Alfvén Waves in Simulations of Solar Photospheric Vortices

Using advanced numerical magneto-hydrodynamic simulations of the magnetized solar photosphere, including non-gray radiative transport and a non-ideal equation of state, we analyze plasma motions in photospheric magnetic vortices. We demonstrate that apparent vortex-like motions in photospheric magnetic field concentrations do not exhibit "tornado"-like behavior or a "bath-tub" effect. While at each time instance the velocity field lines in the upper layers of the solar photosphere show swirls, the test particles moving with the time-dependent velocity field do not demonstrate such structures. Instead, they move in a wave-like fashion with rapidly changing and oscillating velocity field, determined mainly by magnetic tension in the magnetized intergranular downflows. Using time-distance diagrams, we identify horizontal motions in the magnetic flux tubes as torsional Alfvén perturbations propagating along the nearly vertical magnetic field lines with local Alfvén speed.

The effects of transients on photospheric and chromospheric power distributions

We have observed a quiet Sun region with the Swedish 1-meter Solar Telescope (SST) equipped with CRISP Imaging SpectroPolarimeter. High-resolution, high-cadence, H-alpha line scanning images were taken to observe different layers of the solar atmosphere from the photosphere to upper chromosphere. We study the distribution of power in different period-bands at different heights. Power maps of the upper photosphere and the lower chromosphere show suppressed power surrounding the magnetic-network elements, known as "magnetic shadows". These also show enhanced power close to the photosphere, traditionally referred to as"power halos". The interaction between acoustic waves and inclined magnetic fields is generally believed to be responsible for these two effects. In this study we explore if small-scale transients can influence the distribution of power at different heights. We show that the presence of transients, like mottles, Rapid Blueshifted Excursions (RBEs) and Rapid Redshifted Excursions (RREs), can strongly influence the power-maps. The short and finite lifetime of these events strongly affects all powermaps, potentially influencing the observed power distribution. We show that Doppler-shifted transients like RBEs and RREs that occur ubiquitously, can have a dominant effect on the formation ofthe power halos in the quiet Sun. For magnetic shadows, transients like mottles do not seem to have a significant effect in the power suppression around 3 minutes and wave interaction may play a key role here. Our high cadence observations reveal that flows, waves and shocks manifest in presence of magnetic fields to form a non-linear magnetohydrodynamic system.

Characterization of a thymidylate synthase (TS)-inducible cell line: a model system for studying sensitivity to TS- and non-TS-targeted chemotherapies

Thymidylate synthase (TS) is responsible for the de novo synthesis of thymidylate, which is required for DNA synthesis and repair and which is an important target for fluoropyrimidines such as 5-fluorouracil (5-FU), and antifolates such as Tomudex (TDX), ZD9331, and multitargeted antifolate (MTA). To study the importance of TS expression in determining resistance to these agents, we have developed an MDA435 breast cancer-derived cell line with tetracycline-regulated expression of TS termed MTS-5. We have demonstrated that inducible expression of TS increased the IC(50) dose of the TS-targeted therapeutic agents 5-FU, TDX, and ZD9331 by 2-, 9- and 24-fold respectively. An IC(50) dose for MTA was unobtainable when TS was overexpressed in these cells, which indicated that MTA toxicity is highly sensitive to increased TS expression levels. The growth inhibitory effects of the chemotherapeutic agents CPT-11, cisplatin, oxaliplatin, and Taxol were unaffected by TS up-regulation. Cell cycle analyses revealed that IC(50) doses of 5-FU, TDX and MTA caused an S-phase arrest in cells that did not overexpress TS, and this arrest was overcome when TS was up-regulated. Furthermore, the S-phase arrest was accompanied by 2- to 4-fold increased expression of the cell cycle regulatory genes cyclin E, cyclin A, and cyclin dependent kinase 2 (cdk2). These results indicate that acute increases in TS expression levels play a key role in determining cellular sensitivity to TS-directed chemotherapeutic drugs by modulating the degree of S-phase arrest caused by these agents. Moreover, CPT-11, cisplatin, oxaliplatin, and Taxol remain highly cytotoxic in cells that overexpress TS.

Theoretical considerations of electrochemical phase formation for an ideal Frank-van der Merwe system - Ag on Au(111) and Au(100)

: Static calculation and preliminary kinetic Monte Carlo simulation studies are undertaken for the nucleation and growth on a model system which follows a Frank-van der Merwe mechanism. In the present case, we consider the deposition of Ag on Au(100) and Au(111) surfaces. The interactions were calculated using the embedded atom model. The kinetics of formation and growth of 2D Ag structures on Au(100) and Au(111) is investigated and the influence of surface steps on this phenomenon is studied. Very different time scales are predicted for Ag diffusion on Au(100) and Au(111), thus rendering very different regimes for the nucleation and growth of the related 2D phases. These observations are drawn from the application of a model free of any adjustable parameter.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Non-aqueous silicone elastomer gels as a vaginal microbicide delivery system for the HIV-1 entry inhibitor maraviroc

Aqueous semi-solid polymeric gels, such as those based on hydroxyethylcellulose (HEC) and polyacrylic acid (e.g. Carbopol®), have a long history of use in vaginal drug delivery. However, despite their ubiquity, they often provide sub-optimal clinical performance, due to poor mucosal retention and limited solubility for poorly water-soluble actives. These issues are particularly pertinent for vaginal HIV microbicides, since many lead candidates are poorly water-soluble and where a major goal is the development of a coitally independent, once daily gel product. In this study, we report the use of a non-aqueous silicone elastomer gel for vaginal delivery of the HIV-1 entry inhibitor maraviroc. In vitro rheological, syringeability and retention studies demonstrated enhanced performance for silicone gels compared with a conventional aqueous HEC gel, while testing of the gels in the slug model confirmed a lack of mucosal irritancy. Pharmacokinetic studies following single dose vaginal administration of a maraviroc silicone gel in rhesus macaques showed higher and sustained MVC levels in vaginal fluid, vaginal tissue and plasma compared with a HEC gel containing the same maraviroc loading. The results demonstrate that non-aqueous silicone gels have potential as a formulation platform for coitally independent vaginal HIV microbicides.

Role of environmental correlations in the non-Markovian dynamics of a spin system

We study the dynamics of a chain of interacting quantum particles affected by an individual or collective environment(s), focusing on the role played by the environmental quantum correlations over the evolution of the chain. The presence of entanglement in the state of the environment magnifies the non-Markovian nature of the chain's dynamics, giving rise to structures in figures of merit such as spin entanglement and purity that are not observed under a separable environmental state. Our analysis can be relevant to problems tackling the open-system dynamics of biological complexes of strong current interest.

Non-Markovian effects on the nonlocality of a qubit-oscillator system

Non-Markovian evolutions are responsible for a wide variety of physically interesting effects. Here, we study nonlocality of the nonclassical state of a system consisting of a qubit and an oscillator exposed to the effects of non-Markovian evolutions. We find that the different facets of non-Markovianity affect nonlocality in different and nonobvious ways, ranging from pronounced insensitivity of the Bell function to quite spectacular evidence of information kickback.

Non-competitive phenotypic differences can have a strong effect on ideal free distributions

1. We present a model of the ideal free distribution (IFD) where differences between phenotypes other than those involved in direct competition for resources are considered. We show that these post-acquisitional differences can have a dramatic impact on the predicted distributions of individuals.

2. Specifically, we predict that, when the relative abilities of phenotypes are independent of location, there will be a continuum of mixed evolutionarily stable strategy (ESS) distributions (where all phenotypes are present in all patches).

3, When the relative strengths of the post-acquisitional trait in the two phenotypes differ between patches, however, we predict only a single ESS at equilibrium. Further, this distribution may be fully or partially segregated (with the distribution of at least one phenotype being spatially restricted) but it will never be mixed.

4, Our results for post-acquisitional traits mirror those of Parker (1982) for direct competitive traits. This comparison illustrates that it does not matter whether individual differences are expressed before or after competition for resources, they will still exert considerable influence on the distribution of the individuals concerned.

Dynamical role of system-environment correlations in non-Markovian dynamics

We analyze the role played by system-environment correlations in the emergence of non-Markovian dynamics. By working within the framework developed in Breuer et al. [Phys. Rev. Lett. 103, 210401 (2009)], we unveil a fundamental connection between non-Markovian behavior and dynamics of system-environment correlations. We derive an upper bound to the rate of change of the distinguishability between different states of the system that explicitly depends on the establishment of correlations between system and environment. We illustrate our results using a fully solvable spin-chain model, which allows us to gain insight into the mechanisms triggering non-Markovian evolution. © 2012 American Physical Society.

On Variable Selection of a Nonlinear Non-parametric System with a Limited Data Set: A Stepwise Algorithm

his paper considers a problem of identification for a high dimensional nonlinear non-parametric system when only a limited data set is available. The algorithms are proposed for this purpose which exploit the relationship between the input variables and the output and further the inter-dependence of input variables so that the importance of the input variables can be established. A key to these algorithms is the non-parametric two stage input selection algorithm.

Irish Power System Primary Frequency Response Metrics during Different System Non Synchronous Penetrations.

This paper discusses the use of primary frequency response metrics to assess the dynamics of frequency disturbance data with the presence of high system non synchronous penetration (SNSP) and system inertia variation. The Irish power system has been chosen as a study case as it experiences a significant level of SNSP from wind turbine generation and imported active power from HVDC interconnectors. Several recorded actual frequency disturbances were used in the analysis. These data were measured and collected from the Irish power system from October 2010 to June 2013. The paper has shown the impact of system inertia and SNSP variation on the performance of primary frequency response metrics, namely: nadir frequency, rate of change of frequency, inertial and primary frequency response.