Development of retinal blood vessel segmentation methodology using wavelet transforms for assessment of diabetic retinopathy

Automated image processing has the potential to assist in the early detection of diabetes, by detecting changes in blood vessel diameter and patterns in the retina. This paper describes the development of segmentation methodology in the processing of retinal blood vessel images obtained using non-mydriatic colour photography. The methods used include wavelet analysis, supervised classifier probabilities and adaptive threshold procedures, as well as morphology-based techniques. We show highly accurate identification of blood vessels for the purpose of studying changes in the vessel network that can be utilized for detecting blood vessel diameter changes associated with the pathophysiology of diabetes. In conjunction with suitable feature extraction and automated classification methods, our segmentation method could form the basis of a quick and accurate test for diabetic retinopathy, which would have huge benefits in terms of improved access to screening people for risk or presence of diabetes

Information flow in a kinetic ising model peaks in the disordered phase

There is growing evidence that for a range of dynamical systems featuring complex interactions between large ensembles of interacting elements, mutual information peaks at order-disorder phase transitions. We conjecture that, by contrast, information flow in such systems will generally peak strictly on the disordered side of a phase transition. This conjecture is verified for a ferromagnetic 2D lattice Ising model with Glauber dynamics and a transfer entropy-based measure of systemwide information flow. Implications of the conjecture are considered, in particular, that for a complex dynamical system in the process of transitioning from disordered to ordered dynamics (a mechanism implicated, for example, in financial market crashes and the onset of some types of epileptic seizures); information dynamics may be able to predict an imminent transition

Emerging interdependence between stock values during financial crashes

To identify emerging interdependencies between traded stocks we investigate the behavior of the stocks of FTSE 100 companies in the period 2000-2015, by looking at daily stock values. Exploiting the power of information theoretical measures to extract direct influences between multiple time series, we compute the information flow across stock values to identify several different regimes. While small information flows is detected in most of the period, a dramatically different situation occurs in the proximity of global financial crises, where stock values exhibit strong and substantial interdependence for a prolonged period. This behavior is consistent with what one would generally expect from a complex system near criticality in physical systems, showing the long lasting effects of crashes on stock markets

Phase-transition–like behaviour of information measures in financial markets

We apply measures based on information theory to the analysis of day close equity prices traded on US stock markets over the 13-year interval from 1995 up until after the market crash of September 2008. We show that the mutual information between prices provides insight into the changing relationships between equities over a time period which includes three known market crashes and two events which have not previously been included in this type of study, one of which is related to the sub-prime meltdown starting in 2007. Specifically, the mutual information around market crashes shows behaviour typical of the phase transitions studied in condensed-matter physics, however similar but more extended peaks in mutual information are also observed at other times not associated with any known market crashes

CALCULATIONS OF ELECTRONIC-STRUCTURES OF CAGE MOLECULES USING FREE-ELECTRON ORBITALS AS A BASIS

A non-empirical molecular orbital method, particularly suitable for calculations on cage-like molecules, is described. The method uses as basis functions the set of free-electron functions which are the solutions of Schrödinger's equation for an electron confined between two concentric, spherical potential energy barriers. Application of the theory to the SCF calculation of the energies of the delocalized electrons in benzene and tetrasulphur tetranitride shows that the model is capable of interpreting the properties of such systems. However, it does highlight a difficulty in the calculation of excited state energies with one-centre models which appears to be largely unrecognized. Extension of the method to a consideration of all the valence electrons, using P4 as an example, reveals problems the origin of which is an inadequate treatment of the core electrons. It is suggested that these problems may best be dealt with by use of a suitable pseudo potential. © 1977 Springer-Verlag

Complexity, creativity and computers

Volume 10 Creativity, one of the hallmarks of the human spirit, has yet to travel deep into the domain of artificial intelligence and computers. We argue that creativity intrinsically requires and exploits complexity. The dynamic multilevel properties of complex systems give us a natural way of scaling creative solutions, from the everyday to the paradigm shift. In particular, the complexity model implies that deep far-reaching creative solutions may emerge without the originator having any clear idea of what the outcomes might be. This has implications for fostering creativity in individuals and the resourcing of the creative class. Finally, it implies that the major paradigm shifts of the future may be created by computers rather than people, in analogy with how acts of genius can arise from an autistic mind. 1