22 resultados para alternative modeling approaches

em Aston University Research Archive


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Large-scale introduction of Organic Solar Cells (OSCs) onto the market is currently limited by their poor stability in light and air, factors present in normal working conditions for these devices. Thus, great efforts have to be undertaken to understand the photodegradation mechanisms of their organic materials in order to find solutions that mitigate these effects. This study reports on the elucidation of the photodegradation mechanisms occurring in a low bandgap polymer, namely, Si-PCPDTBT (poly[(4,4′-bis(2-ethylhexyl)dithieno[3,2-b:2′,3′-d]silole)-2,6-diyl-alt-(4,7-bis(2-thienyl)-2,1,3-benzothiadiazole)-5,5′-diyl]). Complementary analytical techniques (AFM, HS-SPME-GC-MS, UV-vis and IR spectroscopy) have been employed to monitor the modification of the chemical structure of the polymer upon photooxidative aging and the subsequent consequences on its architecture and nanomechanical properties. Furthermore, these different characterization techniques have been combined with a theoretical approach based on quantum chemistry to elucidate the evolution of the polymer alkyl side chains and backbone throughout exposure. Si-PCPDTBT is shown to be more stable against photooxidation than the commonly studied p-type polymers P3HT and PCDTBT, while modeling demonstrated the benefits of using silicon as a bridging atom in terms of photostability. (Figure Presented).

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For the drug discovery process, a library of 168 multisubstituted 1,4-benzodiazepines were prepared by a 5-step solid phase combinatorial approach. Substituents were varied in the 3,5, 7 and 8-position on the benzodiazepine scaffold. The combinatorial library was evaluated in a CCK radiolabelled binding assay and CCKA (alimentary) and CCKB (brain) selective lead structures were discovered. The template of CCKA selective 1,4-benzodiazepin-2-ones bearing the tryptophan moiety was chemically modified by selective alkylation and acylation reactions. These studies provided a series of Asperlicin naturally analogues. The fully optimised Asperlicin related compound possessed a similar CCKA activity as the natural occuring compound. 3-Alkylated 1,4-benzodiazepines with selectivity towards the CCKB receptor subtype were optimised on A) the lipophilic side chain and B) the 2-aminophenyl-ketone moiety, together with some stereochemical changes. A C3 unit in the 3-position of 1,4-benzodiazepines possessed a CCKB activity within the nanomolar range. Further SAR optimisation on the N1-position by selective alkylation resulted in an improved CCKB binding with potentially decreased activity on the GABAA/benzodiazepine receptor complex. The in vivo studies revealed two N1-alkylated compounds containing unsaturated alkyl groups with anxiolytic properties. Alternative chemical approaches have been developed, including a route that is suitable for scale up of the desired target molecule in order to provide sufficient quantities for further in vivo evaluation.

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Cholecystokinin (CCK) is a peptide hormone, present in the alimentary and the CNS. It is the most abundant peptide in the brain. CCK has been implicated in a number of disorders. The link between CCK and anxiety was the basis for this research. A comprehensive discussion on the many types of CCK receptor antagonists is included. For the drug discovery process, a number of synthetic approaches have been investigated and alternative chemical approaches developed. 1,4-Benzodiazepine analogues were prepared, with substitutents In the 1,2 & 3- position of the benzodiazepine scaffold varied, and substituted 3-anilino benzodiazepines exhibited the greatest in vitro activity towards the CCKA receptor subtype. Through extensive screening, pyrazolinone-ureido derivatives were identified, optimised, SAR studied and re-screened. A comprehensive in vivo study on the most active analogue is included, which has a number of common structural features with L-36S, 260 including activity. Pyrazolinone-amide derivatives, bearing the tryptophan moiety were equally active. A number of existing and novel furan- 2(SH)-one building blocks were prepared, from which a selected mini-library of 4- amino-substituted furan-2(SH)-ones were prepared and evaluated. All synthesised compounds were evaluated in a CCK radiolabelled binding assay (CCKA & CCKB), with compounds demonstrating receptor selectivity and lead structures being discovered. The work in this thesis has identified a number of highly active prime structures, from which further investigations are essential in providing more in vitro & in vivo data and the need to prepare more analogues.

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This investigation sought to explore the nature and extent of school mathematical difficulties among the dyslexic population. Anecdotal reports have suggested that many dyslexics may have difficulties in arithmetic, but few systematic studies have previously been undertaken. The literature pertaining to dyslexia and school mathematics respectively is reviewed. Clues are sought in studies of dyscalculia. These seem inadequate in accounting for dyslexics' reported mathematical difficulties. Similarities between aspects of language and mathematics are examined for underlying commonalities that may partially account for concomitant problems in mathematics, in individuals with a written language dysfunction. The performance of children taught using different mathematics work-schemes is assessed to ascertain if these are associated with differential levels of achievement that may be reflected in the dyslexic population few are found. Findings from studies designed to assess the relationship between written language failure and achievement in mathematics are reported. Study 1 reveals large correlational differences between subtest scores (Wechsler Intelligence Scale for Children, Wechsler, 1976) and three mathematics tests, for young dyslexics and children without literacy difficulties. However, few differences are found between levels of attainment, at this age (6 ½ - 9 years). Further studies indicate that, for dyslexics, achievement in school mathematics, may be independent of measured intelligence, as is the case with their literacy skills. Studies 3 and 4 reveal that dyslexics' performances on a range of school mathematical topics gets relatively worse compared with that of Controls (age range 8 - 17 years), as they get older. Extensive item analyses reveal many errors relating strongly to known deficits in the dyslexics' learning style - poor short-term memory, sequencing skills and verbal labelling strategies. Subgroups of dyslexics are identified on the basis of mathematical performance. Tentative explanations, involving alternative neuropsychological approaches, are offered for the measured differences in attainment between these groups.

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This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.

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A combination of the two-fluid and drift flux models have been used to model the transport of fibrous debris. This debris is generated during loss of coolant accidents in the primary circuit of pressurized or boiling water nuclear reactors, as high pressure steam or water jets can damage adjacent insulation materials including mineral wool blankets. Fibre agglomerates released from the mineral wools may reach the containment sump strainers, where they can accumulate and compromise the long-term operation of the emergency core cooling system. Single-effect experiments of sedimentation in a quiescent rectangular column and sedimentation in a horizontal flow are used to verify and validate this particular application of the multiphase numerical models. The utilization of both modeling approaches allows a number of pseudocontinuous dispersed phases of spherical wetted agglomerates to be modeled simultaneously. Key effects on the transport of the fibre agglomerates are particle size, density and turbulent dispersion, as well as the relative viscosity of the fluid-fibre mixture.

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WiMAX has been introduced as a competitive alternative for metropolitan broadband wireless access technologies. It is connection oriented and it can provide very high data rates, large service coverage, and flexible quality of services (QoS). Due to the large number of connections and flexible QoS supported by WiMAX, the uplink access in WiMAX networks is very challenging since the medium access control (MAC) protocol must efficiently manage the bandwidth and related channel allocations. In this paper, we propose and investigate a cost-effective WiMAX bandwidth management scheme, named the WiMAX partial sharing scheme (WPSS), in order to provide good QoS while achieving better bandwidth utilization and network throughput. The proposed bandwidth management scheme is compared with a simple but inefficient scheme, named the WiMAX complete sharing scheme (WCPS). A maximum entropy (ME) based analytical model (MEAM) is proposed for the performance evaluation of the two bandwidth management schemes. The reason for using MEAM for the performance evaluation is that MEAM can efficiently model a large-scale system in which the number of stations or connections is generally very high, while the traditional simulation and analytical (e.g., Markov models) approaches cannot perform well due to the high computation complexity. We model the bandwidth management scheme as a queuing network model (QNM) that consists of interacting multiclass queues for different service classes. Closed form expressions for the state and blocking probability distributions are derived for those schemes. Simulation results verify the MEAM numerical results and show that WPSS can significantly improve the network's performance compared to WCPS.

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Over recent years, the role of engineering in promoting a sustainable society has received much public attention [1] with particular emphasis given to the need to promote the future prosperity and security of society through the recruitment and education of more engineers [2,3]. From an employment perspective, the Leitch Review [4] suggested that ‘generic’ transferable employability skills development should constitute a more substantial part of university education. This paper argues that the global drivers impacting engineering education [5] correlate strongly to those underpinning the Leitch review, therefore the question of how to promote transferable employability skills within the wider engineering curriculum is increasingly relevant. By exploring the use of heritage in the engineering curriculum as a way to promote learning and engage students, a less familiar approach to study is discussed. This approach moves away from stereotypical notions of the use of information technology as representing the pinnacle of innovation in education. Taking the student experience as its starting point, the paper draws upon the findings of an exploratory study critically analysing the pedagogical value of using heritage in engineering education. It discusses a teaching approach in which engineering students are taken out of their ‘comfort zone’ - away from the classroom, laboratory and computer, to a heritage site some 100 miles away from the university. The primary learning objective underpinning this approach is to develop students’ transferable skills by encouraging them to consider how to apply theoretical concepts to a previously unexplored situation. By reflecting upon students’ perceptions of the value of this approach, and by identifying how heritage may be utilised as an innovative learning and teaching approach in engineering education, this paper makes a notable contribution to current pedagogical debates in the discipline.

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Purpose: The purpose of this paper is to describe how the application of systems thinking to designing, managing and improving business processes has resulted in a new and unique holonic-based process modeling methodology know as process orientated holonic modeling. Design/methodology/approach: The paper describes key systems thinking axioms that are built upon in an overview of the methodology; the techniques are described using an example taken from a large organization designing and manufacturing capital goods equipment operating within a complex and dynamic environment. These were produced in an 18 month project, using an action research approach, to improve quality and process efficiency. Findings: The findings of this research show that this new methodology can support process depiction and improvement in industrial sectors which are characterized by environments of high variety and low volume (e.g. projects; such as the design and manufacture of a radar system or a hybrid production process) which do not provide repetitive learning opportunities. In such circumstances, the methodology has not only been able to deliver holonic-based process diagrams but also been able to transfer strategic vision from top management to middle and operational levels without being reductionistic. Originality/value: This paper will be of interest to organizational analysts looking at large complex projects whom require a methodology that does not confine them to thinking reductionistically in "task-breakdown" based approaches. The novel ideas in this paper have great impact on the way analysts should perceive organizational processes. Future research is applying the methodology in similar environments in other industries. © Emerald Group Publishing Limited.

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Most object-based approaches to Geographical Information Systems (GIS) have concentrated on the representation of geometric properties of objects in terms of fixed geometry. In our road traffic marking application domain we have a requirement to represent the static locations of the road markings but also enforce the associated regulations, which are typically geometric in nature. For example a give way line of a pedestrian crossing in the UK must be within 1100-3000 mm of the edge of the crossing pattern. In previous studies of the application of spatial rules (often called 'business logic') in GIS emphasis has been placed on the representation of topological constraints and data integrity checks. There is very little GIS literature that describes models for geometric rules, although there are some examples in the Computer Aided Design (CAD) literature. This paper introduces some of the ideas from so called variational CAD models to the GIS application domain, and extends these using a Geography Markup Language (GML) based representation. In our application we have an additional requirement; the geometric rules are often changed and vary from country to country so should be represented in a flexible manner. In this paper we describe an elegant solution to the representation of geometric rules, such as requiring lines to be offset from other objects. The method uses a feature-property model embraced in GML 3.1 and extends the possible relationships in feature collections to permit the application of parameterized geometric constraints to sub features. We show the parametric rule model we have developed and discuss the advantage of using simple parametric expressions in the rule base. We discuss the possibilities and limitations of our approach and relate our data model to GML 3.1. © 2006 Springer-Verlag Berlin Heidelberg.

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In this chapter, the authors use an EGARCH-ECM to estimate the pass-through effects of Foreign Exchange (FX) rate changes and changes in producers' prices for 20 U.K. export sectors. The long-run adjustments of export prices to FX rate changes and changes in producers' prices are within the range of -1.02% (for the Textiles sector) and -17.22% (for the Meat sector). The contemporaneous Pricing-To-Market (PTM) coefficients are within the range of -72.84% (for the Fuels sector) and -8.05% (for the Textiles sector). Short-run FX rate pass-through is not complete even after several months. Rolling EGARCH-ECMs show that the short and long-run effects of changes in FX rate and producers' prices vary substantially, as do asymmetry and volatility estimates before equilibrium is achieved.

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In inflammatory diseases, release of oxidants leads to oxidative damage to proteins. The precise nature of oxidative damage to individual proteins depends on the oxidant involved. Chlorination and nitration are markers of modification by the myeloperoxidase-H2O2-Cl- system and nitric oxide-derived oxidants, respectively. Although these modifications can be detected by western blotting, currently no reliable method exists to identify the specific sites damage to individual proteins in complex mixtures such as clinical samples. We are developing novel LCMS2 and precursor ion scanning methods to address this. LC-MS2 allows separation of peptides and detection of mass changes in oxidized residues on fragmentation of the peptides. We have identified indicative fragment ions for chlorotyrosine, nitrotyrosine, hydroxytyrosine and hydroxytryptophan. A nano-LC/MS3 method involving the dissociation of immonium ions to give specific fragments for the oxidized residues has been developed to overcome the problem of false positives from ions isobaric to these immonium ions that exist in unmodified peptides. The approach has proved able to identify precise protein modifications in individual proteins and mixtures of proteins. An alternative methodology involves multiple reaction monitoring for precursors and fragment ions are specific to oxidized and chlorinated proteins, and this has been tested with human serum albumin. Our ultimate aim is to apply this methodology to the detection of oxidative post-translational modifications in clinical samples for disease diagnosis, monitoring the outcomes of therapy, and improved understanding of disease biochemistry.

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Sentiment analysis has long focused on binary classification of text as either positive or negative. There has been few work on mapping sentiments or emotions into multiple dimensions. This paper studies a Bayesian modeling approach to multi-class sentiment classification and multidimensional sentiment distributions prediction. It proposes effective mechanisms to incorporate supervised information such as labeled feature constraints and document-level sentiment distributions derived from the training data into model learning. We have evaluated our approach on the datasets collected from the confession section of the Experience Project website where people share their life experiences and personal stories. Our results show that using the latent representation of the training documents derived from our approach as features to build a maximum entropy classifier outperforms other approaches on multi-class sentiment classification. In the more difficult task of multi-dimensional sentiment distributions prediction, our approach gives superior performance compared to a few competitive baselines. © 2012 ACM.

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Development of mass spectrometry techniques to detect protein oxidation, which contributes to signalling and inflammation, is important. Label-free approaches have the advantage of reduced sample manipulation, but are challenging in complex samples owing to undirected analysis of large data sets using statistical search engines. To identify oxidised proteins in biological samples, we previously developed a targeted approach involving precursor ion scanning for diagnostic MS3 ions from oxidised residues. Here, we tested this approach for other oxidations, and compared it with an alternative approach involving the use of extracted ion chromatograms (XICs) generated from high-resolution MSMS data using very narrow mass windows. This accurate mass XIC data methodology was effective at identifying nitrotyrosine, chlorotyrosine, and oxidative deamination of lysine, and for tyrosine oxidations highlighted more modified peptide species than precursor ion scanning or statistical database searches. Although some false positive peaks still occurred in the XICs, these could be identified by comparative assessment of the peak intensities. The method has the advantage that a number of different modifications can be analysed simultaneously in a single LC-MSMS run. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine. Biological significance: The use of accurate mass extracted product ion chromatograms to detect oxidised peptides could improve the identification of oxidatively damaged proteins in inflammatory conditions. © 2013 Elsevier B.V.

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Liquids and gases produced through biomass pyrolysis have potential as renewable fuels to replace fossil fuels in conventional internal combustion engines. This review compares the properties of pyrolysis fuels, produced from a variety of feedstocks and using different pyrolysis techniques, against those of fossil fuels. High acidity, the presence of solid particles, high water content, high viscosity, storage and thermal instability, and low energy content are typical characteristics of pyrolysis liquids. A survey of combustion, performance and exhaust emission results from the use of pyrolysis liquids (both crude and up-graded) in compression ignition engines is presented. With only a few exceptions, most authors have reported difficulties associated with the adverse properties of pyrolysis liquids, including: corrosion and clogging of the injectors, long ignition delay and short combustion duration, difficulty in engine start-up, unstable operation, coking of the piston and cylinders and subsequent engine seizure. Pyrolysis gas can be used more readily, either in spark ignition or compression ignition engines; however, NO reduction techniques are desirable. Various approaches to improve the properties of pyrolysis liquids are discussed and a comparison of the properties of up-graded vs. crude pyrolysis liquid is included. Further developments in up-gradation techniques, such as hydrocracking and bio-refinery approaches, could lead to the production of green diesel and green gasoline. Modifications required to engines for use with pyrolysis liquids, for example in the fuel supply and injection systems, are discussed. Storage stability and economic issues are also reviewed. Our study presents recent progress and important R&D areas for successful future use of pyrolysis fuels in internal combustion engines.