Types of the cerebral arterial circle (circle of Willis) in a Sri Lankan Population

<p>Abstract</p> <p>Background</p> <p>The variations of the circle of Willis (CW) are clinically important as patients with effective collateral circulations have a lower risk of transient ischemic attack and stroke than those with ineffective collaterals. The aim of the present cadaveric study was to investigate the anatomical variations of the CW and to compare the frequency of prevalence of the different variations with previous autopsy studies as variations in the anatomy of the CW as a whole have not been studied in the Indian subcontinent.</p> <p>Methods</p> <p>The external diameter of all the arteries forming the CW in 225 normal Sri Lankan adult cadaver brains was measured using a calibrated grid to determine the prevalence in the variation in CW. Chisquared tests and a correspondence analysis were performed to compare the relative frequencies of prevalence of anatomical variations in the CW across 6 studies of diverse ethnic populations.</p> <p>Results</p> <p>We report 15 types of variations of CW out of 22 types previously described and one additional type: hypoplastic precommunicating part of the anterior cerebral arteries (A1) and contralateral posterior communicating arteries (PcoA) 5(2%). Statistically significant differences (p < 0.0001) were found between most of the studies except for the Moroccan study. An especially notable difference was observed in the following 4 configurations: 1) hypoplastic precommunicating part of the posterior cerebral arteries (P1), and contralateral A1, 2) hypoplastic PcoA and contralateral P1, 3) hypoplastic PcoA, anterior communicating artery (AcoA) and contralateral P1, 4) bilateral hypoplastic P1s and AcoA in a Caucasian dominant study by Fisher versus the rest of the studies.</p> <p>Conclusion</p> <p>The present study reveals that there are significant variations in the CW among intra and inter ethnic groups (Caucasian, African and Asian: Iran and Sri Lanka dominant populations), and warrants further studies keeping the methods of measurements, data assessment, and the definitions of hypoplasia the same.</p

Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector

YesThe prevalence of big data is starting to spread across the public and private sectors however, an impediment to its widespread adoption orientates around a lack of appropriate big data analytics (BDA) and resulting skills to exploit the full potential of big data availability. In this paper, we propose a novel BDA to contribute towards this void, using a fuzzy cognitive map (FCM) approach that will enhance decision-making thus prioritising IT service procurement in the public sector. This is achieved through the development of decision models that capture the strengths of both data analytics and the established intuitive qualitative approach. By taking advantages of both data analytics and FCM, the proposed approach captures the strength of data-driven decision-making and intuitive model-driven decision modelling. This approach is then validated through a decision-making case regarding IT service procurement in public sector, which is the fundamental step of IT infrastructure supply for publics in a regional government in the Russia federation. The analysis result for the given decision-making problem is then evaluated by decision makers and e-government expertise to confirm the applicability of the proposed BDA. In doing so, demonstrating the value of this approach in contributing towards robust public decision-making regarding IT service procurement.EU FP7 project Policy Compass (Project No. 612133

Novel iodinated tracers, MIBG and BMIPP, for nuclear cardiology

With the rapid growth of molecular biology, in vivo imaging of such molecular process (i.e., molecular imaging) has been well developed. The molecular imaging has been focused on justifying advanced treatments and for assessing the treatment effects. Most of molecular imaging has been developed using PET camera and suitable PET radiopharmaceuticals. However, this technique cannot be widely available and we need alternative approach. 123I-labeled compounds have been also suitable for molecular imaging using single-photon computed tomography (SPECT) 123I-labeled meta-iodobenzylguanidine (MIBG) has been used for assessing severity of heart failure and prognosis. In addition, it has a potential role to predict fatal arrhythmia, particularly for those who had and are planned to receive implantable cardioverter-defibrillator treatment. 123I-beta-methyl-iodophenylpentadecanoic acid (BMIPP) plays an important role for identifying ischemia at rest, based on the unique capability to represent persistent metabolic alteration after recovery of ischemia, so called ischemic memory. Since BMIPP abnormalities may represent severe ischemia or jeopardized myocardium, it may permit risk analysis in CAD patients, particularly for those with chronic kidney disease and/or hemodialysis patients. This review will discuss about recent development of these important iodinated compounds

MTV and MGV: Two Criteria for Nonlinear PCA

ized Variance) are popular criteria for PCA with optimal scaling. They are adopted by the SAS-PRINQUAL procedure and OSMOD (Saito and Otsu,1988). MTV is an intuitive generalization of linear PCA criterion. We will show some proper-ties of nonlinear PCA with these criteria in an application to the data of NLSY79 (Zagorsky,1997), a large panel survey in the U.S., conducted over twenty years. We will show the following. (1) The effectiveness of PCA with optimal scaling as a tool for large social research data analysis. We can obtain useful results when it complements analyses by regression models. (2) Features of MTV and MGV, especially their abilities and deficiencies in real data analysis. 1

A spatial interaction model for deriving joint space maps of bundle compositions and market segments from pick-any/J data: An application to new product options

We propose an approach for deriving joint space maps of bundle compositions and market segments from three-way (e.g., consumers x product options/benefits/features x usage situations/scenarios/time periods) pick-any/J data. The proposed latent structure multidimensional scaling procedure simultaneously extracts market segment and product option positions in a joint space map such that the closer a product option is to a particlar segment, the higher the likelihood of its being chosen by that segment. A segment-level threshold parameter is estimated that spatially delineates the bundle of product options that are predicted to be chosen by each segment. Estimates of the probability of each consumer belonging to the derived segments are simultaneously obtained. Explicit treatment of product and consumer characteristics are allowed via optional model reparameterizations of the product option locations and segment memberships. We illustrate the use of the proposed approach using an actual commercial application involving pick-any/J data gathered by a major hi-tech firm for some 23 advanced technological options for new automobiles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47207/1/11002_2004_Article_BF00434905.pd

A stochastic multidimensional scaling vector threshold model for the spatial representation of “pick any/ n ” data

This paper presents a new stochastic multidimensional scaling vector threshold model designed to analyze “pick any/ n ” choice data (e.g., consumers rendering buy/no buy decisions concerning a number of actual products). A maximum likelihood procedure is formulated to estimate a joint space of both individuals (represented as vectors) and stimuli (represented as points). The relevant psychometric literature concerning the spatial treatment of such binary choice data is reviewed. The nonlinear probit type model is described, as well as the conjugate gradient procedure used to estimate parameters. Results of Monte Carlo analyses investigating the performance of this methodology with synthetic choice data sets are presented. An application concerning consumer choices for eleven competitive brands of soft drinks is discussed. Finally, directions for future research are presented in terms of further applications and generalizing the model to accommodate three-way choice data.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45743/1/11336_2005_Article_BF02294452.pd

A stochastic multidimensional scaling procedure for the spatial representation of three-mode, three-way pick any/ J data

This paper presents a new stochastic multidimensional scaling procedure for the analysis of three-mode, three-way pick any/ J data. The method provides either a vector or ideal-point model to represent the structure in such data, as well as “floating” model specifications (e.g., different vectors or ideal points for different choice settings), and various reparameterization options that allow the coordinates of ideal points, vectors, or stimuli to be functions of specified background variables. A maximum likelihood procedure is utilized to estimate a joint space of row and column objects, as well as a set of weights depicting the third mode of the data. An algorithm using a conjugate gradient method with automatic restarts is developed to estimate the parameters of the models. A series of Monte Carlo analyses are carried out to investigate the performance of the algorithm under diverse data and model specification conditions, examine the statistical properties of the associated test statistic, and test the robustness of the procedure to departures from the independence assumptions. Finally, a consumer psychology application assessing the impact of situational influences on consumers' choice behavior is discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45749/1/11336_2005_Article_BF02294486.pd