Photo-ionization and residual electron effects in guided streamers

Complementary experiments and numerical modeling reveal the important role of photo-ionization in the guided streamer propagation in helium-air gas mixtures. It is shown that the minimum electron concentration ∼108 cm−3 is required for the regular, repeated propagation of the plasma bullets, while the streamers propagate in the stochastic mode below this threshold. The stochastic-to-regular mode transition is related to the higher background electron density in front of the propagating streamers. These findings help improving control of guided streamer propagation in applications from health care to nanotechnology and improve understanding of generic pre-breakdown phenomena.

Dioxin risk reduction programme at the most severe dioxin hot spot in Vietnam: Residual knowledge, attitude and practices five years post intervention

Bien Hoa Airbase was one of the bulk storage and supply facilities for defoliants during the Vietnam War. Environmental and biological samples taken around the airbase have elevated levels of dioxin. In 2007, a pre-intervention knowledge, attitude and practice (KAP) survey of local residents living in Trung Dung and Tan Phong wards was undertaken regarding appropriate strategies to reduce dioxin exposure. A risk reduction programme was implemented in 2008 and post-intervention KAP surveys were undertaken in 2009 and 2013 to evaluate the longer term impacts. Quantitative assessment was undertaken via a KAP survey in 2013 among 600 local residents randomly selected from the two intervention wards and one control ward (Buu Long). Eight in-depth interviews and two focus group discussions were also undertaken for qualitative assessment. Most programme activities had ceased and dioxin risk communication activities had not been integrated into local routine health education programmes; however, main results generally remained and were better than that in Buu Long. In total, 48.2% of households undertook measures to prevent exposure, higher than those in pre- and post-intervention surveys (25.8% and 39.7%) and the control ward (7.7%). Migration and the sensitive nature of dioxin issues were the main challenges for the programme's sustainability

Cumulative effects on the change of residual value in PPP projects: A comparative case study

Public private partnerships (PPPs) have been adopted widely to provide public facilities and services. According to the PPP agreement, PPP projects would be transferred to the public sector. However, problems related to the subsequent management of ongoing PPP projects have not been studied thoroughly. Residual value risk (RVR) can occur if the public sector cannot obtain the project in the desired conditions as required in the agreement when a project is being transferred. RVR has been identified as an important risk in PPPs and has greatly influenced the outputs of the projects. In order to further observe the change of residual value (RV) during the process of PPP projects and to reveal the internal mechanism for reducing the RVR, a comparative case study of two PPP projects in mainland China and Hong Kong was conducted. Based on the case study, different factors leading to RVR and a series of key risk indicators (KRIs) were identified. The comparison demonstrates that RVR is an important risk that could influence the success of PPP projects. The cumulative effects during the concession period can play significant roles in the occurrence of RVR. Additionally, the cumulative effects in different cases can make the RVR different because of different stakeholders’ efforts on the projects and ways to treat RVR. Finally, alternatives for the public sector to treat RVR were proposed. The findings of this research can reduce RVR and improve the performance of PPP projects.

Analysis of differential gene expression based on Bayesian estimation of variance

Gene expression is arguably the most important indicator of biological function. Thus identifying differentially expressed genes is one of the main aims of high throughout studies that use microarray and RNAseq platforms to study deregulated cellular pathways. There are many tools for analysing differentia gene expression from transciptomic datasets. The major challenge of this topic is to estimate gene expression variance due to the high amount of ‘background noise’ that is generated from biological equipment and the lack of biological replicates. Bayesian inference has been widely used in the bioinformatics field. In this work, we reveal that the prior knowledge employed in the Bayesian framework also helps to improve the accuracy of differential gene expression analysis when using a small number of replicates. We have developed a differential analysis tool that uses Bayesian estimation of the variance of gene expression for use with small numbers of biological replicates. Our method is more consistent when compared to the widely used cyber-t tool that successfully introduced the Bayesian framework to differential analysis. We also provide a user-friendly web based Graphic User Interface for biologists to use with microarray and RNAseq data. Bayesian inference can compensate for the instability of variance caused when using a small number of biological replicates by using pseudo replicates as prior knowledge. We also show that our new strategy to select pseudo replicates will improve the performance of the analysis. - See more at: http://www.eurekaselect.com/node/138761/article#sthash.VeK9xl5k.dpuf

Enhanced sensitivity in detection of Kerr rotation by double modulation and time averaging based on Allan variance

Experiments in spintronics necessarily involve the detection of spin polarization. The sensitivity of this detection becomes an important factor to consider when extending the low temperature studies on semiconductor spintronic devices to room temperature, where the spin signal is weaker. In pump-probe experiments, which optically inject and detect spins, the sensitivity is often improved by using a photoelastic modulator (PEM) for lock-in detection. However, spurious signals can arise if diode lasers are used as optical sources in such experiments, along with a PEM. In this work, we eliminated the spurious electromagnetic coupling of the PEM onto the probe diode laser, by the double modulation technique. We also developed a test for spurious modulated interference in the pump-probe signal, due to the PEM. Besides, an order of magnitude enhancement in the sensitivity of detection of spin polarization by Kerr rotation, to 3x10(-8) rad was obtained by using the concept of Allan variance to optimally average the time series data over a period of 416 s. With these improvements, we are able to experimentally demonstrate at room temperature, photoinduced steady-state spin polarization in bulk GaAs. Thus, the advances reported here facilitate the use of diode lasers with a PEM for sensitive pump-probe experiments. They also constitute a step toward detection of spin-injection in Si at room temperature.

Model selection with misspecified spatial covariance structure

Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.

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.

Smooth bootstrap methods for analysis of longitudinal data

In analysis of longitudinal data, the variance matrix of the parameter estimates is usually estimated by the 'sandwich' method, in which the variance for each subject is estimated by its residual products. We propose smooth bootstrap methods by perturbing the estimating functions to obtain 'bootstrapped' realizations of the parameter estimates for statistical inference. Our extensive simulation studies indicate that the variance estimators by our proposed methods can not only correct the bias of the sandwich estimator but also improve the confidence interval coverage. We applied the proposed method to a data set from a clinical trial of antibiotics for leprosy.

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.

Reduced complexity two stage vector quantization

We address the issue of complexity for vector quantization (VQ) of wide-band speech LSF (line spectrum frequency) parameters. The recently proposed switched split VQ (SSVQ) method provides better rate-distortion (R/D) performance than the traditional split VQ (SVQ) method, even at the requirement of lower computational complexity. but at the expense of much higher memory. We develop the two stage SVQ (TsSVQ) method, by which we gain both the memory and computational advantages and still retain good R/D performance. The proposed TsSVQ method uses a full dimensional quantizer in its first stage for exploiting all the higher dimensional coding advantages and then, uses an SVQ method for quantizing the residual vector in the second stage so as to reduce the complexity. We also develop a transform domain residual coding method in this two stage architecture such that it further reduces the computational complexity. To design an effective residual codebook in the second stage, variance normalization of Voronoi regions is carried out which leads to the design of two new methods, referred to as normalized two stage SVQ (NTsSVQ) and normalized two stage transform domain SVQ (NTsTrSVQ). These two new methods have complimentary strengths and hence, they are combined in a switched VQ mode which leads to the further improvement in R/D performance, but retaining the low complexity requirement. We evaluate the performances of new methods for wide-band speech LSF parameter quantization and show their advantages over established SVQ and SSVQ methods.

Low-density koala (Phascolarctos cinereus) populations in the mulgalands of south-west Queensland. IV. Abundance and conservation status

Urban encroachment on dense, coastal koala populations has ensured that their management has received increasing government and public attention. The recently developed National Koala Conservation Strategy calls for maintenance of viable populations in the wild. Yet the success of this, and other, conservation initiatives is hampered by lack of reliable and generally accepted national and regional population estimates. In this paper we address this problem in a potentially large, but poorly studied, regional population in the State that is likely to have the largest wild populations. We draw on findings from previous reports in this series and apply the faecal standing-crop method (FSCM) to derive a regional estimate of more than 59 000 individuals. Validation trials in riverine communities showed that estimates of animal density obtained from the FSCM and direct observation were in close agreement. Bootstrapping and Monte Carlo simulations were used to obtain variance estimates for our population estimates in different vegetation associations across the region. The most favoured habitat was riverine vegetation, which covered only 0.9% of the region but supported 45% of the koalas. We also estimated that between 1969 and 1995 -30% of the native vegetation associations that are considered as potential koala habitat were cleared, leading to a decline of perhaps 10% in koala numbers. Management of this large regional population has significant implications for the national conservation of the species: the continued viability of this population is critically dependent on the retention and management of riverine and residual vegetation communities, and future vegetation-management guidelines should be cognisant of the potential impacts of clearing even small areas of critical habitat. We also highlight eight management implications.

Brownian particles in stationary and moving traps: The mean and variance of the heat distribution function

A recent theoretical model developed by Imparato et al. Phys of the experimentally measured heat and work effects produced by the thermal fluctuations of single micron-sized polystyrene beads in stationary and moving optical traps has proved to be quite successful in rationalizing the observed experimental data. The model, based on the overdamped Brownian dynamics of a particle in a harmonic potential that moves at a constant speed under a time-dependent force, is used to obtain an approximate expression for the distribution of the heat dissipated by the particle at long times. In this paper, we generalize the above model to consider particle dynamics in the presence of colored noise, without passing to the overdamped limit, as a way of modeling experimental situations in which the fluctuations of the medium exhibit long-lived temporal correlations, of the kind characteristic of polymeric solutions, for instance, or of similar viscoelastic fluids. Although we have not been able to find an expression for the heat distribution itself, we do obtain exact expressions for its mean and variance, both for the static and for the moving trap cases. These moments are valid for arbitrary times and they also hold in the inertial regime, but they reduce exactly to the results of Imparato et al. in appropriate limits. DOI: 10.1103/PhysRevE.80.011118 PACS.

Immediate, cumulative and residual effects of short- and long-term low plane of nutrition on milk protein and casein composition

Immediate and residual effects of two lengths of low plane of nutrition (PON) on the synthesis of milk protein and protein fractions were studied at the Mutdapilly Research Station, in south-east Queensland. Thirty-six multiparous Holstein-Friesian cows, between 46 and 102 days in milk (DIM) initially, were used in a completely randomised design experiment with three treatments. All cows were fed on a basal diet of ryegrass pasture (7.0 kg DM/cow.day), barley-sorghum concentrate mix (2.7 kg DM/cow.day) and a canola meal-mineral mix (1.3 kg DM/cow.day). To increase PON, 5.0 kg DM/cow.day supplemental maize and forage sorghum silage was added to the basal diet. The three treatments were (C) high PON (basal diet + supplemental silage); (L9) low PON (basal diet only) for a period of 9 weeks; and (L3) low PON (basal diet only) for a period of 3 weeks. The experiment comprised three periods (1) covariate – high PON, all groups (5 weeks), (2) period of low PON for either 3 weeks (L3) or 9 weeks (L9), and (3) period of high PON (all groups) to assess ability of cows to recover any production lost as a result of treatments (5 weeks). The low PON treatment periods for L3 and L9 were end-aligned so that all treatment groups began Period 3 together. Although there was a significant effect of L9 on yields of milk, protein, fat and lactose, and concentrations of true protein, whey protein and urea, these were not significantly different from L3. There were no residual effects of L3 or L9 on protein concentration or nitrogen distribution after 5 weeks of realimentation. There was no significant effect of low PON for 3 or 9 weeks on casein concentration or composition.

Self-tuning minimum-variance control of nonlinear systems of the Hammerstein model

Self-tuning is applied to the control of nonlinear systems represented by the Hammerstein model wherein the nonlinearity is any odd-order polynomial. But control costing is not feasible in general. Initial relay control is employed to contain the deviations.