Geometric models of internal shape change as

This paper systematically presents geometric models for describing internal shape change during plane strain extension of sheet. The models describe the geometry of plastic flow localization during sheet necking and formation of sample-scale shear bands within the neck. The emphasis is toward identifying three-dimensional, solid element models that correctly describe (1) the heterogeneous initiation of simple shearing flow, inside a band that occupies just a small fraction of the sheet thickness, (2) the gradual growth of bands of simple shearing across the sheet cross section, and (3) the development of a variety of patterns of sample-scale shear bands before sheet fracture. Models are identified that agree with experimental evidence. The geometry of these models provides quantitative links between flow localization throughout a deforming sample and changes in microscopic or crystal-scale flow behavior.     

An evaluation of the effectiveness, safety and acceptability of a nurse practitioner in a rheumatology outpatient clinic

In the paper, a preliminary real-time corona discharge imaging system is introduced, and the effects of the imaging parameters, such as electric field intensities and their frequencies, on the resulting images are investigated. From experiments using metal phantoms and plant leaves, it is found that no insulators can be captured by the corona discharge, and the effect of imaging parameters on the image quality is clearly demonstrated. For the future application of this real-time corona discharge imaging system, a composite phantom made of four different metal substances is investigated, along with the various combinations of imaging parameters, and the corona discharge images of a fresh plant leaf are captured as a test version of biomedical objects. The ionisation current, which is important in biomedical applications, is measured in each imaging procedure and estimated by curve-fitting the measured values to the previously known theory of ionisation.     

Autosomal dominant optic atrophy with asymptomatic peripheral neuropathy

The association between hereditary motor and sensory neuropathy (HMSN) and optic atrophy has been termed HMSN type VI. The autosomal dominant inheritance of this syndrome is reported. Three generations were affected with optic atrophy, which differed in some respects from classic dominant optic atrophy, and an asymptomatic, mainly sensory, neuropathy.     

Coeliac disease in primary care: case finding study

OBJECTIVES: To provide evidence of underdiagnosis of coeliac disease and to describe the main presenting symptoms of coeliac disease in primary care. DESIGN: Case finding in a primary care setting by testing for coeliac disease by using the endomysial antibody test. SETTING: Nine surgeries in and around a market town in central England, serving a population of 70 000. PARTICIPANTS: First 1000 patients screened from October 1996 to October 1997. OUTCOME MEASURES: Determination of endomysial antibody titre of patients fulfilling the study criteria, followed by small intestine biopsy of those with positive results. RESULTS: The 30 patients (out of 1000 samples) with positive results on the endomysial antibody test all had histological confirmation on small intestine biopsy. The commonest mode of presentation (15/30) was anaemia of varying severity. Most patients (25/30) presented with non-gastrointestinal symptoms. Specificity of the endomysial antibody test was 30/30. CONCLUSIONS: Underdiagnosis and misdiagnosis of coeliac disease are common in general practice and often result in protracted and unnecessary morbidity. Serological screening in primary care will uncover a large proportion of patients with this condition and should be made widely available and publicised. Coeliac disease should be considered in patients who have anaemia or are tired all the time, especially when there is a family history of the disease.     

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.     

Robust resource allocation in a cluster based imaging system

Recently there has been an increased demand for imaging systems in support of high-speed digital printing. The required increase in performance in support of such systems can be accomplished through an effective parallel execution of image processing applications in a distributed cluster computing environment. The output of the system must be presented to a raster based display at regular intervals, effectively establishing a hard deadline for the production of each image. Failure to complete a rasterization task before its deadline will result in an interruption of service that is unacceptable. The goal of this research was to derive a metric for measuring robustness in this environment and to design a resource allocation heuristic capable of completing each rasterization task before its assigned deadline, thus, preventing any service interruptions. We present a mathematical model of such a cluster based raster imaging system, derive a robustness metric for evaluating heuristics in this environment, and demonstrate using the metric to make resource allocation decisions. The heuristics are evaluated within a simulation of the studied raster imaging system. We clearly demonstrate the effectiveness of the heuristics by comparing their results with the results of a resource allocation heuristic commonly used in this type of system.     

A rapid computational filter for predicting the rate of human renal clearance

In silico models that predict the rate of human renal clearance for a diverse set of drugs, that exhibit both active secretion and net re-absorption, have been produced using three statistical approaches. Partial Least Squares (PLS) and Random Forests (RF) have been used to produce continuous models whereas Classification And Regression Trees (CART) has only been used for a classification model. The best models generated from either PLS or RF produce significant models that can predict acids/zwitterions, bases and neutrals with approximate average fold errors of 3, 3 and 4, respectively, for an independent test set that covers oral drug-like property space. These models contain additional information on top of any influence arising from plasma protein binding on the rate of renal clearance. Classification And Regression Trees (CART) has been used to generate a classification tree leading to a simple set of Renal Clearance Rules (RCR) that can be applied to man. The rules are influenced by lipophilicity and ion class and can correctly predict 60% of an independent test set. These percentages increase to 71% and 79% for drugs with renal clearances of < 0.1 ml/min/kg and > 1 ml/min/kg, respectively. As far as the authors are aware these are the first set of models to appear in the literature that predict the rate of human renal clearance and can be used to manipulate molecular properties leading to new drugs that are less likely to fail due to renal clearance.     

Temperature-dependent mechanical and long crack behavior of zirconium diboride–silicon carbide composite

Hot pressed ZrB2–20 vol.% SiC ultra-high temperature ceramic composites have been prepared for strength and fracture investigations. Two composites fabricated under differing hot pressing temperatures with (ZSB) and without (ZS) B4C sintering aids were selected for room temperature modulus of rupture (MOR) strength and single-edge-notch bend (SENB) fracture toughness experiments. Structure property relationships were examined for both composites. MOR and stiffness temperature dependence was also investigated up to 1500 °C. Long crack propagation studies were conducted up to 1400 °C using the double cantilevered beam geometry with half-chevron-notch initiation zones. Residual Boron-rich carbide maximum particle sizes were found to be strength limiting in ZSB billets while SiC controlled strength in ZS billets. Flexure strength decreased linearly with temperature from 1000 to 1500 °C with no visible plastic deformation prior to fracture. Similar stiffness decreases were observed with a transition temperature range of 1100–1200 °C. Long crack studies produced R-curves that show no significant toughening behavior at room temperature with some modest rising R-curve behavior appearing at higher temperatures. These studies also show the plateau toughness increases with temperature up to 1200 °C. This is supported by an observed transition from primarily transgranular fracture at room temperature to primarily intergranular fracture at high temperatures. Wake zone toughening is evident up to 1000 °C with K_R rise from 0.1 to 0.5 MPa√m. Beyond 1000 °C fracture mechanism transitions to include creep zone development ahead of crack tip with wake zone toughening vanishing.