenarios that can explain the available evidence. However, software aimed at assisting human crime investigators by automatically constructing crime scenarios from evidence is difficult to develop because of the almost infinite variation of plausible crime scenarios. This paper introduces a novel knowledge driven methodology for crime scenario construction and it presents a decision support system based on it. The approach works by storing the component events of the scenarios instead of entire scenarios and by providing an algorithm that can instantiate and compose these component events into useful scenarios. The scenario composition approach is highly adaptable to unanticipated cases because it allows component events to match the case under investigation in many different ways. Given a description of the available evidence, it generates a network of plausible scenarios that can then be analysed to devise effective evidence collection strategies. The applicability of the ideas presented here are demonstrated by means of a realistic example and prototype decision support software.