The strategic role of relational capabilities in the business-to-business service profit chain

This paper extends the original service profit chain by examining the role of relational capabilities with employees, customers and strategic partners on process and performance outcomes in a business-to-business context. More specifically, we demonstrate how satisfied and loyal employees are better in developing relationships with customers and strategic partners. These relationships enable firms to be more responsive towards customers and become more innovative, which increase customer satisfaction and loyalty and, ultimately, financial performance. Our results provide support for the development of relational capabilities in a business-to-business environment by extending the service profit chain (SPC) model. However, we find that while the development of strong customer relationships contributes to an improved service responsiveness of the firm, strategic partners do not.

Self-association of calcium-binding protein S100A4 and metastasis

Elevated levels of the calcium-binding protein S100A4 promote metastasis and in carcinoma cells are associated with reduced survival of cancer patients. S100A4 interacts with target proteins that affect a number of activities associated with metastatic cells. However, it is not known how many of these interactions are required for S100A4-promoted metastasis, thus hampering the design of specific inhibitors of S100A4-induced metastasis. Intracellular S100A4 exists as a homodimer through previously identified, well conserved, predominantly hydrophobic key contacts between the subunits. Here it is shown that mutating just one key residue, phenylalanine 72, to alanine is sufficient to reduce the metastasis-promoting activity of S100A4 to 50% that of the wild type protein, and just 2 or 3 specific mutations reduces the metastasis-promoting activity of S100A4 to less than 20% that of the wild type protein. These mutations inhibit the self-association of S100A4 in vivo and reduce markedly the affinity of S100A4 for at least two of its protein targets, a recombinant fragment of non-muscle myosin heavy chain isoform A, and p53. Inhibition of the self-association of S100 proteins might be a novel means of inhibiting their metastasis-promoting activities.

Composite materials impact damage detection using neural networks

This thesis considers two basic aspects of impact damage in composite materials, namely damage severity discrimination and impact damage location by using Acoustic Emissions (AE) and Artificial Neural Networks (ANNs). The experimental work embodies a study of such factors as the application of AE as Non-destructive Damage Testing (NDT), and the evaluation of ANNs modelling. ANNs, however, played an important role in modelling implementation. In the first aspect of the study, different impact energies were used to produce different level of damage in two composite materials (T300/914 and T800/5245). The impacts were detected by their acoustic emissions (AE). The AE waveform signals were analysed and modelled using a Back Propagation (BP) neural network model. The Mean Square Error (MSE) from the output was then used as a damage indicator in the damage severity discrimination study. To evaluate the ANN model, a comparison was made of the correlation coefficients of different parameters, such as MSE, AE energy, AE counts, etc. MSE produced an outstanding result based on the best performance of correlation. In the second aspect, a new artificial neural network model was developed to provide impact damage location on a quasi-isotropic composite panel. It was successfully trained to locate impact sites by correlating the relationship between arriving time differences of AE signals at transducers located on the panel and the impact site coordinates. The performance of the ANN model, which was evaluated by calculating the distance deviation between model output and real location coordinates, supports the application of ANN as an impact damage location identifier. In the study, the accuracy of location prediction decreased when approaching the central area of the panel. Further investigation indicated that this is due to the small arrival time differences, which defect the performance of ANN prediction. This research suggested increasing the number of processing neurons in the ANNs as a practical solution.

A Bayesian perspective on stochastic neurocontrol

Control design for stochastic uncertain nonlinear systems is traditionally based on minimizing the expected value of a suitably chosen loss function. Moreover, most control methods usually assume the certainty equivalence principle to simplify the problem and make it computationally tractable. We offer an improved probabilistic framework which is not constrained by these previous assumptions, and provides a more natural framework for incorporating and dealing with uncertainty. The focus of this paper is on developing this framework to obtain an optimal control law strategy using a fully probabilistic approach for information extraction from process data, which does not require detailed knowledge of system dynamics. Moreover, the proposed control method framework allows handling the problem of input-dependent noise. A basic paradigm is proposed and the resulting algorithm is discussed. The proposed probabilistic control method is for the general nonlinear class of discrete-time systems. It is demonstrated theoretically on the affine class. A nonlinear simulation example is also provided to validate theoretical development.

Novel glucagon-like peptide-1 (GLP-1) analog (Val8)GLP-1 results in significant improvements of glucose tolerance and pancreatic β-cell function after 3-week daily administration in obese diabetic (ob/ob) mice

This study evaluates the antidiabetic potential of an enzyme-resistant analog, (Val8)GLP-1. The effects of daily administration of a novel dipeptidyl peptidase IV-resistant glucagon-like peptide-1 (GLP-1) analog, (Val8)GLP-1, on glucose tolerance and pancreatic β-cell function were examined in obese-diabetic (ob/ob) mice. Acute intraperitoneal administration of (Val8)GLP-1 (6.25-25 nmol/kg) with glucose increased the insulin response and reduced the glycemic excursion in a dose-dependent manner. The effects of (Val8)GLP-1 were greater and longer lasting than native GLP-1. Once-daily subcutaneous administration of (Val8)GLP-1 (25 nmol/kg) for 21 days reduced plasma glucose concentrations, increased plasma insulin, and reduced body weight more than native GLP-1 without a significant change in daily food intake. Furthermore, (Val8)GLP-1 improved glucose tolerance, reduced the glycemic excursion after feeding, increased the plasma insulin response to glucose and feeding, and improved insulin sensitivity. These effects were consistently greater with (Val8)GLP-1 than with native GLP-1, and both peptides retained or increased their acute efficacy compared with initial administration. (Val8)GLP-1 treatment increased average islet area 1.2-fold without changing the number of islets, resulting in an increased number of larger islets. These data demonstrate that (Val8)GLP-1 is more effective and longer acting than native GLP-1 in obese-diabetic ob/ob mice.

Effects of substituents in polyvinylcarbazole structures on their optical properties

Absorption, photoluminescence, and photoluminescence excitation spectra of solutions and thin films of N-vinylcarbazole polymers and copolymers with various substituents directly on the carbazole moiety and on the polymer chain were studied comprehensively. Polymers that were used previously to develop polymer composites with polymethine dyes having photosensitivity over a broad spectral range including the visible and near-IR regions were selected for the studies.