Percolation of randomly distributed growing clusters

We investigate the problem of growing clusters, which is modeled by two dimensional disks and three dimensional droplets. In this model we place a number of seeds on random locations on a lattice with an initial occupation probability, $p$. The seeds simultaneously grow with a constant velocity to form clusters. When two or more clusters eventually touch each other they immediately stop their growth. The probability that such a system will result in a percolating cluster depends on the density of the initially distributed seeds and the dimensionality of the system. For very low initial values of $p$ we find a power law behavior for several properties that we investigate, namely for the size of the largest and second largest cluster, for the probability for a site to belong to the finally formed spanning cluster, and for the mean radius of the finally formed droplets. We report the values of the corresponding scaling exponents. Finally, we show that for very low initial concentration of seeds the final coverage takes a constant value which depends on the system dimensionality.Comment: 5 pages, 7 figure

Percolation of randomly distributed growing clusters: Finite Size Scaling and Critical Exponents

We study the percolation properties of the growing clusters model. In this model, a number of seeds placed on random locations on a lattice are allowed to grow with a constant velocity to form clusters. When two or more clusters eventually touch each other they immediately stop their growth. The model exhibits a discontinuous transition for very low values of the seed concentration $p$ and a second, non-trivial continuous phase transition for intermediate $p$ values. Here we study in detail this continuous transition that separates a phase of finite clusters from a phase characterized by the presence of a giant component. Using finite size scaling and large scale Monte Carlo simulations we determine the value of the percolation threshold where the giant component first appears, and the critical exponents that characterize the transition. We find that the transition belongs to a different universality class from the standard percolation transition.Comment: 5 two-column pages, 6 figure

Variational finite-difference representation of the kinetic energy operator

A potential disadvantage of real-space-grid electronic structure methods is the lack of a variational principle and the concomitant increase of total energy with grid refinement. We show that the origin of this feature is the systematic underestimation of the kinetic energy by the finite difference representation of the Laplacian operator. We present an alternative representation that provides a rigorous upper bound estimate of the true kinetic energy and we illustrate its properties with a harmonic oscillator potential. For a more realistic application, we study the convergence of the total energy of bulk silicon using a real-space-grid density-functional code and employing both the conventional and the alternative representations of the kinetic energy operator.Comment: 3 pages, 3 figures, 1 table. To appear in Phys. Rev. B. Contribution for the 10th anniversary of the eprint serve

Priority diffusion model in lattices and complex networks

We introduce a model for diffusion of two classes of particles ($A$ and $B$) with priority: where both species are present in the same site the motion of $A$'s takes precedence over that of $B$'s. This describes realistic situations in wireless and communication networks. In regular lattices the diffusion of the two species is normal but the $B$ particles are significantly slower, due to the presence of the $A$ particles. From the fraction of sites where the $B$ particles can move freely, which we compute analytically, we derive the diffusion coefficients of the two species. In heterogeneous networks the fraction of sites where $B$ is free decreases exponentially with the degree of the sites. This, coupled with accumulation of particles in high-degree nodes leads to trapping of the low priority particles in scale-free networks.Comment: 5 pages, 3 figure

Role of Human-Induced Pluripotent Stem Cell-Derived Spinal Cord Astrocytes in the Functional Maturation of Motor Neurons in a Multielectrode Array System

The ability to generate human-induced pluripotent stem cell (hiPSC)-derived neural cells displaying region-specific phenotypes is of particular interest for modeling central nervous system biology in vitro. We describe a unique method by which spinal cord hiPSC-derived astrocytes (hiPSC-A) are cultured with spinal cord hiPSC-derived motor neurons (hiPSC-MN) in a multielectrode array (MEA) system to record electrophysiological activity over time. We show that hiPSC-A enhance hiPSC-MN electrophysiological maturation in a time-dependent fashion. The sequence of plating, density, and age in which hiPSC-A are cocultured with MN, but not their respective hiPSC line origin, are factors that influence neuronal electrophysiology. When compared to coculture with mouse primary spinal cord astrocytes, we observe an earlier and more robust electrophysiological maturation in the fully human cultures, suggesting that the human origin is relevant to the recapitulation of astrocyte/motor neuron crosstalk. Finally, we test pharmacological compounds on our MEA platform and observe changes in electrophysiological activity, which confirm hiPSC-MN maturation. These findings are supported by immunocytochemistry and real-time PCR studies in parallel cultures demonstrating human astrocyte mediated changes in the structural maturation and protein expression profiles of the neurons. Interestingly, this relationship is reciprocal and coculture with neurons influences astrocyte maturation as well. Taken together, these data indicate that in a human in vitro spinal cord culture system, astrocytes support hiPSC-MN maturation in a time-dependent and species-specific manner and suggest a closer approximation of in vivo conditions

Time-dependent calculation of ionization in Potassium at mid-infrared wavelengths

We study the dynamics of the Potassium atom in the mid-infrared, high intensity, short laser pulse regime. We ascertain numerical convergence by comparing the results obtained by the direct expansion of the time-dependent Schroedinger equation onto B-Splines, to those obtained by the eigenbasis expansion method. We present ionization curves in the 12-, 13-, and 14-photon ionization range for Potassium. The ionization curve of a scaled system, namely Hydrogen starting from the 2s, is compared to the 12-photon results. In the 13-photon regime, a dynamic resonance is found and analyzed in some detail. The results for all wavelengths and intensities, including Hydrogen, display a clear plateau in the peak-heights of the low energy part of the Above Threshold Ionization (ATI) spectrum, which scales with the ponderomotive energy Up, and extends to 2.8 +- 0.5 Up.Comment: 15 two-column pages with 15 figures, 3 tables. Accepted for publication in Phys. Rev A. Improved figures, language and punctuation, and made minor corrections. We also added a comparison to the ADK theor

Mechanisms, models and biomarkers in amyotrophic lateral sclerosis

The last 30 years have seen a major advance in the understanding of the clinical and pathological heterogeneity of amyotrophic lateral sclerosis (ALS), and its overlap with frontotemporal dementia. Multiple, seemingly disparate biochemical pathways converge on a common clinical syndrome characterized by progressive loss of upper and lower motor neurons. Pathogenic themes in ALS include excitotoxicity, oxidative stress, mitochondrial dysfunction, neuroinflammation, altered energy metabolism, and most recently RNA mis-processing. The transgenic rodent, overexpressing mutant superoxide dismutase-1, is now only one of several models of ALS pathogenesis. The nematode, fruit fly and zebrafish all offer fresh insight, and the development of induced pluripotent stem cell-derived motor neurons holds promise for the screening of candidate therapeutics. The lack of useful biomarkers in ALS contributes to diagnostic delay, and the inability to stratify patients by prognosis may be an important factor in the failure of therapeutic trials. Biomarkers sensitive to disease activity might lessen reliance on clinical measures and survival as trial endpoints and reduce study length. Emerging proteomic markers of neuronal loss and glial activity in cerebrospinal fluid, a cortical signature derived from advanced structural and functional MRI, and the development of more sensitive measurements of lower motor neuron physiology are leading a new phase of biomarker-driven therapeutic discovery

Many-electron tunneling in atoms

A theoretical derivation is given for the formula describing N-electron ionization of atom by a dc field and laser radiation in tunneling regime. Numerical examples are presented for noble gases atoms.Comment: 11 pages, 1 EPS figure, submitted to JETP (Jan 99

Strategies to prevent Clostridium difficile infections in acute care hospitals: 2014 update

Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). The intent of this document is to highlight practical recommendations in a concise format designed to assist acute care hospitals in implementing and prioritizing their Clostridium difficile infection (CDI) prevention efforts. This document updates “Strategies to Prevent Clostridium difficile Infections in Acute Care Hospitals,” published in 2008. This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA) and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the American Hospital Association (AHA), the Association for Professionals in Infection Control and Epidemiology (APIC), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise. The list of endorsing and supporting organizations is presented in the introduction to the 2014 updates

Dynamic correlations in an ordered c(2×\times2) lattice gas

We obtain the dynamic correlation function of two-dimensional lattice gas with nearest-neighbor repulsion in ordered c(2$\times$2) phase (antiferromagnetic ordering) under the condition of low concentration of structural defects. It is shown that displacements of defects of the ordered state are responsible for the particle number fluctuations in the probe area. The corresponding set of kinetic equations is derived and solved in linear approximation on the defect concentration. Three types of strongly correlated complex jumps are considered and their contribution to fluctuations is analysed. These are jumps of excess particles, vacancies and flip-flop jumps. The kinetic approach is more general than the one based on diffusion-like equations used in our previous papers. Thus, it becomes possible to adequately describe correlations of fluctuations at small times, where our previous theory fails to give correct results. Our new analytical results for fluctuations of particle number in the probe area agree well with those obtained by Monte Carlo simulations.Comment: 10 pages, 7 figure