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.

Neuronal Thy-1 induces astrocyte adhesion by engaging syndecan-4 in a cooperative interaction with alphavbeta3 integrin that activates PKCalpha and RhoA.

Clustering of alphavbeta3 integrin after interaction with the RGD-like integrin-binding sequence present in neuronal Thy-1 triggers formation of focal adhesions and stress fibers in astrocytes via RhoA activation. A putative heparin-binding domain is present in Thy-1, raising the possibility that this membrane protein stimulates astrocyte adhesion via engagement of an integrin and the proteoglycan syndecan-4. Indeed, heparin, heparitinase treatment and mutation of the Thy-1 heparin-binding site each inhibited Thy-1-induced RhoA activation, as well as formation of focal adhesions and stress fibers in DI TNC(1) astrocytes. These responses required both syndecan-4 binding and signaling, as evidenced by silencing syndecan-4 expression and by overexpressing a syndecan-4 mutant lacking the intracellular domain, respectively. Furthermore, lack of RhoA activation and astrocyte responses in the presence of a PKC inhibitor or a dominant-negative form of PKCalpha implicated PKCalpha and RhoA activation in these events. Therefore, combined interaction of the astrocyte alphavbeta3-integrin-syndecan-4 receptor pair with Thy-1, promotes adhesion to the underlying matrix via PKCalpha- and RhoA-dependent pathways. Importantly, signaling events triggered by such receptor cooperation are shown here to be the consequence of cell-cell rather than cell-matrix interactions. These observations are likely to be of widespread biological relevance because Thy-1-integrin binding is reportedly relevant to melanoma invasion, monocyte transmigration through endothelial cells and host defense mechanisms.

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.

Dyadic pulsations as a signature of sustainability in correspondence networks

In this paper, we introduce the concept of dyadic pulsations as a measure of sustainability in online discussion groups. Dyadic pulsations correspond to new communication exchanges occurring between two participants in a discussion group. A group that continuously integrates new participants in the on-going conversation is characterized by a steady dyadic pulsation rhythm. On the contrary, groups that either pursue close conversation or unilateral communication have no or very little dyadic pulsations. We show on two examples taken from Usenet discussion groups, that dyadic pulsations permit to anticipate future bursts in response delay time which are signs of group discussion collapses. We discuss ways of making this measure resilient to spam and other common algorithmic production that pollutes real discussions

Incremental neural networks for function approximation

A new strategy for incremental building of multilayer feedforward neural networks is proposed in the context of approximation of functions from R-p to R-q using noisy data. A stopping criterion based on the properties of the noise is also proposed. Experimental results for both artificial and real data are performed and two alternatives of the proposed construction strategy are compared.

KAP1 regulates gene networks controlling T-cell development and responsiveness.

Chromatin remodeling at specific genomic loci controls lymphoid differentiation. Here, we investigated the role played in this process by Kruppel-associated box (KRAB)-associated protein 1 (KAP1), the universal cofactor of KRAB-zinc finger proteins (ZFPs), a tetrapod-restricted family of transcriptional repressors. T-cell-specific Kap1-deleted mice displayed a significant expansion of immature thymocytes, imbalances in CD4(+)/CD8(+) cell ratios, and altered responses to TCR and TGFβ stimulation when compared to littermate KAP1 control mice. Transcriptome and chromatin studies revealed that KAP1 binds T-cell-specific cis-acting regulatory elements marked by the H3K9me3 repressive mark and enriched in Ikaros/NuRD complexes. Also, KAP1 directly controls the expression of several genes involved in TCR and cytokine signaling. Among these, regulation of FoxO1 seems to play a major role in this system. Likely responsible for tethering KAP1 to at least part of its genomic targets, a small number of KRAB-ZFPs are selectively expressed in T-lymphoid cells. These results reveal the so far unsuspected yet important role of KAP1-mediated epigenetic regulation in T-lymphocyte differentiation and activation.

Active solubilization and refolding of stable protein aggregates by cooperative unfolding action of individual hsp70 chaperones.

Hsp70 is a central molecular chaperone that passively prevents protein aggregation and uses the energy of ATP hydrolysis to solubilize, translocate, and mediate the proper refolding of proteins in the cell. Yet, the molecular mechanism by which the active Hsp70 chaperone functions are achieved remains unclear. Here, we show that the bacterial Hsp70 (DnaK) can actively unfold misfolded structures in aggregated polypeptides, leading to gradual disaggregation. We found that the specific unfolding and disaggregation activities of individual DnaK molecules were optimal for large aggregates but dramatically decreased for small aggregates. The active unfolding of the smallest aggregates, leading to proper global refolding, required the cooperative action of several DnaK molecules per misfolded polypeptide. This finding suggests that the unique ATP-fueled locking/unlocking mechanism of the Hsp70 chaperones can recruit random chaperone motions to locally unfold misfolded structures and gradually disentangle stable aggregates into refoldable proteins.

An architecture for adaptive replication-based multimedia streaming in P2P networks

This PhD thesis addresses the issue of scalable media streaming in large-scale networking environments. Multimedia streaming is one of the largest sink of network resources and this trend is still growing as testified by the success of services like Skype, Netflix, Spotify and Popcorn Time (BitTorrent-based). In traditional client-server solutions, when the number of consumers increases, the server becomes the bottleneck. To overcome this problem, the Content-Delivery Network (CDN) model was invented. In CDN model, the server copies the media content to some CDN servers, which are located in different strategic locations on the network. However, they require heavy infrastructure investment around the world, which is too expensive. Peer-to-peer (P2P) solutions are another way to achieve the same result. These solutions are naturally scalable, since each peer can act as both a receiver and a forwarder. Most of the proposed streaming solutions in P2P networks focus on routing scenarios to achieve scalability. However, these solutions cannot work properly in video-on-demand (VoD) streaming, when resources of the media server are not sufficient. Replication is a solution that can be used in these situations. This thesis specifically provides a family of replication-based media streaming protocols, which are scalable, efficient and reliable in P2P networks. First, it provides SCALESTREAM, a replication-based streaming protocol that adaptively replicates media content in different peers to increase the number of consumers that can be served in parallel. The adaptiveness aspect of this solution relies on the fact that it takes into account different constraints like bandwidth capacity of peers to decide when to add or remove replicas. SCALESTREAM routes media blocks to consumers over a tree topology, assuming a reliable network composed of homogenous peers in terms of bandwidth. Second, this thesis proposes RESTREAM, an extended version of SCALESTREAM that addresses the issues raised by unreliable networks composed of heterogeneous peers. Third, this thesis proposes EAGLEMACAW, a multiple-tree replication streaming protocol in which two distinct trees, named EAGLETREE and MACAWTREE, are built in a decentralized manner on top of an underlying mesh network. These two trees collaborate to serve consumers in an efficient and reliable manner. The EAGLETREE is in charge of improving efficiency, while the MACAWTREE guarantees reliability. Finally, this thesis provides TURBOSTREAM, a hybrid replication-based streaming protocol in which a tree overlay is built on top of a mesh overlay network. Both these overlays cover all peers of the system and collaborate to improve efficiency and low-latency in streaming media to consumers. This protocol is implemented and tested in a real networking environment using PlanetLab Europe testbed composed of peers distributed in different places in Europe.