A simulation model of time-dependent plasma-spacecraft interactions

A plasma simulation code is presented that models the time-dependent plasma properties in the vicinity of a spherical, charged spacecraft. After showing agreement with analytic, steady-state theories and ATS-6 satellite data, the following three problems are treated: (1) transient pulses from photoemission at various emission temperatures and ambient plasma conditions, (2) spacecharge limited emission, and (3) simulated plasma oscillations in the long wavelength limit

Going from microscopic to macroscopic on nonuniform growing domains

Throughout development, chemical cues are employed to guide the functional specification of underlying tissues while the spatiotemporal distributions of such chemicals can be influenced by the growth of the tissue itself. These chemicals, termed morphogens, are often modeled using partial differential equations (PDEs). The connection between discrete stochastic and deterministic continuum models of particle migration on growing domains was elucidated by Baker, Yates, and Erban [ Bull. Math. Biol. 72 719 (2010)] in which the migration of individual particles was modeled as an on-lattice position-jump process. We build on this work by incorporating a more physically reasonable description of domain growth. Instead of allowing underlying lattice elements to instantaneously double in size and divide, we allow incremental element growth and splitting upon reaching a predefined threshold size. Such a description of domain growth necessitates a nonuniform partition of the domain. We first demonstrate that an individual-based stochastic model for particle diffusion on such a nonuniform domain partition is equivalent to a PDE model of the same phenomenon on a nongrowing domain, providing the transition rates (which we derive) are chosen correctly and we partition the domain in the correct manner. We extend this analysis to the case where the domain is allowed to change in size, altering the transition rates as necessary. Through application of the master equation formalism we derive a PDE for particle density on this growing domain and corroborate our findings with numerical simulations

Phosphoregulation of DNA repair via the Rad51 auxiliary factor Swi5-Sfr1

Homologous recombination (HR) is a major pathway for the repair of DNA double-strand breaks, the most severe form of DNA damage. The Rad51 protein is central to HR, but multiple auxiliary factors regulate its activity. The heterodimeric Swi5-Sfr1 complex is one such factor. It was previously shown that two sites within the intrinsically disordered domain of Sfr1 are critical for the interaction with Rad51. Here, we show that phosphorylation of five residues within this domain regulates the interaction of Swi5-Sfr1 with Rad51. Biochemical reconstitutions demonstrated that a phosphomimetic mutant version of Swi5-Sfr1 is defective in both the physical and functional interaction with Rad51. This translated to a defect in DNA repair, with the phosphomimetic mutant yeast strain phenocopying the previously established interaction mutant. Interestingly, a strain in which Sfr1 phosphorylation was blocked also displayed sensitivity to DNA damage. Taken together, we propose that controlled phosphorylation of Sfr1 is important for the role of Swi5-Sfr1 in promoting Rad51-dependent DNA repair

CVD of CrO2: towards a lower temperature deposition process

We report on the synthesis of highly oriented a-axis CrO2 films onto (0001) sapphire by atmospheric pressure CVD from CrO3 precursor, at growth temperatures down to 330 degree Celsius, i.e. close to 70 degrees lower than in published data for the same chemical system. The films keep the high quality magnetic behaviour as those deposited at higher temperature, which can be looked as a promising result in view of their use with thermally sensitive materials, e.g. narrow band gap semiconductors.Comment: 13 pages, 4 figure

Evidence for Nodal superconductivity in Sr2_{2}ScFePO3_{3}

Point contact Andreev reflection spectra have been taken as a function of temperature and magnetic field on the polycrystalline form of the newly discovered iron-based superconductor Sr2ScFePO3. A zero bias conductance peak which disappears at the superconducting transition temperature, dominates all of the spectra. Data taken in high magnetic fields show that this feature survives until 7T at 2K and a flattening of the feature is observed in some contacts. Here we inspect whether these observations can be interpreted within a d-wave, or nodal order parameter framework which would be consistent with the recent theoretical model where the height of the P in the Fe-P-Fe plane is key to the symmetry of the superconductivity. However, in polycrystalline samples care must be taken when examining Andreev spectra to eliminate or take into account artefacts associated with the possible effects of Josephson junctions and random alignment of grains.Comment: Published versio

Order preserving pattern matching on trees and DAGs

The order preserving pattern matching (OPPM) problem is, given a pattern string $p$ and a text string $t$, find all substrings of $t$ which have the same relative orders as $p$. In this paper, we consider two variants of the OPPM problem where a set of text strings is given as a tree or a DAG. We show that the OPPM problem for a single pattern $p$ of length $m$ and a text tree $T$ of size $N$ can be solved in $O(m+N)$ time if the characters of $p$ are drawn from an integer alphabet of polynomial size. The time complexity becomes $O(m \log m + N)$ if the pattern $p$ is over a general ordered alphabet. We then show that the OPPM problem for a single pattern and a text DAG is NP-complete

A theoretical framework for transitioning from patient-level to population-scale epidemiological dynamics:influenza A as a case study

Multi-scale epidemic forecasting models have been used to inform population-scale predictions with within-host models and/or infection data collected in longitudinal cohort studies. However, most multi-scale models are complex and require significant modelling expertise to run. We formulate an alternative multi-scale modelling framework using a compartmental model with multiple infected stages. In the large-compartment limit, our easy-to-use framework generates identical results compared to previous more complicated approaches. We apply our framework to the case study of influenza A in humans. By using a viral dynamics model to generate synthetic patient-level data, we explore the effects of limited and inaccurate patient data on the accuracy of population-scale forecasts. If infection data are collected daily, we find that a cohort of at least 40 patients is required for a mean population-scale forecasting error below 10%. Forecasting errors may be reduced by including more patients in future cohort studies or by increasing the frequency of observations for each patient. Our work, therefore, provides not only an accessible epidemiological modelling framework but also an insight into the data required for accurate forecasting using multi-scale models

Random Surfing Without Teleportation

In the standard Random Surfer Model, the teleportation matrix is necessary to ensure that the final PageRank vector is well-defined. The introduction of this matrix, however, results in serious problems and imposes fundamental limitations to the quality of the ranking vectors. In this work, building on the recently proposed NCDawareRank framework, we exploit the decomposition of the underlying space into blocks, and we derive easy to check necessary and sufficient conditions for random surfing without teleportation.Comment: 13 pages. Published in the Volume: "Algorithms, Probability, Networks and Games, Springer-Verlag, 2015". (The updated version corrects small typos/errors

Correlations between structure and dynamics in complex networks

Previous efforts in complex networks research focused mainly on the topological features of such networks, but now also encompass the dynamics. In this Letter we discuss the relationship between structure and dynamics, with an emphasis on identifying whether a topological hub, i.e. a node with high degree or strength, is also a dynamical hub, i.e. a node with high activity. We employ random walk dynamics and establish the necessary conditions for a network to be topologically and dynamically fully correlated, with topological hubs that are also highly active. Zipf's law is then shown to be a reflection of the match between structure and dynamics in a fully correlated network, as well as a consequence of the rich-get-richer evolution inherent in scale-free networks. We also examine a number of real networks for correlations between topology and dynamics and find that many of them are not fully correlated.Comment: 16 pages, 7 figures, 1 tabl