Evolutionary Subnetworks in Complex Systems

Links in a practical network may have different functions, which makes the original network a combination of some functional subnetworks. Here, by a model of coupled oscillators, we investigate how such functional subnetworks are evolved and developed according to the network structure and dynamics. In particular, we study the case of evolutionary clustered networks in which the function of each link (either attractive or repulsive coupling) is updated by the local dynamics. It is found that, during the process of system evolution, the network is gradually stabilized into a particular form in which the attractive (repulsive) subnetwork consists only the intralinks (interlinks). Based on the properties of subnetwork evolution, we also propose a new algorithm for network partition which is distinguished by the convenient operation and fast computing speed.Comment: 4 pages, 4 figure

Study on thermal conductivity of gas phase in nano-porous aerogel

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.Nano-porous aerogel has an ultra low thermal conductivity and is usually used as the super insulator. To evaluate the insulation performance of the aerogel, we focus on studying the thermal conductivity of gas phase in the aerogel. We present a modified model to take into account the effect of nonuniform pore-size distribution on the gaseous thermal conductivity, and the present model predicts more agreement results with available data than the existing models. The gaseous thermal conductivity of the aerogel at high temperature gradient condition is also numerically studied. We also study the effect of the thermal transpiration flow on the gaseous thermal conductivity, and the results shows that the thermal transpiration flow effect leads to a reduction of the gaseous thermal conductivity

Small‐for‐size liver transplanted into larger recipient: A model of hepatic regeneration

Orthotopic liver transplantation was performed in 60 recipient rats weighing 200 to 250 gm. Sixty rats of the same strain were used as liver donors, 30 weighing 100 to 140 gm (small for size) and the other 30 weighing 200 to 250 gm (same size). After 1, 2, 3, 4, 7 and 14 days (n = 5 each) DNA synthesis, nuclear thymidine labeling and mitoses were increased in both the small‐for‐size and same‐size groups, but significantly more in the former. These changes were maximal after 48 to 72 hr, similar to but later than the well‐known regeneration response after partial hepatectomy, which peaks at 24 hr in rats. Indirect indexes of regeneration of the transplanted livers also were measured: plasma or serum ornithine decarboxylase; insulin and glucagon serum levels; estradiol and testosterone serum levels (and their nuclear and cytosolic receptors); and transforming growth factor‐ß, c‐Ha‐ras and c‐jun mRNA expressions. With the small‐for‐size transplantation, these followed the same delayed pattern as the direct regeneration parameters. The small livers gradually increased in size over the course of 1 to 2 wk and achieved a volume equal to that of the liver originally present in the recipient. In contrast, no significant liver weight gain occurred in the transplanted livers from same‐size donors despite the evidence of regeneration by direct indexes, but not by most of the surrogate parameters, including ornithine decarboxylase. (Hepatology 1993;19:210–216). Copyright © 1994 American Association for the Study of Liver Disease

Split Two-Higgs-Doublet Model and Neutrino Condensation

We split the two-Higgs-doublet model by assuming very different vevs for the two doublets: the vev is at weak scale (174 GeV) for the doublet \Phi_1 and at neutrino-mass scale (10^{-2} \sim 10^{-3} eV) for the doublet \Phi_2. \Phi_1 is responsible for giving masses to all fermions except neutrinos; while \Phi_2 is responsible for giving neutrino masses through its tiny vev without introducing see-saw mechanism. Among the predicted five physical scalars H, h, A^0 and H^{\pm}, the CP-even scalar h is as light as 10^{-2} \sim 10^{-3}eV while others are at weak scale. We identify h as the cosmic dark energy field and the other CP-even scalar H as the Standard Model Higgs boson; while the CP-odd A^0 and the charged H^{\pm} are the exotic scalars to be discovered at future colliders. Also we demonstrate a possible dynamical origin for the doublet \Phi_2 from neutrino condensation caused by some unknown dynamics.Comment: version in Europhys. Lett. (discussions added

Path probability distribution of stochastic motion of non dissipative systems: a classical analog of Feynman factor of path integral

We investigate, by numerical simulation, the path probability of non dissipative mechanical systems undergoing stochastic motion. The aim is to search for the relationship between this probability and the usual mechanical action. The model of simulation is a one-dimensional particle subject to conservative force and Gaussian random displacement. The probability that a sample path between two fixed points is taken is computed from the number of particles moving along this path, an output of the simulation, devided by the total number of particles arriving at the final point. It is found that the path probability decays exponentially with increasing action of the sample paths. The decay rate increases with decreasing randomness. This result supports the existence of a classical analog of the Feynman factor in the path integral formulation of quantum mechanics for Hamiltonian systems.Comment: 19 pages, 6 figures, 1 table. It is a new text based on arXiv:1202.0924 (to be withdrawn) with a completely different presentation. Accepted by Chaos, Solitons & Fractals for publication 201

Stable Hebbian learning from spike timing-dependent plasticity

We explore a synaptic plasticity model that incorporates recent findings that potentiation and depression can be induced by precisely timed pairs of synaptic events and postsynaptic spikes. In addition we include the observation that strong synapses undergo relatively less potentiation than weak synapses, whereas depression is independent of synaptic strength. After random stimulation, the synaptic weights reach an equilibrium distribution which is stable, unimodal, and has positive skew. This weight distribution compares favorably to the distributions of quantal amplitudes and of receptor number observed experimentally in central neurons and contrasts to the distribution found in plasticity models without size-dependent potentiation. Also in contrast to those models, which show strong competition Changes in the synaptic connections between neurons are widely believed to contribute to memory storage, and the activitydependen

Robustness and Enhancement of Neural Synchronization by Activity-Dependent Coupling

We study the synchronization of two model neurons coupled through a synapse having an activity-dependent strength. Our synapse follows the rules of Spike-Timing Dependent Plasticity (STDP). We show that this plasticity of the coupling between neurons produces enlarged frequency locking zones and results in synchronization that is more rapid and much more robust against noise than classical synchronization arising from connections with constant strength. We also present a simple discrete map model that demonstrates the generality of the phenomenon.Comment: 4 pages, accepted for publication in PR