Genetic algorithms for discovery of matrix multiplication methods

We present a parallel genetic algorithm for nding matrix multiplication algo-rithms. For 3 x 3 matrices our genetic algorithm successfully discovered algo-rithms requiring 23 multiplications, which are equivalent to the currently best known human-developed algorithms. We also studied the cases with less mul-tiplications and evaluated the suitability of the methods discovered. Although our evolutionary method did not reach the theoretical lower bound it led to an approximate solution for 22 multiplications.

A solvent-free matrix application method for matrix-assisted laser desorption/ionization imaging of small molecules

Matrix application continues to be a critical step in sample preparation for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). Imaging of small molecules such as drugs and metabolites is particularly problematic because the commonly used washing steps to remove salts are usually omitted as they may also remove the analyte, and analyte spreading is more likely with conventional wet matrix application methods. We have developed a method which uses the application of matrix as a dry, finely divided powder, here referred to as dry matrix application, for the imaging of drug compounds. This appears to offer a complementary method to wet matrix application for the MALDI-MSI of small molecules, with the alternative matrix application techniques producing different ion profiles, and allows the visualization of compounds not observed using wet matrix application methods. We demonstrate its value in imaging clozapine from rat kidney and 4-bromophenyl-1,4-diazabicyclo(3.2.2)nonane-4-carboxylic acid from rat brain. In addition, exposure of the dry matrix coated sample to a saturated moist atmosphere appears to enhance the visualization of a different set of molecules.

An investigation of the factor-analytic approach to the determination of abilities involved in psychomotor learning

This research began with an attempt to solve a practical problem, namely, the prediction of the rate at which an operator will learn a task. From a review of the literature, communications with researchers in this area and the study of psychomotor learning in factories it was concluded that a more fundamental approach was required which included the development of a task taxonomy. This latter objective had been researched for over twenty years by E. A. Fleishman and his approach was adopted. Three studies were carried out to develop and extend Fleishman's approach to the industrial area. However, the results of these studies were not in accord with FIeishman's conclusions and suggested that a critical re-assessment was required of the arguments, methods and procedures used by Fleishman and his co-workers. It was concluded that Fleishman's findings were to some extent an artifact of the approximate methods and procedures which he used in the original factor analyses and that using the more modern computerised factor analytic methods a reliable ability taxonomy could be developed to describe the abilities involved in the learning of psychomotor tasks. The implications for a changing-task or changing-subject model were drawn and it was concluded that a changing task and subject model needs to be developed.

Learning to collaborate:a study of individual and organizational learning, and interorganizational relationships

This paper examines learning to collaborate in the context of industrial supply relationships. Evidence of collaboration, and individual and organizational learning, from an in-depth case study of a large organization and its relations with two key suppliers is discussed. Analytic methods developed to elicit such evidence and provide insights into learning processes and outcomes are presented. It is argued that it is possible for an organization and individuals to learn to develop resilient collaborative relationships, but this requires a more thorough consideration and understanding of issues such as trust, commitment and teamwork than has been typical to date. Suggestions for future practice and research are presented.

Syndromes of self-reported psychopathology for ages 18-59 in 29 societies

This study tested the multi-society generalizability of an eight-syndrome assessment model derived from factor analyses of American adults' self-ratings of 120 behavioral, emotional, and social problems. The Adult Self-Report (ASR; Achenbach and Rescorla 2003) was completed by 17,152 18-59-year-olds in 29 societies. Confirmatory factor analyses tested the fit of self-ratings in each sample to the eight-syndrome model. The primary model fit index (Root Mean Square Error of Approximation) showed good model fit for all samples, while secondary indices showed acceptable to good fit. Only 5 (0.06%) of the 8,598 estimated parameters were outside the admissible parameter space. Confidence intervals indicated that sampling fluctuations could account for the deviant parameters. Results thus supported the tested model in societies differing widely in social, political, and economic systems, languages, ethnicities, religions, and geographical regions. Although other items, societies, and analytic methods might yield different results, the findings indicate that adults in very diverse societies were willing and able to rate themselves on the same standardized set of 120 problem items. Moreover, their self-ratings fit an eight-syndrome model previously derived from self-ratings by American adults. The support for the statistically derived syndrome model is consistent with previous findings for parent, teacher, and self-ratings of 11/2-18-year-olds in many societies. The ASR and its parallel collateral-report instrument, the Adult Behavior Checklist (ABCL), may offer mental health professionals practical tools for the multi-informant assessment of clinical constructs of adult psychopathology that appear to be meaningful across diverse societies. © 2014 Springer Science+Business Media New York.

Sub-types of nonbelieved memories reveal differential outcomes of challenges to memories

Nonbelieved memories (NBMs) highlight the independence between metamemorial judgments that contribute to the experience of remembering. Initial definitions of NBMs portrayed them as involving the withdrawal of autobiographical belief despite sustained recollection. While people rate belief for their NBMs as weaker than recollection, the average difference is too small to support the idea that belief is completely withdrawn in all cases. Furthermore, ratings vary considerably across NBMs. In two studies, we reanalyzed reports from prior studies to examine whether NBM reports reflect a single category or multiple sub-categories using cluster analytic methods. In Study 1, we identified three sub-types of NBMs. In Study 2 we incorporated the concept of belief in accuracy, and found that two of the clusters from Study 1 split into two clusters apiece. Higher ratings of recollection than belief in occurrence characterized all clusters, which were differentiated by the degree of difference between these variables. In both studies the clusters were differentiated by a number of memory characteristic ratings and by reasons reported as leading to the alteration of belief. Implications for understanding the remembering of past events and predicting the creation of NBMs are discussed.

Managing healthcare quality using combined SWOT and the analytic process

Improving healthcare quality is a growing need of any society. Although various quality improvement projects are routinely deployed by the healthcare professional, they are characterised by a fragmented approach, i.e. they are not linked with the strategic intent of the organisation. This study introduces a framework which integrates all quality improvement projects with the strategic intent of the organisation. It first derives the strengths, weaknesses, opportunities and threats (SWOT) matrix of the system with the involvement of the concerned stakeholders (clinical professional), which helps identify a few projects, the implementation of which ensures achievement of desired quality. The projects are then prioritised using the analytic hierarchy process with the involvement of the concerned stakeholders (clinical professionals) and implemented in order to improve system performance. The effectiveness of the method has been demonstrated using a case study in the intensive care unit of Queen Elizabeth Hospital in Bridgetown, Barbados.

Application of analytic hierarchy process for measuring and comparing the global performance of intensive care units

Purpose: To develop a model for the global performance measurement of intensive care units (ICUs) and to apply that model to compare the services for quality improvement. Materials and Methods: Analytic hierarchy process, a multiple-attribute decision-making technique, is used in this study to evolve such a model. The steps consisted of identifying the critical success factors for the best performance of an ICU, identifying subfactors that influence the critical factors, comparing them pairwise, deriving their relative importance and ratings, and calculating the cumulative performance according to the attributes of a given ICU. Every step in the model was derived by group discussions, brainstorming, and consensus among intensivists. Results: The model was applied to 3 ICUs, 1 each in Barbados, Trinidad, and India in tertiary care teaching hospitals of similar setting. The cumulative performance rating of the Barbados ICU was 1.17 when compared with that of Trinidad and Indian ICU, which were 0.82 and 0.75, respectively, showing that the Trinidad and Indian ICUs performed 70% and 64% with respect to Barbados ICU. The model also enabled identifying specific areas where the ICUs did not perform well, which helped to improvise those areas. Conclusions: Analytic hierarchy process is a very useful model to measure the global performance of an ICU. © 2005 Elsevier Inc. All rights reserved.

Discourse-analytic approaches to text and talk

This chapter explores the different ways in which discourse-analytic approaches reveal the ‘meaningfulness’ of text and talk. It reviews four diverse approaches to discourse analysis of particular value for current research in linguistics: Conversation Analysis (CA), Discourse Analysis (DA), Critical Discourse Analysis (CDA) and Feminist Post-structuralist Discourse Analysis (FPDA). Each approach is examined in terms of its background, motivation, key features, and possible strengths and limitations in relation to the field of linguistics. A key way to schematize discourse-analytic methodology is in terms of its relationship between microanalytical approaches, which examine the finer detail of linguistic interactions in transcripts, and macroanalytical approaches, which consider how broader social processes work through language (Heller, 2001). This chapter assesses whether there is a strength in a discourse-analytic approach that aligns itself exclusively with either a micro- or macrostrategy, or whether, as Heller suggests, the field needs to fi nd a way of ‘undoing’ the micro–macro dichotomy in order to produce richer, more complex insights within linguistic research.

Complementary methods to investigate the development of clogging within a horizontal sub-surface flow tertiary treatment wetland

A combination of experimental methods was applied at a clogged, horizontal subsurface flow (HSSF) municipal wastewater tertiary treatment wetland (TW) in the UK, to quantify the extent of surface and subsurface clogging which had resulted in undesirable surface flow. The three dimensional hydraulic conductivity profile was determined, using a purpose made device which recreates the constant head permeameter test in-situ. The hydrodynamic pathways were investigated by performing dye tracing tests with Rhodamine WT and a novel multi-channel, data-logging, flow through Fluorimeter which allows synchronous measurements to be taken from a matrix of sampling points. Hydraulic conductivity varied in all planes, with the lowest measurement of 0.1 md1 corresponding to the surface layer at the inlet, and the maximum measurement of 1550 md1 located at a 0.4m depth at the outlet. According to dye tracing results, the region where the overland flow ceased received five times the average flow, which then vertically short-circuited below the rhizosphere. The tracer break-through curve obtained from the outlet showed that this preferential flow-path accounted for approximately 80% of the flow overall and arrived 8 h before a distinctly separate secondary flow-path. The overall volumetric efficiencyof the clogged system was 71% and the hydrology was simulated using a dual-path, dead-zone storage model. It is concluded that uneven inlet distribution, continuous surface loading and high rhizosphere resistance is responsible for the clog formation observed in this system. The average inlet hydraulic conductivity was 2 md1, suggesting that current European design guidelines, which predict that the system will reach an equilibrium hydraulic conductivity of 86 md1, do not adequately describe the hydrology of mature systems.

Modulation of interleukin-6 and matrix metalloproteinase 2 expression in human fibroblast-like synoviocytes by functional ionotropic glutamate receptors

Objective. Patients with rheumatoid arthritis (RA) have increased concentrations of the amino acid glutamate in synovial fluid. This study was undertaken to determine whether glutamate receptors are expressed in the synovial joint, and to determine whether activation of glutamate receptors on human synoviocytes contributes to RA disease pathology. Methods. Glutamate receptor expression was examined in tissue samples from rat knee joints and in human fibroblast-like synoviocytes (FLS). FLS from 5 RA patients and 1 normal control were used to determine whether a range of glutamate receptor antagonists influenced expression of the proinflammatory cytokine interleukin-6 (IL-6), enzymes involved in matrix degradation and cytokine processing (matrix metalloproteinase 2 [MMP-2] and MMP-9), and the inhibitors of these enzymes (tissue inhibitor of metalloproteinases 1 [TIMP-1] and TIMP-2). IL-6 concentrations were determined by enzyme-linked immunosorbent assay, MMP activity was measured by gelatin zymography, and TIMP activity was determined by reverse zymography. Fluorescence imaging of intracellular calcium concentrations in live RA FLS stimulated with specific antagonists was used to reveal functional activation of glutamate receptors that modulated IL-6 or MMP-2. Results. Ionotropic and metabotropic glutamate receptor subunit mRNA were expressed in the patella, fat pad, and meniscus of the rat knee and in human articular cartilage. Inhibition of N-methyl-D-aspartate (NMDA) receptors in RA FLS increased proMMP-2 release, whereas non-NMDA ionotropic glutamate receptor antagonists reduced IL-6 production by these cells. Stimulation with glutamate, NMDA, or kainate (KA) increased intracellular calcium concentrations in RA FLS, demonstrating functional activation of specific ionotropic glutamate receptors. Conclusion. Our findings indicate that activation of NMDA and KA glutamate receptors on human synoviocytes may contribute to joint destruction by increasing IL-6 expression. © 2007, American College of Rheumatology.

Public scientific communication on Twitter:visual analytic approach

Purpose - The purpose of this paper is to assess high-dimensional visualisation, combined with pattern matching, as an approach to observing dynamic changes in the ways people tweet about science topics. Design/methodology/approach - The high-dimensional visualisation approach was applied to three scientific topics to test its effectiveness for longitudinal analysis of message framing on Twitter over two disjoint periods in time. The paper uses coding frames to drive categorisation and visual analytics of tweets discussing the science topics. Findings - The findings point to the potential of this mixed methods approach, as it allows sufficiently high sensitivity to recognise and support the analysis of non-trending as well as trending topics on Twitter. Research limitations/implications - Three topics are studied and these illustrate a range of frames, but results may not be representative of all scientific topics. Social implications - Funding bodies increasingly encourage scientists to participate in public engagement. As social media provides an avenue actively utilised for public communication, understanding the nature of the dialog on this medium is important for the scientific community and the public at large. Originality/value - This study differs from standard approaches to the analysis of microblog data, which tend to focus on machine driven analysis large-scale datasets. It provides evidence that this approach enables practical and effective analysis of the content of midsize to large collections of microposts.