25 resultados para model testing

em Aston University Research Archive


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The aim of this project was to develop the education work of an environmental pressure group. The research devised and implemented a project to produce multi-media teaching packs on the urban environment. Whilst this involved understanding environmental education it was necessary to research beyond this to include the various structural and dynamic constraints on change in the field. This presented a number of methodological difficulties; from the resolution of which a model of the research process involved in this project has been developed. It is argued that research oriented towards practical change requires the insights of an experienced practitioner to be combined with the rigours of controlled systematic enquiry. Together these function as a model-building process encompassing intuition, induction and deduction. Model testing is carried out through repeated intervention in the field; thus an interplay between researcher and client ensues such that the project develops in a mutually acceptable direction. In practice, this development will be both unpredictable and erratic. Although the conclusions reached here are based on a single case study they address general methodological issues likely to be encountered in different field settings concerned with different practical problems.

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The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately apparent, as we demonstrate. While more flexible algorithms have been developed, their widespread use has been hindered by their computational and technical complexity. Motivated by these considerations, we present a flexible alternative to K-means that relaxes most of the assumptions, whilst remaining almost as fast and simple. This novel algorithm which we call MAP-DP (maximum a-posteriori Dirichlet process mixtures), is statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling. This approach allows us to overcome most of the limitations imposed by K-means. The number of clusters K is estimated from the data instead of being fixed a-priori as in K-means. In addition, while K-means is restricted to continuous data, the MAP-DP framework can be applied to many kinds of data, for example, binary, count or ordinal data. Also, it can efficiently separate outliers from the data. This additional flexibility does not incur a significant computational overhead compared to K-means with MAP-DP convergence typically achieved in the order of seconds for many practical problems. Finally, in contrast to K-means, since the algorithm is based on an underlying statistical model, the MAP-DP framework can deal with missing data and enables model testing such as cross validation in a principled way. We demonstrate the simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism.

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The airway epithelium is the first point of contact in the lung for inhaled material, including infectious pathogens and particulate matter, and protects against toxicity from these substances by trapping and clearance via the mucociliary escalator, presence of a protective barrier with tight junctions and initiation of a local inflammatory response. The inflammatory response involves recruitment of phagocytic cells to neutralise and remove and invading materials and is oftern modelled using rodents. However, development of valid in vitro airway epithelial models is of great importance due to the restrictions on animal studies for cosmetic compound testing implicit in the 7th amendment to the European Union Cosmetics Directive. Further, rodent innate immune responses have fundamental differences to human. Pulmonary endothelial cells and leukocytes are also involved in the innate response initiated during pulmonary inflammation. Co-culture models of the airways, in particular where epithelial cells are cultured at air liquid interface with the presence of tight junctions and differentiated mucociliary cells, offer a solution to this problem. Ideally validated models will allow for detection of early biomarkers of response to exposure and investigation into inflammatory response during exposure. This thesis describes the approaches taken towards developing an in vitro epithelial/endothelial cell model of the human airways and identification biomarkers of response to exposure to xenobiotics. The model comprised normal human primary microvascular endothelial cells and the bronchial epithelial cell line BEAS-2B or normal human bronchial epithelial cells. BEAS-2B were chosen as their characterisation at air liquid interface is limited but they are robust in culture, thereby predicted to provide a more reliable test system. Proteomics analysis was undertaken on challenged cells to investigate biomarkers of exposure. BEAS-2B morphology was characterised at air liquid interface compared with normal human bronchial epithelial cells. The results indicate that BEAS-2B cells at an air liquid interface form tight junctions as shown by expression of the tight junction protein zonula occludens-1. To this author’s knowledge this is the first time this result has been reported. The inflammatory response of BEAS-2B (measured as secretion of the inflammatory mediators interleukin-8 and -6) air liquid interface mono-cultures to Escherichia coli lipopolysaccharide or particulate matter (fine and ultrafine titanium dioxide) was comparable to published data for epithelial cells. Cells were also exposed to polymers of “commercial interest” which were in the nanoparticle range (and referred to particles hereafter). BEAS-2B mono-cultures showed an increased secretion of inflammatory mediators after challenge. Inclusion of microvascular endothelial cells resulted in protection against LPS- and particle- induced epithelial toxicity, measured as cell viability and inflammatory response, indicating the importance of co-cultures for investigations into toxicity. Two-dimensional proteomic analysis of lysates from particle-challenged cells failed to identify biomarkers of toxicity due to assay interference and experimental variability. Separately, decreased plasma concentrations of serine protease inhibitors, and the negative acute phase proteins transthyretin, histidine-rich glycoprotein and alpha2-HS glycoprotein were identified as potential biomarkers of methyl methacrylate/ethyl methacrylate/butylacrylate treatment in rats.

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Developmental neurotoxicity is a major issue in human health and may have lasting neurological implications. In this preliminary study we exposed differentiating Ntera2/clone D1 (NT2/D1) cell neurospheres to known human teratogens classed as non-embryotoxic (acrylamide), weakly embryotoxic (lithium, valproic acid) and strongly embryotoxic (hydroxyurea) as listed by European Centre for the Validation of Alternative Methods (ECVAM) and examined endpoints of cell viability and neuronal protein marker expression specific to the central nervous system, to identify developmental neurotoxins. Following induction of neuronal differentiation, valproic acid had the most significant effect on neurogenesis, in terms of reduced viability and decreased neuronal markers. Lithium had least effect on viability and did not significantly alter the expression of neuronal markers. Hydroxyurea significantly reduced cell viability but did not affect neuronal protein marker expression. Acrylamide reduced neurosphere viability but did not affect neuronal protein marker expression. Overall, this NT2/D1 -based neurosphere model of neurogenesis, may provide the basis for a model of developmental neurotoxicity in vitro.

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Drawing on the perceived organizational membership theoretical framework and the social identity view of dissonance theory, I examined in this study the dynamics of the relationship between psychological contract breach and organizational identification. I included group-level transformational and transactional leadership as well as procedural justice in the hypothesized model as key antecedents for organizational membership processes. I further explored the mediating role of psychological contract breach in the relationship between leadership, procedural justice climate, and organizational identification and proposed separateness–connectedness self-schema as an important moderator of the above mediated relationship. Hierarchical linear modeling results from a sample of 864 employees from 162 work units in 10 Greek organizations indicated that employees' perception of psychological contract breach negatively affected their organizational identification. I also found psychological contract breach to mediate the impact of transformational and transactional leadership on organizational identification. Results further provided support for moderated mediation and showed that the indirect effects of transformational and transactional leadership on identification through psychological contract breach were stronger for employees with a low connectedness self-schema.

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Many papers claim that a Log Periodic Power Law (LPPL) model fitted to financial market bubbles that precede large market falls or 'crashes', contains parameters that are confined within certain ranges. Further, it is claimed that the underlying model is based on influence percolation and a martingale condition. This paper examines these claims and their validity for capturing large price falls in the Hang Seng stock market index over the period 1970 to 2008. The fitted LPPLs have parameter values within the ranges specified post hoc by Johansen and Sornette (2001) for only seven of these 11 crashes. Interestingly, the LPPL fit could have predicted the substantial fall in the Hang Seng index during the recent global downturn. Overall, the mechanism posited as underlying the LPPL model does not do so, and the data used to support the fit of the LPPL model to bubbles does so only partially. © 2013.

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Design verification in the digital domain, using model-based principles, is a key research objective to address the industrial requirement for reduced physical testing and prototyping. For complex assemblies, the verification of design and the associated production methods is currently fragmented, prolonged and sub-optimal, as it uses digital and physical verification stages that are deployed in a sequential manner using multiple systems. This paper describes a novel, hybrid design verification methodology that integrates model-based variability analysis with measurement data of assemblies, in order to reduce simulation uncertainty and allow early design verification from the perspective of satisfying key assembly criteria.

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One of the current challenges in model-driven engineering is enabling effective collaborative modelling. Two common approaches are either storing the models in a central repository, or keeping them under a traditional file-based version control system and build a centralized index for model-wide queries. Either way, special attention must be paid to the nature of these repositories and indexes as networked services: they should remain responsive even with an increasing number of concurrent clients. This paper presents an empirical study on the impact of certain key decisions on the scalability of concurrent model queries, using an Eclipse Connected Data Objects model repository and a Hawk model index. The study evaluates the impact of the network protocol, the API design and the internal caching mechanisms and analyzes the reasons for their varying performance.

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Brand extensions are increasingly used by multinational corporations in emerging markets such as China. However, understanding how consumers in the emerging markets evaluate brand extensions is hampered by a lack of research in the emerging markets contexts. To address the knowledge void, we built on an established brand extension evaluation framework in the West, namely Aaker and Keller (1990)1. Aaker , D. A. and Keller , K. L. 1990 . Consumer evaluations of brand extensions . Journal of Marketing , 54 ( 1 ) : 27 – 41 . [CrossRef], [Web of Science ®] View all references, and extended the model by incorporating two new factors: perceived fit based on brand image consistency and competition intensity in the brand extension category. The additions of two factors are made in recognition of the uniqueness of the considerations of consumers in the emerging markets in their brand extension evaluations. The extended model was tested by an empirical experiment using consumers in China. The results partly validated the Aaker and Keller model, and evidence that both newly added factors were significant in influencing consumers' evaluation of brand extensions was also found. More important, one new factor proposed, namely, consumer-perceived fit based on brand image consistency, was found to be more significant than all the factors in Aaker and Keller's original model, suggesting that the Aaker and Keller model may be limited in explaining how consumers in the emerging markets evaluate brand extensions. Further research implications and limitations are discussed in the paper.

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A cell culture model of the gastric epithelial cell surface would prove useful for biopharmaceutical screening of new chemical entities and dosage forms. A successful model should exhibit tight junction formation, maintenance of differentiation and polarity. Conditions for primary culture of guinea-pig gastric mucous epithelial cell monolayers on Tissue Culture Plastic (TCP) and membrane insects (Transwells) were established. Tight junction formation for cells grown on Transwells for three days was assessed by measurement of transepithelial resistance (TEER) and permeability of mannitol and fluorescein. Coating the polycarbonate filter with collagen IV, rather with collagen I, enhanced tight junction formation. TEER for cells grown on Transwells coated with collagen IV was close to that obtained with intact guinea-pig gastric epithelium in vitro. Differentiation was assessed by incorporation of [3H] glucosamine into glycoprotein and by activity of NADPH oxidase, which produces superoxide. Both of these measures were greater for cells grown on filters coated with collagen I than for cells grown on TCP, but no major difference was found between cells grown on collagens I and IV. However, monolayers grown on membranes coated with collagen IV exhibited apically polarized secretion of mucin and superoxide. The proportion of cells, which stained positively for mucin with periodic Schiff reagent, was greater than 95% for all culture conditions. Gastric epithelial monolayers grown on Transwells coated with collagen IV were able to withstand transient (30 min) apical acidification to pH 3, which was associated with a decrease in [3H] mannitol flux and an increase in TEER relative to pH 7.4. The model was used to provide the first direct demonstration that an NSAID (indomethacin) accumulated in gastric epithelial cells exposed to low apical pH. In conclusion, guinea-pig epithelial cells cultured on collagen IV represent a promising model of the gastric surface epithelium suitable for screening procedures.

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Safety enforcement practitioners within Europe and marketers, designers or manufacturers of consumer products need to determine compliance with the legal test of "reasonable safety" for consumer goods, to reduce the "risks" of injury to the minimum. To enable freedom of movement of products, a method for safety appraisal is required for use as an "expert" system of hazard analysis by non-experts in safety testing of consumer goods for implementation consistently throughout Europe. Safety testing approaches and the concept of risk assessment and hazard analysis are reviewed in developing a model for appraising consumer product safety which seeks to integrate the human factors contribution of risk assessment, hazard perception, and information processing. The model develops a system of hazard identification, hazard analysis and risk assessment which can be applied to a wide range of consumer products through use of a series of systematic checklists and matrices and applies alternative numerical and graphical methods for calculating a final product safety risk assessment score. It is then applied in its pilot form by selected "volunteer" Trading Standards Departments to a sample of consumer products. A series of questionnaires is used to select participating Trading Standards Departments, to explore the contribution of potential subjective influences, to establish views regarding the usability and reliability of the model and any preferences for the risk assessment scoring system used. The outcome of the two stage hazard analysis and risk assessment process is considered to determine consistency in results of hazard analysis, final decisions regarding the safety of the sample product and to determine any correlation in the decisions made using the model and alternative scoring methods of risk assessment. The research also identifies a number of opportunities for future work, and indicates a number of areas where further work has already begun.

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The primary objective of this research was to understand what kinds of knowledge and skills people use in `extracting' relevant information from text and to assess the extent to which expert systems techniques could be applied to automate the process of abstracting. The approach adopted in this thesis is based on research in cognitive science, information science, psycholinguistics and textlinguistics. The study addressed the significance of domain knowledge and heuristic rules by developing an information extraction system, called INFORMEX. This system, which was implemented partly in SPITBOL, and partly in PROLOG, used a set of heuristic rules to analyse five scientific papers of expository type, to interpret the content in relation to the key abstract elements and to extract a set of sentences recognised as relevant for abstracting purposes. The analysis of these extracts revealed that an adequate abstract could be generated. Furthermore, INFORMEX showed that a rule based system was a suitable computational model to represent experts' knowledge and strategies. This computational technique provided the basis for a new approach to the modelling of cognition. It showed how experts tackle the task of abstracting by integrating formal knowledge as well as experiential learning. This thesis demonstrated that empirical and theoretical knowledge can be effectively combined in expert systems technology to provide a valuable starting approach to automatic abstracting.

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The starting point of this research was the belief that manufacturing and similar industries need help with the concept of e-business, especially in assessing the relevance of possible e-business initiatives. The research hypotheses was that it should be possible to produce a systematic model that defines, at a useful level of detail, the probable e-business requirements of an organisation based on objective criteria with an accuracy of 85%-90%. This thesis describes the development and validation of such a model. A preliminary model was developed from a variety of sources, including a survey of current and planned e-business activity and representative examples of e-business material produced by e-business solution providers. The model was subject to a process of testing and refinement based on recursive case studies, with controls over the improving accuracy and stability of the model. Useful conclusions were also possible as to the relevance of e-business functions to the case study participants themselves. Techniques were evolved to synthesise the e-business requirements of an organisation and present them at a management summary level of detail. The results of applying these techniques to all the case studies used in this research were discussed. The conclusion of the research was that the case study methodology employed was successful. A model was achieved suitable for practical application in a manufacturing organisation requiring help with a requirements definition process.

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Cystic fibrosis (CF) is the most common lethal inherited disease among Caucasians and arises due to mutations in a chloride channel, called cystic fibrosis transmembrane conductance regulator. A hallmark of this disease is the chronic bacterial infection of the airways, which is usually, associated with pathogens such as Pseudomonas aeruginosa, S. aureus and recently becoming more prominent, B. cepacia. The excessive inflammatory response, which leads to irreversible lung damage, will in the long term lead to mortality of the patient at around the age of 40 years. Understanding the pathogenesis of CF currently relies on animal models, such as those employing genetically-modified mice, and on single cell culture models, which are grown either as polarised or non-polarised epithelium in vitro. Whilst these approaches partially enable the study of disease progression in CF, both types of models have inherent limitations. The overall aim of this thesis was to establish a multicellular co-culture model of normal and CF human airways in vitro, which helps to partially overcome these limitations and permits analysis of cell-to-cell communication in the airways. These models could then be used to examine the co-ordinated response of the airways to infection with relevant pathogens in order to validate this approach over animals/single cell models. Therefore epithelial cell lines of non-CF and CF background were employed in a co-culture model together with human pulmonary fibroblasts. Co-cultures were grown on collagen-coated permeable supports at air-liquid interface to promote epithelial cell differentiation. The models were characterised and essential features for investigating CF infections and inflammatory responses were investigated and analysed. A pseudostratified like epithelial cell layer was established at air liquid interface (ALI) of mono-and co-cultures and cell layer integrity was verified by tight junction (TJ) staining and transepithelial resistance measurements (TER). Mono- and co-cultures were also found to secrete the airway mucin MUC5AC. Influence of bacterial infections was found to be most challenging when intact S. aureus, B. cepacia and P. aeruginosa were used. CF mono- and co-cultures were found to mimic the hyperinflammatory state found in CF, which was confirmed by analysing IL-8 secretions of these models. These co-culture models will help to elucidate the role fibroblasts play in the inflammatory response to bacteria and will provide a useful testing platform to further investigate the dysregulated airway responses seen in CF.

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We discuss aggregation of data from neuropsychological patients and the process of evaluating models using data from a series of patients. We argue that aggregation can be misleading but not aggregating can also result in information loss. The basis for combining data needs to be theoretically defined, and the particular method of aggregation depends on the theoretical question and characteristics of the data. We present examples, often drawn from our own research, to illustrate these points. We also argue that statistical models and formal methods of model selection are a useful way to test theoretical accounts using data from several patients in multiple-case studies or case series. Statistical models can often measure fit in a way that explicitly captures what a theory allows; the parameter values that result from model fitting often measure theoretically important dimensions and can lead to more constrained theories or new predictions; and model selection allows the strength of evidence for models to be quantified without forcing this into the artificial binary choice that characterizes hypothesis testing methods. Methods that aggregate and then formally model patient data, however, are not automatically preferred to other methods. Which method is preferred depends on the question to be addressed, characteristics of the data, and practical issues like availability of suitable patients, but case series, multiple-case studies, single-case studies, statistical models, and process models should be complementary methods when guided by theory development.