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One of the main themes in modern Islamic debate has been the relationship between universal and cultural particularistic norms regulating human affairs, the sphere which in classical Islamic tradition is designated as mu´amalat. A recurrent topic of contest has been the universal character of international conventions on human rights. In this paper I will discuss two attempts at accommodation by
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Ligand stimulation of the platelet-derived growth factor (PDGF) beta-receptor leads to activation of its intrinsic tyrosine kinase and autophosphorylation of the intracellular part of the receptor. The autophosphorylated tyrosine residues mediate interactions with downstream signal transduction molecules and thereby initiate different signalling pathways. A pathway leading to activation of the GTP
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In this paper, we argue for the design of off-task interaction in technology enchanced learning. This implies a rethinking of pedagogy which can substantially contribute to achieving specific learning goals. We describe a work-in-progress and provide concrete examples of how we deal with relevant issues raised by allowing for off-task interactions in an educational math game as an integrated learn
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This work presents a technique to reduce the phase errors of quadrature signals. The proposed concept is demonstrated on a 2.4-GHz single-sideband up-converter in a 0.35-/spl mu/m BiCMOS process. The quadrature LO signals are obtained on-chip by means of two coupled oscillators, achieving a figure-of-merit of 186 dB. The image-rejection ratio improves by 7 to 11dB across the 28% LO tuning range wi
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The aim of this study is to systematically compare parametric and non-parametric techniques for analyzing trends in annual NDVI derived from NOAA AVHRR sensor in order to examine how trend type and departure from normality assumptions affect the accuracy of detecting long-term change. To generate annual data, the mean NDVI of a four-month long ‘green’ season was computed for fifteen sites (located
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An adaptive predictor for discrete time stochastic processes with constant but unknown parameters is described. The predictor which in real time tunes its parameters using the method of least squares is called a self-tuning predictor. The predictor has attractive asymptotic properties. If the parameter estimation converges and if the predictor contains parameters enough, then it will converge to t