24 resultados para Simplified and advanced calculation methods


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This thesis introduces a flexible visual data exploration framework which combines advanced projection algorithms from the machine learning domain with visual representation techniques developed in the information visualisation domain to help a user to explore and understand effectively large multi-dimensional datasets. The advantage of such a framework to other techniques currently available to the domain experts is that the user is directly involved in the data mining process and advanced machine learning algorithms are employed for better projection. A hierarchical visualisation model guided by a domain expert allows them to obtain an informed segmentation of the input space. Two other components of this thesis exploit properties of these principled probabilistic projection algorithms to develop a guided mixture of local experts algorithm which provides robust prediction and a model to estimate feature saliency simultaneously with the training of a projection algorithm.Local models are useful since a single global model cannot capture the full variability of a heterogeneous data space such as the chemical space. Probabilistic hierarchical visualisation techniques provide an effective soft segmentation of an input space by a visualisation hierarchy whose leaf nodes represent different regions of the input space. We use this soft segmentation to develop a guided mixture of local experts (GME) algorithm which is appropriate for the heterogeneous datasets found in chemoinformatics problems. Moreover, in this approach the domain experts are more involved in the model development process which is suitable for an intuition and domain knowledge driven task such as drug discovery. We also derive a generative topographic mapping (GTM) based data visualisation approach which estimates feature saliency simultaneously with the training of a visualisation model.

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This thesis reports the results of research into the connections between transaction attributes and buyer-supplier relationships (BSR) in advanced manufacturing technology (AMT) acquisitions and implementation. It also examines the impact of the different patterns of BSR on performance. Specifically, it addresses the issues of how the three transaction attributes; namely level of complexity, level of asset specificity, and level of uncertainty, can affect the relationships between the technology buyer and suppler in AMT acquisition and implementation, and then to see the impact of different patterns of BSR on the two aspect of performance; namely technology and implementation performance. In understanding the pohenomena, the study mainly draws on and integrates the literature of transaction cost economics theory,buyer-supplier relationships and advanced manufacturing technology as a basis of theoretical framework and hypotheses development.data were gathered through a questionnaire survey with 147 responses and seven semi-structured interviews of manufacturing firms in Malaysia. Quantitative data were analysed mainly using the AMOS (Analysis of Moment Structure) package for structural equation modeling and SPSS (Statistical Package for Social Science) for analysis of variance (ANOVA). Data from interview sessions were used to develop a case study with the intention of providing a richer and deeper understanding on the subject under investigation and to offer triangulation in the research process. he results of the questionnaire survey indicate that the higher the level of technological specificity and uncertainty, the more firms are likely to engage in a closer relationship with technology suppliers.However, the complexity of the technology being implemented is associated with BSR only because it is associated with the level of uncertainty that has direct impact upon BSR.The analysis also provides strong support for the premise that developing strong BSR could lead to an improved performance. However, with high levels of transaction attribute, implementation performance suffers more when firms have weak relationships with technology suppliers than with moderate and low levels of transaction attributes. The implications of the study are offered for both the academic and practitioner audience. The thesis closes with reports on its limitations and suggestions for further research that would address some of these limitations.

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This thesis is an exploration of the organisation and functioning of the human visual system using the non-invasive functional imaging modality magnetoencephalography (MEG). Chapters one and two provide an introduction to the ‘human visual system and magnetoencephalographic methodologies. These chapters subsequently describe the methods by which MEG can be used to measure neuronal activity from the visual cortex. Chapter three describes the development and implementation of novel analytical tools; including beamforming based analyses, spectrographic movies and an optimisation of group imaging methods. Chapter four focuses on the use of established and contemporary analytical tools in the investigation of visual function. This is initiated with an investigation of visually evoked and induced responses; covering visual evoked potentials (VEPs) and event related synchronisation/desynchronisation (ERS/ERD). Chapter five describes the employment of novel methods in the investigation of cortical contrast response and demonstrates distinct contrast response functions in striate and extra-striate regions of visual cortex. Chapter six use synthetic aperture magnetometry (SAM) to investigate the phenomena of visual cortical gamma oscillations in response to various visual stimuli; concluding that pattern is central to its generation and that it increases in amplitude linearly as a function of stimulus contrast, consistent with results from invasive electrode studies in the macaque monkey. Chapter seven describes the use of driven visual stimuli and tuned SAM methods in a pilot study of retinotopic mapping using MEG; finding that activity in the primary visual cortex can be distinguished in four quadrants and two eccentricities of the visual field. Chapter eight is a novel implementation of the SAM beamforming method in the investigation of a subject with migraine visual aura; the method reveals desynchronisation of the alpha and gamma frequency bands in occipital and temporal regions contralateral to observed visual abnormalities. The final chapter is a summary of main conclusions and suggested further work.

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The investigation of renal pathophysiology and toxicology has traditionally been advanced by the development of increasingly defined and refined in vitro preparations. This study has sought to develop and evaluate various methods of producing pure samples of renal proximal tubules (PTs) from the Fischer rat. The introduction summarised the most common in vitro preparations together with the parameters used to monitor viability - particularly with regard to toxic events. The most prevalent isolation methods have involved the use of collagenase to produce dissociation of the cortex. However, the present study has shown that even the mildest collagenase treatment caused significant structural damage which resulted in a longevity of only 3hr in suspension. An alternative mechanical isolation technique has been developed in this study that consists of perfusion loading the renal glomeruli with Fe304 followed by disruption of the cortex by homogenisation and sequential sieving. The glomeruli are removed magnetically and the PTs then harvested by a 64μM sieve. PTs isolated in this way showed a vastly superior structural preservation over their collagenase isolated counterparts; also oxygen consumption and enzyme leakage measurements showed a longevity in excess of 6hr when incubated in a very basic medium. Attempts were then made to measure the cytosolic calcium levels in both mechanical and collagenase isolated PTs using the fluorescent calcium indicator Fura. However results were inconclusive due to significant binding of the Fura to the external PT surfaces. In conclusion, PTs prepared by the present mechanical isolation technique exhibit superior preservation and longevity compared with even the mildest collagenase isolation technique and hence appear to offer potential advantages over collagenase isolation as an in vitro renal system.

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BACKGROUND: Patients with advanced cancer suffer from cachexia, which is characterised by a marked weight loss, and is invariably associated with the presence of tumoral and humoral factors which are mainly responsible for the depletion of fat stores and muscular tissue. METHODS: In this work, we used cytotoxicity and enzymatic assays and morphological analysis to examine the effects of a proteolysis-inducing factor (PIF)-like molecule purified from ascitic fluid of Walker tumour-bearing rats (WF), which has been suggested to be responsible for muscle atrophy, on cultured C2C12 muscle cells. RESULTS: WF decreased the viability of C2C12 myotubes, especially at concentrations of 20-25 mug.mL-1. There was an increase in the content of the pro-oxidant malondialdehyde, and a decrease in antioxidant enzyme activity. Myotubes protein synthesis decreased and protein degradation increased together with an enhanced in the chymotrypsin-like enzyme activity, a measure of functional proteasome activity, after treatment with WF. Morphological alterations such as cell retraction and the presence of numerous cells in suspension were observed, particularly at high WF concentrations. CONCLUSION: These results indicate that WF has similar effects to those of proteolysis-inducing factor, but is less potent than the latter. Further studies are required to determine the precise role of WF in this experimental model. © 2008 Yano et al; licensee BioMed Central Ltd.

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Silicon carbide ceramics are candidate materials for use in aggressive environments, including those where aqueous acids are present. Standard corrosion testing methods such as immersion testing are not always sufficiently sensitive for these ceramics owing to the very low, almost unobservable, corrosion rates encountered. Using electrochemical methods the corrosion processes can be assisted, leading to higher rates and thus the elucidation of reaction mechanisms. The behaviour of a sintered and a reaction bonded silicon carbide has been investigated in aqueous HCl, HF, HNO3, and H2SO4, using standard immersion and new electrochemical methods. Both materials were passive in HCl, HNO3, and H2SO4 because of the formation of a surface silica film, and were active in HF. In HF, corrosion of sintered silicon carbide was slight and the residual silicon was removed from reaction bonded specimens.

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Background and aims: Diabetic Retinopathy (DR) is a leading cause of blindness. OSA is associated with increased oxidative and nitrosative stress and endothelial dysfunction in patients with type 2 diabetes (T2DM). Hence, it is plausible that OSA can promote the development and progression of DR. Materials and methods: An observational longitudinal study in adults with T2DM. Patients with pre-existing OSA, end-stage renal disease and non-diabetic retinopathy were excluded. OSA (apnoea hypopnea index ≥ 5 events/hour) was assessed by a single overnight home-based cardio-respiratory monitoring (Alice PDX, etc.). DR was assesses using retinal images between 2007 and 2012. Sight threatening retinopathy (STR) was defined as pre-proliferative or proliferative DR, maculopathy or photocoagulation. Advanced DR was defined as pre-proliferative or proliferative DR. Results: 199 patients were included (57.3% men, 47.7% White Europeans). STR and OSA prevalence were 38.7 % and 62.8% respectively. STR preva-lence was higher in patients with OSA (OSA+) compared to those with-out (OSA-) [48.8% vs. 21.6%, p <0.001]. After adjustment for confounders, OSA remained independently associated with STR (OR 3.7, 95%CI 1.6-8.9, p=0.006, maculopathy (OR 4.5, 1.8-11.4, p=0.002) and advanced DR (OR 3.9, 1.02-15.3, p=0.047). Over 4.4±1 years, more OSA+ patients progressed from no or background DR to advanced DR (15.3% vs. 3%, p=0.01). OSA was an independent predictor of advanced DR development after adjustment (OR 6.6, 95%CI 1.2-35.1, p=0.03). OSA did not predict the development of maculopathy. Patients received continuous positive airway pressure treatment were less likely to develop advanced DR. Conclusion: OSA is independently associated with STR and predicts the development of preproliferative and proliferative DR. Interventional studies are needed to assess the impact of OSA treatment on DR.Supported by: NIHR (UK) and The UK Novo Nordisk Research Foundation.

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Motivation: In any macromolecular polyprotic system - for example protein, DNA or RNA - the isoelectric point - commonly referred to as the pI - can be defined as the point of singularity in a titration curve, corresponding to the solution pH value at which the net overall surface charge - and thus the electrophoretic mobility - of the ampholyte sums to zero. Different modern analytical biochemistry and proteomics methods depend on the isoelectric point as a principal feature for protein and peptide characterization. Protein separation by isoelectric point is a critical part of 2-D gel electrophoresis, a key precursor of proteomics, where discrete spots can be digested in-gel, and proteins subsequently identified by analytical mass spectrometry. Peptide fractionation according to their pI is also widely used in current proteomics sample preparation procedures previous to the LC-MS/MS analysis. Therefore accurate theoretical prediction of pI would expedite such analysis. While such pI calculation is widely used, it remains largely untested, motivating our efforts to benchmark pI prediction methods. Results: Using data from the database PIP-DB and one publically available dataset as our reference gold standard, we have undertaken the benchmarking of pI calculation methods. We find that methods vary in their accuracy and are highly sensitive to the choice of basis set. The machine-learning algorithms, especially the SVM-based algorithm, showed a superior performance when studying peptide mixtures. In general, learning-based pI prediction methods (such as Cofactor, SVM and Branca) require a large training dataset and their resulting performance will strongly depend of the quality of that data. In contrast with Iterative methods, machine-learning algorithms have the advantage of being able to add new features to improve the accuracy of prediction. Contact: yperez@ebi.ac.uk Availability and Implementation: The software and data are freely available at https://github.com/ypriverol/pIR. Supplementary information: Supplementary data are available at Bioinformatics online.

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We survey articles covering how hedge fund returns are explained, using largely non-linear multifactor models that examine the non-linear pay-offs and exposures of hedge funds. We provide an integrated view of the implicit factor and statistical factor models that are largely able to explain the hedge fund return-generating process. We present their evolution through time by discussing pioneering studies that made a significant contribution to knowledge, and also recent innovative studies that examine hedge fund exposures using advanced econometric methods. This is the first review that analyzes very recent studies that explain a large part of hedge fund variation. We conclude by presenting some gaps for future research.