Platelet adhesion to collagen and collagen-related peptide under flow. Roles of the alpha(2)beta(1) integrin, GPVI, and Src tyrosine kinases

Objective - Platelet stimulation by collagen and collagen-related peptides (CRPs) is associated with activation of protein tyrosine kinases. In the present study, we investigated the role of Src family tyrosine kinases in the initial adhesion events of human platelets to collagen and cross-linked CRP. Methods and Results - Under arterial flow conditions, a glycoprotein VI - specific substrate, cross-linked CRP, caused rapid (<2 second) platelet retention and protein tyrosine phosphorylation that were markedly decreased by the Src family kinase inhibitor pyrozolopyrimidine (PP2) or by aggregation inhibitor GRGDSP. CRP-induced platelet retention was transient, and 90% of single platelets or aggregates detached within seconds. PP2, although having no effect on RGD peptide-binding to CRP, completely blocked aggregation and tyrosine phosphorylation of Syk and phospholipase Cγ2 (PLCγ2). In contrast, PP2 weakly (<30%) suppressed firm adhesion to collagen mediated primarily by the alpha(2)beta(1) integrin. Although PP2 prevented activation of Syk and PLCgamma2 in collagen-adherent platelets, tyrosine phosphorylation of several unidentified protein bands persisted, as did autophosphorylation of pp125(FAK). Conclusions - These findings indicate that activation of Src-tyrosine kinases Syk and PLCgamma2 is not required for the initial stable attachment of human platelets to collagen and for FAK autophosphorylation. However, Src-tyrosine kinases are critical for glycoprotein VI - mediated signaling leading to platelet aggregation.

Irrelevant sound effects amongst younger and older adults: objective findings and subjective insights

Two experiments examine the effects of extraneous speech and nonspeech noise on a visual short-term memory task administered to younger and older adults. Experiment 1 confirms an earlier report that playing task-irrelevant speech is no more distracting for older adults than for younger adults (Rouleau T Belleville, 1996), indicating that "irrelevant sound effects" in short-term memory operate in a different manner to recalling targets in the presence of competing speech (Tun, O'Kane, T Wingfield, 2002). Experiment 2 extends this result to nonspeech noise and demonstrates that the result cannot be ascribed to hearing difficulties amongst the older age group, although the data also show that older adults rated the noise as less annoying and uncomfortable than younger adults. Implications for theories of the irrelevant sound effect, and for cognitive ageing, are discussed.

A knowledge-based evolution strategy for the multi-objective minimum spanning tree problem

A fast Knowledge-based Evolution Strategy, KES, for the multi-objective minimum spanning tree, is presented. The proposed algorithm is validated, for the bi-objective case, with an exhaustive search for small problems (4-10 nodes), and compared with a deterministic algorithm, EPDA and NSGA-II for larger problems (up to 100 nodes) using benchmark hard instances. Experimental results show that KES finds the true Pareto fronts for small instances of the problem and calculates good approximation Pareto sets for larger instances tested. It is shown that the fronts calculated by YES are superior to NSGA-II fronts and almost as good as those established by EPDA. KES is designed to be scalable to multi-objective problems and fast due to its small complexity.

RBF equalizer design using directional evolutionary multi-objective optimization

Whilst radial basis function (RBF) equalizers have been employed to combat the linear and nonlinear distortions in modern communication systems, most of them do not take into account the equalizer's generalization capability. In this paper, it is firstly proposed that the. model's generalization capability can be improved by treating the modelling problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets. Then, as a modelling application, a new RBF equalizer learning scheme is introduced based on the directional evolutionary MOO (EMOO). Directional EMOO improves the computational efficiency of conventional EMOO, which has been widely applied in solving MOO problems, by explicitly making use of the directional information. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good performance not only on explaining the training samples but on predicting the unseen samples.

Nonlinear channel equalizer design using directional evolutionary multi-objective optimization

In this paper, a new equalizer learning scheme is introduced based on the algorithm of the directional evolutionary multi-objective optimization (EMOO). Whilst nonlinear channel equalizers such as the radial basis function (RBF) equalizers have been widely studied to combat the linear and nonlinear distortions in the modern communication systems, most of them do not take into account the equalizers' generalization capabilities. In this paper, equalizers are designed aiming at improving their generalization capabilities. It is proposed that this objective can be achieved by treating the equalizer design problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets, followed by deriving equalizers with good capabilities of recovering the signals for all the training sets. Conventional EMOO which is widely applied in the MOO problems suffers from disadvantages such as slow convergence speed. Directional EMOO improves the computational efficiency of the conventional EMOO by explicitly making use of the directional information. The new equalizer learning scheme based on the directional EMOO is applied to the RBF equalizer design. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good generalization capabilities, i.e., good performance on predicting the unseen samples.

Critical notices: subjective, intersubjective, objective

Book review of 'Subjective, intersubjective, objective' by Donald Davidson.

Knowledge and information evaluation practice: an exploratory study in a construction firm

There are a number of challenges associated with managing knowledge and information in construction organizations delivering major capital assets. These include the ever-increasing volumes of information, losing people because of retirement or competitors, the continuously changing nature of information, lack of methods on eliciting useful knowledge, development of new information technologies and changes in management and innovation practices. Existing tools and methodologies for valuing intangible assets in fields such as engineering, project management and financial, accounting, do not address fully the issues associated with the valuation of information and knowledge. Information is rarely recorded in a way that a document can be valued, when either produced or subsequently retrieved and re-used. In addition there is a wealth of tacit personal knowledge which, if codified into documentary information, may prove to be very valuable to operators of the finished asset or future designers. This paper addresses the problem of information overload and identifies the differences between data, information and knowledge. An exploratory study was conducted with a leading construction consultant examining three perspectives (business, project management and document management) by structured interviews and specifically how to value information in practical terms. Major challenges in information management are identified. An through-life Information Evaluation methodology (IEM) is presented to reduce information overload and to make the information more valuable in the future.