Nanolines on silicon surfaces

Although a wide range of periodic surface nets can be grown on low index silicon surfaces, only a few of these have quasi-one dimensional symmetry. If high index silicon surfaces, such as (553) and (557), are used instead, the surface unit cell contains steps. It is possible to fabricate a number of quasi-one dimensional nanoline systems on the terraces and some of these have nested energy bands near the Fermi level. These nano-scale systems may support exotic many-electron states produced by enhanced electron correlations and a reduction in electron screening in one spatial dimension. In this paper, our groups' experimental and theoretical studies of nanolines phases, grown on both low index and vicinal silicon surfaces are reviewed. These studies give us insight into the electronic properties of artificial nanoline structures.

Synthesis, crystal structure and DNA cleavage activity of (aqua)bis(dipyridophenazine)copper(II) complex

A copper(II) complex of dipyridophenazine, viz., [Cu(dppz)(2)(H2O)](ClO4)(2) (I), has been prepared and structurally characterized by X-ray crystallography. The crystal structure of the complex shows a five-coordinate structure in which two N,N-donor dipyridophenazine (dppz) and one aqua ligand bind to the copper(II) center giving Cu-O and Cu-N bond distances in the range of 1.981(6) to 2.043(6) angstrom. The ESI-MS spectrum of 1 in MeCN shows a peak at m/z value of 313 (100%) indicating the dissociation of the aqua ligand in the solution phase. The complex is one-electron paramagnetic (mu(eff), 1.86 mu(B)). It displays a quasi-reversible Cu(II)/Cu(I) redox process at 0.096 V. The complex is an avid binder to CT DNA giving a binding constant value of 3.5 x 10(5) M-1. It shows significant hydrolytic cleavage of supercoiled pUC19 DNA in dark ill the absence of any external agents. The complex exhibits chemical nuclease activity oil treatment with 3-mercaptopropionic acid as a reducing agent forming hydroxyl radicals. Complex 1 is a model synthetic nuclease and hydrolase showing both modes of DNA cleavage under different reaction conditions. The DNA cleavage activity of 1 is significantly better than its phen analogue but similar to that of the bis-dpq complex.

Photoinduced DNA and Protein Cleavage Activity of Ferrocene-Conjugated Ternary Copper(II) Complexes

Ferrocene-conjugated ternary copper(II) complexes [Cu(L)(B)](ClO4)(2), where L is FcCH(2)N(CH2Py)(2) (Fc = (eta(5)-C5H4)Fe-II(eta(5)-C5H5)) and B is a phenanthroline base, viz., 2,2'-bipyridine (bpy, 1), 1, 10-phenanthroline (phen, 2), dipyrido[3,2-d:2',3'-f]quinoxaline (dpq, 3), and dipyrido[3,2-a:2',3'-c]phenazine (dppz, 4), have been synthesized and characterized by various spectroscopic and analytical techniques. The bpy complex 1, as its hexafluorophosphate salt, has been structurally characterized by X-ray crystallography. The molecular structure shows the copper(II) center having an essentially square-pyramidal coordination geometry in which L with a pendant ferrocenyl (Fc) moiety and bpy show respective tridentate and bidentate modes of binding to the metal center. The complexes are redox active, showing a reversible cyclic voltammetric response of the Fc(+)-Fc couple near 0.5 V vs SCE and a quasi-reversible Cu(II)-Cu(I) couple near 0.0 V. Complexes 2-4 show binding affinity to calf thymus (CT) DNA, giving binding constant (K-b) values in the range of 4.2 x 10(4) to 2.5 x 10(5) M-1. Thermal denaturation and viscometric titration data suggest groove binding and/or a partial intercalative mode of binding of the complexes to CT DNA. The complexes show good binding propensity to the bovine serum albumin (BSA) protein, giving K-BSA values of similar to 10(4) M-1 for the bpy and phen complexes and similar to 10(5) M-1 for the dpq and dppz complexes. Complexes 2-4 exhibit efficient chemical nuclease activity in the presence of 3-mercapto-propionic acid (MPA) as a reducing agent or hydrogen peroxide (H2O2) as an oxidizing agent. Mechanistic studies reveal formation of hydroxyl radicals as the reactive species. The dpq and dppz complexes are active in cleaving supercoiled (SC) pUC19 DNA on photoexposure to visible light of different wavelengths including red light using an argon-krypton mixed gas ion laser. Mechanistic investigations using various inhibitors reveal the fort-nation of hydroxyl radicals in the DNA photocleavage reactions. The dppz complex 4, which shows efficient photoioduced BSA cleavage activity, is a potent multifunctional model nuclease and protease in the chemistry of photodynamic therapy (PDT) of cancer.

Haemodialysis work environment contributors to job satisfaction and stress: A sequential mixed methods study

Background: Haemodialysis nurses form long term relationships with patients in a technologically complex work environment. Previous studies have highlighted that haemodialysis nurses face stressors related to the nature of their work and also their work environments leading to reported high levels of burnout. Using Kanters (1997) Structural Empowerment Theory as a guiding framework, the aim of this study was to explore the factors contributing to satisfaction with the work environment, job satisfaction, job stress and burnout in haemodialysis nurses. Methods: Using a sequential mixed-methods design, the first phase involved an on-line survey comprising demographic and work characteristics, Brisbane Practice Environment Measure (B-PEM), Index of Work Satisfaction(IWS), Nursing Stress Scale (NSS) and the Maslach Burnout Inventory (MBI). The second phase involved conducting eight semi-structured interviews with data thematically analyzed. Results: From the 417 nurses surveyed the majority were female (90.9 %), aged over 41 years of age (74.3 %), and 47.4 % had worked in haemodialysis for more than 10 years. Overall the work environment was perceived positively and there was a moderate level of job satisfaction. However levels of stress and emotional exhaustion (burnout) were high. Two themes, ability to care and feeling successful as a nurse, provided clarity to the level of job satisfaction found in phase 1. While two further themes, patients as quasi-family and intense working teams, explained why working as a haemodialysis nurse was both satisfying and stressful. Conclusions: Nurse managers can use these results to identify issues being experienced by haemodialysis nurses working in the unit they are supervising.

Synthesis, crystal structures and protease activity of amino acid Schiff base iron(III) complexes

Iron(III) complexes, (NHEt3)[Fe(III)(sal-met)(2)] and (NHEt3)[Fe(III)(sal-phe)(2)], of amino acid Schiffbase ligands, viz., N-salicylidene-L-methionine and N-salicylidene L-phenylalanine, have been prepared and their binding to bovine serum albumin (BSA) and photo-induced BSA cleavage activity have been investigated. The complexes are structurally characterized by single crystal X-ray crystallography. The crystal Structures of the discrete mononuclear rnonoanionic complexes show FeN2O4 octahedral coordination geometry in which the tridentate dianionic amino acid Schiff base ligand binds through phenolate and carboxylate oxygen and imine nitrogen atoms. The imine nitrogen atoms are trans to each other. The Fe-O and Fe-N bond distances range between 1.9 and 2.1 angstrom. The sal-met complex has two pendant thiomethyl groups. The high-spin iron(III) complexes (mu(eff) similar to 5.9 mu(B)) exhibit quasi-reversible Fe(III)/Fe(II) redox process near -0.6 V vs. SCE in water. These complexes display a visible electronic hand near 480 nm in tris-HCl buffer assignable to the phenolate-to-iron(III) charge transfer transition. The water soluble complexes bind to BSA giving binding constant values of similar to 10(5) M-1. The Complexes show non-specific oxidative cleavage of BSA protein on photo-irradiation with UV-A light of 365 nm.

Modeling strategies in longitudinal data analysis: Covariate, variance function and correlation structure selection

A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

Analytical studies of gain optimization in CO2-N2 gasdynamic lasers employing two-dimensional wedge nozzles

An analytical method has been proposed to optimise the small-signaloptical gain of CO2-N2 gasdynamic lasers (gdl) employing two-dimensional (2D) wedge nozzles. Following our earlier work the equations governing the steady, inviscid, quasi-one-dimensional flow in the wedge nozzle of thegdl are reduced to a universal form so that their solutions depend on a single unifying parameter. These equations are solved numerically to obtain similar solutions for the various flow quantities, which variables are subsequently used to optimize the small-signal-gain. The corresponding optimum values like reservoir pressure and temperature and 2D nozzle area ratio also have been predicted and graphed for a wide range of laser gas compositions, with either H2O or He as the catalyst. A large number of graphs are presented which may be used to obtain the optimum values of small signal gain for a wide range of laser compositions without further computations.

Rank-based regression for analysis of repeated measures

We consider rank-based regression models for repeated measures. To account for possible withinsubject correlations, we decompose the total ranks into between- and within-subject ranks and obtain two different estimators based on between- and within-subject ranks. A simple perturbation method is then introduced to generate bootstrap replicates of the estimating functions and the parameter estimates. This provides a convenient way for combining the corresponding two types of estimating function for more efficient estimation.

A modified pseudolikelihood approach for analysis of longitudinal data

We consider the analysis of longitudinal data when the covariance function is modeled by additional parameters to the mean parameters. In general, inconsistent estimators of the covariance (variance/correlation) parameters will be produced when the "working" correlation matrix is misspecified, which may result in great loss of efficiency of the mean parameter estimators (albeit the consistency is preserved). We consider using different "Working" correlation models for the variance and the mean parameters. In particular, we find that an independence working model should be used for estimating the variance parameters to ensure their consistency in case the correlation structure is misspecified. The designated "working" correlation matrices should be used for estimating the mean and the correlation parameters to attain high efficiency for estimating the mean parameters. Simulation studies indicate that the proposed algorithm performs very well. We also applied different estimation procedures to a data set from a clinical trial for illustration.

Effects of variance-function misspecification in analysis of longitudinal data

The approach of generalized estimating equations (GEE) is based on the framework of generalized linear models but allows for specification of a working matrix for modeling within-subject correlations. The variance is often assumed to be a known function of the mean. This article investigates the impacts of misspecifying the variance function on estimators of the mean parameters for quantitative responses. Our numerical studies indicate that (1) correct specification of the variance function can improve the estimation efficiency even if the correlation structure is misspecified; (2) misspecification of the variance function impacts much more on estimators for within-cluster covariates than for cluster-level covariates; and (3) if the variance function is misspecified, correct choice of the correlation structure may not necessarily improve estimation efficiency. We illustrate impacts of different variance functions using a real data set from cow growth.

Criteria for working-correlation-structure selection in GEE: Assessment via simulation

Efficiency of analysis using generalized estimation equations is enhanced when intracluster correlation structure is accurately modeled. We compare two existing criteria (a quasi-likelihood information criterion, and the Rotnitzky-Jewell criterion) to identify the true correlation structure via simulations with Gaussian or binomial response, covariates varying at cluster or observation level, and exchangeable or AR(l) intracluster correlation structure. Rotnitzky and Jewell's approach performs better when the true intracluster correlation structure is exchangeable, while the quasi-likelihood criteria performs better for an AR(l) structure.

Unbiased estimating equations from working correlation models for irregularly timed repeated measures

The method of generalized estimating equation-, (GEEs) has been criticized recently for a failure to protect against misspecification of working correlation models, which in some cases leads to loss of efficiency or infeasibility of solutions. However, the feasibility and efficiency of GEE methods can be enhanced considerably by using flexible families of working correlation models. We propose two ways of constructing unbiased estimating equations from general correlation models for irregularly timed repeated measures to supplement and enhance GEE. The supplementary estimating equations are obtained by differentiation of the Cholesky decomposition of the working correlation, or as score equations for decoupled Gaussian pseudolikelihood. The estimating equations are solved with computational effort equivalent to that required for a first-order GEE. Full details and analytic expressions are developed for a generalized Markovian model that was evaluated through simulation. Large-sample ".sandwich" standard errors for working correlation parameter estimates are derived and shown to have good performance. The proposed estimating functions are further illustrated in an analysis of repeated measures of pulmonary function in children.

Working correlation structure misspecification, estimation and covariate design: Implications for generalised estimating equations performance

The method of generalised estimating equations for regression modelling of clustered outcomes allows for specification of a working matrix that is intended to approximate the true correlation matrix of the observations. We investigate the asymptotic relative efficiency of the generalised estimating equation for the mean parameters when the correlation parameters are estimated by various methods. The asymptotic relative efficiency depends on three-features of the analysis, namely (i) the discrepancy between the working correlation structure and the unobservable true correlation structure, (ii) the method by which the correlation parameters are estimated and (iii) the 'design', by which we refer to both the structures of the predictor matrices within clusters and distribution of cluster sizes. Analytical and numerical studies of realistic data-analysis scenarios show that choice of working covariance model has a substantial impact on regression estimator efficiency. Protection against avoidable loss of efficiency associated with covariance misspecification is obtained when a 'Gaussian estimation' pseudolikelihood procedure is used with an AR(1) structure.

Community-based social marketing: Effects on social norms

Purpose This research investigates whether application of a community-based social marketing principle, namely increasing the visibility of a target behaviour in the community, can change social norms surrounding the behaviour. Design/methodology/approach A repeated measures quasi-experimental design was employed to evaluate the Victorian Health Promotion Foundation’s Walk to School 2013 programme, which increases the visibility of walking to and from school through programme participation to promote active transportation for primary school children. The target population for the survey were caregivers of primary school children aged between 5-12 years old. The final sample size across the three online surveys administered was 102 respondents. Findings The results suggest that the programme increased caregivers’ perceptions that children in their community walked to and from school and that walking to and from school is socially acceptable. Originality/value The study contributes to addressing the recent call for research examining the relationship between community-based social marketing principles and programme outcomes. Further, the results provide insight for enhancing the social norms approach, which has traditionally relied on changing social norms exclusively through media campaigns.

On the moulding of population viscosity by natural selection

In this paper, we explore the conjoint evolution of dispersal and social behaviour. The model investigated is of a population distributed over a number of sites each with a carrying capacity of two adults and an episode of dispersal in the juvenile stage. The fertilities are governed by whether an individual and its neighbour are selfish or co-operative. It is shown that the best dispersal strategy for the co-operative genotype always involves lower levels of dispersal; and further that ecological conditions favouring low levels of dispersal increase the selective advantage of a co-operative genotype. Given this positive feedback, we suggest that in any taxon viscosity and co-operativity will tend to be correlated and bimodally distributed. Hence we predict the existence of two kinds of animal societies; viscous and co-operative (e.g. quasi-social wasps such as Mischocyttarus), and non-viscous and selfish (e.g. communal sphecid wasps such as Cerceris), and relatively few social groups with intermediate levels of co-operativity and viscosity. We also suggest that when one of the two sexes disperses, it will be the sex with lower potential for co-operative behaviour.