Compilation and analysis of integrated regional input-output tables for NUTS 2 regions in Ireland

In 1966, Roy Geary, Director of the ESRI, noted “the absence of any kind of import and export statistics for regions is a grave lacuna” and further noted that if regional analyses were to be developed then regional Input-Output Tables must be put on the “regular statistical assembly line”. Forty-five years later, the lacuna lamented by Geary still exists and remains the most significant challenge to the construction of regional Input-Output Tables in Ireland. The continued paucity of sufficient regional data to compile effective regional Supply and Use and Input-Output Tables has retarded the capacity to construct sound regional economic models and provide a robust evidence base with which to formulate and assess regional policy. This study makes a first step towards addressing this gap by presenting the first set of fully integrated, symmetric, Supply and Use and domestic Input-Output Tables compiled for the NUTS 2 regions in Ireland: The Border, Midland and Western region and the Southern & Eastern region. These tables are general purpose in nature and are consistent fully with the official national Supply & Use and Input-Output Tables, and the regional accounts. The tables are constructed using a survey-based or bottom-up approach rather than employing modelling techniques, yielding more robust and credible tables. These tables are used to present a descriptive statistical analysis of the two administrative NUTS 2 regions in Ireland, drawing particular attention to the underlying structural differences of regional trade balances and composition of Gross Value Added in those regions. By deriving regional employment multipliers, Domestic Demand Employment matrices are constructed to quantify and illustrate the supply chain impact on employment. In the final part of the study, the predictive capability of the Input-Output framework is tested over two time periods. For both periods, the static Leontief production function assumptions are relaxed to allow for labour productivity. Comparative results from this experiment are presented.

Computing explanations for interactive constraint-based systems

Constraint programming has emerged as a successful paradigm for modelling combinatorial problems arising from practical situations. In many of those situations, we are not provided with an immutable set of constraints. Instead, a user will modify his requirements, in an interactive fashion, until he is satisfied with a solution. Examples of such applications include, amongst others, model-based diagnosis, expert systems, product configurators. The system he interacts with must be able to assist him by showing the consequences of his requirements. Explanations are the ideal tool for providing this assistance. However, existing notions of explanations fail to provide sufficient information. We define new forms of explanations that aim to be more informative. Even if explanation generation is a very hard task, in the applications we consider, we must manage to provide a satisfactory level of interactivity and, therefore, we cannot afford long computational times. We introduce the concept of representative sets of relaxations, a compact set of relaxations that shows the user at least one way to satisfy each of his requirements and at least one way to relax them, and present an algorithm that efficiently computes such sets. We introduce the concept of most soluble relaxations, maximising the number of products they allow. We present algorithms to compute such relaxations in times compatible with interactivity, achieving this by indifferently making use of different types of compiled representations. We propose to generalise the concept of prime implicates to constraint problems with the concept of domain consequences, and suggest to generate them as a compilation strategy. This sets a new approach in compilation, and allows to address explanation-related queries in an efficient way. We define ordered automata to compactly represent large sets of domain consequences, in an orthogonal way from existing compilation techniques that represent large sets of solutions.

Legislative policy, law and competitiveness: a mysterious and difficult relationship in the EU

The Lisbon Agenda places Europe in a uniquely difficult position globally, most particularly as an example of a social and regulatory experiment which many consider to be doomed to failure. The drive towards economic competitiveness has led to a focus on regulation and its effect on entrepreneurship, productivity and business growth but assessing this relationship is complex for a number of reasons. First, not all regulatory effects can be predicted precisely in relation to behavioural outcomes. Path-dependency scholars have also demonstrated that the regulation will have varying effects depending on context. Second, theoretically it is clear that many non-regulatory factors may contribute to economic and competitive success. Third, there is evidence of internal conflict within the Commission as to the relative importance of the Lisbon goals. Finally, the experience of distinct Member States presents challenges both for assessment and prescriptive remedies. The Commission has estimated that the cost of regulatory compliance obligations on businesses in the EU is between 4% and 6% of gross domestic product and that 15% of this figure is avoidable 'red tape' (the term used specifically to signify unnecessary compliance burdens). This article proposes to assess the likely outcomes of de-regulation as we rapidly approach 2010, the year for attainment of the Lisbon goals.

The gut microbiota as a contributing factor to antipsychotic-induced weight gain and metabolic dysfunction

Schizophrenia represents one of the world’s most devastating illnesses due to its often lifelong course and debilitating nature. The treatment of schizophrenia has vastly improved over recent decades with the discovery of several antipsychotic compounds; however these drugs are not without adverse effects that must be addressed to maximize their therapeutic value. Newer, atypical, antipsychotics are associated with a compilation of serious metabolic side effects including weight gain, insulin resistance, fat deposition, glucose dysregulation and ensuing co-morbidities such as type II diabetes mellitus. The mechanisms underlying these side effects remain to be fully elucidated and adequate interventions are lacking. Further understanding of the factors that contribute these side effects is therefore required in order to develop effective adjunctive therapies and to potentially design antipsychotic drugs in the future with reduced impact on the metabolic health of patients. We investigated if the gut microbiota represented a novel mechanism contributing to the metabolic dysfunction associated with atypical antipsychotics. The gut microbiota comprises the bacteria that exist symbiotically within the gastrointestinal tract, and has been shown in recent years to be involved in several aspects of energy balance and metabolism. We have demonstrated that administration of certain antipsychotics in the rat results in an altered microbiota profile and, moreover, that the microbiota is required for the full scale of metabolic dysfunction to occur. We have further shown that specific antibiotics can attenuate certain aspects of olanzapine and risperidone–induced metabolic dysfunction, in particular fat deposition and adipose tissue inflammation. Mechanisms underlying this novel link appear to involve energy utilization via expression of lipogenic genes as well as reduced inflammatory tone. Taken together, these data indicate that the gut microbiota is an important factor involved in the myriad of metabolic complications associated with antipsychotic therapy. Furthermore, these data support the future investigation of microbial-based therapeutics for not only antipsychotic-induced weight gain but also for tackling the global obesity epidemic.

A qualitative study of trends in patient preferences for the management of partial dentition

Objective: To identify factors influencing attitudes of partially dentate adults towards dental treatment in Ireland. Background: People are retaining more teeth later in life than ever before. Management of partially dentate older adults will be a major requirement for the future and it is important to determine factors which may influence patients’ attitudes to care. Methods: Subjects: A purposive sample of 22 partially dentate patients was recruited; 12 women and 12 men, ranging in age from 45 to 75 years. Data Collection: Semi-structured individual interviews. Results: Dental patients have increasing expectations in relation to (i) a more sophisticated approach to the management of missing teeth and (ii) their right to actively participate in decision making regarding the management of their tooth loss. There is some evidence of a cohort effect with younger patients (45–64 years) having higher expectations. Conclusions: The evidence of a cohort effect within this study in relation to higher patient expectations indicates that both contemporary and future patients are likely to seek a service based on conservation and restoration of missing teeth by fixed prostheses.