A sociolinguistic approach to applied epistemology: Examining technocratic values in global 'knowledge' policy

This special issue presents an excellent opportunity to study applied epistemology in public policy. This is an important task because the arena of public policy is the social domain in which macro conditions for ‘knowledge work’ and ‘knowledge industries’ are defined and created. We argue that knowledge-related public policy has become overly concerned with creating the politico-economic parameters for the commodification of knowledge. Our policy scope is broader than that of Fuller (1988), who emphasizes the need for a social epistemology of science policy. We extend our focus to a range of policy documents that include communications, science, education and innovation policy (collectively called knowledge-related public policy in acknowledgement of the fact that there is no defined policy silo called ‘knowledge policy’), all of which are central to policy concerned with the ‘knowledge economy’ (Rooney and Mandeville, 1998). However, what we will show here is that, as Fuller (1995) argues, ‘knowledge societies’ are not industrial societies permeated by knowledge, but that knowledge societies are permeated by industrial values. Our analysis is informed by an autopoietic perspective. Methodologically, we approach it from a sociolinguistic position that acknowledges the centrality of language to human societies (Graham, 2000). Here, what we call ‘knowledge’ is posited as a social and cognitive relationship between persons operating on and within multiple social and non-social (or, crudely, ‘physical’) environments. Moreover, knowing, we argue, is a sociolinguistically constituted process. Further, we emphasize that the evaluative dimension of language is most salient for analysing contemporary policy discourses about the commercialization of epistemology (Graham, in press). Finally, we provide a discourse analysis of a sample of exemplary texts drawn from a 1.3 million-word corpus of knowledge-related public policy documents that we compiled from local, state, national and supranational legislatures throughout the industrialized world. Our analysis exemplifies a propensity in policy for resorting to technocratic, instrumentalist and anti-intellectual views of knowledge in policy. We argue that what underpins these patterns is a commodity-based conceptualization of knowledge, which is underpinned by an axiology of narrowly economic imperatives at odds with the very nature of knowledge. The commodity view of knowledge, therefore, is flawed in its ignorance of the social systemic properties of ��knowing’.

Phylogenetic analysis of evolutionary relationships of the planctomycete division of the domain bacteria based on amino acid sequences of elongation factor Tu

Sequences from the tuf gene coding for the elongation factor EF-Tu were amplified and sequenced from the genomic DNA of Pirellula marina and Isosphaera pallida, two species of bacteria within the order Planctomycetales. A near-complete (1140-bp) sequence was obtained from Pi. marina and a partial (759-bp) sequence was obtained for I. pallida. Alignment of the deduced Pi. marina EF-Tu amino acid sequence against reference sequences demonstrated the presence of a unique Il-amino acid sequence motif not present in any other division of the domain Bacteria. Pi. marina shared the highest percentage amino acid sequence identity with I. pallida but showed only a low percentage identity with other members of the domain Bacteria. This is consistent with the concept of the planctomycetes as a unique division of the Bacteria. Neither primary sequence comparison of EF-Tu nor phylogenetic analysis supports any close relationship between planctomycetes and the chlamydiae, which has previously been postulated on the basis of 16S rRNA. Phylogenetic analysis of aligned EF-Tu amino acid sequences performed using distance, maximum-parsimony, and maximum likelihood approaches yielded contradictory results with respect to the position of planctomycetes relative to other bacteria, It is hypothesized that long-branch attraction effects due to unequal evolutionary rates and mutational saturation effects may account for some of the contradictions.

MRI based diffusion and perfusion predictive model to estimate stroke evolution

In this study we present a novel automated strategy for predicting infarct evolution, based on MR diffusion and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs) defining the initial diffusion lesion and tissue with abnormal hemodynamic function as defined by the mean transit time (MTT) abnormality were automatically extracted from DWI/PI maps. Quantitative measures of cerebral blood flow (CBF) and volume (CBV) along with ratio measures defined relative to the contralateral hemisphere (r(a)CBF and r(a)CBV) were calculated for the MTT ROIs. A parametric normal classifier algorithm incorporating these measures was used to predict infarct growth. The mean r(a)CBF and r(a)CBV values for eventually infarcted MTT tissue were 0.70 +/-0.19 and 1.20 +/-0.36. For recovered tissue the mean values were 0.99 +/-0.25 and 1.87 +/-0.71, respectively. There was a significant difference between these two regions for both measures (P

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.

Identity and genetic diversity of the sorghum ergot pathogen in Australia

Sorghum ergot was first discovered in Australia in 1996. It affects seed production and grain usage in stock feed due to concerns of animal toxicity. Three species of Claviceps are known to cause ergot of sorghum with different epidemiological, animal toxicity, and management implications. Claviceps africana was identified as the causal agent but morphological differences between isolates raised the possibility of more than one species being involved. The major aim of this study was to identify the Claviceps species causing sorghum ergot and to determine the genetic diversity among isolates of the ergot pathogen from Australia and overseas. Symptom development, sequencing of the ITS1 region, and radiolabelled DNA amplification fingerprints (RAF) were used to confirm that ergot of sorghum in Australia is caused by C. africana. The morphology of sphacelia, microconidia, macroconidia, and secondary conidia of all 36 Australian isolates studied matched the description for C. africana and the DNA sequence of the ITS1 region of 2 selected Australian isolates was identical to that of C. africana. Based on RAF analysis of 110 Australian and overseas isolates of Claviceps spp., C. africana isolates could be clearly distinguished (

Modeling of gas adsorption equilibrium over a wide range of pressure: A thermodynamic approach based on equation of state

A thermodynamic approach based on the Bender equation of state is suggested for the analysis of supercritical gas adsorption on activated carbons at high pressure. The approach accounts for the equality of the chemical potential in the adsorbed phase and that in the corresponding bulk phase and the distribution of elements of the adsorption volume (EAV) over the potential energy for gas-solid interaction. This scheme is extended to subcritical fluid adsorption and takes into account the phase transition in EAV The method is adapted to gravimetric measurements of mass excess adsorption and has been applied to the adsorption of argon, nitrogen, methane, ethane, carbon dioxide, and helium on activated carbon Norit R I in the temperature range from 25 to 70 C. The distribution function of adsorption volume elements over potentials exhibits overlapping peaks and is consistently reproduced for different gases. It was found that the distribution function changes weakly with temperature, which was confirmed by its comparison with the distribution function obtained by the same method using nitrogen adsorption isotherm at 77 K. It was shown that parameters such as pore volume and skeleton density can be determined directly from adsorption measurements, while the conventional approach of helium expansion at room temperature can lead to erroneous results due to the adsorption of helium in small pores of activated carbon. The approach is a convenient tool for analysis and correlation of excess adsorption isotherms over a wide range of pressure and temperature. This approach can be readily extended to the analysis of multicomponent adsorption systems. (C) 2002 Elsevier Science (USA).

Prediction of Golgi Type II membrane proteins based on their transmembrane domains

Motivation: A major issue in cell biology today is how distinct intracellular regions of the cell, like the Golgi Apparatus, maintain their unique composition of proteins and lipids. The cell differentially separates Golgi resident proteins from proteins that move through the organelle to other subcellular destinations. We set out to determine if we could distinguish these two types of transmembrane proteins using computational approaches. Results: A new method has been developed to predict Golgi membrane proteins based on their transmembrane domains. To establish the prediction procedure, we took the hydrophobicity values and frequencies of different residues within the transmembrane domains into consideration. A simple linear discriminant function was developed with a small number of parameters derived from a dataset of Type II transmembrane proteins of known localization. This can discriminate between proteins destined for Golgi apparatus or other locations (post-Golgi) with a success rate of 89.3% or 85.2%, respectively on our redundancy-reduced data sets.

An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks Data

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.

Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

Oxide ionic conductivity and microstructures of Sm- or La-doped CeO2-based systems

The concept of crystallographic index termed the effective index is suggested and applied to the design of ceria (CeO2)-based electrolytes to maximize oxide ionic conductivity. The suggested index considers the fluorite structure, and combines the expected oxygen vacancy level with the ionic radius mismatch between host and dopant cations. Using this approach, oxide ionic conductivity of Sm- or La-doped CeO2-based system has been optimized and tested under operating conditions of a solid oxide fuel cell. In the observation of microstructure in atomic scale, both Sm-doped CeO2 and La-doped CeO2 electrolytes had large micro-domains over 10 nm in the lattice. On the other hand, Sm or La and alkaline earth co-doped CeO2-based electrolytes with high effective index had small micro-domains around 1-3 nm in the microstructure. The large micro-domain would prevent oxide ion from passing through the lattice. Therefore, it is concluded that the improvement of ionic conductivity is reflected in changes of microstructure in atomic scale. (C) 2002 Elsevier Science B.V. All rights reserved.

Determination of the effect of lipophilicity on the in vitro permeability and tissue reservoir characteristics of topically applied solutes in human skin layers

In order to establish the relationship between solute lipophilicity and skin penetration (including flux and concentration behavior), we examined the in vitro penetration and membrane concentration of a series of homologous alcohols (C2-C10) applied topically in aqueous solutions to human epidermal, full-thickness, and dermal membranes. The partitioning/distribution of each alcohol between the donor solution, stratum corneum, viable epidermis, dermis, and receptor phase compartments was determined during the penetration process and separately to isolated samples of each tissue type. Maximum flux and permeability coefficients are compared for each membrane and estimates of alcohol diffusivity are made based on flux/concentration data and also the related tissue resistance (the reciprocal of permeability coefficient) for each membrane type. The permeability coefficient increased with increasing lipophilicity to alcohol C8 (octanol) with no further increase for C10 (decanol). Log vehicle:stratum corneum partition coefficients were related to logP , and the concentration of alcohols in each of the tissue layers appeared to increase with lipophilicity. No difference was measured in the diffusivity of smaller more polar alcohols in the three membranes; however, the larger more lipophilic solutes showed slower diffusivity values. The study showed that the dermis may be a much more lipophilic environment than originally believed and that distribution of smaller nonionized solutes into local tissues below a site of topical application may be estimated based on knowledge of their lipophilicity alone.

Knowledge-based system on optimum design of liquid retaining structures with genetic algorithms

This paper delineates the development of a prototype hybrid knowledge-based system for the optimum design of liquid retaining structures by coupling the blackboard architecture, an expert system shell VISUAL RULE STUDIO and genetic algorithm (GA). Through custom-built interactive graphical user interfaces under a user-friendly environment, the user is directed throughout the design process, which includes preliminary design, load specification, model generation, finite element analysis, code compliance checking, and member sizing optimization. For structural optimization, GA is applied to the minimum cost design of structural systems with discrete reinforced concrete sections. The design of a typical example of the liquid retaining structure is illustrated. The results demonstrate extraordinarily converging speed as near-optimal solutions are acquired after merely exploration of a small portion of the search space. This system can act as a consultant to assist novice designers in the design of liquid retaining structures.

Model-based analysis of anaerobic acetate uptake by a mixed culture of polyphosphate-accumulating and glycogen-accumulating organisms

An increasing number of studies shows that the glycogen-accumulating organisms (GAOs) can survive and may indeed proliferate under the alternating anaerobic/aerobic conditions found in EBPR systems, thus forming a strong competitor of the polyphosphate-accumulating organisms (PAOs). Understanding their behaviors in a mixed PAO and GAO culture under various operational conditions is essential for developing operating strategies that disadvantage the growth of this group of unwanted organisms. A model-based data analysis method is developed in this paper for the study of the anaerobic PAO and GAO activities in a mixed PAO and GAO culture. The method primarily makes use of the hydrogen ion production rate and the carbon dioxide transfer rate resulting from the acetate uptake processes by PAOs and GAOs, measured with a recently developed titration and off-gas analysis (TOGA) sensor. The method is demonstrated using the data from a laboratory-scale sequencing batch reactor (SBR) operated under alternating anaerobic and aerobic conditions. The data analysis using the proposed method strongly indicates a coexistence of PAOs and GAOs in the system, which was independently confirmed by fluorescent in situ hybridization (FISH) measurement. The model-based analysis also allowed the identification of the respective acetate uptake rates by PAOs and GAOs, along with a number of kinetic and stoichiometric parameters involved in the PAO and GAO models. The excellent fit between the model predictions and the experimental data not involved in parameter identification shows that the parameter values found are reliable and accurate. It also demonstrates that the current anaerobic PAO and GAO models are able to accurately characterize the PAO/GAO mixed culture obtained in this study. This is of major importance as no pure culture of either PAOs or GAOs has been reported to date, and hence the current PAO and GAO models were developed for the interpretation of experimental results of mixed cultures. The proposed method is readily applicable for detailed investigations of the competition between PAOs and GAOs in enriched cultures. However, the fermentation of organic substrates carried out by ordinary heterotrophs needs to be accounted for when the method is applied to the study of PAO and GAO competition in full-scale sludges. (C) 2003 Wiley Periodicals, Inc.

The use of 16s rDNA restriction fragment length polymorphism analysis for the identification of non-fermenting gram negative bacilli in a cystic fibrosis microbiology referral service

The utility of 16s rDNA restriction fragment length polymorphism (RFLP) analysis for the partial genomovar differentiation of Burkholderia cepacia complex bacterium is well documented. We compared the 16s rDNA RFLP signatures for a number of non-fermenting gram negative bacilli (NF GNB) LMG control strains and clinical isolates pertaining to the genera Burkholderia, Pseudomonas, Achromobacter (Alcaligenes), Ralstonia, Stenotrophomonas and Pandoraea. A collection of 24 control strain (LMG) and 25 clinical isolates were included in the study. Using conventional PCR, a 1.2 kbp 16s rDNA fragment was generated for each organism. Following restriction digestion and electrophoresis, each clinical isolate RFLP signature was compared to those of the control strain panel. Nineteen different RFLP signatures were detected from the 28 control strains included in the study. TwentyoneyTwenty- five of the clinical isolates could be classified by RFLP analysis into a single genus and species when compared to the patterns produced by the control strain panel. Four clinical B. pseudomallei isolates produced RFLP signatures which were indistinguishable from B. cepacia genomovars I, III and VIII. The identity of these four isolates were confirmed using B. pseudomallei specific PCR. 16s rDNA RFLP analysis can be a useful identification strategy when applied to NF GNB, particularly for those which exhibit colistin sulfate resistance. The use of this molecular based methodology has proved very useful in the setting of a CF referral laboratory particularly when utilised in conjunction with B. cepacia complex and genomovar specific PCR techniques. Species specific PCR or sequence analysis should be considered for selected isolates; especially where discrepancies between epidemiology, phenotypic and genotypic characteristics occur.

Design gráfico : análise da relação com a performance da micro e pequena empresa

O design possui um papel central nos negócios, participando de forma crucial no intercambio cultural e econômico da sociedade. Uma das competências do profissional de design gráfico é o desenvolvimento da Identidade Visual Corporativa (IVC). Ela tem como função definir visualmente o perfil de uma empresa, configurando-se, assim, como um composto mercadológico de fundamental importância para diferenciação das organizações, possuindo um importante papel para o crescimento das micro e pequenas empresas (MPEs). O objetivo desta pesquisa é verificar de que forma os gestores de MPEs percebem a atuação do design gráfico sobre a performance do seu negócio, avaliada a partir da sua experiência com a IVC desenvolvida por um profissional de design e aplicada pela empresa em suas atividades. A pesquisa é aplicada, em relação a sua finalidade, e exploratória, quanto ao seu objetivo. Sua condução se deu a partir de pesquisa bibliográfica, entrevista semiestruturada com os gestores das MPEs investigadas e pesquisa documental em materiais fornecidos pelos sujeitos da pesquisa, realizando-se, desta forma, uma triangulação metodológica a fim de contribuir para o exame do fenômeno. Como estratégia de investigação foi utilizado o estudo de casos múltiplos, realizado com 7 (sete) MPEs que haviam incorporado sua IVC há pelo menos 2 (dois) anos, dos setores de comércio e serviço, localizadas nos municípios de Vitória, Vila Velha, Serra ou Cariacica. Os dados coletados foram analisados por meio da Análise de Conteúdo, com base nas etapas descritas por Bardin (1977) e Laville (1999), distribuindo as unidades de análise (frases e parágrafos) nas categorias desenvolvidas: Motivação, Integração da IVC, Gestão da IVC, Relevância da IVC, IVC e Performance e Expressão Visual. A análise utilizou a abordagem quantitativa, realizada por meio da técnica de percentagem, e qualitativa, com maior ênfase na última, onde foram analisadas as categorias e seus elementos, assim como as relações entre elas, buscando extrair os significados construídos. Desta forma, foi possível verificar que a maior parte dos gestores das MPEs investigadas identificam que o design gráfico, por meio da IVC, contribui de forma positiva para a performance do seu negócio, proporcionando diferentes tipos de benefícios, dentre os mais citados foram: Identificação/Reconhecimento, Fortalecimento (solidez, estabilidade, profissionalismo), Novos Clientes, Imagem, Receptividade, Agregação de Valor para a Marca e Diferenciação.