Critical Lattice Size Limit for Synchronized Chaotic State in 1-D and 2-D Diffusively Coupled Map Lattices

We consider diffusively coupled map lattices with $P$ neighbors (where $P$ is arbitrary) and study the stability of synchronized state. We show that there exists a critical lattice size beyond which the synchronized state is unstable. This generalizes earlier results for nearest neighbor coupling. We confirm the analytical results by performing numerical simulations on coupled map lattices with logistic map at each node. The above analysis is also extended to 2-dimensional $P$-neighbor diffusively coupled map lattices.Comment: 4 pages, 2 figure

Analyzing Stability of Equilibrium Points in Neural Networks: A General Approach

Networks of coupled neural systems represent an important class of models in computational neuroscience. In some applications it is required that equilibrium points in these networks remain stable under parameter variations. Here we present a general methodology to yield explicit constraints on the coupling strengths to ensure the stability of the equilibrium point. Two models of coupled excitatory-inhibitory oscillators are used to illustrate the approach.Comment: 20 pages, 4 figure

Length control of microtubules by depolymerizing motor proteins

In many intracellular processes, the length distribution of microtubules is controlled by depolymerizing motor proteins. Experiments have shown that, following non-specific binding to the surface of a microtubule, depolymerizers are transported to the microtubule tip(s) by diffusion or directed walk and, then, depolymerize the microtubule from the tip(s) after accumulating there. We develop a quantitative model to study the depolymerizing action of such a generic motor protein, and its possible effects on the length distribution of microtubules. We show that, when the motor protein concentration in solution exceeds a critical value, a steady state is reached where the length distribution is, in general, non-monotonic with a single peak. However, for highly processive motors and large motor densities, this distribution effectively becomes an exponential decay. Our findings suggest that such motor proteins may be selectively used by the cell to ensure precise control of MT lengths. The model is also used to analyze experimental observations of motor-induced depolymerization.Comment: Added section with figures and significantly expanded text, current version to appear in Europhys. Let

Ballistic transport and electrostatics in metallic carbon nanotubes

We calculate the current and electrostatic potential drop in metallic carbon nanotube wires self-consistently, by solving the Green's function and electrostatics equations in the ballistic case. About one tenth of the applied voltage drops across the bulk of a nanowire, independent of the lengths considered here. The remaining nine tenths of the bias drops near the contacts, thereby creating a non linear potential drop. The scaling of the electric field at the center of the nanotube with length (L) is faster than 1/L (roughly $1/L^{1.25-1.75}$). At room temperature, the low bias conductance of large diameter nanotubes is larger than $4e^2/h$ due to occupation of non crossing subbands. The physics of conductance evolution with bias due to the transmission Zener tunneling in non crossing subbands is discussed

Long term persistence in the sea surface temperature fluctuations

We study the temporal correlations in the sea surface temperature (SST) fluctuations around the seasonal mean values in the Atlantic and Pacific oceans. We apply a method that systematically overcome possible trends in the data. We find that the SST persistence, characterized by the correlation $C(s)$ of temperature fluctuations separated by a time period $s$, displays two different regimes. In the short-time regime which extends up to roughly 10 months, the temperature fluctuations display a nonstationary behavior for both oceans, while in the asymptotic regime it becomes stationary. The long term correlations decay as $C(s) \sim s^{-\gamma}$ with $\gamma \sim 0.4$ for both oceans which is different from $\gamma \sim 0.7$ found for atmospheric land temperature.Comment: 14 pages, 5 fiure

Duality and Non-Commutative Gauge Theory

We study the generalization of S-duality to non-commutative gauge theories. For rank one theories, we obtain the leading terms of the dual theory by Legendre transforming the Lagrangian of the non-commutative theory expressed in terms of a commutative gauge field. The dual description is weakly coupled when the original theory is strongly coupled if we appropriately scale the non-commutativity parameter. However, the dual theory appears to be non-commutative in space-time when the original theory is non-commutative in space. This suggests that locality in time for non-commutative theories is an artifact of perturbation theory.Comment: 7 pages, harvmac; a typo fixe

Volcanic forcing improves Atmosphere-Ocean Coupled General Circulation Model scaling performance

Recent Atmosphere-Ocean Coupled General Circulation Model (AOGCM) simulations of the twentieth century climate, which account for anthropogenic and natural forcings, make it possible to study the origin of long-term temperature correlations found in the observed records. We study ensemble experiments performed with the NCAR PCM for 10 different historical scenarios, including no forcings, greenhouse gas, sulfate aerosol, ozone, solar, volcanic forcing and various combinations, such as it natural, anthropogenic and all forcings. We compare the scaling exponents characterizing the long-term correlations of the observed and simulated model data for 16 representative land stations and 16 sites in the Atlantic Ocean for these scenarios. We find that inclusion of volcanic forcing in the AOGCM considerably improves the PCM scaling behavior. The scenarios containing volcanic forcing are able to reproduce quite well the observed scaling exponents for the land with exponents around 0.65 independent of the station distance from the ocean. For the Atlantic Ocean, scenarios with the volcanic forcing slightly underestimate the observed persistence exhibiting an average exponent 0.74 instead of 0.85 for reconstructed data.Comment: 4 figure

Spatial synchronization and extinction of species under external forcing

We study the interplay between synchronization and extinction of a species. Using a general model we show that under a common external forcing, the species with a quadratic saturation term in the population dynamics first undergoes spatial synchronization and then extinction, thereby avoiding the rescue effect. This is because the saturation term reduces the synchronization time scale but not the extinction time scale. The effect can be observed even when the external forcing acts only on some locations provided there is a synchronizing term in the dynamics. Absence of the quadratic saturation term can help the species to avoid extinction.Comment: 4 pages, 2 figure

Customized Prediction of Short Length of Stay Following Elective Cardiac Surgery in Elderly Patients Using a Genetic Algorithm

Objective: To develop a customized short LOS (<6 days) prediction model for geriatric patients receiving cardiac surgery, using local data and a computational feature selection algorithm. Design: Utilization of a machine learning algorithm in a prospectively collected STS database consisting of patients who received cardiac surgery between January 2002 and June 2011. Setting: Urban tertiary-care center. Participants: Geriatric patients aged 70 years or older at the time of cardiac surgery. Interventions None. Measurements and Main Results Predefined morbidity and mortality events were collected from the STS database. 23 clinically relevant predictors were investigated for short LOS prediction with a genetic algorithm (GenAlg) in 1426 patients. Due to the absence of an STS model for their particular surgery type, STS risk scores were unavailable for 771 patients. STS prediction achieved an AUC of 0.629 while the GenAlg achieved AUCs of 0.573 (in those with STS scores) and 0.691 (in those without STS scores). Among the patients with STS scores, the GenAlg features significantly associated with shorter LOS were absence of congestive heart failure (CHF) (OR = 0.59, p = 0.04), aortic valve procedure (OR = 1.54, p = 0.04), and shorter cross clamp time (OR = 0.99, p = 0.004). In those without STS prediction, short LOS was significantly correlated with younger age (OR = 0.93, p < 0.001), absence of CHF (OR = 0.53, p = 0.007), no preoperative use of beta blockers (OR = 0.66, p = 0.03), and shorter cross clamp time (OR = 0.99, p < 0.001). Conclusion: While the GenAlg-based models did not outperform STS prediction for patients with STS risk scores, our local-data-driven approach reliably predicted short LOS for cardiac surgery types that do not allow STS risk calculation. We advocate that each institution with sufficient observational data should build their own cardiac surgery risk models

Two-Dimensional Quantum Model of a Nanotransistor

A mathematical model, and software to implement the model, have been devised to enable numerical simulation of the transport of electric charge in, and the resulting electrical performance characteristics of, a nanotransistor [in particular, a metal oxide/semiconductor field-effect transistor (MOSFET) having a channel length of the order of tens of nanometers] in which the overall device geometry, including the doping profiles and the injection of charge from the source, gate, and drain contacts, are approximated as being two-dimensional. The model and software constitute a computational framework for quantitatively exploring such device-physics issues as those of source-drain and gate leakage currents, drain-induced barrier lowering, and threshold voltage shift due to quantization. The model and software can also be used as means of studying the accuracy of quantum corrections to other semiclassical models