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network topology

Alberto Baggioli, Carlo A Cavallotti, Antonino Famulari
From proteins and peptides to semiconducting polymers, aliphatic chains on aromatic groups are recurring motifs in macromolecules from very diverse application fields. Fields in which molecular folding and packing determine the macroscopic physical properties that make such advanced materials appealing in the first place. Within each macromolecule, the intrinsic structure of each unit defines how it interacts with its neighbours, ultimately opening up or denying certain backbone conformations. This eventually also determines how macromolecules interact with each other...
October 18, 2016: Physical Chemistry Chemical Physics: PCCP
Negisa Darajeh, Azni Idris, Hamid Reza Fard Masoumi, Abolfazl Nourani, Paul Truong, Shahabaldin Rezania
Artificial neural networks (ANN) have been widely used to solve the problems because of their reliable, robust, and salient characteristics in capturing the non-linear relationships between variables in complex systems. In this study ANN was applied for modeling of COD and BOD removal from Palm Oil Mill Secondary Effluent (POMSE) by Vetiver system. The independent variable including POMSE concentration, Vetiver slips density, and removal time has been considered as input parameters to optimize the network, while the removal percentage of COD and BOD were selected as output...
October 17, 2016: International Journal of Phytoremediation
Rainer Engelken, Farzad Farkhooi, David Hansel, Carl van Vreeswijk, Fred Wolf
Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics. Various theoretical studies predict that the rich dynamics of rate models operating in the chaotic regime can subserve circuit computation and learning. Neurons in the brain, however, communicate via spikes and it is a theoretical challenge to obtain similar rate fluctuations in networks of spiking neuron models...
2016: F1000Research
Chensong Li, Jun Zhao
In this work, we investigate the output synchronization problem for discrete-time dynamical networks with identical nodes. Firstly, if each node of a network is geometrically incrementally dissipative, the entire network can be viewed as a geometrically dissipative nonlinear system by choosing a particular input-output pair. Then, based on the geometrical dissipativity property, we consider two cases: output synchronization under arbitrary topology and switching topology, respectively. For the first case, we establish several criteria of output synchronization under arbitrary switching between a set of connection topologies by employing a common Lyapunov function...
October 12, 2016: ISA Transactions
Michelle N Servaas, Linda Geerligs, Jojanneke A Bastiaansen, Remco J Renken, Jan-Bernard C Marsman, Ilja M Nolte, Johan Ormel, André Aleman, Harriëtte Riese
Neuroticism and genetic variation in the serotonin-transporter (SLC6A4) and catechol-O-methyltransferase (COMT) gene are risk factors for psychopathology. Alterations in the functional integration and segregation of neural circuits have recently been found in individuals scoring higher on neuroticism. The aim of the current study was to investigate how genetic risk factors impact functional network organization and whether genetic risk factors moderate the association between neuroticism and functional network organization...
October 14, 2016: Brain Imaging and Behavior
P Zhang, L Tao, X Zeng, C Qin, S Y Chen, F Zhu, S Y Yang, Z R Li, W P Chen, Y Z Chen
The studies of biological, disease and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web-servers for computing network descriptors, but many descriptors are not covered including those used or useful for biological studies...
October 11, 2016: Journal of Molecular Biology
Jiaolong Qin, Haiyan Liu, Maobin Wei, Ke Zhao, Jianhuai Chen, Jingyu Zhu, Xiangyu Shen, Rui Yan, Zhijian Yao, Qing Lu
BACKGROUND: The role of abnormal communications among large-scale brain networks have been given increasing attentions in the pathophysiology of major depressive disorder (MDD). However, few studies have investigated the effect of antidepressant medication treatment on the information communication of structural brain networks, especially converged from the individual analysis. METHODS: Nineteen unipolar MDD patients completed two diffusion tensor imaging (DTI) scans before and after 8-week treatment with selective serotonin reuptake inhibitor...
September 29, 2016: Journal of Affective Disorders
Behnam Behinaein, Karen Rudie, Waheed Sangrar
Epidermal Growth Factor Receptor (EGFR) signaling to the Ras-MAPK pathway is implicated in the development and progression of cancer and is a major focus of targeted combination therapies. Physiochemical models have been used for identifying and testing the signal-inhibiting potential of targeted therapies, however, their application to larger multi-pathway networks is limited by the availability of experimentally-determined rate and concentration parameters. An alternate strategy for identifying and evaluating drug-targetable nodes is proposed...
October 3, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
María Pereda
In this work, we aim to contribute to the understanding of human prosocial behavior by studying the influence that a particular form of social pressure, "being watched," has on the evolution of cooperative behavior. We study how cooperation emerges in multiplex complex topologies by analyzing a particular bidirectionally coupled dynamics on top of a two-layer multiplex network (duplex). The coupled dynamics appears between the prisoner's dilemma game in a network and a threshold cascade model in the other. The threshold model is intended to abstract the behavior of a network of vigilant nodes that impose the pressure of being observed altering hence the temptation to defect of the dilemma...
September 2016: Physical Review. E
Jason Hindes, Klementyna Szwaykowska, Ira B Schwartz
Swarming behavior continues to be a subject of immense interest because of its centrality in many naturally occurring systems in physics and biology, as well as its importance in applications such as robotics. Here we examine the effects on swarm pattern formation from delayed communication and topological heterogeneity, and in particular, the inclusion of a relatively small number of highly connected nodes, or "motherships," in a swarm's communication network. We find generalized forms of basic patterns for networks with general degree distributions, and a variety of dynamic behaviors including parameter regions with multistability and hybrid motions in bimodal networks...
September 2016: Physical Review. E
Marco A Amaral, Lucas Wardil, Matjaž Perc, Jafferson K L da Silva
In times of plenty expectations rise, just as in times of crisis they fall. This can be mathematically described as a win-stay-lose-shift strategy with dynamic aspiration levels, where individuals aspire to be as wealthy as their average neighbor. Here we investigate this model in the realm of evolutionary social dilemmas on the square lattice and scale-free networks. By using the master equation and Monte Carlo simulations, we find that cooperators coexist with defectors in the whole phase diagram, even at high temptations to defect...
September 2016: Physical Review. E
Chad Giusti, Lia Papadopoulos, Eli T Owens, Karen E Daniels, Danielle S Bassett
Developing quantitative methods for characterizing structural properties of force chains in densely packed granular media is an important step toward understanding or predicting large-scale physical properties of a packing. A promising framework in which to develop such methods is network science, which can be used to translate particle locations and force contacts into a graph in which particles are represented by nodes and forces between particles are represented by weighted edges. Recent work applying network-based community-detection techniques to extract force chains opens the door to developing statistics of force-chain structure, with the goal of identifying geometric and topological differences across packings, and providing a foundation on which to build predictions of bulk material properties from mesoscale network features...
September 2016: Physical Review. E
Tanmoy Banerjee, Partha Sharathi Dutta, Anna Zakharova, Eckehard Schöll
This paper reports the occurrence of several chimera patterns and the associated transitions among them in a network of coupled oscillators, which are connected by a long-range interaction that obeys a distance-dependent power law. This type of interaction is common in physics and biology and constitutes a general form of coupling scheme, where by tuning the power-law exponent of the long-range interaction the coupling topology can be varied from local via nonlocal to global coupling. To explore the effect of the power-law coupling on collective dynamics, we consider a network consisting of a realistic ecological model of oscillating populations, namely the Rosenzweig-MacArthur model, and show that the variation of the power-law exponent mediates transitions between spatial synchrony and various chimera patterns...
September 2016: Physical Review. E
Yang Yang, Filippo Radicchi
We consider the observability model in networks with arbitrary topologies. We introduce a system of coupled nonlinear equations, valid under the locally treelike ansatz, to describe the size of the largest observable cluster as a function of the fraction of directly observable nodes present in the network. We perform a systematic analysis on 95 real-world graphs and compare our theoretical predictions with numerical simulations of the observability model. Our method provides almost perfect predictions in the majority of the cases, even for networks with very large values of the clustering coefficient...
September 2016: Physical Review. E
M J Paldino, F Golriz, M L Chapieski, W Zhang, Z D Chu
BACKGROUND AND PURPOSE: The biologic basis for intelligence rests to a large degree on the capacity for efficient integration of information across the cerebral network. We aimed to measure the relationship between network architecture and intelligence in the pediatric, epileptic brain. MATERIALS AND METHODS: Patients were retrospectively identified with the following: 1) focal epilepsy; 2) brain MR imaging at 3T, including resting-state functional MR imaging; and 3) full-scale intelligence quotient measured by a pediatric neuropsychologist...
October 13, 2016: AJNR. American Journal of Neuroradiology
Hussein A Hejase, Kevin J Liu
BACKGROUND: Branching events in phylogenetic trees reflect bifurcating and/or multifurcating speciation and splitting events. In the presence of gene flow, a phylogeny cannot be described by a tree but is instead a directed acyclic graph known as a phylogenetic network. Both phylogenetic trees and networks are typically reconstructed using computational analysis of multi-locus sequence data. The advent of high-throughput sequencing technologies has brought about two main scalability challenges: (1) dataset size in terms of the number of taxa and (2) the evolutionary divergence of the taxa in a study...
October 13, 2016: BMC Bioinformatics
Michelangelo Puliga, Andrea Flori, Giuseppe Pappalardo, Alessandro Chessa, Fabio Pammolli
The role of Network Theory in the study of the financial crisis has been widely spotted in the latest years. It has been shown how the network topology and the dynamics running on top of it can trigger the outbreak of large systemic crisis. Following this methodological perspective we introduce here the Accounting Network, i.e. the network we can extract through vector similarities techniques from companies' financial statements. We build the Accounting Network on a large database of worldwide banks in the period 2001-2013, covering the onset of the global financial crisis of mid-2007...
2016: PloS One
Anida Sarajlić, Noël Malod-Dognin, Ömer Nebil Yaveroğlu, Nataša Pržulj
We are flooded with large-scale, dynamic, directed, networked data. Analyses requiring exact comparisons between networks are computationally intractable, so new methodologies are sought. To analyse directed networks, we extend graphlets (small induced sub-graphs) and their degrees to directed data. Using these directed graphlets, we generalise state-of-the-art network distance measures (RGF, GDDA and GCD) to directed networks and show their superiority for comparing directed networks. Also, we extend the canonical correlation analysis framework that enables uncovering the relationships between the wiring patterns around nodes in a directed network and their expert annotations...
October 13, 2016: Scientific Reports
Taichi Haruna, Yuuya Fujiki
We investigate the influence of the small-world topology on the composition of information flow on networks. By appealing to the combinatorial Hodge theory, we decompose information flow generated by random threshold networks on the Watts-Strogatz model into three components: gradient, harmonic and curl flows. The harmonic and curl flows represent globally circular and locally circular components, respectively. The Watts-Strogatz model bridges the two extreme network topologies, a lattice network and a random network, by a single parameter that is the probability of random rewiring...
2016: Frontiers in Neural Circuits
XiaoHao Sun, HengAn Wu, Rong Long
We study a covalent adaptable polymer that can rearrange its network topology through thermally activated bond exchange reactions. When the polymer is deformed, such a network rearrangement leads to macroscopic stress relaxation, which allows the polymer to be thermoformed without a mold. Based on a previously developed constitutive model, we investigate thermal-mechanical behaviors of this material under a non-uniform and evolving temperature field through numerical simulations. Our focus is on the complex coupling between mechanical deformation, heat conduction and bond exchange reactions...
October 12, 2016: Soft Matter
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