Cauchy problems for a class of linear differential equations with constant coefficients and Riemann-Liouville derivatives of real orders, are analyzed and solved in cases when some of the real orders are irrational numbers and when all real orders appearing in the derivatives are rational numbers. Our analysis is motivated by a forced linear oscillator with fractional damping. We pay special attention to the case when the leading term is an integer order derivative. A new form of solution, in terms of Wright's function for the case of equations of rational order, is presented. An example is treated in detail.MSC 2010 : Primary 26A33; Secondary 33E12, 34A08, 34K37, 35R11, 60G22

This study presents a new nonlinear two compartmental model and its application to the evaluation of valproic acid (VPA) pharmacokinetics in human volunteers after oral administration. We have used literature VPA concentrations. In the model, the integer order derivatives are replaced by derivatives of real order often called fractional order derivatives. Physically that means that the history (memory) of a biological process, realized as a transfer from one compartment to another, is taken into account with the mass balance conservation observed. Our contribution is the analysis of a specific nonlinear two compartmental model with the application in evaluation of VPA pharmacokinetics. The agreement of the values predicted by the proposed model with the values obtained through experiments is shown to be good. Thus, pharmacokinetics of VPA after oral application can be described well by a nonlinear two compartmental model with fractional derivatives of the same order proposed here. Parameters in the model are determined by the least-squares method and the particle swarm optimization (PSO) numerical procedure is used. The results show that the nonlinear fractional order two compartmental model for VPA pharmacokinetics is superior in comparison to the classical (integer order) linear two compartmental model and to the linear fractional order two compartmental model.

Since the exact time a specific nucleus undergoes radioactive decay cannot be specified, nor can showers caused by secondary cosmic rays be predicted, statistical laws play an important role in almost all cases of experimental nuclear physics. This paper describes the method for the statistical treatment of nuclear counting results obtained experimentally by taking into account random variables pertaining to both frequent and infrequent phenomena. When processing counting measurement data, it is recommended to first discard spurious random variables that spoil the statistics by using Chauvenet’s criterion, as well as to test if the results in the statistical sample follow a unique statistical distribution by using the Wilcoxon rank-sum test (U-test). The verification of the suggested statistical method was performed on counting statistics obtained both from the radioactive source Cs-137 and background radiation, expected to follow the normal distribution and the Poisson distribution, respectively. Results show that the application of the proposed statistical method excludes random fluctuations of the radioactive source or of the background radiation from the total statistical sample, as well as possible inadequacies in the experimental set-up and show an extremely effective agreement of the theoretical distribution of random variables with the corresponding experimentally obtained random variables

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