Design software architecture models using ontology

Software architecture plays an essential role in the high level description of a system design, where the structure and communication are emphasized. Despite its importance in the software engineering process, the lack of formal description and automated verification hinders the development of good software architecture models. In this paper, we present an approach to support the rigorous design and verification of software architecture models using the semantic web technology. We view software architecture models as ontology representations, where their structures and communication constraints are captured by the Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL). Specific configurations on the design are represented as concrete instances of the ontology, to which their structures and dynamic behaviors must conform. Furthermore, ontology reasoning tools can be applied to perform various automated verification on the design to ensure correctness, such as consistency checking, style recognition, and behavioral inference.

The Long-Term impact of Business Support? - Exploring the Role of Evaluation Timing using Micro Data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.

The long-term impact of business support? - Exploring the role of evaluation timing using micro data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.

The role of protein oxidation in ageing & disease

Ageing is a natural phenomenon of the human lifecycle, yet it is still not understood what causes the deterioration of the human body near the end of the lifespan. One popular theory is the Free Radical Theory of Ageing, which proposes that oxidative damage to biomolecules causes ageing of tissues. The ageing population is affected by many chronic diseases. This study focused on sarcopenia (muscle loss in ageing) and obesity as two models for comparison of oxidative damage in muscle proteins in mice. The aim of the study was to develop advanced mass spectrometry methods to detect specific oxidative modifications to mouse muscle proteins, including oxidation, nitration, chlorination, and carbonyl group formation, but western blotting was also used to provide complementary information on the oxidative state of proteins from aged and obese muscle. Mass spectrometry proved to be a powerful tool, enabling identification of the types of modifications present, the sites at which they were present and percentage of the peptide populations that were modified. Targeted and semi-targeted mass spectrometry methods were optimised for the identification and quantitation of the oxidised residues in muscle proteins. The development of the quantitative methods enabled comparisons of mass spectrometry instruments. Both the Time of Flight and QTRAP systems showed advantages of using the different mass analysers to quantify oxidative modifications. Several oxidised residues were characterised and quantified in both the obese and sarcopenic models, and higher levels of oxidation were found compared to their control counterparts. Residues found to be oxidised were oxidation of proline, tyrosine and tryptophan, dioxidation of methionine, allysine and nitration of tyrosine. However quantification was performed on methionine dioxidation and cysteine trioxidation containing residues in SERCA. The combination of measuring residue susceptibility and functional studies could contribute to understanding the overall role of oxidation in ageing and obesity.