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Text is not unadulterated fact. A text can make you laugh or cry but can it also make you short sell your stocks in company A and buy up options in company B? Research in the domain of finance strongly suggests that it can. Studies have shown that both the informational and affective aspects of news text affect the markets in profound ways, im-pacting on(More)
Cells undergoing programmed cell death (apoptosis) are cleared rapidly in vivo by phagocytes without inducing inflammation. Here we show that the glycosylphosphatidylinositol-linked plasma-membrane glycoprotein CD14 on the surface of human macrophages is important for the recognition and clearance of apoptotic cells. CD14 can also act as a receptor that(More)
Bayesian Networks are probabilistic structured representations of domains which have been applied to monitoring and manipulating cause and effects for modelled systems as disparate as the weather, disease and mobile telecommunications networks. Although useful, Bayesian Networks are notoriously difficult to build accurately and efficiently which has(More)
Cells undergoing apoptosis are cleared rapidly by phagocytes, thus preventing tissue damage caused by loss of plasma membrane integrity. In this study, we show that the surface of leukocytes is altered during apoptosis such that the first Ig-like domain of ICAM-3 (CD50) can participate in the recognition and phagocytosis of the apoptotic cells by(More)
Increasingly powerful fault management systems are required to ensure robustness and quality of service in today's networks. In this context, event correlation is of prime importance to extract meaningful information from the wealth of alarm data generated by the network. Existing sequential data mining techniques address the task of identifying possible(More)
— The ongoing work presented in this paper is aimed at bringing self-configuration capabilities into next generation radio access networks. We present the main concepts and architecture of our prototype. We also introduce briefly a novel strategy for foreseeing the outcome of enforcing policies integrating behaviour discovery techniques and finite state(More)
Bayesian Networks are probabilistic structured representations of domains which have been applied to monitoring and manipulating cause and effects for modelled systems as disparate as the weather, disease and mobile telecommunications networks. Although useful, Bayesian Networks are notoriously difficult to build accurately and efficiently which has(More)