Development of a near activity visual questionnaire to assess accommodating intraocular lenses

Purpose: To develop a questionnaire that subjectively assesses near visual function in patients with 'accommodating' intraocular lenses (IOLs). Methods: A literature search of existing vision-related quality-of-life instruments identified all questions relating to near visual tasks. Questions were combined if repeated in multiple instruments. Further relevant questions were added and item interpretation confirmed through multidisciplinary consultation and focus groups. A preliminary 19-item questionnaire was presented to 22 subjects at their 4-week visit post first eye phacoemulsification with 'accommodative' IOL implantation, and again 6 and 12 weeks post-operatively. Rasch Analysis, Frequency of Endorsement, and tests of normality (skew and kurtosis) were used to reduce the instrument. Cronbach's alpha and test-retest reliability (intraclass correlation coefficient, ICC) were determined for the final questionnaire. Construct validity was obtained by Pearson's product moment correlation (PPMC) of questionnaire scores to reading acuity (RA) and to Critical Print Size (CPS) reading speed. Criterion validity was obtained by receiver operating characteristic (ROC) curve analysis and dimensionality of the questionnaire was assessed by factor analysis. Results: Rasch Analysis eliminated nine items due to poor fit statistics. The final items have good separation (2.55), internal consistency (Cronbach's α = 0.97) and test-retest reliability (ICC = 0.66). PPMC of questionnaire scores with RA was 0.33, and with CPS reading speed was 0.08. Area under the ROC curve was 0.88 and Factor Analysis revealed one principal factor. Conclusion: The pilot data indicates the questionnaire to be internally consistent, reliable and a valid instrument that could be useful for assessing near visual function in patients with 'accommodating' IOLS. The questionnaire will now be expanded to include other types of presbyopic correction. © 2007 British Contact Lens Association.

An efficient tagging data interpretation and representation scheme for item recommendation

A tag-based item recommendation method generates an ordered list of items, likely interesting to a particular user, using the users past tagging behaviour. However, the users tagging behaviour varies in different tagging systems. A potential problem in generating quality recommendation is how to build user profiles, that interprets user behaviour to be effectively used, in recommendation models. Generally, the recommendation methods are made to work with specific types of user profiles, and may not work well with different datasets. In this paper, we investigate several tagging data interpretation and representation schemes that can lead to building an effective user profile. We discuss the various benefits a scheme brings to a recommendation method by highlighting the representative features of user tagging behaviours on a specific dataset. Empirical analysis shows that each interpretation scheme forms a distinct data representation which eventually affects the recommendation result. Results on various datasets show that an interpretation scheme should be selected based on the dominant usage in the tagging data (i.e. either higher amount of tags or higher amount of items present). The usage represents the characteristic of user tagging behaviour in the system. The results also demonstrate how the scheme is able to address the cold-start user problem.

The BRICS and R2P : contestation, re-interpretation and norm entrepreneurship

The intra-state humanitarian crises in Libya and Syria have led to renewed debate over the content and implementation of pillar three of the responsibility to protect (R2P). This paper examines the BRICS’ (Brazil, Russia, India, China, South Africa) current perspectives on R2P and their recent efforts to shape the concept’s evolution. While Brazil’s “Responsibility while Protecting” (RwP) proposal has been widely discussed, the central focus here is on the lesser-known, semi-official Chinese idea of “Responsible Protection” (RP). Like RwP, RP proposes decision-making criteria and accountability mechanisms for UN-authorised military intervention under R2P’s third pillar. This paper argues that although RP draws heavily on previous R2P proposals such as the original 2001 ICISS report and Brazil’s RwP, by amalgamating and re-packaging these earlier ideas in a more restrictive form the Chinese initiative represents a new and distinctive interpretation of R2P. However, as it currently stands, some aspects of RP appear to be framed too strictly to provide workable guidelines for determining the permissibility of R2P military intervention, and would, therefore, benefit from clarification and refinement. Of broader significance, China’s RP and Brazil’s RwP initiatives point to the growing willingness of rising, non-Western powers to articulate and promote their own normative preferences on sovereignty, intervention and global governance. This development has potential implications both for R2P’s evolution and for the structure of the international system.

A Statutory interpretation EXperience : putting the SEX into statutory interpretation

With the growing proliferation of statute laws, the skill of statutory interpretation is an increasingly important aspect of legal practice. Despite the importance, statutory interpretation can be a challenging area of law to teach to undergraduate law students, who may find the topic dry and disengaging when taught through traditional methods. Such disengagement may adversely affect knowledge retention, particularly if the material is taught in the first or second year of study and not explicitly reinforced in subsequent years. Concern over the present standard of statutory interpretation skills being exhibited by practitioners, has prompted the Chief Justice of the Supreme Court of Queensland to contact law schools, enquiring how and to what extent statutory interpretation is being taught...

Do-Rank: DCG optimization for learning-to-rank in tag-based item recommendation systems

Discounted Cumulative Gain (DCG) is a well-known ranking evaluation measure for models built with multiple relevance graded data. By handling tagging data used in recommendation systems as an ordinal relevance set of {negative,null,positive}, we propose to build a DCG based recommendation model. We present an efficient and novel learning-to-rank method by optimizing DCG for a recommendation model using the tagging data interpretation scheme. Evaluating the proposed method on real-world datasets, we demonstrate that the method is scalable and outperforms the benchmarking methods by generating a quality top-N item recommendation list.