Remarks on Bootstrap Percolation in Metric Networks

We examine bootstrap percolation in d-dimensional, directed metric graphs in the context of recent measurements of firing dynamics in 2D neuronal cultures. There are two regimes, depending on the graph size N. Large metric graphs are ignited by the occurrence of critical nuclei, which initially occupy an infinitesimal fraction, f_* -> 0, of the graph and then explode throughout a finite fraction. Smaller metric graphs are effectively random in the sense that their ignition requires the initial ignition of a finite, unlocalized fraction of the graph, f_* >0. The crossover between the two regimes is at a size N_* which scales exponentially with the connectivity range \lambda like_* \sim \exp\lambda^d. The neuronal cultures are finite metric graphs of size N \simeq 10^5-10^6, which, for the parameters of the experiment, is effectively random since N<< N_*. This explains the seeming contradiction in the observed finite f_* in these cultures. Finally, we discuss the dynamics of the firing front

Leaders of neuronal cultures in a quorum percolation model

We present a theoretical framework using quorum-percolation for describing the initiation of activity in a neural culture. The cultures are modeled as random graphs, whose nodes are excitatory neurons with kin inputs and kout outputs, and whose input degrees kin = k obey given distribution functions pk. We examine the firing activity of the population of neurons according to their input degree (k) classes and calculate for each class its firing probability \Phi_k(t) as a function of t. The probability of a node to fire is found to be determined by its in-degree k, and the first-to-fire neurons are those that have a high k. A small minority of high-k classes may be called "Leaders", as they form an inter-connected subnetwork that consistently fires much before the rest of the culture. Once initiated, the activity spreads from the Leaders to the less connected majority of the culture. We then use the distribution of in-degree of the Leaders to study the growth rate of the number of neurons active in a burst, which was experimentally measured to be initially exponential. We find that this kind of growth rate is best described by a population that has an in-degree distribution that is a Gaussian centered around k = 75 with width {\sigma} = 31 for the majority of the neurons, but also has a power law tail with exponent -2 for ten percent of the population. Neurons in the tail may have as many as k = 4, 700 inputs. We explore and discuss the correspondence between the degree distribution and a dynamic neuronal threshold, showing that from the functional point of view, structure and elementary dynamics are interchangeable. We discuss possible geometric origins of this distribution, and comment on the importance of size, or of having a large number of neurons, in the culture.Comment: Keywords: Neuronal cultures, Graph theory, Activation dynamics, Percolation, Statistical mechanics of networks, Leaders of activity, Quorum. http://www.weizmann.ac.il/complex/tlusty/papers/FrontCompNeuro2010.pd

An experimental investigation of chatter effects on tool life

Tool wear is one of the most important considerations in machining operations as it affects surface quality and integrity, productivity and cost. The most commonly used model for tool life analysis is the one proposed by F.W. Taylor about a century ago. Although the extended form of this equation includes the effects of important cutting conditions on tool wear, tool life studies are mostly performed under stable cutting conditions where the effect of chatter vibrations are not considered. This paper presents an empirical attempt to understand tool life under vibratory cutting conditions. Tool wear data are collected in turning and milling on different work materials under stable and chatter conditions. The effects of cutting conditions as well as severity of chatter on tool life are analyzed. The results indicate significant reduction in tool life due to chatter as expected. They also show that the severity of chatter, and thus the vibration amplitude, strongly reduces the life of cutting tools. These results can be useful in evaluating the real cost of chatter by including the reduced tool life. They can also be useful in justifying the cost of chatter suppression and more rigid machining systems

Percolation in living neural networks

We study living neural networks by measuring the neurons' response to a global electrical stimulation. Neural connectivity is lowered by reducing the synaptic strength, chemically blocking neurotransmitter receptors. We use a graph-theoretic approach to show that the connectivity undergoes a percolation transition. This occurs as the giant component disintegrates, characterized by a power law with critical exponent $\beta \simeq 0.65$ is independent of the balance between excitatory and inhibitory neurons and indicates that the degree distribution is gaussian rather than scale freeComment: PACS numbers: 87.18.Sn, 87.19.La, 64.60.Ak http://www.weizmann.ac.il/complex/tlusty/papers/PhysRevLett2006.pd

Compliance error compensation in robotic-based milling

The paper deals with the problem of compliance errors compensation in robotic-based milling. Contrary to previous works that assume that the forces/torques generated by the manufacturing process are constant, the interaction between the milling tool and the workpiece is modeled in details. It takes into account the tool geometry, the number of teeth, the feed rate, the spindle rotation speed and the properties of the material to be processed. Due to high level of the disturbing forces/torques, the developed compensation technique is based on the non-linear stiffness model that allows us to modify the target trajectory taking into account nonlinearities and to avoid the chattering effect. Illustrative example is presented that deals with robotic-based milling of aluminum alloy

On Bootstrap Percolation in Living Neural Networks

Recent experimental studies of living neural networks reveal that their global activation induced by electrical stimulation can be explained using the concept of bootstrap percolation on a directed random network. The experiment consists in activating externally an initial random fraction of the neurons and observe the process of firing until its equilibrium. The final portion of neurons that are active depends in a non linear way on the initial fraction. The main result of this paper is a theorem which enables us to find the asymptotic of final proportion of the fired neurons in the case of random directed graphs with given node degrees as the model for interacting network. This gives a rigorous mathematical proof of a phenomena observed by physicists in neural networks

Model and parameter dependence of heavy quark energy loss in a hot and dense medium

Within the framework of the Langevin equation, we study the energy loss of heavy quark due to quasi-elastic multiple scatterings in a quark-gluon plasma created by relativistic heavy-ion collisions. We investigate how the initial configuration of the quark-gluon plasma as well as its properties affect the final state spectra and elliptic flow of D meson and non-photonic electron. We find that both the geometric anisotropy of the initial quark-gluon plasma and the flow profiles of the hydrodynamic medium play important roles in the heavy quark energy loss process and the development of elliptic flow. The relative contribution from charm and bottom quarks is found to affect the transverse momentum dependence of the quenching and flow patterns of heavy flavor decay electron; such influence depends on the interaction strength between heavy quark and the medium.Comment: 16 pages, 7 figure

Nematic-Wetted Colloids in the Isotropic Phase: Pairwise Interaction, Biaxiality and Defects

We calculate the interaction between two spherical colloidal particles embedded in the isotropic phase of a nematogenic liquid. The surface of the particles induces wetting nematic coronas that mediate an elastic interaction. In the weak wetting regime, we obtain exact results for the interaction energy and the texture, showing that defects and biaxiality arise, although they are not topologically required. We evidence rich behaviors, including the possibility of reversible colloidal aggregation and dispersion. Complex anisotropic self-assembled phases might be formed in dense suspensions.Comment: 4 pages, 6 figure

Electromagnetic Calorimeter for HADES

We propose to build the Electromagnetic calorimeter for the HADES di-lepton spectrometer. It will enable to measure the data on neutral meson production from nucleus-nucleus collisions, which are essential for interpretation of dilepton data, but are unknown in the energy range of planned experiments (2-10 GeV per nucleon). The calorimeter will improve the electron-hadron separation, and will be used for detection of photons from strange resonances in elementary and HI reactions. Detailed description of the detector layout, the support structure, the electronic readout and its performance studied via Monte Carlo simulations and series of dedicated test experiments is presented. The device will cover the total area of about 8 m^2 at polar angles between 12 and 45 degrees with almost full azimuthal coverage. The photon and electron energy resolution achieved in test experiments amounts to 5-6%/sqrt(E[GeV]) which is sufficient for the eta meson reconstruction with S/B ratio of 0.4% in Ni+Ni collisions at 8 AGeV. A purity of the identified leptons after the hadron rejection, resulting from simulations based on the test measurements, is better than 80% at momenta above 500 MeV/c, where time-of-flight cannot be used.Comment: 40 pages, 38 figures version2 - the time schedule added, information about PMTs in Sec.III update

Molecular Model of the Contractile Ring

We present a model for the actin contractile ring of adherent animal cells. The model suggests that the actin concentration within the ring and consequently the power that the ring exerts both increase during contraction. We demonstrate the crucial role of actin polymerization and depolymerization throughout cytokinesis, and the dominance of viscous dissipation in the dynamics. The physical origin of two phases in cytokinesis dynamics ("biphasic cytokinesis") follows from a limitation on the actin density. The model is consistent with a wide range of measurements of the midzone of dividing animal cells.Comment: PACS numbers: 87.16.Ka, 87.16.Ac http://www.ncbi.nlm.nih.gov/pubmed/16197254 http://www.weizmann.ac.il/complex/tlusty/papers/PhysRevLett2005.pd