Reading skills are related to global, but not local, acoustic pattern perception

Although reading ability has been related to the processing of simple pitch features such as isolated transitions or continuous modulation spoken language also contains complex patterns of pitch changes that are important for establishing stress location and for segmenting the speech stream. These aspects of spoken language processing depend critically on pitch pattern (global structure) rather than on absolute pitch values (local structure). Here we show that the detection of global structure, and not local structure, is predictive of performance on measures of phonological skill and reading ability, which supports a critical importance of pitch contour processing in the acquisition of literacy.

Design determines 70% of cost? A review of implications for design evaluation

This paper disputes the fact that product design determines 70% of costs and the implications that follow for design evaluation tools. Using the idea of decision chains, it is argued that such tools need to consider more of the downstream business activities and should take into account the current and future state of the business rather than some idealized view of it. To illustrate the argument, a series of experiments using an enterprise simulator are described that show the benefit from the application of a more holistic 'design for' technique. Design For the Existing Environment.

Evaluating design implementation strategies using enterprise simulation

Concurrent engineering and design for manufacture and assembly strategies have become pervasive in use in a wide array of industrial settings. These strategies have generally focused on product and process design issues based on capability concerns. The strategies have been historically justified using cost savings calculations focusing on easily quantifiable costs such as raw material savings or manufacturing or assembly operations no longer required. It is argued herein that neither the focus of the strategies nor the means of justification are adequate. Product and process design strategies should include both capability and capacity concerns and justification procedures should include the financial effects that the product and process changes would have on the entire company. The authors of this paper take this more holistic view of the problem and examine an innovative new design strategy using a comprehensive enterprise simulation tool. The results indicate that both the design strategy and the simulator show promise for further industrial use. © 2001 Elsevier Science B.V. All rights reserved.

Toward bacterial protein sub-cellular location prediction:single-class discrimminant models for all gram- and gram+ compartments

Based on Bayesian Networks, methods were created that address protein sequence-based bacterial subcellular location prediction. Distinct predictive algorithms for the eight bacterial subcellular locations were created. Several variant methods were explored. These variations included differences in the number of residues considered within the query sequence - which ranged from the N-terminal 10 residues to the whole sequence - and residue representation - which took the form of amino acid composition, percentage amino acid composition, or normalised amino acid composition. The accuracies of the best performing networks were then compared to PSORTB. All individual location methods outperform PSORTB except for the Gram+ cytoplasmic protein predictor, for which accuracies were essentially equal, and for outer membrane protein prediction, where PSORTB outperforms the binary predictor. The method described here is an important new approach to method development for subcellular location prediction. It is also a new, potentially valuable tool for candidate subunit vaccine selection.

TATPred:a Bayesian method for the identification of twin arginine translocation pathway signal sequences

The twin arginine translocation (TAT) system ferries folded proteins across the bacterial membrane. Proteins are directed into this system by the TAT signal peptide present at the amino terminus of the precursor protein, which contains the twin arginine residues that give the system its name. There are currently only two computational methods for the prediction of TAT translocated proteins from sequence. Both methods have limitations that make the creation of a new algorithm for TAT-translocated protein prediction desirable. We have developed TATPred, a new sequence-model method, based on a Nave-Bayesian network, for the prediction of TAT signal peptides. In this approach, a comprehensive range of models was tested to identify the most reliable and robust predictor. The best model comprised 12 residues: three residues prior to the twin arginines and the seven residues that follow them. We found a prediction sensitivity of 0.979 and a specificity of 0.942.

A predictor of membrane class:discriminating α-helical and β-barrel membrane proteins from non-membranous proteins

Accurate protein structure prediction remains an active objective of research in bioinformatics. Membrane proteins comprise approximately 20% of most genomes. They are, however, poorly tractable targets of experimental structure determination. Their analysis using bioinformatics thus makes an important contribution to their on-going study. Using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we have addressed the alignment-free discrimination of membrane from non-membrane proteins. The method successfully identifies prokaryotic and eukaryotic α-helical membrane proteins at 94.4% accuracy, β-barrel proteins at 72.4% accuracy, and distinguishes assorted non-membranous proteins with 85.9% accuracy. The method here is an important potential advance in the computational analysis of membrane protein structure. It represents a useful tool for the characterisation of membrane proteins with a wide variety of potential applications.

Alpha helical trans-membrane proteins:enhanced prediction using a Bayesian approach

Membrane proteins, which constitute approximately 20% of most genomes, are poorly tractable targets for experimental structure determination, thus analysis by prediction and modelling makes an important contribution to their on-going study. Membrane proteins form two main classes: alpha helical and beta barrel trans-membrane proteins. By using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we addressed alpha-helical topology prediction. This method has accuracies of 77.4% for prokaryotic proteins and 61.4% for eukaryotic proteins. The method described here represents an important advance in the computational determination of membrane protein topology and offers a useful, and complementary, tool for the analysis of membrane proteins for a range of applications.

Beta barrel trans-membrane proteins:enhanced prediction using a Bayesian approach

Membrane proteins, which constitute approximately 20% of most genomes, form two main classes: alpha helical and beta barrel transmembrane proteins. Using methods based on Bayesian Networks, a powerful approach for statistical inference, we have sought to address beta-barrel topology prediction. The beta-barrel topology predictor reports individual strand accuracies of 88.6%. The method outlined here represents a potentially important advance in the computational determination of membrane protein topology.

Combining algorithms to predict bacterial protein sub-cellular location:parallel versus concurrent implementations

We describe a novel and potentially important tool for candidate subunit vaccine selection through in silico reverse-vaccinology. A set of Bayesian networks able to make individual predictions for specific subcellular locations is implemented in three pipelines with different architectures: a parallel implementation with a confidence level-based decision engine and two serial implementations with a hierarchical decision structure, one initially rooted by prediction between membrane types and another rooted by soluble versus membrane prediction. The parallel pipeline outperformed the serial pipeline, but took twice as long to execute. The soluble-rooted serial pipeline outperformed the membrane-rooted predictor. Assessment using genomic test sets was more equivocal, as many more predictions are made by the parallel pipeline, yet the serial pipeline identifies 22 more of the 74 proteins of known location.

Multi-class subcellular location prediction for bacterial proteins

Two algorithms, based onBayesian Networks (BNs), for bacterial subcellular location prediction, are explored in this paper: one predicts all locations for Gram+ bacteria and the other all locations for Gram- bacteria. Methods were evaluated using different numbers of residues (from the N-terminal 10 residues to the whole sequence) and residue representation (amino acid-composition, percentage amino acid-composition or normalised amino acid-composition). The accuracy of the best resulting BN was compared to PSORTB. The accuracy of this multi-location BN was roughly comparable to PSORTB; the difference in predictions is low, often less than 2%. The BN method thus represents both an important new avenue of methodological development for subcellular location prediction and a potentially value new tool of true utilitarian value for candidate subunit vaccine selection.

LIPPRED:a web server for accurate prediction of lipoprotein signal sequences and cleavage sites

Bacterial lipoproteins have many important functions and represent a class of possible vaccine candidates. The prediction of lipoproteins from sequence is thus an important task for computational vaccinology. Naïve-Bayesian networks were trained to identify SpaseII cleavage sites and their preceding signal sequences using a set of 199 distinct lipoprotein sequences. A comprehensive range of sequence models was used to identify the best model for lipoprotein signal sequences. The best performing sequence model was found to be 10-residues in length, including the conserved cysteine lipid attachment site and the nine residues prior to it. The sensitivity of prediction for LipPred was 0.979, while the specificity was 0.742. Here, we describe LipPred, a web server for lipoprotein prediction; available at the URL: http://www.jenner.ac.uk/LipPred/. LipPred is the most accurate method available for the detection of SpaseIIcleaved lipoprotein signal sequences and the prediction of their cleavage sites.

BPROMPT:a consensus server for membrane protein prediction

Protein structure prediction is a cornerstone of bioinformatics research. Membrane proteins require their own prediction methods due to their intrinsically different composition. A variety of tools exist for topology prediction of membrane proteins, many of them available on the Internet. The server described in this paper, BPROMPT (Bayesian PRediction Of Membrane Protein Topology), uses a Bayesian Belief Network to combine the results of other prediction methods, providing a more accurate consensus prediction. Topology predictions with accuracies of 70% for prokaryotes and 53% for eukaryotes were achieved. BPROMPT can be accessed at http://www.jenner.ac.uk/BPROMPT.

Online grooming: moves and strategies

Using transcripts of chatroom grooming interactions, this paper explores and evaluates the usefulness of Swales’ (1981) move analysis framework in contributing to the current understanding of online grooming processes. The framework is applied to seven transcripts of grooming interactions taken from perverted-justice.com. The paper presents 14 identified rhetorical moves used in chatroom grooming and explores the broad structures that grooming conversations take by presenting these structures as colour-coded visualisations which we have termed “move maps”. It also examines how some individual linguistic features are used to realise a single move termed “Assessing and Managing Risk”. The findings suggest that move analysis can usefully contribute in two key ways: determining communicative functions associated with 'grooming language' and the visualisation of variation between grooming interactions.

To what extent and in what manner do Chinese and Indian contract research organisation learn and upgrade with the unbundling the global pharmaceutical R&D value chain?

The paper applies the GVC framework to analyse the organisational and geographical reconfiguration of the global R&D function of leading US and European pharmaceutical MNCs. Though pharmaceutical MNCs have been outsourcing clinical trial activities since the mid-1990s, the outsourcing of discovery research tasks is a phenomenon of the 2000s (Ramirez 2013). Moreover, in the context of a crisis of R&D productivity and increasing pressure from shareholders, a number of US and European pharmaceutical MNCs are breaking up their R&D function in an attempt to increase flexibility and reduce risk as well as costs and are thereby restructuring the global architecture of their R&D function. This break-up, or unbundling (Sako 2006), of the R&D function is particularly interesting given the prevalence of market failure in innovation (Howells et al 2008), the non-modular nature of the R&D process in this industry (Pisano 2006) and the strategic important of this activity to the core competence and long-term competitive advantage of firms in this sector. The focus of this paper is on the outsourcing of R&D activities to Chinese and Indian independently-owned contract research organisations (CROs) and the way these firms are becoming integrated as service providers into the global R&D function (or R&D value chain) of pharmaceutical MNCs. Above all the paper is concerned with the development of capabilities of CROs from these two countries and the dynamics of upgrading in GVCs in knowledge-intensive functions. The paper therefore discusses the role of both knowledge flows within global pharmaceutical R&D value chains as well as national innovation systems on the development of capabilities of Chinese and Indian CROs. Our analysis is based on data from semi-structured interviews collected from senior R&D managers from a sample of ten US and European pharmaceutical MNCs and owners and senior R&D managers from five Chinese and five Indian CROs who are providing research services to MNCs in this industry. We discuss the emergence of R&D outsourcing in this industry and the nature and mechanisms of knowledge flows within R&D value chains. The embeddedness of CROS in the national innovation systems of their home countries is also discussed.

Shared services and outsourcing : a contemporary outlook:10th Global Sourcing Workshop 2016, Val d'Isère, France, February 16-19, 2016, revised selected papers

This book constitutes the revised selected papers from the 10th Global Sourcing Workshop held in Val d’Isère, France, in February 2016. The 11 papers presented in this volume were carefully reviewed and selected from 47 submissions. The book offers a review of the key topics in outsourcing and offshoring of information technology and business services offering practical frameworks that serve as a tool kit to students and managers. The range of topics covered is wide and diverse, but predominately focused on how to achieve success in shared services and outsourcing. More specifically, the book examines outsourcing decisions and management practices, giving specific attention to shared services that have become one of the dominant sourcing models. The topics discussed combine theoretical and practical insights regarding challenges that industry leaders, policy makers, and professionals face or should be concerned with. Case studies from various organizations, industries and countries such as UK, Italy, The Netherlands, Canada, Australia and Denmark complete the book.