Assessing the energy efficiency of gear oils via the FZG test machine

Energy efficient lubricants are becoming increasingly popular. This is due to a global increase in environmental awareness combined with the potential of reducing operating costs. A new test method of evaluating the energy efficiency of gear oils has been described in this report. The method involves measuring the power required by an FZG test rig to run while using a particular test lubricant. For each oil that was being evaluated, the rig was run for 10 minutes at a load stage of 10. Six extreme pressure (EP) industrial gear oils of mineral base were tested. The difference in power requirements between the best and the worst performing oils was 2.77 and 3.24 kW, respectively. This equates to a 14.6% reduction in power, a significant amount if considered in relation to a high powered industrial machine. The oils of superior performance were noticed to run at reduced temperatures. They were also more expensive than the other products of lesser performance.

Using a current source to improve efficiency of a plasma system

This paper presents the possibility of utilizing a current source topology instead of a voltage source as an efficient, flexible and reliable power supply for plasma applications. A buck-boost converter with a current controller has been used to transfer energy from an inductor to a plasma system. A control strategy has also been designed to satisfy all the desired purposes. The main concept behind this topology is to provide high dv/dt regardless of the switching speed of a power switch and to control the current level to properly transfer adequate energy to various plasma applications.

Enhancing agrobacterium-mediated transformation efficiency of sugarcane : progress towards an efficient, genotype-independent method

Several key issues need to be resolved before an efficient and reproducible Agrobacterium-mediated sugarcane transformation method can be developed for a wider range of sugarcane cultivars. These include loss of morphogenetic potential in sugarcane cells after Agrobacterium-mediated transformation, effect of exposure to abiotic stresses during in vitro selection, and most importantly the hypersensitive cell death response of sugarcane (and other nonhost plants) to Agrobacterium tumefaciens. Eight sugarcane cultivars (Q117, Q151, Q177, Q200, Q208, KQ228, QS94-2329, and QS94-2174) were evaluated for loss of morphogenetic potential in response to the age of the culture, exposure to Agrobacterium strains, and exposure to abiotic stresses during selection. Corresponding changes in the polyamine profiles of these cultures were also assessed. Strategies were then designed to minimize the negative effects of these factors on the cell survival and callus proliferation following Agrobacterium-mediated transformation. Some of these strategies, including the use of cell death protector genes and regulation of intracellular polyamine levels, will be discussed.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Correlations between designability and various structural characteristics of protein lattice models

Using six kinds of lattice types (4×4 ,5×5 , and6×6 square lattices;3×3×3 cubic lattice; and2+3+4+3+2 and4+5+6+5+4 triangular lattices), three different size alphabets (HP ,HNUP , and 20 letters), and two energy functions, the designability of proteinstructures is calculated based on random samplings of structures and common biased sampling (CBS) of proteinsequence space. Then three quantities stability (average energy gap),foldability, and partnum of the structure, which are defined to elucidate the designability, are calculated. The authors find that whatever the type of lattice, alphabet size, and energy function used, there will be an emergence of highly designable (preferred) structure. For all cases considered, the local interactions reduce degeneracy and make the designability higher. The designability is sensitive to the lattice type, alphabet size, energy function, and sampling method of the sequence space. Compared with the random sampling method, both the CBS and the Metropolis Monte Carlo sampling methods make the designability higher. The correlation coefficients between the designability, stability, and foldability are mostly larger than 0.5, which demonstrate that they have strong correlation relationship. But the correlation relationship between the designability and the partnum is not so strong because the partnum is independent of the energy. The results are useful in practical use of the designability principle, such as to predict the proteintertiary structure.

Use of virtual index for measuring efficiency of innovation systems : a cross-country study

In this study we propose a virtual index for measuring the relative innovativeness of countries. Using a multistage virtual benchmarking process, the best and rational benchmark is extracted for inefficient ISs. Furthermore, Tobit and Ordinary Least Squares (OLS) regression models are used to investigate the likelihood of changes in inefficiencies by investigating country-specific factors. The empirical results relating to the virtual benchmarking process suggest that the OLS regression model would better explain changes in the performance of innovation- inefficient countries.

The Relative Efficiency of International, Domestic, and Budget Airlines : Nonparametric Evidence

This study determines whether the inclusion of low-cost airlines in a dataset of international and domestic airlines has an impact on the efficiency scores of so-called ‘prestigious’ purportedly ‘efficient’ airlines. This is because while many airline studies concern efficiency, none has truly included a combination of international, domestic and budget airlines. The present study employs the nonparametric technique of data envelopment analysis (DEA) to investigate the technical efficiency of 53 airlines in 2006. The findings reveal that the majority of budget airlines are efficient relative to their more prestigious counterparts. Moreover, most airlines identified as inefficient are so largely because of the overutilization of non-flight assets.

Efficiency of research performance of Australian universities : a reappraisal using a bootstrap truncated regression approach

The motivation of the study stems from the results reported in the Excellence in Research for Australia (ERA) 2010 report. The report showed that only 12 universities performed research at or above international standards, of which, the Group of Eight (G8) universities filled the top eight spots. While performance of universities was based on number of research outputs, total amount of research income and other quantitative indicators, the measure of efficiency or productivity was not considered. The objectives of this paper are twofold. First, to provide a review of the research performance of 37 Australian universities using the data envelopment analysis (DEA) bootstrap approach of Simar and Wilson (2007). Second, to determine sources of productivity drivers by regressing the efficiency scores against a set of environmental variables.

The FAM deubiquitylating enzyme localizes to multiple points of protein trafficking in epithelia, where it associates with E-cadherin and β-catenin

Ubiquitylation is a necessary step in the endocytosis and lysosomal trafficking of many plasma membrane proteins and can also influence protein trafficking in the biosynthetic pathway. Although a molecular understanding of ubiquitylation in these processes is beginning to emerge, very little is known about the role deubiquitylation may play. Fat Facets in mouse (FAM) is substrate-specific deubiquitylating enzyme highly expressed in epithelia where it interacts with its substrate, β-catenin. Here we show, in the polarized intestinal epithelial cell line T84, FAM localized to multiple points of protein trafficking. FAM interacted with β-catenin and E-cadherin in T84 cells but only in subconfluent cultures. FAM extensively colocalized with β-catenin in cytoplasmic puncta but not at sites of cell-cell contact as well as immunoprecipitating with β-catenin and E-cadherin from a higher molecular weight complex (~500 kDa). At confluence FAM neither colocalized with, nor immunoprecipitated, β-catenin or E-cadherin, which were predominantly in a larger molecular weight complex (~2 MDa) at the cell surface. Overexpression of FAM in MCF-7 epithelial cells resulted in increased β-catenin levels, which localized to the plasma membrane. Expression of E-cadherin in L-cell fibroblasts resulted in the relocalization of FAM from the Golgi to cytoplasmic puncta. These data strongly suggest that FAM associates with E-cadherin and β-catenin during trafficking to the plasma membrane.