Clustering of cerebral cortical lesions in patients with corticobasal degeneration

Clustering of ballooned neurons (BN) and tau positive neurons with inclusion bodies (tau+ neurons) was studied in the upper and lower laminae of the frontal, parietal and temporal cortex in 12 patients with corticobasal degeneration (CBD). In a significant proportion of brain areas examined, BN and tau+ neurons exhibited clustering with a regular distribution of clusters parallel to the pia mater. A regular pattern of clustering of BN and tau+ neurons was observed equally frequently in all cortical areas examined and in the upper and lower laminae. No significant correlations were observed between the cluster sizes of BN or tau+ neurons in the upper compared with the lower cortex or between the cluster sizes of BN and tau+ neurons. The results suggest that BN and tau+ neurons in CBD exhibit the same type of spatial pattern as lesions in Alzheimer's disease, Lewy body dementia and Pick's disease. The regular periodicity of the cerebral cortical lesions is consistent with the degeneration of the cortico-cortical projections in CBD.

Is the clustering of β-amyloid (Aβ) deposits in the frontal cortex of Alzheimer patients determined by blood vessels?

The clustering pattern of diffuse, primitive and classic β-amyloid (Aβ) deposits was studied in the upper laminae of the frontal cortex of 9 patients with sporadic Alzheimer's disease (AD). Aβ stained tissue was counterstained with collagen type IV antiserum to determine whether the clusters of Aβ deposits were related to blood vessels. In all patients, Aβ deposits and blood vessels were clustered, with in many patients, a regular periodicity of clusters along the cortex parallel to the pia. The classic Aβ deposit clusters coincided with those of the larger blood vessels in all patients and with clusters of smaller blood vessels in 4 patients. Diffuse deposit clusters were related to blood vessels in 3 patients. Primitive deposit clusters were either unrelated to or negatively correlated with the blood vessels in six patients. Hence, Aβ deposit subtypes differ in their relationship to blood vessels. The data suggest a direct and specific role for the larger blood vessels in the formation of amyloid cores in AD. © 1995.

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

Dynamic simulation of chemical plant

This thesis describes the design and implementation of a new dynamic simulator called DASP. It is a computer program package written in standard Fortran 77 for the dynamic analysis and simulation of chemical plants. Its main uses include the investigation of a plant's response to disturbances, the determination of the optimal ranges and sensitivities of controller settings and the simulation of the startup and shutdown of chemical plants. The design and structure of the program and a number of features incorporated into it combine to make DASP an effective tool for dynamic simulation. It is an equation-oriented dynamic simulator but the model equations describing the user's problem are generated from in-built model equation library. A combination of the structuring of the model subroutines, the concept of a unit module, and the use of the connection matrix of the problem given by the user have been exploited to achieve this objective. The Executive program has a structure similar to that of a CSSL-type simulator. DASP solves a system of differential equations coupled to nonlinear algebraic equations using an advanced mixed equation solver. The strategy used in formulating the model equations makes it possible to obtain the steady state solution of the problem using the same model equations. DASP can handle state and time events in an efficient way and this includes the modification of the flowsheet. DASP is highly portable and this has been demonstrated by running it on a number of computers with only trivial modifications. The program runs on a microcomputer with 640 kByte of memory. It is a semi-interactive program, with the bulk of all input data given in pre-prepared data files with communication with the user is via an interactive terminal. Using the features in-built in the package, the user can view or modify the values of any input data, variables and parameters in the model, and modify the structure of the flowsheet of the problem during a simulation session. The program has been demonstrated and verified using a number of example problems.

Premature cardiovascular events and mortality in south Asians with type 2 diabetes in the United Kingdom Asian Diabetes Study - effect of ethnicity on risk

Background/Aim - People of south Asian origin have an excessive risk of morbidity and mortality from cardiovascular disease. We examined the effect of ethnicity on known risk factors and analysed the risk of cardiovascular events and mortality in UK south Asian and white Europeans patients with type 2 diabetes over a 2 year period. Methods - A total of 1486 south Asian (SA) and 492 white European (WE) subjects with type 2 diabetes were recruited from 25 general practices in Coventry and Birmingham, UK. Baseline data included clinical history, anthropometry and measurements of traditional risk factors – blood pressure, total cholesterol, HbA1c. Multiple linear regression models were used to examine ethnicity differences in individual risk factors. Ten-year cardiovascular risk was estimated using the Framingham and UKPDS equations. All subjects were followed up for 2 years. Cardiovascular events (CVD) and mortality between the two groups were compared. Findings - Significant differences were noted in risk profiles between both groups. After adjustment for clustering and confounding a significant ethnicity effect remained only for higher HbA1c (0.50 [0.22 to 0.77]; P?=?0.0004) and lower HDL (-0.09 [-0.17 to -0.01]; P?=?0.0266). Baseline CVD history was predictive of CVD events during follow-up for SA (P?type 2 diabetes in the UK have a higher cardiovascular risk and present with cardiovascular events at a significantly younger age than white Europeans. Enhanced and ethnicity specific targets and effective treatments are needed if these inequalities are to be reduced.

Illness perceptions, beliefs and prevention of Type 2 Diabetes among British Pakistani mothers and young British Pakistani women

The prevalence rates of type2 diabetes mellitus (T2DM) continues to rise among British Pakistanis. The aim of this project was to explore T2DM perceptions and any preventative intentions among British Pakistani women and to discover whether they are doing anything to prevent the onset in themselves and their families. Initially a systematic review was conducted to investigate 20 existing prevention interventions and to assess their effectiveness (n=12,419). Mixed methods approach was adopted and three studies were conducted. The first study consisted of two focus groups with T2DM mothers (n=8) and three focus groups with non-T2DM mothers (n=17). The second study consisted of four focus groups young British Pakistani females (n=11). All focus groups were transcribed verbatim and analysed using thematic analysis. Following these a quantitative study was undertaken comprising of a questionnaire survey; 12 prevention-perception items (derived from the qualitative data) and the Illness-Perception Questionnaire Revised (IPQ-R) using participants from the same populations: T2DM mothers (n=41), non-T2DM mother (n=47) and young women (n=42). Results were analysed using multiple/hierarchical regression. The systematic review highlighted that the most effective prevention programmes focussed on behaviour and lifestyle with a combination of support and education to participants. The research studies demonstrated that T2DM was seen as an older person’s disease to be dealt with if/when it happens. T2DM mothers demonstrated knowledge and prevention understanding. There were non-significant relationships between prevention perceptions and T2DM illness perceptions across all three groups. The finding of this thesis emphasised that lifestyle interventions are crucial to aiding T2DM preventions as a good healthy diet and regular physical activity are the key components to T2DM prevention, and the importance of personal experience in perceived severity and lay-beliefs regarding T2DM and on family/cultural influences in British-Pakistanis. The findings of this project can be used to design culturally specific interventions towards preventing T2DM in the British Pakistani community.

Negative brand personality:the construct, its antecedents and outcome variables

By evolving brands and building on the importance of self-expression, Aaker (1997) developed the brand personality framework as a means to understand brand-consumer relationships. The brand personality framework captures the core values and characteristics described in human personality research in an attempt to humanize brands. Although influential across many streams of brand personality research, the current conceptualization of brand personality only offers a positively-framed approach. To date, no research, both conceptually and empirically, has thoroughly incorporated factors reflective of Negative Brand Personality, despite the fact that almost all researchers in personality are in agreement that factors akin to Extraversion (positive) and Neuroticism (negative) should be in a comprehensive personality scale to accommodate consumers’ expressions. As a result, the study of brand personality is only half complete since the current research trend is to position brand personality under brand image. However, with the brand personality concept being confused with brand identity at the empirical stage, factors reflective of Negative Brand Personality have been neglected. Accordingly, this thesis extends the current conceptualization of brand personality by demarcating the existing typologies of desirable brand personality and incorporating the characteristics reflective of consumers’ discrepant self-meaning to provide a more complete understanding of brand personality. However, it is not enough to interpret negative factors as the absence of positive factors. Negative factors reflect consumers’ anxious and frustrated feelings. Therefore, this thesis contributes to the current conceptualization of brand personality by, firstly, presenting a conceptual definition of Negative Brand Personality in order to provide a theoretical basis for the development of a Negative Brand Personality scale, then, secondly, identifying what constitutes Negative Brand Personality and to what extent consumers’ cognitive dissonance explains the nature of Negative Brand Personality, and, thirdly, ascertaining the impact Negative Brand Personality has on attitudinal constructs, namely: Negative Attitude, Detachment, Brand Loyalty and Satisfaction, which have proven to predict behaviors such as choice and (re-)purchasing. In order to deliver on the three main contributions, two comprehensive studies were conducted to a) develop a valid, parsimonious, yet relatively short measure of Negative Brand Personality, and b) ascertain how the Negative Brand Personality measure behaves within a network of related constructs. The mixed methods approach, grounded in theoretical and empirical development, provides evidence to suggest that there are four factors to Negative Brand Personality and, tested through use of a structural equation modeling technique, that these are influenced by Brand Confusion, Price Unfairness, Self- Incongruence and Corporate Hypocrisy. Negative Brand Personality factors mainly determined Consumers Negative Attitudes and Brand Detachment. The research contributes to the literature on brand personality by improving the consumer-brand relationship by means of engaging in a brandconsumer conversation in order to reduce consumers’ cognitive strain. The study concludes with a discussion on the theoretical and practical implications of the findings, its limitations, and potential directions for future research.

The classification of HLA supertypes by GRID/CPCA and hierarchical clustering methods

Biological experiments often produce enormous amount of data, which are usually analyzed by data clustering. Cluster analysis refers to statistical methods that are used to assign data with similar properties into several smaller, more meaningful groups. Two commonly used clustering techniques are introduced in the following section: principal component analysis (PCA) and hierarchical clustering. PCA calculates the variance between variables and groups them into a few uncorrelated groups or principal components (PCs) that are orthogonal to each other. Hierarchical clustering is carried out by separating data into many clusters and merging similar clusters together. Here, we use an example of human leukocyte antigen (HLA) supertype classification to demonstrate the usage of the two methods. Two programs, Generating Optimal Linear Partial Least Square Estimations (GOLPE) and Sybyl, are used for PCA and hierarchical clustering, respectively. However, the reader should bear in mind that the methods have been incorporated into other software as well, such as SIMCA, statistiXL, and R.

A general route to synthesize supported isolated oxide and mixed-oxide nanoclusters at sizes below 5 nm

A simple and efficient route to prepare supported nanocrystalline oxides is presented. The synthesis procedure, i.e. in situ autocombustion of a glycine complex, allows the production of nanocrystals in a porous matrix presenting larger pore size. An example of successful formation of 2-5 nm nanocrystals is given for a single oxide (Fe2O3), a mixed-oxide structure (LaCoO3 perovskite-type) and a nickel-doped oxide. © 2011 The Royal Society of Chemistry.

The New Software Package for Dynamic Hierarchical Clustering for Circles Types of Shapes

In data mining, efforts have focused on finding methods for efficient and effective cluster analysis in large databases. Active themes of research focus on the scalability of clustering methods, the effectiveness of methods for clustering complex shapes and types of data, high-dimensional clustering techniques, and methods for clustering mixed numerical and categorical data in large databases. One of the most accuracy approach based on dynamic modeling of cluster similarity is called Chameleon. In this paper we present a modified hierarchical clustering algorithm that used the main idea of Chameleon and the effectiveness of suggested approach will be demonstrated by the experimental results.

Generalizing of Neural Nets: Functional Nets of Special Type

Special generalizing for the artificial neural nets: so called RFT – FN – is under discussion in the report. Such refinement touch upon the constituent elements for the conception of artificial neural network, namely, the choice of main primary functional elements in the net, the way to connect them(topology) and the structure of the net as a whole. As to the last, the structure of the functional net proposed is determined dynamically just in the constructing the net by itself by the special recurrent procedure. The number of newly joining primary functional elements, the topology of its connecting and tuning of the primary elements is the content of the each recurrent step. The procedure is terminated under fulfilling “natural” criteria relating residuals for example. The functional proposed can be used in solving the approximation problem for the functions, represented by its observations, for classifying and clustering, pattern recognition, etc. Recurrent procedure provide for the versatile optimizing possibilities: as on the each step of the procedure and wholly: by the choice of the newly joining elements, topology, by the affine transformations if input and intermediate coordinate as well as by its nonlinear coordinate wise transformations. All considerations are essentially based, constructively and evidently represented by the means of the Generalized Inverse.

Learning Technology in Scheduling Based on the Mixed Graphs

We propose the adaptive algorithm for solving a set of similar scheduling problems using learning technology. It is devised to combine the merits of an exact algorithm based on the mixed graph model and heuristics oriented on the real-world scheduling problems. The former may ensure high quality of the solution by means of an implicit exhausting enumeration of the feasible schedules. The latter may be developed for certain type of problems using their peculiarities. The main idea of the learning technology is to produce effective (in performance measure) and efficient (in computational time) heuristics by adapting local decisions for the scheduling problems under consideration. Adaptation is realized at the stage of learning while solving a set of sample scheduling problems using a branch-and-bound algorithm and structuring knowledge using pattern recognition apparatus.

Laparoscopic greater curvature plication in morbidly obese women with type 2 diabetes:effects on glucose homeostasis, postprandial triglyceridemia and selected gut hormones

Background: Laparoscopic greater curvature plication (LGCP) is an emerging bariatric procedure that reduces the gastric volume without implantable devices or gastrectomy. The aim of this study was to explore changes in glucose homeostasis, postprandial triglyceridemia, and meal-stimulated secretion of selected gut hormones [glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide-1 (GLP-1), ghrelin, and obestatin] in patients with type 2 diabetes mellitus (T2DM) at 1 and 6 months after the procedure. Methods: Thirteen morbidly obese T2DM women (mean age, 53.2 ± 8.76 years; body mass index, 40.1 ± 4.59 kg/m2) were prospectively investigated before the LGCP and at 1- and 6-month follow-up. At these time points, all study patients underwent a standardized liquid mixed-meal test, and blood was sampled for assessment of plasma levels of glucose, insulin, C-peptide, triglycerides, GIP, GLP-1, ghrelin, and obestatin. Results: All patients had significant weight loss both at 1 and 6 months after the LGCP (p≤0.002), with mean percent excess weight loss (%EWL) reaching 29.7 ;plusmn2.9 % at the 6-month follow-up. Fasting hyperglycemia and hyperinsulinemia improved significantly at 6 months after the LGCP (p<0.05), with parallel improvement in insulin sensitivity and HbA1c levels (p<0.0001). Meal-induced glucose plasma levels were significantly lower at 6 months after the LGCP (p<0.0001), and postprandial triglyceridemia was also ameliorated at the 6-month follow-up (p<0.001). Postprandial GIP plasma levels were significantly increased both at 1 and 6 months after the LGCP (p<0.0001), whereas the overall meal-induced GLP-1 response was not significantly changed after the procedure (p ;gt0.05). Postprandial ghrelin plasma levels decreased at 1 and 6 months after the LGCP (p<0.0001) with no significant changes in circulating obestatin levels. Conclusion: During the initial 6-month postoperative period, LGCP induces significant weight loss and improves the metabolic profile of morbidly obese T2DM patients, while it also decreases circulating postprandial ghrelin levels and increases the meal-induced GIP response. © 2013 Springer Science+Business Media New York.

Influence of processing and clay type on nanostructure and stability of polypropylene-clay nanocomposites

Melt processing is a critical step in the manufacture of polymer articles and is even more critical when dealing with inhomogeneous polymer-clay nanocomposites systems. The chemical composition, and in particular the clay type and its organic modification, also plays a major contribution in determining the final properties and in particular the thermal and long-term oxidative stability of the resulting polymer nanocomposites. Proper selection and tuning of the process variable should, in principle, lead to improved characteristics of the fabricated product. With multiphase systems containing inorganic nanoclays, however, this is not straightforward and it is often the case that the process conditions are chosen initially to improve one or more desired properties at the expense of others. This study assesses the influence of organo-modified clays and the processing parameters (extrusion temperature and screw speed) on the rheological and morphological characteristics of polymer nanocomposites as well as on their melt and thermo-oxidative stability. Nanocomposites (PPNCs) based on PP, maleated PP and organically modified clays were prepared in different co-rotating twin-screw extruders ranging from laboratory scale to semi-industrial scale. Results show that the amount of surfactant present in similar organo-modified clays affects differently the thermo-oxidative stability of the extruded PPNCs and that changes in processing conditions affect the clay morphology too. By choosing an appropriate set of tuned process variables for the extrusion process it would be feasible to selectively fabricate polymer-clay nanocomposites, with the desired mechanical and thermo-oxidative characteristics. © 2013 Elsevier Ltd. All rights reserved.

Deconstructing phonological tasks:the contribution of stimulus and response type to the prediction of early decoding skills

Abstract Phonological tasks are highly predictive of reading development but their complexity obscures the underlying mechanisms driving this association. There are three key components hypothesised to drive the relationship between phonological tasks and reading; (a) the linguistic nature of the stimuli, (b) the phonological complexity of the stimuli, and (c) the production of a verbal response. We isolated the contribution of the stimulus and response components separately through the creation of latent variables to represent specially designed tasks that were matched for procedure. These tasks were administered to 570 6 to 7-year-old children along with standardised tests of regular word and non-word reading. A structural equation model, where tasks were grouped according to stimulus, revealed that the linguistic nature and the phonological complexity of the stimulus predicted unique variance in decoding, over and above matched comparison tasks without these components. An alternative model, grouped according to response mode, showed that the production of a verbal response was a unique predictor of decoding beyond matched tasks without a verbal response. In summary, we found that multiple factors contributed to reading development, supporting multivariate models over those that prioritize single factors. More broadly, we demonstrate the value of combining matched task designs with latent variable modelling to deconstruct the components of complex tasks.