By Vladimir V. Mityushev, Michael Ruzhansky

The booklet comprises lectures given by way of the plenary and key audio system on the ninth overseas ISAAC Congress held 2013 in Krakow, Poland. The contributions deal with fresh advancements in research and surrounding parts, touching on themes from the speculation of partial differential equations, functionality areas, scattering, chance thought, and others, in addition to purposes to biomathematics, queueing types, fractured porous media and geomechanics.

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**Example text**

12) 0 We can now generalise the estimates (10): Theorem 5 If Assumption 4 holds then for all t > 0, x, y ∈ M C β φt (x, y) 1+ d ρ(x, y) −(d+2β) . 1 t 2β t 2β Proof We apply subordination so using (12), (11) and monotonicity, we have ∞ β φt (x, y) C 0 1 s d 2 exp − ρ(x, y)2 cs β γt (s)ds. We fix x, y ∈ M and write λ = ρ(x, y). Now make a change of variable s = use the scaling property β 1 γt (b β s) = b for all u > 0 where b = 4 β c . − β1 β γbt (s), Then we obtain ∞ β φt (x, y) C β κu (0, λ)γbt (u)du 0 β = qbt (0, λ), by (8) and the result follows by using (10).

Jl. Mech. Appl. Math. 63, 497–519 (2010) 18. E. V. Craster, J. Kaplunov, High frequency homogenization for structural mechanics. J. Mech. Phys. Solids 59, 651–671 (2011) 19. T. V. Craster, S. Guenneau, High-frequency homogenization of zero frequency stop band photonic and phononic crystals. New J. Phys. 15, 103014 (2013) 20. T. V. Craster, High frequency asymptotics for microstructured thin elastic plates and platonics. Proc. R. Soc. Lond. A 468, 1408–1427 (2012) 21. T. Antonakakis, S. V. Craster, Homogenisation for elastic photonic crystals and dynamic anisotropy, under review (2014) 22.

Soc. Lond. A 469, 20120533 (2013) Queueing Models for Performance Evaluation of Computer Networks—Transient State Analysis Tadeusz Czachórski Abstract Queueing theory is a useful tool in design of computer networks and their performance evaluation. The literature concerning this subject is abundant. However, it is in general limited to the analysis of steady states. It means that flows of customers considered in models are constant and obtained solutions do not depend on time. It is in glaring contrast with the flows observed in real networks where the perpetual changes of traffic intensities are due to the nature of users, sending variable quantities of data, cf.