Insights into bacterial genome composition through variable target GC content profiling

This study presents a new computational method for guanine (G) and cytosine (C), or GC, content profiling based on the idea of multiple resolution sampling (MRS). The benefit of our new approach over existing techniques follows from its ability to locate significant regions without prior knowledge of the sequence, nor the features being sought. The use of MRS has provided novel insights into bacterial genome composition. Key findings include those that are related to the core composition of bacterial genomes, to the identification of large genomic islands (in Enterobacterial genomes), and to the identification of surface protein determinants in human pathogenic organisms (e.g., Staphylococcus genomes). We observed that bacterial surface binding proteins maintain abnormal GC content, potentially pointing to a viral origin. This study has demonstrated that GC content holds a high informational worth and hints at many underlying evolutionary processes. For online Supplementary Material, see www.liebertonline.com.

Textural fractography of fatigue failures under variable cycle loading

A new concept of counting time at fatigue processes is proposed, aimed to reach fractographic compatibility in cases of different loading sequences. Values of cycle effectivity are summarized to give the new reference time. The improvement is shown in application - textural fractography of three specimens loaded by constant cycle, constant cycle with periodic overloading, and a random block, respectively. In contrast to the conventional crack growth rate, the reference crack growth rate is related to common morphologic features of all fracture surfaces.

Variable incidence angle localized surface plasmon resonance graphene biosensor

This paper investigates the enhancement of sensitivity of variable incidence angle LSPR biosensor by monitoring biomolecular interactions of biotin-streptavidin with gold thin film. The investigation is carried out by means of introducing an additional layer of graphene sheet on top of gold layer (graphene biosensor) and using different coupling configuration of laser beam. The sensitivity, which is indicated by the shift of plasmon resonance angle, increases with graphene deposited onto the gold layers and is linearly related with the number of graphene layers. In addition, an investigation of the shift of plasmon dip is carried out for two different analyte interfaces: air and water. It is found that graphene biosensor has better sensitivity for triangular prism, higher prism angle, and water interface. The evaluation approach involves a plot of a reflectivity curve as a function of the angle of incidence while the operating wavelength is kept fixed.

Latent variable models of need for uniqueness

The theory of uniqueness has been invoked to explain attitudinal and behavioral nonconformity with respect to peer-group, social-cultural, and statistical norms, as well as the development of a distinctive view of self via seeking novelty goods, adopting new products, acquiring scarce commodities, and amassing material possessions. Present research endeavors in psychology and consumer behavior are inhibited by uncertainty regarding the psychometric properties of the Need for Uniqueness Scale, the primary instrument for measuring individual differences in uniqueness motivation. In an important step toward facilitating research on uniqueness motivation, we used confirmatory factor analysis to evaluate three a priori latent variable models of responses to the Need for Uniqueness Scale. Among the a priori models, an oblique three-factor model best accounted for commonality among items. Exploratory factor analysis followed by estimation of unrestricted three- and four-factor models revealed that a model with a complex pattern of loadings on four modestly correlated factors may best explain the latent structure of the Need for Uniqueness Scale. Additional analyses evaluated the associations among the three a priori factors and an array of individual differences. Results of those analyses indicated the need to distinguish among facets of the uniqueness motive in behavioral research.

Performance of the Giant Reed (Arundo donax) in experimental wetlands receiving variable loads of industrial stormwater

Two emergent macrophytes, Arundo donax and Phragmites australis, were established in experimental subsurface flow, gravel-based constructed wetlands (CWs) and challenged by untreated stormwater collected from the hard-pan and other surfaces of a dairy processing factory in south-west Victoria, Australia. The hydraulic loading rate was tested at two levels, sequentially, 3.75 and 7.5 cm day -1. Some of the monitored variables were removed more efficiently by the planted beds in comparison to unplanted CWs (biochemical oxygen demand (BOD), total nitrogen (TN) and total phosphorus (TP); p<0.007) but there was no significant difference between the A. donax and P. australis CWs in removal of BOD, suspended solids (SS) and TN (p>0.007) at 3.75 cm day -1 or SS and TN at 7.5 cm day -1. At 3.75 cm day -1, BOD, SS, TN and TP removal in the A. donax and P. australis CWs was 71%, 61%, 78% and 75% and 65%, 60%, 73% and 41%, respectively. Nutrient removal at 7.5 cm day -1 in the A. donax and P. australis beds was 87%, 91%, 84% and 71% and 96%, 94%, 87% and 55%, respectively. As expected, the A. donax CWs produced considerably more biomass (10±1.2 kg wet weight) than the P. australis CWs (2.7±1.2 kg wet weight). This equates to approximately 107 and 36 tonnes ha -1 year -1 biomass (dry weight) for A. donax and P. australis, respectively (assuming 250 days of growing season and singlecut harvest). The performance similarity of the A. donax- and P. australis-planted CWs indicates that either may be used in HSSF wetlands treating dairy factory stormwater, although the planting of A. donax provides additional opportunities for secondary income streams through utilisation of the biomass produced.

Direct method for optimal power management in hybrid electric vehicles

Hybrid electric vehicles are powered by an electric system and an internal combustion engine. The components of a hybrid electric vehicle need to be coordinated in an optimal manner to deliver the desired performance. This paper presents an approach based on direct method for optimal power management in hybrid electric vehicles with inequality constraints. The approach consists of reducing the optimal control problem to a set of algebraic equations by approximating the state variable which is the energy of electric storage, and the control variable which is the power of fuel consumption. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The advantage of the developed method is that its computational complexity is less than that of dynamic and non-linear programming approaches. Also, to use dynamic or non-linear programming, the problem should be discretized resulting in the loss of optimization accuracy. The propsed method, on the other hand, does not require the discretization of the problem producing more accurate results. An example is solved to demonstrate the accuracy of the proposed approach. The results of Haar wavelets, and Chebyshev and Legendre polynomials are presented and discussed. © 2011 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

Video genre categorization using audio wavelet coefficients

In this paper, we investigate the use of a wavelet transform-based analysis of audio tracks accompanying videos for the problem of automatic program genre detection. We compare the classification performance based on wavelet-based audio features to that using conventional features derived from Fourier and time analysis for the task of discriminating TV programs such as news, commercials, music shows, concerts, motor racing games, and animated cartoons. Three different classifiers namely the Decision Trees, SVMs, and k-Nearest Neighbours are studied to analyse the reliability of the performance of our wavelet features based approach. Further, we investigate the issue of an appropriate duration of an audio clip to be analyzed for this automatic genre determination. Our experimental results show that features derived from the wavelet transform of the audio signal can very well separate the six video genres studied. It is also found that there is no significant difference in performance with varying audio clip durations across the classifiers.

Labour productivity measurement with variable returns to scale in Australia's construction industry

As an important productivity indicator, the change of labour productivity is one indispensable marker in determining the rise or fall of overall industrial performance. This study aims to address whether the labour productivity level of the Australian construction industry has, in fact, shown a huge improvement during the last few decades. This article constructs a measuring method estimating labour productivity changes based on the data envelopment analysis technique with variable returns to scale. By adopting a production frontier approach, the labour productivity index can be broken down into components attributable to efficiency change, technological progress and capital accumulation. The numerical results exemplified by a single-input and single-output system indicate that the average annual labour productivity levels of the construction industry are slowly growing in all the Australian states and territories. However, the year-on-year change in the overall labour productivity performance does not maintain a long-term increase over the period 1990–2008. The study forms the basis for further industrial productivity research. Proposals and recommendations are expected to be beneficial for making policy and strategic decisions to improve the performance of the construction industry.

Combustion simulations for a self controlling variable compression ratio connecting rod

Variable compression ratio enables an engine to achieve increased efficiency at part loads, where the majority of driving occurs, without sacrificing full load power requirements or increasing the risk of engine knock. Although over 100 patents and patent applications exist none of these systems has been commercialized yet due to issues related to feasibility, cost and frictional loss. A new approach of a self controlling variable compression ratio connecting rod is presented that does not need a friction intensive external activation and that could even be retrofitted. The potential in fuel consumption and exhaust emission reduction as well as increased power and torque output for this concept has been verified in combustion simulations utilizing the latest research results related to the dynamic heat transfer in the combustion chamber from Professor Kleinschmidt from the University of Siegen, Germany. The self controlling variable compression ratio connecting rod allows the con rod to compress at high load conditions thereby increasing cylinder volume to alleviate combustion pressures and temperatures and therefore limit knock onset. The biggest efficiency gains can be achieved at medium load where the reduction of heat loss during the compression of the connecting rod plays a major role additional to the well known efficiency gains of an increased compression ratio. The combustion simulation results shows fuel consumption can be reduced by between 3% and 5% during part load and wide open throttle operation at various engine speeds. Emissions are also reduced significantly; particularly NOx and CO emissions were reduced by up to 35%.The self controlling variable compression ratio connecting rod allows the con rod to compress at high load conditions thereby increasing cylinder volume to alleviate combustion pressures and temperatures and therefore limit knock onset. The biggest efficiency gains can be achieved at medium load where the reduction of heat loss during the compression of the connecting rod plays a major role additional to the well known efficiency gains of an increased compression ratio.The combustion simulation results shows fuel consumption can be reduced by between 3% and 5% during part load and wide open throttle operation at various engine speeds. Emissions are also reduced significantly; particularly NOx and CO emissions were reduced by up to 35%.