A novel fuzzy clustering algorithm for the analysis of axillary lymph node tissue sections

Recently Fourier Transform Infrared (FTIR) spectroscopic imaging has been used as a tool to detect the changes in cellular composition that may reflect the onset of a disease. This approach has been investigated as a mean of monitoring the change of the biochemical composition of cells and providing a diagnostic tool for various human cancers and other diseases. The discrimination between different types of tissue based upon spectroscopic data is often achieved using various multivariate clustering techniques. However, the number of clusters is a common unknown feature for the clustering methods, such as hierarchical cluster analysis, k-means and fuzzy c-means. In this study, we apply a FCM based clustering algorithm to obtain the best number of clusters as given by the minimum validity index value. This often results in an excessive number of clusters being created due to the complexity of this biochemical system. A novel method to automatically merge clusters was developed to try to address this problem. Three lymph node tissue sections were examined to evaluate our new method. These results showed that this approach can merge the clusters which have similar biochemistry. Consequently, the overall algorithm automatically identifies clusters that accurately match the main tissue types that are independently determined by the clinician.     

Automatic generation of explanations: AGE

Explaining how engineering devices work is important to students, engineers, and operators. In general, machine generated explanations have been produced from a particular perspective. This paper introduces a system called automatic generation of explanations (AGE) capable of generating causal, behavioral, and functional explanations of physical devices in natural language. AGE explanations can involve different user selected state variables at different abstraction levels. AGE uses a library of engineering components as building blocks. Each component is associated with a qualitative model, information about the meaning of state variables and their possible values, information about substances, and information about the different functions each component can perform. AGE uses: (i) a compositional modeling approach to construct large qualitative models, (ii) causal analysis to build a causal dependency graph, (iii) a novel qualitative simulation approach to efficiently obtain the system's behavior on large systems, and (iv) decomposition analysis to automatically divide large devices into smaller subsystems. AGE effectiveness is demonstrated with different devices that range from a simple water tank to an industrial chemical plant.     

A model for bilayer membrane electroporation based on resultant electromechanical stress

Reconsideration of the effect of an electrical field applied across a phospholipid bilayer membrane shows that, in addition to a compressive stress normal to the membrane plane, transverse traction stresses are generated in the lateral plane of the membrane. In the fields usually employed for electroporation these transverse stresses are likely to be sufficient to reduce the membrane tension considerably, causing electroporation and rupture. This mode of field-induced change in the membrane provides a natural model for the various forms of electroporation.     

Formal techniques for performance analysis: blending SAN and PEPA

In this paper we consider two performance modelling techniques from the perspectives of model construction, generation of an underlying continuous time Markov process, and the potential for reduction in the Markov process. Such careful comparison of modelling techniques allows us to appreciate the strengths and weaknesses of different approaches, and facilitates cross-fertilization between them. In the present case we take a characteristic of one formalism, functional rates in Stochastic Automata Networks, and introduce it to the other formalism, Performance Evaluation Process Algebra. We investigate the benefits of this cross-fertilization, particularly from the perspectives of Markov process generation and reduction.     

Al–Si cast alloys under isothermal and thermomechanical fatigue conditions

This work presents a survey of the isothermal and anisothermal fatigue behavior of aluminum casting alloys obtained from different processes. Experimental results have shown that porosity, especially large and irregular pores, provides the main factor in decreasing fatigue properties of the tested alloys. In materials with similar porosity levels, other microstructural factors became relevant such as, matrix morphology and the amount of alloying elements. Fractographic analyses showed that fatigue cracks preferentially start to propagate in microcracks or interdendritic shrinkage usually located next to the surface. In most cases, propagation takes place in the eutectic phase, although in the thixoformed material, a transition from transgranular to intergranular mode was observed in the crack propagation mode.     

Interlaboratory ring test of time-resolved fluoroimmunoassays for zeranol and alpha-zearalenol and comparison with zeranol test kits.

Many zeranol immunoassay test kits cross-react with toxins formed by naturally occurring Fusarium spp. fungi, leading to false-positive screening results. This paper describes the evaluation and application of recently published, dry reagent time-resolved fluoroimmunoassays (TR-FIA) for zeranol and the toxin alpha-zearalenol. A ring test of bovine urine fortified with zeranol and/or alpha-zearalenol in four European Union National Reference Laboratories demonstrated that the TR-FIA tests were accurate and robust. The alpha-zearalenol TR-FIA satisfactorily quantified alpha-zearalenol in urine fortified at 10-30 ng ml(-1). The specificity-enhanced zeranol TR-FIA accurately quantified zeranol in the range 2-5 ng ml(-1) and gave no false-positive results in blank urine, even in the presence of 30 ng ml(-1) alpha-zearalenol. Zeranol TR-FIA specificity was demonstrated further by analysing incurred zeranol-free urine samples containing natural Fusarium spp. toxins. The TR-FIA yielded no false-positive results in the presence of up to 22 ng ml(-1) toxins. The performance of four commercially available zeranol immunoassay test kits was more variable. Three kits produced many false-positive results. One kit produced only one potential false-positive using a protocol that was longer than that of the TR-FIA. These TR-FIAs will be valuable tools to develop inspection criteria to distinguish illegal zeranol abuse from contamination arising from in vivo metabolism of Fusarium spp. toxins.