The precursors and impacts of BSR on AMT acquisition and implementation

This paper reports on the results of research into the connections between transaction attributes and buyer-supplier relationships (BSRs) in advanced manufacturing technology (AMT) acquisition and implementation. The investigation began by examining the impact of the different patterns of BSR on the performance of the AMT acquisition. In understanding the phenomena, the study drew upon and integrated the literature of transaction cost economics theory, BSRs, and AMT, and used this as the basis for a theoretical framework and hypotheses development. This framework was then empirically tested using data that were gathered through a questionnaire survey with 147 companies and analyzed using a structural equation modeling technique. The results of the analysis indicated that the higher the level of technological specificity and uncertainty, the more firms are likely to engage in a stronger relationship with technology suppliers. However, the complexity of the technology being implemented was associated with BSR only indirectly through its association with the level of uncertainty (which has a direct impact upon BSR). The analysis also provided strong support for the premise that developing strong BSR could lead to an improved performance in acquiring and implementing AMT. The implications of the study are offered for both the academic and practitioner audience.

Negative brand personality:the construct, its antecedents and outcome variables

By evolving brands and building on the importance of self-expression, Aaker (1997) developed the brand personality framework as a means to understand brand-consumer relationships. The brand personality framework captures the core values and characteristics described in human personality research in an attempt to humanize brands. Although influential across many streams of brand personality research, the current conceptualization of brand personality only offers a positively-framed approach. To date, no research, both conceptually and empirically, has thoroughly incorporated factors reflective of Negative Brand Personality, despite the fact that almost all researchers in personality are in agreement that factors akin to Extraversion (positive) and Neuroticism (negative) should be in a comprehensive personality scale to accommodate consumers’ expressions. As a result, the study of brand personality is only half complete since the current research trend is to position brand personality under brand image. However, with the brand personality concept being confused with brand identity at the empirical stage, factors reflective of Negative Brand Personality have been neglected. Accordingly, this thesis extends the current conceptualization of brand personality by demarcating the existing typologies of desirable brand personality and incorporating the characteristics reflective of consumers’ discrepant self-meaning to provide a more complete understanding of brand personality. However, it is not enough to interpret negative factors as the absence of positive factors. Negative factors reflect consumers’ anxious and frustrated feelings. Therefore, this thesis contributes to the current conceptualization of brand personality by, firstly, presenting a conceptual definition of Negative Brand Personality in order to provide a theoretical basis for the development of a Negative Brand Personality scale, then, secondly, identifying what constitutes Negative Brand Personality and to what extent consumers’ cognitive dissonance explains the nature of Negative Brand Personality, and, thirdly, ascertaining the impact Negative Brand Personality has on attitudinal constructs, namely: Negative Attitude, Detachment, Brand Loyalty and Satisfaction, which have proven to predict behaviors such as choice and (re-)purchasing. In order to deliver on the three main contributions, two comprehensive studies were conducted to a) develop a valid, parsimonious, yet relatively short measure of Negative Brand Personality, and b) ascertain how the Negative Brand Personality measure behaves within a network of related constructs. The mixed methods approach, grounded in theoretical and empirical development, provides evidence to suggest that there are four factors to Negative Brand Personality and, tested through use of a structural equation modeling technique, that these are influenced by Brand Confusion, Price Unfairness, Self- Incongruence and Corporate Hypocrisy. Negative Brand Personality factors mainly determined Consumers Negative Attitudes and Brand Detachment. The research contributes to the literature on brand personality by improving the consumer-brand relationship by means of engaging in a brandconsumer conversation in order to reduce consumers’ cognitive strain. The study concludes with a discussion on the theoretical and practical implications of the findings, its limitations, and potential directions for future research.

Modeling the peptide-T cell receptor interaction by the comparative molecular similarity indices analysis-soft independent modeling of class analogy technique

A set of 38 epitopes and 183 non-epitopes, which bind to alleles of the HLA-A3 supertype, was subjected to a combination of comparative molecular similarity indices analysis (CoMSIA) and soft independent modeling of class analogy (SIMCA). During the process of T cell recognition, T cell receptors (TCR) interact with the central section of the bound nonamer peptide; thus only positions 4−8 were considered in the study. The derived model distinguished 82% of the epitopes and 73% of the non-epitopes after cross-validation in five groups. The overall preference from the model is for polar amino acids with high electron density and the ability to form hydrogen bonds. These so-called “aggressive” amino acids are flanked by small-sized residues, which enable such residues to protrude from the binding cleft and take an active role in TCR-mediated T cell recognition. Combinations of “aggressive” and “passive” amino acids in the middle part of epitopes constitute a putative TCR binding motif

Three-dimensional modeling of the human eye based on magnetic resonance imaging

PURPOSE. A methodology for noninvasively characterizing the three-dimensional (3-D) shape of the complete human eye is not currently available for research into ocular diseases that have a structural substrate, such as myopia. A novel application of a magnetic resonance imaging (MRI) acquisition and analysis technique is presented that, for the first time, allows the 3-D shape of the eye to be investigated fully. METHODS. The technique involves the acquisition of a T2-weighted MRI, which is optimized to reveal the fluid-filled chambers of the eye. Automatic segmentation and meshing algorithms generate a 3-D surface model, which can be shaded with morphologic parameters such as distance from the posterior corneal pole and deviation from sphericity. Full details of the method are illustrated with data from 14 eyes of seven individuals. The spatial accuracy of the calculated models is demonstrated by comparing the MRI-derived axial lengths with values measured in the same eyes using interferometry. RESULTS. The color-coded eye models showed substantial variation in the absolute size of the 14 eyes. Variations in the sphericity of the eyes were also evident, with some appearing approximately spherical whereas others were clearly oblate and one was slightly prolate. Nasal-temporal asymmetries were noted in some subjects. CONCLUSIONS. The MRI acquisition and analysis technique allows a novel way of examining 3-D ocular shape. The ability to stratify and analyze eye shape, ocular volume, and sphericity will further extend the understanding of which specific biometric parameters predispose emmetropic children subsequently to develop myopia. Copyright © Association for Research in Vision and Ophthalmology.

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).