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We show that the q-Kneser graph $qK_{2k:k}$ (the graph on the k-subspaces of a 2k-space over GF(q), where two k-spaces are adjacent when they intersect trivially), has chromatic number $q^k + q^{k-1}$ for k = 3 and for k <q log q - q. We obtain detailed results on maximal cocliques for k = 3. Keywords: Chromatic number – q-analog of Kneser graph

In the frame of the FP7 POPDAT project the Ionosphere Waves Service (IWS) has been developed and opened for public access by ionosphere experts. IWS is forming a database, derived from archived ionospheric wave records to assist the ionosphere and Space Weather research, and to answer the following questions: How can the data of earlier ionospheric missions be reprocessed with current algorithms to gain more profitable results? How could the scientific community be provided with a new insight on wave processes that take place in the ionosphere? The answer is a specific and unique data mining service accessing a collection of topical catalogs that characterize a huge number of recorded occurrences of Whistler-like Electromagnetic Wave Phenomena, Atmosphere Gravity Waves, and Traveling Ionosphere Disturbances. IWS online service (http://popdat.cbk.waw.pl) offers end users to query optional set of predefined wave phenomena, their detailed characteristics. These were collected by target specific event detection algorithms in selected satellite records during database buildup phase. Result of performed wave processing thus represents useful information on statistical or comparative investigations of wave types, listed in a detailed catalog of ionospheric wave phenomena. The IWS provides wave event characteristics, extracted by specific software systems from data records of the selected satellite missions. The end-user can access targets by making specific searches and use statistical modules within the service in their field of interest. Therefore the IWS opens a new way in ionosphere and Space Weather research. The scientific applications covered by IWS concern beyond Space Weather also other fields like earthquake precursors, ionosphere climatology, geomagnetic storms, troposphere-ionosphere energy transfer, and trans-ionosphere link perturbations. © 2014 C. Ferencz et al.

The Graphics Processing Unit (GPU) is a powerful tool for parallel computing. In the past years the performance and capabilities of GPUs have increased, and the Compute Unified Device Architecture (CUDA) - a parallel computing architecture - has been developed by NVIDIA to utilize this performance in general purpose computations. Here we show for the first time a possible application of GPU for environmental studies serving as a basement for decision making strategies. A stochastic Lagrangian particle model has been developed on CUDA to estimate the transport and the transformation of the radionuclides from a single point source during an accidental release. Our results show that parallel implementation achieves typical acceleration values in the order of 80-120 times compared to CPU using a single-threaded implementation on a 2.33 GHz desktop computer. Only very small differences have been found between the results obtained from GPU and CPU simulations, which are comparable with the effect of stochastic transport phenomena in atmosphere. The relatively high speedup with no additional costs to maintain this parallel architecture could result in a wide usage of GPU for diversified environmental applications in the near future. 5 figures

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