Accumulation of knowledge and accumulation of capital in early ‘theories’ of growth and development

This paper argues that prior to Adam Smith economic progress was largely conceived as being based on the accumulation of knowledge. The development by Turgot and Smith of a concept of capital that subsumed other factors contributing to development led their followers to focus on capital to the neglect of the independent role of knowledge. The paper demonstrates that this paradigmatic shift was identified and challenged by Bentham, Hodgskin and Rae who argued for the independent role of innovation but without lasting impact. © The Author 2009. Published by Oxford University Press on behalf of the Cambridge Political Economy Society. All rights reserved.

A Ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge

Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time-consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In this paper, we introduce our tool for very rapid screening for likely ligands (either substrates or inhibitors) based on reasoning with imprecise probabilistic knowledge elicited from past experiments. Probabilistic knowledge is input to the system via a user-friendly interface showing a base compound structure. A prediction of whether a particular compound is a substrate is queried against the acquired probabilistic knowledge base and a probability is returned as an indication of the prediction. This tool will be particularly useful in situations where a number of similar compounds have been screened experimentally, but information is not available for all possible members of that group of compounds. We use two case studies to demonstrate how to use the tool.

A survey of formalisms for representing and reasoning with scientific knowledge

With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.

Modeling and reasoning with qualitative comparative clinical knowledge

The number of clinical trials reports is increasing rapidly due to a large number of clinical trials being conducted; it, therefore, raises an urgent need to utilize the clinical knowledge contained in the clinical trials reports. In this paper, we focus on the qualitative knowledge instead of quantitative knowledge. More precisely, we aim to model and reason with the qualitative comparison (QC for short) relations which consider qualitatively how strongly one drug/therapy is preferred to another in a clinical point of view. To this end, first, we formalize the QC relations, introduce the notions of QC language, QC base, and QC profile; second, we propose a set of induction rules for the QC relations and provide grading interpretations for the QC bases and show how to determine whether a QC base is consistent. Furthermore, when a QC base is inconsistent, we analyze how to measure inconsistencies among QC bases, and we propose different approaches to merging multiple QC bases. Finally, a case study on lowering intraocular pressure is conducted to illustrate our approaches.

An exploration of knowledge and attitudes related to pre-pregnancy care in women with diabetes

Aims: Pre-pregnancy care optimizes pregnancy outcome in women with pre-gestational diabetes, yet most women enter pregnancy unprepared. We sought to determine knowledge and attitudes of women with Type 1 and Type 2 diabetes of childbearing age towards pre-pregnancy care.

Methods: Twenty-four women (18 with Type 1 diabetes and six with Type 2 diabetes) aged 17–40 years took part in one of four focus group sessions: young nulliparous women with Type 1 diabetes (Group A), older nulliparous women with Type 1 diabetes (Group B), parous women with Type 1 diabetes (Group C) and women with Type 2 diabetes of mixed parity (Group D).

Results: Content analysis of transcribed focus groups revealed that, while women were well informed about the need to plan pregnancy, awareness of the rationale for planning was only evident in parous women or those who had actively sought pre-pregnancy advice. Within each group, there was uncertainty about what pre-pregnancy advice entailed. Despite many women reporting positive healthcare experiences, frequently cited barriers to discussing issues around family planning included unsupportive staff, busy clinics and perceived social stereotypes held by health professionals.

Conclusions: Knowledge and attitudes reported in this study highlight the need for women with diabetes, regardless of age, marital status or type of diabetes, to receive guidance about planning pregnancy in a motivating, positive and supportive manner. The important patient viewpoints expressed in this study may help health professionals determine how best to encourage women to avail of pre-pregnancy care