Description and critical appraisal of principal components analysis (PCA) methodology applied to pulsed-field gel electrophoresis profiles of methicillin-resistant Staphylococcus aureus isolates

Principal components analysis (PCA) has been described for over 50 years; however, it is rarely applied to the analysis of epidemiological data. In this study PCA was critically appraised in its ability to reveal relationships between pulsed-field gel electrophoresis (PFGE) profiles of methicillin- resistant Staphylococcus aureus (MRSA) in comparison to the more commonly employed cluster analysis and representation by dendrograms. The PFGE type following SmaI chromosomal digest was determined for 44 multidrug-resistant hospital-acquired methicillin-resistant S. aureus (MR-HA-MRSA) isolates, two multidrug-resistant community-acquired MRSA (MR-CA-MRSA), 50 hospital-acquired MRSA (HA-MRSA) isolates (from the University Hospital Birmingham, NHS Trust, UK) and 34 community-acquired MRSA (CA-MRSA) isolates (from general practitioners in Birmingham, UK). Strain relatedness was determined using Dice band-matching with UPGMA clustering and PCA. The results indicated that PCA revealed relationships between MRSA strains, which were more strongly correlated with known epidemiology, most likely because, unlike cluster analysis, PCA does not have the constraint of generating a hierarchic classification. In addition, PCA provides the opportunity for further analysis to identify key polymorphic bands within complex genotypic profiles, which is not always possible with dendrograms. Here we provide a detailed description of a PCA method for the analysis of PFGE profiles to complement further the epidemiological study of infectious disease. © 2005 Elsevier B.V. All rights reserved.

An evaluation of Home Office extended interviews for police personnel

In this thesis the validity of an Assessment Centre (called 'Extended Interview') operated on behalf of the British police is investigated. This Assessment Centre (AC) is used to select from amongst internal candidates (serving policemen and policewomen) and external candidates (graduates) for places on an accelerated promotion scheme. The literature is reviewed with respect to history, content, structure, reliability, validity, efficiency and usefulness of ACs, and to contextual issues surrounding AC use. The history of, background to and content of police Extended Interviews (Els) is described, and research issues are identified. Internal validation involved regression of overall EI grades on measures from component tests, exercises, interviews and peer nominations. Four samples numbering 126, 73, 86 and 109 were used in this part of the research. External validation involved regression of three types of criteria - training grades, rank attained, and supervisory ratings - on all EI measures. Follow-up periods for job criteria ranged from 7 to 19 years. Three samples, numbering 223, 157 and 86, were used in this part of the research. In subsidiary investigations, supervisory ratings were factor analysed and criteria intercorrelated. For two of the samples involved in the external validition, clinical/judgemental prediction was compared with mechanical (unit-weighted composite) prediction. Main conclusions are that: (1) EI selection decisions were valid, but only for a job performance criterion; relatively low validity overall was interpreted principally in terms of the questionable job relatedness of the EI procedure; (2) Els as a whole had more validity than was reflected in final EI decisions; (3) assessors' use of information was not optimum, tending to over-emphasize subjectively derived information particularly from interviews; and (4) mechanical prediction was superior to clinical/judgemental prediction for five major criteria.

Determinants of sponsorship fit:a multilevel analysis

Sponsorship fit is frequently mentioned and empirically examined as a success factor of sponsorship. While sponsorship fit has been considered as a determinant of sponsorship success, little knowledge exists about the antecedents of sponsorship fit. In the present paper, individual and firm-level antecedents of sponsorship fit are examined in a single hierarchical linear model. Results show that sponsorship fit is influenced by the perception of benefits, the firm’s regional identification, sincerity, relatedness to the sponsored activity, and its dominance. On a partnership level, results show that contract length contributes to sponsorship fit while contract value is found to be unrelated.

LRD : Latent Relation Discovery for vector space expansion and information retrieval

In this paper, we propose a text mining method called LRD (latent relation discovery), which extends the traditional vector space model of document representation in order to improve information retrieval (IR) on documents and document clustering. Our LRD method extracts terms and entities, such as person, organization, or project names, and discovers relationships between them by taking into account their co-occurrence in textual corpora. Given a target entity, LRD discovers other entities closely related to the target effectively and efficiently. With respect to such relatedness, a measure of relation strength between entities is defined. LRD uses relation strength to enhance the vector space model, and uses the enhanced vector space model for query based IR on documents and clustering documents in order to discover complex relationships among terms and entities. Our experiments on a standard dataset for query based IR shows that our LRD method performed significantly better than traditional vector space model and other five standard statistical methods for vector expansion.

A framework for automated construction of resource space based on background knowledge

Resource Space Model is a kind of data model which can effectively and flexibly manage the digital resources in cyber-physical system from multidimensional and hierarchical perspectives. This paper focuses on constructing resource space automatically. We propose a framework that organizes a set of digital resources according to different semantic dimensions combining human background knowledge in WordNet and Wikipedia. The construction process includes four steps: extracting candidate keywords, building semantic graphs, detecting semantic communities and generating resource space. An unsupervised statistical language topic model (i.e., Latent Dirichlet Allocation) is applied to extract candidate keywords of the facets. To better interpret meanings of the facets found by LDA, we map the keywords to Wikipedia concepts, calculate word relatedness using WordNet's noun synsets and construct corresponding semantic graphs. Moreover, semantic communities are identified by GN algorithm. After extracting candidate axes based on Wikipedia concept hierarchy, the final axes of resource space are sorted and picked out through three different ranking strategies. The experimental results demonstrate that the proposed framework can organize resources automatically and effectively.©2013 Published by Elsevier Ltd. All rights reserved.

Health and population effects of rare gene knockouts in adult humans with related parents

Examining complete gene knockouts within a viable organism can inform on gene function. We sequenced the exomes of 3222 British Pakistani-heritage adults with high parental relatedness, discovering 1111 rare-variant homozygous genotypes with predicted loss of gene function (knockouts) in 781 genes. We observed 13.7% fewer than expected homozygous knockout genotypes, implying an average load of 1.6 recessive-lethal-equivalent LOF variants per adult. Linking genetic data to lifelong health records, knockouts were not associated with clinical consultation or prescription rate. In this dataset we identified a healthy PRDM9 knockout mother, and performed phased genome sequencing on her, her child and controls, which showed meiotic recombination sites localized away from PRDM9-dependent hotspots. Thus, natural LOF variants inform upon essential genetic loci, and demonstrate PRDM9 redundancy in humans.

Ownership control of foreign affiliates:a property rights theory perspective

This paper applies property rights theory to explain changes in foreign affiliates’ ownership. Post-entry ownership change is driven by both firm-level characteristics and by the differences in the institutional environments in host countries. We distinguish between financial market development and the level of corruption as two different institutional dimensions, such that changes along these dimensions impact upon ownership change in different ways. Furthermore, we argue that changes in ownership are affected by the foreign affiliate’s relatedness with its parent’s sector, as well as by the affiliate’s maturity. We use firm level data across 125 host countries to test our hypotheses.