From a ‘borderless world’ to a ‘world of borders’: ‘bringing history back in’

The first part of the paper explores some of the reasons why contemporary border studies understate the full significance of state borders and their global primacy. It is argued that this failing is rooted in a much wider lack of historical reflexivity-a reluctance to acknowledge the historical positioning (the 'where and when') of contemporary border studies themselves. This reluctance encourages a form of pseudohistory, or 'epochal thinking', which disfigures perspective on the present. Among the consequences are (a) exaggerated claims of the novelty of contemporary border change, propped up by poorly substantiated benchmarks in the past; (b) an incapacity to recognise the 'past in the present' as in the various historical deposits of state formation processes; and (c) a failure to recognise the distinctiveness of contemporary state borders and how they differ from other borders in their complexity and globality. The second part of the paper argues for a recalibration of border studies aimed at balancing their spatial emphases with a much greater, and more critical, historical sensitivity. It insists that 'boundedness', and state boundedness in particular, is a variable that must be understood historically. This is illustrated by arguing that a better analysis of contemporary border change means rethinking the crude periodisation which distinguishes the age of empire from the age of nation-states and, in turn, from some putative contemporary era 'beyond nation-states' and their borders.

Effect of signal intensity normalization on the multivariate analysis of spectral data in complex 'real-world' datasets

Spectral signal intensities, especially in 'real-world' applications with nonstandardized sample presentation due to uncontrolled variables/factors, commonly require additional spectral processing to normalize signal intensity in an effective way. In this study, we have demonstrated the complexity of choosing a normalization routine in the presence of multiple spectrally distinct constituents by probing a dataset of Raman spectra. Variation in absolute signal intensity (90.1% of total variance) of the Raman spectra of these complex biological samples swamps the variation in useful signals (9.4% of total variance), degrading its diagnostic and evaluative potential.

China and the changing landscape of the world economy

The rapid development of emerging markets is changing the landscape of the world economy and may have profound implications for international relations. China is often regarded as the most influential emerging market economy because, during the last three decades, it has become increasingly integrated into the world economic system and its success and failure now affect the well-being of other nations in the world. As the financial crisis in the US and EU intensifies, the economic prosperity of the world depends to a large extent on the sustained development of the Chinese economy and other emerging markets, and vice versa.