Modelling the growth of prion protein aggregates in the brain in variant Creutzfeldt-Jakob disease

Deposition of insoluble prion protein (PrP) in the brain in the form of protein aggregates or deposits is characteristic of the ‘transmissible spongiform encephalopathies’ (TSEs). Understanding the growth and development of these PrP aggregates is important both in attempting to the elucidate of the pathogenesis of prion disease and in the development of treatments designed to prevent or inhibit the spread of prion pathology within the brain. Aggregation and disaggregation of proteins and the diffusion of substances into the developing aggregates (surface diffusion) are important factors in the development of protein aggregates. Mathematical models suggest that if aggregation/disaggregation or surface diffusion is the predominant factor, the size frequency distribution of the resulting protein aggregates in the brain should be described by either a power-law or a log-normal model respectively. This study tested this hypothesis for two different types of PrP deposit, viz., the diffuse and florid-type PrP deposits in patients with variant Creutzfeldt-Jakob disease (vCJD). The size distributions of the florid and diffuse plaques were fitted by a power-law function in 100% and 42% of brain areas studied respectively. By contrast, the size distributions of both types of plaque deviated significantly from a log-normal model in all brain areas. Hence, protein aggregation and disaggregation may be the predominant factor in the development of the florid plaques. A more complex combination of factors appears to be involved in the pathogenesis of the diffuse plaques. These results may be useful in the design of treatments to inhibit the development of protein aggregates in vCJD.

Modelling the dynamics of genetic algorithms using statistical mechanics

A formalism for modelling the dynamics of Genetic Algorithms (GAs) using methods from statistical mechanics, originally due to Prugel-Bennett and Shapiro, is reviewed, generalized and improved upon. This formalism can be used to predict the averaged trajectory of macroscopic statistics describing the GA's population. These macroscopics are chosen to average well between runs, so that fluctuations from mean behaviour can often be neglected. Where necessary, non-trivial terms are determined by assuming maximum entropy with constraints on known macroscopics. Problems of realistic size are described in compact form and finite population effects are included, often proving to be of fundamental importance. The macroscopics used here are cumulants of an appropriate quantity within the population and the mean correlation (Hamming distance) within the population. Including the correlation as an explicit macroscopic provides a significant improvement over the original formulation. The formalism is applied to a number of simple optimization problems in order to determine its predictive power and to gain insight into GA dynamics. Problems which are most amenable to analysis come from the class where alleles within the genotype contribute additively to the phenotype. This class can be treated with some generality, including problems with inhomogeneous contributions from each site, non-linear or noisy fitness measures, simple diploid representations and temporally varying fitness. The results can also be applied to a simple learning problem, generalization in a binary perceptron, and a limit is identified for which the optimal training batch size can be determined for this problem. The theory is compared to averaged results from a real GA in each case, showing excellent agreement if the maximum entropy principle holds. Some situations where this approximation brakes down are identified. In order to fully test the formalism, an attempt is made on the strong sc np-hard problem of storing random patterns in a binary perceptron. Here, the relationship between the genotype and phenotype (training error) is strongly non-linear. Mutation is modelled under the assumption that perceptron configurations are typical of perceptrons with a given training error. Unfortunately, this assumption does not provide a good approximation in general. It is conjectured that perceptron configurations would have to be constrained by other statistics in order to accurately model mutation for this problem. Issues arising from this study are discussed in conclusion and some possible areas of further research are outlined.

A note on the modelling the efficiency of top Arab banks

The major aim of this research is benchmarking top Arab banks using Data Envelopment Analysis (DEA) technique and to compare the results with that of published recently in Mostafa (2007a,b) [Mostafa, M. M. (2007a). Modeling the efficiency of top Arab banks: A DEA–neural network approach. Expert Systems with Applications, doi:10.1016/j.eswa.2007.09.001; Mostafa M. M. (2007b), Benchmarking top Arab banks’ efficiency through efficient frontier analysis, Industrial Management & Data Systems, 107(6) 802–823]. Data for 85 Arab banks used to conduct the analysis of relative efficiency. Our findings indicate that (1) the efficiency of Arab banks reported in Mostafa (2007a,b) is incorrect, hence, readers should take extra caution of using such results, (2) the corrected efficiency scores suggest that there is potential for significant improvements in Arab banks. In summary, this study overcomes with some data and methodology issues in measuring efficiency of Arab banks and highlights the importance of encouraging increased efficiency throughout the banking industry in the Arab world using the new results.

Modelling the relationship between local logistics management decisions and overall supply chain performance:A research agenda

Supply chains are advocated widely as being the new units for commercial competition and developments have made the sharing of supply chain wide information increasingly common. Most organisations however still make operational decisions intended to maximise local organisational performance. With improved information sharing a holistic focus for operational decisions should now be possible. The development of a pan supply chain performance framework requires an examination of the conditions under which holistic-decisions provide benefits to either the individual enterprise or the complete supply chain. This paper presents the background and supporting methodology for a study of the impact of an overall supply chain performance metric framework upon local logistics decisions and the conditions under which such a framework would improve overall supply chain performance. The methodology concludes a simulation approach using a functionally extended Gensym's e-SCOR model, together with case based triangulation, to be optimum. Copyright © 2007 Inderscience Enterprises Ltd.

Modelling the resuspensions of fibres in the racetrack channel

Presentation of the progress made in modelling fibre agglomerate transport in the racetrack channel. Fibre agglomerates can be generated through the disruption of insulation materials during LOCA in NPPs. The fibres can make their way to the containment sump strainers and lead to their blockage. This blockage can lead to an increase in the pressure drop acting across the strainers, which can lead to cavitation behind the strainer and in the recirculation pumps. This will lead to a loss of ECC water reaching the reactor. A small proportion of the fibres may also reach the reactor vessel. Therefore reliable numerical models of the three-dimensional flow behaviour of the fibres must be developed. The racetrack channel offers the chance to validate such models. The presentation describes the techniques involved and the results obtained from transient simulations of the whole channel.

Modelling the innovation value chain

Innovation events – the introduction of new products or processes – represent the end of a process of knowledge sourcing and transformation. They also represent the beginning of a process of exploitation which may result in an improvement in the performance of the innovating business. This recursive process of knowledge sourcing, transformation and exploitation comprises the innovation value chain. Modelling the innovation value chain for a large group of manufacturing firms in Ireland and Northern Ireland highlights the drivers of innovation, productivity and firm growth. In terms of knowledge sourcing,we find strong complementarity between horizontal, forwards, backwards, public and internal knowledge sourcing activities. Each of these forms of knowledge sourcing also makes a positive contribution to innovation in both products and processes although public knowledge sources have only an indirect effect on innovation outputs. In the exploitation phase, innovation in both products and processes contribute positively tocompany growth, with product innovation having a short-term ‘disruption’ effect on labour productivity. Modelling the complete innovation value chain highlights the structure and complexity of the process of translating knowledge into business value and emphasises the role of skills, capital investment and firms’ other resources in the value creation process.

Measuring and modelling the influence of investor behaviour on investment decision making

Guest editorial

CFD modelling of the fast pyrolysis of biomass in fluidised bed reactors: modelling the impact of biomass shrinkage

The fluid–particle interaction and the impact of shrinkage on pyrolysis of biomass inside a 150 g/h fluidised bed reactor is modelled. Two 500 View the MathML sourcem in diameter biomass particles are injected into the fluidised bed with different shrinkage conditions. The two different conditions consist of (1) shrinkage equal to the volume left by the solid devolatilization, and (2) shrinkage parameters equal to approximately half of particle volume. The effect of shrinkage is analysed in terms of heat and momentum transfer as well as product yields, pyrolysis time and particle size considering spherical geometries. The Eulerian approach is used to model the bubbling behaviour of the sand, which is treated as a continuum. Heat transfer from the bubbling bed to the discrete biomass particle, as well as biomass reaction kinetics are modelled according to the literature. The particle motion inside the reactor is computed using drag laws, dependent on the local volume fraction of each phase. FLUENT 6.2 has been used as the modelling framework of the simulations with the whole pyrolysis model incorporated in the form of user defined function (UDF).

Semantic and organization considerations in database conceptual modelling : the Semantic Conceptual Organizational Model (SECOM)

This thesis presents a new approach to designing large organizational databases. The approach emphasizes the need for a holistic approach to the design process. The development of the proposed approach was based on a comprehensive examination of the issues of relevance to the design and utilization of databases. Such issues include conceptual modelling, organization theory, and semantic theory. The conceptual modelling approach presented in this thesis is developed over three design stages, or model perspectives. In the semantic perspective, concept definitions were developed based on established semantic principles. Such definitions rely on meaning - provided by intension and extension - to determine intrinsic conceptual definitions. A tool, called meaning-based classification (MBC), is devised to classify concepts based on meaning. Concept classes are then integrated using concept definitions and a set of semantic relations which rely on concept content and form. In the application perspective, relationships are semantically defined according to the application environment. Relationship definitions include explicit relationship properties and constraints. The organization perspective introduces a new set of relations specifically developed to maintain conformity of conceptual abstractions with the nature of information abstractions implied by user requirements throughout the organization. Such relations are based on the stratification of work hierarchies, defined elsewhere in the thesis. Finally, an example of an application of the proposed approach is presented to illustrate the applicability and practicality of the modelling approach.

Modelling the gastric epithelium for testing of new chemical entities

A cell culture model of the gastric epithelial cell surface would prove useful for biopharmaceutical screening of new chemical entities and dosage forms. A successful model should exhibit tight junction formation, maintenance of differentiation and polarity. Conditions for primary culture of guinea-pig gastric mucous epithelial cell monolayers on Tissue Culture Plastic (TCP) and membrane insects (Transwells) were established. Tight junction formation for cells grown on Transwells for three days was assessed by measurement of transepithelial resistance (TEER) and permeability of mannitol and fluorescein. Coating the polycarbonate filter with collagen IV, rather with collagen I, enhanced tight junction formation. TEER for cells grown on Transwells coated with collagen IV was close to that obtained with intact guinea-pig gastric epithelium in vitro. Differentiation was assessed by incorporation of [3H] glucosamine into glycoprotein and by activity of NADPH oxidase, which produces superoxide. Both of these measures were greater for cells grown on filters coated with collagen I than for cells grown on TCP, but no major difference was found between cells grown on collagens I and IV. However, monolayers grown on membranes coated with collagen IV exhibited apically polarized secretion of mucin and superoxide. The proportion of cells, which stained positively for mucin with periodic Schiff reagent, was greater than 95% for all culture conditions. Gastric epithelial monolayers grown on Transwells coated with collagen IV were able to withstand transient (30 min) apical acidification to pH 3, which was associated with a decrease in [3H] mannitol flux and an increase in TEER relative to pH 7.4. The model was used to provide the first direct demonstration that an NSAID (indomethacin) accumulated in gastric epithelial cells exposed to low apical pH. In conclusion, guinea-pig epithelial cells cultured on collagen IV represent a promising model of the gastric surface epithelium suitable for screening procedures.

Modelling the dynamics of cutting during turning

This thesis presents an approach to cutting dynamics during turning based upon the mechanism of deformation of work material around the tool nose known as "ploughing". Starting from the shearing process in the cutting zone and accounting for "ploughing", new mathematical models relating turning force components to cutting conditions, tool geometry and tool vibration are developed. These models are developed separately for steady state and for oscillatory turning with new and worn tools. Experimental results are used to determine mathematical functions expressing the parameters introduced by the steady state model in the case of a new tool. The form of these functions are of general validity though their coefficients are dependent on work and tool materials. Good agreement is achieved between experimental and predicted forces. The model is extended on one hand to include different work material by introducing a hardness factor. The model provides good predictions when predicted forces are compared to present and published experimental results. On the other hand, the extension of the ploughing model to taming with a worn edge showed the ability of the model in predicting machining forces during steady state turning with the worn flank of the tool. In the development of the dynamic models, the dynamic turning force equations define the cutting process as being a system for which vibration of the tool tip in the feed direction is the input and measured forces are the output The model takes into account the shear plane oscillation and the cutting configuration variation in response to tool motion. Theoretical expressions of the turning forces are obtained for new and worn cutting edges. The dynamic analysis revealed the interaction between the cutting mechanism and the machine tool structure. The effect of the machine tool and tool post is accounted for by using experimental data of the transfer function of the tool post system. Steady state coefficients are corrected to include the changes in the cutting configuration with tool vibration and are used in the dynamic model. A series of oscillatory cutting tests at various conditions and various tool flank wear levels are carried out and experimental results are compared with model—predicted forces. Good agreement between predictions and experiments were achieved over a wide range of cutting conditions. This research bridges the gap between the analysis of vibration and turning forces in turning. It offers an explicit expression of the dynamic turning force generated during machining and highlights the relationships between tool wear, tool vibration and turning force. Spectral analysis of tool acceleration and turning force components led to define an "Inertance Power Ratio" as a flank wear monitoring factor. A formulation of an on—line flank wear monitoring methodology is presented and shows how the results of the present model can be applied to practical in—process tool wear monitoring in • turning operations.

Modelling the underlying principles of human aesthetic preference in evolutionary art

Our understanding of creativity is limited, yet there is substantial research trying to mimic human creativity in artificial systems and in particular to produce systems that automatically evolve art appreciated by humans. We propose here to study human visual preference through observation of nearly 500 user sessions with a simple evolutionary art system. The progress of a set of aesthetic measures throughout each interactive user session is monitored and subsequently mimicked by automatic evolution in an attempt to produce an image to the liking of the human user.