Modeling the forensic two-trace problem with Bayesian networks

The forensic two-trace problem is a perplexing inference problem introduced by Evett (J Forensic Sci Soc 27:375-381, 1987). Different possible ways of wording the competing pair of propositions (i.e., one proposition advanced by the prosecution and one proposition advanced by the defence) led to different quantifications of the value of the evidence (Meester and Sjerps in Biometrics 59:727-732, 2003). Here, we re-examine this scenario with the aim of clarifying the interrelationships that exist between the different solutions, and in this way, produce a global vision of the problem. We propose to investigate the different expressions for evaluating the value of the evidence by using a graphical approach, i.e. Bayesian networks, to model the rationale behind each of the proposed solutions and the assumptions made on the unknown parameters in this problem.

Testing Spatial Autocorrelation in Weighted Networks : the Modes Permutation Test

In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

Morphometric shape analysis using learning vector quantization neural networks - an example distinguishing two microtine vole species

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

On circuit functionality in boolean networks.

It has been proved, for several classes of continuous and discrete dynamical systems, that the presence of a positive (resp. negative) circuit in the interaction graph of a system is a necessary condition for the presence of multiple stable states (resp. a cyclic attractor). A positive (resp. negative) circuit is said to be functional when it "generates" several stable states (resp. a cyclic attractor). However, there are no definite mathematical frameworks translating the underlying meaning of "generates." Focusing on Boolean networks, we recall and propose some definitions concerning the notion of functionality along with associated mathematical results.

Attentional networks efficiency in preterm children.

Recent studies have reported specific executive and attentional deficits in preterm children. However, the majority of this research has used multidetermined tasks to assess these abilities, and the interpretation of the results lacks an explicit theoretical backdrop to better understand the origin of the difficulties observed. In the present study, we used the Child Attention Network Task (Child ANT; Rueda et al. 2004) to assess the efficiency of the alerting, orienting and executive control networks. We compared the performance of 25 preterm children (gestational age < or = 32 weeks) to 25 full-term children, all between 5(1/2) and 6(1/2) years of age. Results showed that, as compared to full-term children, preterm children were slower on all conditions of the Child ANT and had a specific deficit in executive control abilities. We also observed a significantly higher correlation between the orienting and executive control networks in the preterm group, suggesting less differentiation of these two networks in this population.

Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.

Emergence of Cooperation on Static and Dynamic Networks

Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.

Poly-N-acetyl glucosamine fibers are synergistic with vacuum-assisted closure in augmenting the healing response of diabetic mice.

BACKGROUND: Vacuum-assisted closure (VAC) has become the preferred modality to treat many complex wounds but could be further improved by methods that minimize bleeding and facilitate wound epithelialization. Short fiber poly-N-acetyl glucosamine nanofibers (sNAG) are effective hemostatic agents that activate platelets and facilitate wound epithelialization. We hypothesized that sNAG used in combination with the VAC device could be synergistic in promoting wound healing while minimizing the risk of bleeding. METHODS: Membranes consisting entirely of sNAG nanofibers were applied immediately to dorsal excisional wounds of db/db mice followed by application of the VAC device. Wound healing kinetics, angiogenesis, and wound-related growth factor expression were measured. RESULTS: The application of sNAG membranes to wounds 24 hours before application of the VAC device was associated with a significant activation of wounds (expression of PDGF, TGFβ, EGF), superior granulation tissue formation rich in Collagen I as well as superior wound epithelialization (8.6% ± 0.3% vs. 1.8% ± 1.1% of initial wound size) and wound contraction. CONCLUSIONS: The application of sNAG fiber-containing membranes before the application of the polyurethane foam interface of VAC devices leads to superior healing in db/db mice and represents a promising wound healing adjunct that can also reduce the risk of bleeding complications.

A collagen-poly(lactic acid-co-ɛ-caprolactone) hybrid scaffold for bladder tissue regeneration.

Scaffold materials should favor cell attachment and proliferation, and provide designable 3D structures with appropriate mechanical strength. Collagen matrices have proven to be beneficial scaffolds for tissue regeneration. However, apart from small intestinal submucosa, they offer a limited mechanical strength even if crosslinking can enhance their mechanical properties. A more cell-friendly way to increase material strength is to combine synthetic polymer meshes with plastic compressed collagen gels. This work describes the potential of plastic compressed collagen-poly(lactic acid-co-ɛ-caprolactone) (PLAC) hybrids as scaffolds for bladder tissue regeneration. Human bladder smooth muscle and urothelial cells were cultured on and inside collagen-PLAC hybrids in vitro. Scaffolds were analyzed by electron microscopy, histology, immunohistochemistry, and AlamarBlue assay. Both cell types proliferated in and on the hybrid, forming dense cell layers on top after two weeks. Furthermore, hybrids were implanted subcutaneously in the backs of nude mice. Host cell infiltration, scaffold degradation, and the presence of the seeded bladder cells were analyzed. Hybrids showed a lower inflammatory reaction in vivo than PLAC meshes alone, and first signs of polymer degradation were visible at six months. Collagen-PLAC hybrids have potential for bladder tissue regeneration, as they show efficient cell seeding, proliferation, and good mechanical properties.