Improved Process Monitoring Using Nonlinear Principal Component Models

This paper presents two new approaches for use in complete process monitoring. The firstconcerns the identification of nonlinear principal component models. This involves the application of linear
principal component analysis (PCA), prior to the identification of a modified autoassociative neural network (AAN) as the required nonlinear PCA (NLPCA) model. The benefits are that (i) the number of the reduced set of linear principal components (PCs) is smaller than the number of recorded process variables, and (ii) the set of PCs is better conditioned as redundant information is removed. The result is a new set of input data for a modified neural representation, referred to as a T2T network. The T2T NLPCA model is then used for complete process monitoring, involving fault detection, identification and isolation. The second approach introduces a new variable reconstruction algorithm, developed from the T2T NLPCA model. Variable reconstruction can enhance the findings of the contribution charts still widely used in industry by reconstructing the outputs from faulty sensors to produce more accurate fault isolation. These ideas are illustrated using recorded industrial data relating to developing cracks in an industrial glass melter process. A comparison of linear and nonlinear models, together with the combined use of contribution charts and variable reconstruction, is presented.

The Rhetorical Construction of Corporate Logos

This research is set in the context of today’s societies, in which the corporate visual symbology of a business, corporation or institution constitutes an essential way to transmit its corporate image. Traditional discursive procedures can be discovered in the development of these signs. The rhetorical strategies developed by the great classical authors appear in the logo-symbols expressing the corporate values of today’s companies. Thus, rhetoric is emerging once again in the sense it had many centuries ago: A repertory of rules that, paradoxically, standardizes the deviations of language and whose control is synonymous with power. The main objective of this study is to substantiate the rhetorical construction of logos using as a model of analysis the classical process of creating discourse. This involves understanding logos as persuasive discourses addressed to a modern audience. Our findings show that the rhetorical paradigm can be considered as a creative model for the con­struction of an original logo consistent with a company’s image.

An exploratory study of Principal Investigator roles in UK University Proof-of-Concept processes: an Absorptive capacity perspective

The increasing emphasis on academic entrepreneurship, technology transfer and research commercialisation within UK universities is predicated on basic research being developed by academics into commercial entities such as university spin-off companies or licensing arrangements. However, this process is fraught with challenges and risks, given the degree of uncertainty regarding future returns. In an attempt to minimise such risks, the Proof-of-Concept (PoC) process has been developed within University Science Park Incubators (USIs) to test the technological, business and market potential of embryonic technology. The key or the pivotal stakeholder within the PoC is the Principal Investigator (PI), who is usually the lead academic responsible for the embryonic technology. Within the current literature, there appears to be a lack of research pertaining to the role of the PI in the PoC process. Moreover, Absorptive Capacity (ACAP) has emerged within the literature as a theoretical framework or lens for exploring the development and application of new knowledge and technology, where the USI is the organisation considered in the current study. Therefore, the aim of this paper is to explore the role and influence of the PI in the PoC process within a USI setting using an ACAP perspective. The research involved a multiple case analysis of PoC applications within a UK university USI. The results demonstrate the role of the PI in developing practices and routines within the PoC process. These practices and processes were initially tacit and informal in nature but became more explicit and formal over time so that knowledge was retained within the USI after the PIs had completed the PoC process. © 2010 The Authors. R&D Management © 2010 Blackwell Publishing Ltd.

Molecular dynamics and principal components analysis of human telomeric quadruplex multimers.

Guanine-rich DNA repeat sequences located at the terminal ends of chromosomal DNA can fold in a sequence-dependent manner into G-quadruplex structures, notably the terminal 150–200 nucleotides at the 3' end, which occur as a single-stranded DNA overhang. The crystal structures of quadruplexes with two and four human telomeric repeats show an all-parallel-stranded topology that is readily capable of forming extended stacks of such quadruplex structures, with external TTA loops positioned to potentially interact with other macromolecules. This study reports on possible arrangements for these quadruplex dimers and tetramers, which can be formed from 8 or 16 telomeric DNA repeats, and on a methodology for modeling their interactions with small molecules. A series of computational methods including molecular dynamics, free energy calculations, and principal components analysis have been used to characterize the properties of these higher-order G-quadruplex dimers and tetramers with parallel-stranded topology. The results confirm the stability of the central G-tetrads, the individual quadruplexes, and the resulting multimers. Principal components analysis has been carried out to highlight the dominant motions in these G-quadruplex dimer and multimer structures. The TTA loop is the most flexible part of the model and the overall multimer quadruplex becoming more stable with the addition of further G-tetrads. The addition of a ligand to the model confirms the hypothesis that flat planar chromophores stabilize G-quadruplex structures by making them less flexible.

VEIDase is a principal caspase-like activity involved in plant programmed cell death and essential for embryonic pattern formation

Plant embryogenesis is intimately associated with programmed cell death. The mechanisms of initiation and control of programmed cell death during plant embryo development are not known. Proteolytic activity associated with caspase-like proteins is paramount for control of programmed cell death in animals and yeasts. Caspase family of proteases has unique strong preference for cleavage of the target proteins next to asparagine residue. In this work, we have used synthetic peptide substrates containing caspase recognition sites and corresponding specific inhibitors to analyse the role of caspase-like activity in the regulation of programmed cell death during plant embryogenesis. We demonstrate that VEIDase is a principal caspase-like activity implicated in plant embryogenesis. This activity increases at the early stages of embryo development that coincide with massive cell death during shape remodeling. The VEIDase activity exhibits high sensitivity to pH, ionic strength and Zn2+ concentration. Altogether, biochemical assays show that VEIDase plant caspase-like activity resembles that of both mammalian caspase-6 and yeast metacaspase, YCA1. In vivo, VEIDase activity is localised specifically in the embryonic cells during both the commitment and in the beginning of the execution phase of programmed cell death. Inhibition of VEIDase prevents normal embryo development via blocking the embryo-suspensor differentiation. Our data indicate that the VEIDase activity is an integral part in the control of plant developmental cell death programme, and that this activity is essential for the embryo pattern formation.

Improved principal component monitoring using the local approach

This paper shows that current multivariate statistical monitoring technology may not detect incipient changes in the variable covariance structure nor changes in the geometry of the underlying variable decomposition. To overcome these deficiencies, the local approach is incorporated into the multivariate statistical monitoring framework to define two new univariate statistics for fault detection. Fault isolation is achieved by constructing a fault diagnosis chart which reveals changes in the covariance structure resulting from the presence of a fault. A theoretical analysis is presented and the proposed monitoring approach is exemplified using application studies involving recorded data from two complex industrial processes. © 2007 Elsevier Ltd. All rights reserved.

A New Principal Curve Algorithm for Nonlinear Principal Component Analysis

This paper emerged from work supported by EPSRC grant GR/S84354/01 and proposes a method of determining principal curves, using spline functions, in principal component analysis (PCA) for the representation of non-linear behaviour in process monitoring. Although principal curves are well established, they are difficult to implement in practice if a large number of variables are analysed. The significant contribution of this paper is that the proposed method has minimal complexity, assuming simple spline geometry, thus enabling efficient computation. The paper provides a foundation for further work where multiple curves may be required to represent underlying non-linear information in complex data.