In this paper the theory of the joint neutron-gamma photon distributions emitted from fissile samples with an
intrinsic neutron source, i.e. spontaneous fission, is described. In a sample of finite size short fission chains will
develop for each initial source event, thereby changing the number distributions (multiplicities) of the emitted
neutrons and gamma photons as compared to the elementary source events. Although in the fission process the
neutrons and the gamma photons are generated independently of each other, since new gamma photons are also
generated in the fission chain, the number of total emitted neutrons and gamma photons will develop correlations
which increase with increasing sample mass. In the paper the general theory of the joint distributions is derived
through master equations for the generating functions. The first few joint factorial moments are calculated
explicitly, including the covariance between the neutron and gamma photon numbers.
The theory of particle transport with branching in a medium randomly varying in time is developed in this paper. We consider an evolution equation for the probability distribution of the number of particles in a multiplying system whose properties jump randomly between two discrete states. A forward type master equation is derived for the probability distributions, and from these, the first two factorial moments are calculated, including the variance. This model can be considered the unification of stochastic methods that were used either for the particle fluctuations in a constant multiplying medium via the master equation technique, or in a fluctuating medium via the
Langevin technique. The results obtain show a much richer variety of behaviour than any of the above two methods separately can reconstruct.
The purpose of this paper is to demonstrate the use of some methods of signal analysis, performed on ECG and in some cases blood pressure signals, for the classification of the health status of the heart of mice and rats. Spectral and wavelet analysis were performed on the raw signals. FFT-based coherence and phase was also calculated between blood pressure and raw ECG signals. Finally, RR-intervals were deduced from the ECG signals and an analysis of the fractal dimensions was performed. The analysis was made on data from mice and rats. A correlation was found between the health status of the mice and the rats and some of the statistical descriptors, most notably the phase of the cross-spectra between ECG and blood pressure, and the fractal properties and dimensions of the interbeat series (RR-interval fluctuations).