5 resultados para knowledge testing

em Aston University Research Archive


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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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Nanotechnologies have been called the "Next Industrial Revolution." At the same time, scientists are raising concerns about the potential health and environmental risks related to the nano-sized materials used in nanotechnologies. Analyses suggest that current U.S. federal regulatory structures are not likely to adequately address these risks in a proactive manner. Given these trends, the premise of this paper is that state and local-level agencies will likely deal with many "end-of-pipe" issues as nanomaterials enter environmental media without prior toxicity testing, federal standards, or emissions controls. In this paper we (1) briefly describe potential environmental risks and benefits related to emerging nanotechnologies; (2) outline the capacities of the Toxic Substances Control Act, the Clean Air Act, the Clean Water Act, and the Resources Conservation and Recovery Act to address potential nanotechnology risks, and how risk data gaps challenge these regulations; (3) outline some of the key data gaps that challenge state-level regulatory capacities to address nanotechnologies' potential risks, using Wisconsin as a case study; and (4) discuss advantages and disadvantages of state versus federal approaches to nanotechnology risk regulation. In summary, we suggest some ways government agencies can be better prepared to address nanotechnology risk knowledge gaps and risk management.

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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 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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The present research represents a coherent approach to understanding the root causes of ethnic group differences in ability test performance. Two studies were conducted, each of which was designed to address a key knowledge gap in the ethnic bias literature. In Study 1, both the LR Method of Differential Item Functioning (DIF) detection and Mixture Latent Variable Modelling were used to investigate the degree to which Differential Test Functioning (DTF) could explain ethnic group test performance differences in a large, previously unpublished dataset. Though mean test score differences were observed between a number of ethnic groups, neither technique was able to identify ethnic DTF. This calls into question the practical application of DTF to understanding these group differences. Study 2 investigated whether a number of non-cognitive factors might explain ethnic group test performance differences on a variety of ability tests. Two factors – test familiarity and trait optimism – were able to explain a large proportion of ethnic group test score differences. Furthermore, test familiarity was found to mediate the relationship between socio-economic factors – particularly participant educational level and familial social status – and test performance, suggesting that test familiarity develops over time through the mechanism of exposure to ability testing in other contexts. These findings represent a substantial contribution to the field’s understanding of two key issues surrounding ethnic test performance differences. The author calls for a new line of research into these performance facilitating and debilitating factors, before recommendations are offered for practitioners to ensure fairer deployment of ability testing in high-stakes selection processes.