Three-sphere low-Reynolds-number swimmer with a cargo container

A recently introduced model for an autonomous swimmer at low Reynolds number that is comprised of three spheres connected by two arms is considered when one of the spheres has a large radius. The Stokes hydrodynamic flow associated with the swimming strokes and net motion of this system can be studied analytically using the Stokes Green's function of a point force in front of a sphere of arbitrary radius R provided by Oseen. The swimming velocity is calculated, and shown to scale as 1/R ³ with the radius of the sphere.     

Comparison of the energetic properties and the dynamical stability in a mathematical model of the stretch reflex

The previous studies on finite-time thermodynamic engines have shown that some of the parameters affecting their thermodynamic performance also affect their stability. Moreover, such parameters have to be tuned to reach an optimal trade-off between these two generic properties. In the present work we carry out a similar analysis on a mathematical model of the stretch reflex regulatory pathway, which is a simplified version of a previously published model. We show that the model has a unique stable fixed point in the absence of time delays. However, when the system inherent time delays are considered, they can destabilize the fixed point and engender a stable limit cycle. We further explore the parameter space to analyse the sensitivity of the system stability to variations in the parameter values. Particular attention is paid to the parameter here denoted as α, which has been shown to determine the muscle thermodynamic properties during steady-state contractions: larger values of α mean more powerful and less efficient muscles. Our results indicate that the stretch reflex pathway is less stable in the more powerful and less efficient muscles. We finally compare these observations with those obtained on thermal engines.     

Generalized relative entropy in functional magnetic resonance imaging

The generalized Kullback-Leibler distance D_q (q is the Tsallis parameter) is shown to be an useful measure for analysis of functional magnetic resonance imaging (fMRI) data series. This generalized form of entropy is used to evaluate the “distance” between the probability functions p₁ and p₂ of the signal levels related to periods of stimulus and non-stimulus in event-related fMRI experiments. The probability densities of the mean distance (averaged over the N epochs of the entire experiment) are obtained through numerical simulations for different values of signal-to-noise ratio (SNR) and found to be fitted very well by Gamma distributions (χ²<0.0008) for small values of N (N<30). These distributions allow us to determine the sensitivity and specificity of the method by construction of the receiver operating characteristic (ROC) curves. The performance of the method is also investigated in terms of the parameters q and L (number of signal levels) and our results indicate that the optimum choice is q=0.8 and L=3. The entropic index q is found to exert control on both sensitivity and specificity of the method. As q (q>0) is raised, sensitivity increases but specificity decreases. Finally, the method is applied in the analysis of a real event-related fMRI motor stimulus experiment and the resulting maps show activation in primary and secondary motor brain areas.     

Rényi and Tsallis entropies for incomplete or overcomplete systems of events

In this article, Shannon, Rényi and Tsallis entropies are considered for a system of events characterized by an arbitrary probability distribution P that can be incomplete, complete or overcomplete. After a suitable transformation that leads to the escort probabilities of P, these can be written as the canonical probability distribution for a set of pseudo-energies (Hartley information, E_n=−lnP_n) and a dimensionless parameter q that plays the role of thermodynamics β. Several relations between the entropies are presented, including the analysis of compound systems. The method is illustrated with an example.     

Genetically engineered cardiac pacemaker: Stem cells transfected with HCN2 gene and myocytes—A model

One of the successfully tested methods to design genetically engineered cardiac pacemaker cells consists in transfecting a human mesenchymal stem cell (hMSC) with a HCN2 gene and connecting it to a myocyte. We develop and study a mathematical model, describing a myocyte connected to a hMSC transfected with a HCN2 gene. The cardiac action potential is described both with the simple Beeler-Reuter model, as well as with the elaborate dynamic Luo-Rudy model. The HCN2 channel is described by fitting electrophysiological records, in the spirit of Hodgkin-Huxley. The model shows that oscillations can occur in a pair myocyte-stem cell, that was not observed in the experiments yet. The model predicted that: (1) HCN pacemaker channels can induce oscillations only if the number of expressed IK1 channels is low enough. At too high an expression level of IK1 channels, oscillations cannot be induced, no matter how many pacemaker channels are expressed. (2) At low expression levels of IK1 channels, a large domain of values in the parameter space (n, N) exists, where oscillations should be observed. We denote N the number of expressed pacemaker channels in the stem cell, and n the number of gap junction channels coupling the stem cell and the myocyte. (3) The expression levels of IK1 channels observed in ventricular myocytes, both in the Beeler-Reuter and in the dynamic Luo-Rudy models are too high to allow to observe oscillations. With expression levels below ∼1/4 of the original value, oscillations can be observed. The main consequence of this work is that in order to obtain oscillations in an experiment with a myocyte-stem cell pair, increasing the values of n, N is unlikely to be helpful, unless the expression level of IK1 has been reduced enough. The model also allows us to explore levels of gene expression not yet achieved in experiments, and could be useful to plan new experiments, aimed at improving the robustness of the oscillations.     

A Tsallis’ statistics based neural network model for novel word learning

We invoke the Tsallis entropy formalism, a nonextensive entropy measure, to include some degree of non-locality in a neural network that is used for simulation of novel word learning in adults. A generalization of the gradient descent dynamics, realized via nonextensive cost functions, is used as a learning rule in a simple perceptron. The model is first investigated for general properties, and then tested against the empirical data, gathered from simple memorization experiments involving two populations of linguistically different subjects. Numerical solutions of the model equations corresponded to the measured performance states of human learners. In particular, we found that the memorization tasks were executed with rather small but population-specific amounts of nonextensivity, quantified by the entropic index q. Our findings raise the possibility of using entropic nonextensivity as a means of characterizing the degree of complexity of learning in both natural and artificial systems.     

Reply to: “Comment on: ‘Epidemic spreading on heterogeneous networks with identical infectivity’ [Phys. Lett. A 364 (2007) 189]” [Phys. Lett. A 372 (2008) 1722]

In a recent Letter [R. Yang, B.H. Wang, J. Ren, W.J. Bai, Z.W. Shi, W.X. Wang, T. Zhou, Phys. Lett. A 364 (2007) 189], we proposed a modified susceptible-infected-recovered (SIR) model, in which each node is assigned with an identical capability of active contact, A, at each time step. We found a threshold value λc=1/A in uncorrelated and unlocalized networks. A corresponding Comment, raised by Alberto d'Onofrio, claimed that (i) our model is not biologically relevant; (ii) our model does not have a threshold behavior for recovered population; (iii) the analytical result λc=1/A is incorrect being considered as a threshold for epidemic outbreak, because of an improper approximation of the initial configuration. In this Reply, I show that, by debating from point to point, our analysis and conclusion are solid and reasonable.     

Dynamical response of multi-patch, flux-based models to the input of infected people: Epidemic response to initiated events

The time course of an epidemic can be modeled using the differential equations that describe the spread of disease and by dividing people into “patches” of different sizes with the migration of people between these patches. We used these multi-patch, flux-based models to determine how the time course of infected and susceptible populations depends on the disease parameters, the geometry of the migrations between the patches, and the addition of infected people into a patch. We found that there are significantly longer lived transients and additional “ancillary” epidemics when the reproductive rate R is closer to 1, as would be typical of SARS (Severe Acute Respiratory Syndrome) and bird flu, than when R is closer to 10, as would be typical of measles. In addition we show, both analytical and numerical, how the time delay between the injection of infected people into a patch and the corresponding initial epidemic that it produces depends on R.     

Epidemic outbreaks in growing scale-free networks with local structure

The class of generative models has already attracted considerable interest from researchers in recent years and much expanded the original ideas described in BA model. Most of these models assume that only one node per time step joins the network. In this paper, we grow the network by adding n interconnected nodes as a local structure into the network at each time step with each new node emanating m new edges linking the node to the preexisting network by preferential attachment. This successfully generates key features observed in social networks. These include power-law degree distribution p_k∼k^−(3+μ), where μ=(n−1)/m is a tuning parameter defined as the modularity strength of the network, nontrivial clustering, assortative mixing, and modular structure. Moreover, all these features are dependent in a similar way on the parameter μ. We then study the susceptible-infected epidemics on this network with identical infectivity, and find that the initial epidemic behavior is governed by both of the infection scheme and the network structure, especially the modularity strength. The modularity of the network makes the spreading velocity much lower than that of the BA model. On the other hand, increasing the modularity strength will accelerate the propagation velocity.     

Detecting community structure from coherent oscillation of excitable systems

Many networks are proved to have community structures. On the basis of the fact that the dynamics on networks are intensively affected by the related topology, in this paper the dynamics of excitable systems on networks and a corresponding approach for detecting communities are discussed. Dynamical networks are formed by interacting neurons; each neuron is described using the FHN model. For noisy disturbance and appropriate coupling strength, neurons may oscillate coherently and their behavior is tightly related to the community structure. Synchronization between nodes is measured in terms of a correlation coefficient based on long time series. The correlation coefficient matrix can be used to project network topology onto a vector space. Then by the K-means cluster method, the communities can be detected. Experiments demonstrate that our algorithm is effective at discovering community structure in artificial networks and real networks, especially for directed networks. The results also provide us with a deep understanding of the relationship of function and structure for dynamical networks.     

Fluid transport at low Reynolds number with magnetically actuated artificial cilia

By numerical modeling we investigate fluid transport in low-Reynolds-number flow achieved with a special elastic filament or artifical cilium attached to a planar surface. The filament is made of superparamagnetic particles linked together by DNA double strands. An external magnetic field induces dipolar interactions between the beads of the filament which provides a convenient way of actuating the cilium in a well-controlled manner. The filament has recently been used to successfully construct the first artificial micro-swimmer (R. Dreyfus et al., Nature 437, 862 (2005)). In our numerical study we introduce a measure, which we call pumping performance, to quantify the fluid transport induced by the magnetically actuated cilium and identify an optimum stroke pattern of the filament. It consists of a slow transport stroke and a fast recovery stroke. Our detailed parameter study also reveals that for sufficiently large magnetic fields the artificial cilium is mainly governed by the Mason number that compares frictional to magnetic forces. Initial studies on multi-cilia systems show that the pumping performance is very sensitive to the imposed phase lag between neighboring cilia, i.e., to the details of the initiated metachronal wave.     

Nonlinear attractor dynamics in the fundamental and extended prism adaptation paradigm

Adaptation and re-adaptation processes are studied in terms of dynamic attractors that evolve and devolve. In doing so, a theoretical account is given for the fundamental observation that adaptation and re-adaptation processes do not exhibit one-trial learning. Moreover, the emergence of the latent aftereffect in the extended prism paradigm is addressed.     

Bifurcation in neuronal networks with hub structure

We investigate bifurcations in neuronal networks with a hub structure. It is known that hubs play a leading role in characterizing the network dynamical behavior. However, the dynamics of hubs or star-coupled systems is not well understood. Here, we study rather subnetworks with a star-like configuration. This coupled system is an important motif in complex networks. Thus, our study is a basic step for understanding structure formation in large networks. We use the Morris-Lecar neuron with class I and class II excitabilities as a node. Homogeneous (coupling the same class neurons) and heterogeneous (coupling different class neurons) cases are considered for both excitatory and inhibitory coupling. For the homogeneous system class II neurons are suitable for achieving both complete and cluster synchronization in excitatory and inhibitory coupling, respectively. For the heterogeneous system with inhibitory coupling, the class I hub neuron has a wider parameter region of synchronous firings than the class II hub. Moreover, the class I hub neuron with the excitatory synapse gives rise to bifurcations of synchronized states and multi-stability (coexistence of a few different states) is observed.     

Generalized multiple-prism dispersion theory for laser pulse compression: higher order phase derivatives

An exact, and explicit, expression for the second derivative of the generalized multiple-prism angular dispersion is provided. This corresponds to the third derivative of the generalized exit angle with respect to the refractive index (∇ _n ³ φ _2,m ). Higher derivatives, in abstract notation, are also given. The generalized equations are presented in a format applicable to practical prismatic configurations utilized in laser pulse compression schemes in the femtosecond domain. Exact values, as a function of the refractive index, are given for the first, second, and third angular derivatives for compensating double-prism and four-prism configurations of practical interest.     

The NN → NNη reaction close to threshold

The pp → ppη and np → npη reactions at energies near the η production threshold are studied in a non-relativistic one boson exchange model, where the (1535 MeV) S11 resonance is excited through the exchange of π, η, ? and ω mesons and subsequently decays into an ηN pair. Energy integrated cross sections and energy spectra of the out going η's are reported. Providing NN and ηN final state interactions are taken into account coherently, the model reproduces both the scale and energy dependence of the cross section for the pp → ppη reactions up to 100 MeV. Final state interaction corrections due to the nucleon-nucleon and meson-nucleon forces influence strongly the scale and shape of the cross sections. The shape of the energy spectra of the outgoing η's provides a clear signature of the ηN force.     

Analysis of various polarization asymmetries in the inclusive b→s?+?? decay in the fourth-generation standard model

In this study a systematical analysis of various polarization asymmetries in inclusive b→s ℓ ⁺ ℓ ⁻ decay in the standard model (SM) with four generation of quarks is carried out. We found that the various asymmetries are sensitive to the new mixing and quark masses for both of the μ and τ channels. Sizable deviations from the SM values are obtained. Hence, b→s ℓ ⁺ ℓ ⁻ decay is a valuable tool for searching physics beyond the SM, especially in the indirect searches for the fourth-generation of quarks (t′,b′).     

Mixing angles of quarks and leptons in quantum field theory

Arguments coming from Quantum Field Theory are supplemented with a 1-loop perturbative calculation to settle the non-unitarity of mixing matrices linking renormalized mass eigenstates to bare flavor states for non-degenerate coupled fermions. We simultaneously diagonalize the kinetic and mass terms and counterterms in the renormalized Lagrangian. SU(2) _L gauge invariance constrains the mixing matrix in charged currents of renormalized mass states, for example the Cabibbo matrix, to stay unitary. Leaving aside CP violation, we observe that the mixing angles exhibit, within experimental uncertainty, a very simple breaking pattern of SU(2) _f horizontal symmetry linked to the algebra of weak neutral currents, the origin of which presumably lies beyond the Standard Model. It concerns on the one hand the three quark mixing angles; on the other hand a neutrino-like pattern in which θ ₂₃ is maximal and tan (2θ ₁₂)=2. The Cabibbo angle fulfills the condition tan (2θ _c )=1/2 and θ ₁₂ for neutrinos satisfies accordingly the “quark–lepton complementarity condition” θ _c +θ ₁₂=π/4. θ ₁₃=±5.7⋅10⁻³ are the only values obtained for the third neutrino mixing angle that lie within present experimental bounds. Flavor symmetries, their breaking by a non-degenerate mass spectrum, and their entanglement with the gauge symmetry, are scrutinized; the special role of flavor rotations as a very mildly broken symmetry of the Standard Model is outlined.     

Effective potential for highly relativistic neutrinos in a weakly magnetized medium and their oscillation

We have calculated the effective potential experienced by highly relativistic neutrinos in a weakly magnetized electron–positron plasma, where a momentum-dependent finite-width correction to the propagator of W is considered to account for the threshold effect. Magnetars are believed to be sources of TeV–PeV neutrinos which are produced due to photomeson and proton–proton interactions in their atmosphere. We have studied the resonant-oscillation process ν _e ↔ ν _μ,τ of the highly relativistic neutrinos in the atmosphere of SGR 1806-20, which is a magnetar. It is shown that, for high-energy neutrinos propagating within the magnetar atmosphere, the resonance condition can never be satisfied. On the other hand, if GeV neutrinos are produced deep inside the magnetar atmosphere, where the temperature is about 50 keV or more, then these neutrinos can undergo resonant oscillation.     

Magnetic dipole,electric quadrupole and magnetic octupole moments of the <Emphasis Type="Italic">Δ</Emphasis> baryons in light cone QCD sum rules

Due to the very short life time of the Δ baryons, a direct measurement on the electromagnetic moments of these systems is almost impossible in the experiment and can only be done indirectly. Although only for the magnetic dipole moments of Δ ⁺⁺ and Δ ⁺ systems there are some experimental data, the theoretical, phenomenological and lattice calculations could play crucial role. In the present work, the magnetic dipole (μ _Δ ), electric quadrupole (Q _Δ ) and magnetic octupole (O _Δ ) moments of these baryons are computed within the light cone QCD sum rules. The results are compared with the predictions of the other phenomenological approaches, lattice QCD and existing experimental data.