SPI-23 of S.Derby: role in adherence and invasion of porcine tissues

Salmonella enterica serovars Derby and Mbandaka are isolated from different groups of livestock species in the UK. S. Derby is predominantly isolated from pigs and turkeys and S. Mbandaka is predominantly isolated from cattle and chickens. Alignment of the genome sequences of two isolates of each serovar led to the discovery of a new putative Salmonella pathogenicity island, SPI-23, in the chromosome sequence of S. Derby isolates. SPI-23 is 37 kb in length and contains 42 ORFs, ten of which are putative type III effector proteins. In this study we use porcine jejunum derived cell line IPEC-J2 and in vitro organ culture of porcine jejunum and colon, to characterise the association and invasion rates of S. Derby and S. Mbandaka, and tissue tropism of S. Derby respectively. We show that S. Derby invades and associates to an IPEC-J2 monolayer in significantly greater numbers than S. Mbandaka, and that S. Derby preferentially attaches to porcine jejunum over colon explants. We also show that nine genes across SPI-23 are up-regulated to a greater degree in the jejunum compared to the colon explants. Furthermore, we constructed a mutant of the highly up-regulated, pilV-like gene, potR, and find that it produces an excess of surface pili compared to the parent strain which form a strong agglutinating phenotype interfering with association and invasion of IPEC-J2 monolayers. We suggest that potR may play a role in tissue tropism.

Prediction of Parkinson’s Disease tremor onset using a radial basis function neural network based on particle swarm optimization

Deep Brain Stimulation (DBS) has been successfully used throughout the world for the treatment of Parkinson's disease symptoms. To control abnormal spontaneous electrical activity in target brain areas DBS utilizes a continuous stimulation signal. This continuous power draw means that its implanted battery power source needs to be replaced every 18–24 months. To prolong the life span of the battery, a technique to accurately recognize and predict the onset of the Parkinson's disease tremors in human subjects and thus implement an on-demand stimulator is discussed here. The approach is to use a radial basis function neural network (RBFNN) based on particle swarm optimization (PSO) and principal component analysis (PCA) with Local Field Potential (LFP) data recorded via the stimulation electrodes to predict activity related to tremor onset. To test this approach, LFPs from the subthalamic nucleus (STN) obtained through deep brain electrodes implanted in a Parkinson patient are used to train the network. To validate the network's performance, electromyographic (EMG) signals from the patient's forearm are recorded in parallel with the LFPs to accurately determine occurrences of tremor, and these are compared to the performance of the network. It has been found that detection accuracies of up to 89% are possible. Performance comparisons have also been made between a conventional RBFNN and an RBFNN based on PSO which show a marginal decrease in performance but with notable reduction in computational overhead.

Photopolymerization of Pluronic F127 diacrylate: a colloid-templated polymerization

Pluronic F127 diacrylate (F127DA) is a bifunctional acrylate and as such it should in principle produce macroscopically cross-linked materials; however, its photopolymerization in water does not lead to 3D-extended hydrogels. The main species present after photopolymerization appear to be cross-linked micelles, which indicates that the micellar morphology of F127DA has a template effect on the polymerization. The structural analogy causes the physical state of precursor and polymerized materials to be very similar for a wide range of concentrations (5–25% wt) and temperatures (10–37 °C). Also the long-range morphology of F127DA appears to have a template effect: samples photopolymerized in a micellar gel state and redispersed at high concentration (25% wt) show a long-range organization that depended on the concentration and therefore on the order of the precursor.

An evaluation of the performance of UK real estate forecasters

Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. It compares the performance of real estate forecasters with non-real estate forecasters. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters and a similar survey of macro-economic and capital market forecasters, these forecasts are compared with actual performance to assess a number of forecasting issues in the UK over 1999-2004, including forecast error, bias and consensus. The results suggest that both groups are biased, less volatile compared to market returns and inefficient in that forecast errors tend to persist. The strongest finding is that forecasters display the characteristics associated with a consensus indicating herding.

A framework of brand value in B2B markets: the contributing role of functional and emotional components

The creation of value is admittedly a critical task for marketers regardless of industry. This paper focuses on a type of value that has traditionally been perceived as irrelevant to industrial markets and argues that brand value facilitates the progression from goods and services value to relationship value. To address the limited amount of research on B2B branding from the suppliers' point of view, we complement insights gained from a literature review with ten exploratory interviews with B2B supplier managers, and develop a framework of brand value applicable to industrial markets. This identifies both the functional (i.e., quality, technology, capacity, infrastructure, after sales service, capabilities, reliability, innovation) and emotional qualities (i.e., risk reduction, reassurance, trust) important for the development of industrial brand equity. Situational (e.g. nature of the purchase) and environmental factors (e.g. the economic situation) affecting suppliers' perceptions of the importance of brand in a B2B context and the role of functional versus emotional brand qualities are discussed. The value of the brand as a driver for the development of business to business relationships is also highlighted. The framework provides a basis for B2B practitioners to build their brands in such a way as to make a functional as well as an emotional connection with buyers that is more likely to lead to a supplier–buyer relationship.

Analyzing the performance of non-listed real estate funds: an panel data analysis

The rapid growth of non-listed real estate funds over the last several years has contributed towards establishing this sector as a major investment vehicle for gaining exposure to commercial real estate. Academic research has not kept up with this development, however, as there are still only a few published studies on non-listed real estate funds. This paper aims to identify the factors driving the total return over a seven-year period. Influential factors tested in our analysis include the weighted underlying direct property returns in each country and sector as well as fund size, investment style gearing and the distribution yield. Furthermore, we analyze the interaction of non-listed real estate funds with the performance of the overall economy and that of competing asset classes and found that lagged GDP growth and stock market returns as well as contemporaneous government bond rates are significant and positive predictors of annual fund performance.

Chapter 4: Simulation of reaction injection moulding

Reaction Injection Moulding is a technology that enables the rapid production of complex plastic parts directly from a mixture of two reactive materials of low viscosity. The reactants are mixed in specific quantities and injected into a mould. This process allows large complex parts to be produced without the need for high clamping pressures. This chapter explores the simulation of the complex processes involved in reaction injection moulding. The reaction processes mean that the dynamics of the material in the mould are in constant evolution and an effective model which takes full account of these changing dynamics is introduced and incorporated in to finite element procedures, which are able to provide a complete simulation of the cycle of mould filling and subsequent curing.