Nonlinear aeroelastic reduced order modeling by recurrent neural networks

The paper develops a reduction scheme based on the identification of continuous time recursive neural networks from input–output data obtained through high fidelity simulations of a nonlinear aerodynamic model at hand. The training of network synaptic weights is accomplished either with standard or automatic differentiation integration techniques. Particular emphasis is given to using such a reduced system in the determination of aeroelastic limit cycles. The related solutions are obtained with the adoption of two different approaches: one trivially producing a limit cycle through time marching simulations, and the other solving a periodic boundary value problem through a direct periodic time collocation with unknown period. The presented formulations are verified for a typical section and the BACT wing.     

导电聚合物的纳米结构及其在生物医学领域的应用

由于表面效应、小尺寸效应和量子效应,使纳米结构的导电聚合物材料与传统聚合物材料相比,显示出更优越的性能。基于神经组织对电场和电刺激敏感性,使得导电聚合物纳米材料在生物医学应用方面很有前景。本文综述了纳米结构的导电聚合物的合成方法,及其在生物医学领域的应用。合成方法主要关注于硬模板法、软模板法和无模板自组装法,以及这些方法中导电聚合物纳米结构的形成机理。总结了具有纳米结构的导电聚合物,如纳米颗粒、纳米纤维和纳米管等作为神经电极涂层材料和生物传感器等方面的应用。     

神经网络在ACE抑制肽QSAR中的应用研

通过对天然氨基酸的457种物化性质参数进行主成分分析后得到SVHEHS描述符,用该描述符分别对血管紧张素转化酶(ACE)抑制二肽、三肽、四肽进行表征,并建立了肽结构与活性的神经网络模型。ACE抑制二肽神经网络模型的相关系数、交叉验证相关系数、均方根误差和外部验证相关系数分别为0.946、0.951、0.249、0.852,三肽模型分别为0.973、0.945、0.135、0.813,四肽模型分别为0.915、0.879、0.250、0.814。由此表明SVHEHS描述符结合神经网络对ACE抑制肽的建模效果及模型预测能力均较理想,在此基础上进一步通过平均影响值(Mean impact value,MIV)法确定了显著影响各类肽活性的结构因素,从而为新的强活性ACE抑制肽的分子设计提供了理论基础。     

Chemical network algorithms for the risk assessment and management of chemical threats

A network of chemical threats: Current regulatory protocols are insufficient to monitor and block many short-route syntheses of chemical weapons, including those that start from household products. Network searches combined with game-theory algorithms provide an effective means of identifying and eliminating chemical threats. (Picture: an algorithm-detected pathway that yields sarin (bright red node) in three steps from unregulated substances.).     

Competing edge networks

We introduce a model for a pair of nonlinear evolving networks, defined over a common set of vertices, subject to edgewise competition. Each network may grow new edges spontaneously or through triad closure. Both networks inhibit the other?s growth and encourage the other?s demise. These nonlinear stochastic competition equations yield to a mean field analysis resulting in a nonlinear deterministic system. There may be multiple equilibria; and bifurcations of different types are shown to occur within a reduced parameter space. This situation models competitive communication networks such as BlackBerry Messenger displacing SMS; or instant messaging displacing emails.     

Emergence of complex networks from diffusion on fractal lattices. A special case of the Sierpinski gasket and tetrahedron

A new approach to the assemblage of complex networks displaying the scale-free architecture is proposed. While the growth and the preferential attachment of incoming nodes assure an emergence of such networks according to the Barabási–Albert model, it is argued here that the preferential linking condition needs not to be a principal rule. To assert this statement a simple computer model based on random walks on fractal lattices is introduced. It is shown that the model successfully reproduces the degree distributions, the ultra-small-worldness and the high clustering arising from the topology of scale-free networks.     

Ecological interaction and phylogeny, studying functionality on composed networks

We study a class of composed networks that are formed by two tree networks, T_P and T_A, whose end points touch each other through a bipartite network B_PA. We explore this network using a functional approach. We are interested in how much the topology, or the structure, of T_X (X=A or P) determines the links of B_PA. This composed structure is a useful model in evolutionary biology, where T_P and T_A are the phylogenetic trees of plants and animals that interact in an ecological community. We make use of ecological networks of dispersion of fruits, which are formed by frugivorous animals and plants with fruits; the animals, usually birds, eat fruits and disperse their seeds. We analyse how the phylogeny of T_X determines or is correlated with B_PA using a Monte Carlo approach. We use the phylogenetic distance among elements that interact with a given species to construct an index κ that quantifies the influence of T_X over B_PA. The algorithm is based on the assumption that interaction matrices that follows a phylogeny of T_X have a total phylogenetic distance smaller than the average distance of an ensemble of Monte Carlo realisations. We find that the effect of phylogeny of animal species is more pronounced in the ecological matrix than plant phylogeny.     

The influence of connectivity on the firing rate in a neuronal network with electrical and chemical synapses

We study the firing rate properties of a cellular automaton model for a neuronal network with chemical synapses. We propose a simple mechanism in which the nonlocal connections are included, through electrical and chemical synapses. In the latter case, we introduce a time delay which produces self-sustained activity. Nonlocal connections, or shortcuts, are randomly introduced according to a specified connection probability. There is a range of connection probabilities for which neuron firing occurs, as well as a critical probability for which the firing ceases in the absence of time delay. The critical probability for nonlocal shortcuts depends on the network size according to a power-law. We also compute the firing rate amplification factor by varying both the connection probability and the time delay for different network sizes.     

Analysis of the effects of the global financial crisis on the Turkish economy, using hierarchical methods

We have analyzed the topology of 50 important Turkish companies for the period 2006-2010 using the concept of hierarchical methods (the minimal spanning tree (MST) and hierarchical tree (HT)). We investigated the statistical reliability of links between companies in the MST by using the bootstrap technique. We also used the average linkage cluster analysis (ALCA) technique to observe the cluster structures much better. The MST and HT are known as useful tools to perceive and detect global structure, taxonomy, and hierarchy in financial data. We obtained four clusters of companies according to their proximity. We also observed that the Banks and Holdings cluster always forms in the centre of the MSTs for the periods 2006-2007, 2008, and 2009-2010. The clusters match nicely with their common production activities or their strong interrelationship. The effects of the Automobile sector increased after the global financial crisis due to the temporary incentives provided by the Turkish government. We find that Turkish companies were not very affected by the global financial crisis.     

The emergence of leadership in social networks

We study a networked version of the minority game in which agents can choose to follow the choices made by a neighbouring agent in a social network. We show that for a wide variety of networks a leadership structure always emerges, with most agents following the choice made by a few agents. We find a suitable parameterisation which highlights the universal aspects of the behaviour and which also indicates where results depend on the type of social network.