Globalisation and the technology gap: Regional and time evidence

This chapter examines the relationship between globalisation and technological progress. It computes an annual and country specific measure of technological gap, the technology ratio (TGR), using a recently proposed method known as metafrontiers. The TGR is measured as the distance from a group frontier to the global (or meta) frontier. The TGRs provide a measure to compare technological capability across countries. The ranking obtained from the metafrontiers method is first compared to other methods based on the direct measure of patents, science articles, schooling etc. The TGRs are then related to levels of trade openness and inbound and outbound foreign direct investment within regions and overtime in an effort to identify the relationship between technological gap and outward orientation.

Anisotropy-based performance analysis of linear discrete time invariant control systems

The anisotropic norm of a linear discrete-time-invariant system measures system output sensitivity to stationary Gaussian input disturbances of bounded mean anisotropy. Mean anisotropy characterizes the degree of predictability (or colouredness) and spatial non-roundness of the noise. The anisotropic norm falls between the H-2 and H-infinity norms and accommodates their loss of performance when the probability structure of input disturbances is not exactly known. This paper develops a method for numerical computation of the anisotropic norm which involves linked Riccati and Lyapunov equations and an associated special type equation.

Quantitative analysis of the time courses of enzyme-catalyzed reactions

The catalytic properties of enzymes are usually evaluated by measuring and analyzing reaction rates. However, analyzing the complete time course can be advantageous because it contains additional information about the properties of the enzyme. Moreover, for systems that are not at steady state, the analysis of time courses is the preferred method. One of the major barriers to the wide application of time courses is that it may be computationally more difficult to extract information from these experiments. Here the basic approach to analyzing time courses is described, together with some examples of the essential computer code to implement these analyses. A general method that can be applied to both steady state and non-steady-state systems is recommended. (C) 2001 academic Press.