More rain compensation results

To reduce the impact of rain-induced attenuation in the 20/30 GHz band, the attenuation at a specified signal frequency must be estimated and extrapolated forward in time on the basis of a noisy beacon measurement. Several studies have used model based procedures for solving this problem in statistical inference. Perhaps the most widely used model-based paradigm leads to the Kalman filter and its lineal variants. In this formulation, the dynamic features of the attenuation are represented by a state process (x(sub t)). The observation process (y(sub t)) is derived from beacon measurements. Some ideas relating to the signal processing problems related to uplink power control are presented. It is shown that some easily implemented algorithms hold promise for use in estimating rain induced fades. The algorithms were applied to actual data generated at the Virginia Polytechnic Institute and State University (VPI) test facility. Because only one such event was studied, it is not clear that the algorithms will have the same effectiveness when a wide range of events are studied

A non-autonomous stochastic discrete time system with uniform disturbances

The main objective of this article is to present Bayesian optimal control over a class of non-autonomous linear stochastic discrete time systems with disturbances belonging to a family of the one parameter uniform distributions. It is proved that the Bayes control for the Pareto priors is the solution of a linear system of algebraic equations. For the case that this linear system is singular, we apply optimization techniques to gain the Bayesian optimal control. These results are extended to generalized linear stochastic systems of difference equations and provide the Bayesian optimal control for the case where the coefficients of these type of systems are non-square matrices. The paper extends the results of the authors developed for system with disturbances belonging to the exponential family

Superparamagnetic Iron Oxide Nanoparticles Labeling of Bone Marrow Stromal (Mesenchymal) Cells Does Not Affect Their “Stemness”

Superparamagnetic iron oxide nanoparticles (SPION) are increasingly used to label human bone marrow stromal cells (BMSCs, also called “mesenchymal stem cells”) to monitor their fate by in vivo MRI, and by histology after Prussian blue (PB) staining. SPION-labeling appears to be safe as assessed by in vitro differentiation of BMSCs, however, we chose to resolve the question of the effect of labeling on maintaining the “stemness” of cells within the BMSC population in vivo. Assays performed include colony forming efficiency, CD146 expression, gene expression profiling, and the “gold standard” of evaluating bone and myelosupportive stroma formation in vivo in immuncompromised recipients. SPION-labeling did not alter these assays. Comparable abundant bone with adjoining host hematopoietic cells were seen in cohorts of mice that were implanted with SPION-labeled or unlabeled BMSCs. PB+ adipocytes were noted, demonstrating their donor origin, as well as PB+ pericytes, indicative of self-renewal of the stem cell in the BMSC population. This study confirms that SPION labeling does not alter the differentiation potential of the subset of stem cells within BMSCs

Integration of the European Union's energy policy for Climate Change and the European Internal Market for Electricity: cohesive or divisive?

Imperial Users onl