A New Approach for Simulating Galaxy Cluster Properties

We describe a subgrid model for including galaxies into hydrodynamical cosmological simulations of galaxy cluster evolution. Each galaxy construct- or galcon- is modeled as a physically extended object within which star formation, galactic winds, and ram pressure stripping of gas are modeled analytically. Galcons are initialized at high redshift (z~3) after galaxy dark matter halos have formed but before the cluster has virialized. Each galcon moves self-consistently within the evolving cluster potential and injects mass, metals, and energy into intracluster (IC) gas through a well-resolved spherical interface layer. We have implemented galcons into the Enzo adaptive mesh refinement code and carried out a simulation of cluster formation in a LambdaCDM universe. With our approach, we are able to economically follow the impact of a large number of galaxies on IC gas. We compare the results of the galcon simulation with a second, more standard simulation where star formation and feedback are treated using a popular heuristic prescription. One advantage of the galcon approach is explicit control over the star formation history of cluster galaxies. Using a galactic SFR derived from the cosmic star formation density, we find the galcon simulation produces a lower stellar fraction, a larger gas core radius, a more isothermal temperature profile, and a flatter metallicity gradient than the standard simulation, in better agreement with observations.Comment: 4 pages, 2 figures, submitted for publication in ApJ

The Controversy of Myopia as a Risk Factor for Glaucoma: a Mathematical Approach

poster abstractPurpose: to quantify how individual variations in anatomical parameters often associated with myopia (e.g. longer ocular axial length (OAL), reduced scleral thickness (ST), lamina cribrosa diameter (LCD) and thickness (LCT)) affect retinal blood flow (RBF) and its sensitivity to ocular perfusion pressure (OPP). Methods: A mathematical model is used to calculate RBF through central retinal artery (CRA), arterioles, capillaries, venules, and central retinal vein (CRV). The flow is time-dependent, driven by systemic pressure and regulated by variable resistances to account for nonlinear effects due to (1) autoregulation (AR), and (2) lamina cribrosa effect on CRA and CRV. The latter is a nonlinear function of intraocular pressure (IOP), cerebrospinal fluid pressure (CSF) and OAL, ST, LCD, and LCT. RBF is computed as the solution of a system of five non-linear ordinary differential equations. The system is solved for different OPP values, obtained by varying independently IOP and mean arterial pressure (MAP), with and without AR. Results: Four representative eyes are compared: Eye 1 (OAL=24mm, ST=1mm, LCD=3mm, LCT=0.4mm), Eye 2 (OAL=28mm, ST=1mm, LCD=3mm, LCT=0.4mm), Eye 3 (OAL=24mm, ST=0.7mm, LCD=2mm, LCT=0.2mm), Eye 4 (OAL=28mm, ST=0.7mm, LCD=2mm, LCT=0.2mm). The model predicts that the cardiac cycle RBF average (RBFav) for eyes with smaller LCD and LCT is notably less than in normal eyes when IOP is elevated and without AR (c). Without AR and reduced MAP, the four eyes show similar RBFav reductions (d). With AR, anatomical changes do not induce notable changes in RBFav, (a) and (b). Conclusions: Reduced LCD and LCT, often associated with myopia, seem to affect RBFav more than elevated OAL. RBFav reductions magnify when AR is impaired, and this might reduce IOP safe levels for eyes with reduced LCD and LCT. These findings suggest that a combination of anatomical and vascular factors might cause certain myopic eyes to be at higher risk for glaucomatous damage than others

Using penetration depth for phase matching in photonic crystal waveguides

A new method of design for the phase-matching in waveguides is suggested. The approach is based on utilizing the concept of the penetration depth of light into the waveguide walls. The lateral components of wavevectors are employed to adjust the phase-matching condition in the propagation direction. The method is demonstrated in two systems: one using single and the other using double photonic-crystal mirrors

Sulfide quinone reductase (SQR) activity in Chlorobium

AbstractMembranes of the green sulfur bacterium, Chlorobium limicola f, thiosulfatophilum, catalyze the reduction of externally added isoprenoid quinones by sulfide. This activity is highly sensitive to stigmatellin and aurachins. It is also inhibited by 2-n-nonyl-4-hydroxyquinoline-N-oxide, antimycin, myxothiazol and cyanide. It is concluded that in sulfide oxidizing bacteria like Chlorobium, sulfide oxidation involves a sulfide-quinone reductase (SQR) similar to the one found in Oscilatoria limnetica [Arieli, B., Padan, E. and Shahak, Y. (1991) J. Biol. Chem. 266. 104–111]

Weak pairwise correlations imply strongly correlated network states in a neural population

Biological networks have so many possible states that exhaustive sampling is impossible. Successful analysis thus depends on simplifying hypotheses, but experiments on many systems hint that complicated, higher order interactions among large groups of elements play an important role. In the vertebrate retina, we show that weak correlations between pairs of neurons coexist with strongly collective behavior in the responses of ten or more neurons. Surprisingly, we find that this collective behavior is described quantitatively by models that capture the observed pairwise correlations but assume no higher order interactions. These maximum entropy models are equivalent to Ising models, and predict that larger networks are completely dominated by correlation effects. This suggests that the neural code has associative or error-correcting properties, and we provide preliminary evidence for such behavior. As a first test for the generality of these ideas, we show that similar results are obtained from networks of cultured cortical neurons.Comment: Full account of work presented at the conference on Computational and Systems Neuroscience (COSYNE), 17-20 March 2005, in Salt Lake City, Utah (http://cosyne.org

Neural Network Mechanisms Underlying Stimulus Driven Variability Reduction

It is well established that the variability of the neural activity across trials, as measured by the Fano factor, is elevated. This fact poses limits on information encoding by the neural activity. However, a series of recent neurophysiological experiments have changed this traditional view. Single cell recordings across a variety of species, brain areas, brain states and stimulus conditions demonstrate a remarkable reduction of the neural variability when an external stimulation is applied and when attention is allocated towards a stimulus within a neuron's receptive field, suggesting an enhancement of information encoding. Using an heterogeneously connected neural network model whose dynamics exhibits multiple attractors, we demonstrate here how this variability reduction can arise from a network effect. In the spontaneous state, we show that the high degree of neural variability is mainly due to fluctuation-driven excursions from attractor to attractor. This occurs when, in the parameter space, the network working point is around the bifurcation allowing multistable attractors. The application of an external excitatory drive by stimulation or attention stabilizes one specific attractor, eliminating in this way the transitions between the different attractors and resulting in a net decrease in neural variability over trials. Importantly, non-responsive neurons also exhibit a reduction of variability. Finally, this reduced variability is found to arise from an increased regularity of the neural spike trains. In conclusion, these results suggest that the variability reduction under stimulation and attention is a property of neural circuits