No abstract

No abstract

We report the results of an experiment of cavitation, carried out by means of a sonotrode working at a frequency of 20 kHz and a power of 100 W. The analysis of water was carried out through an ICP mass spectrometer continuously during the cavitation process, in the mass regions from 90 to 150 amu and from 200 to 255 amu, that include also the rare earth elements. We found a significant peak corresponding to a nuclide with atomic mass (137.93 +/- 0.01) amu and a half-life 12 +/- 1 seconds, identified with Eu-138. This result, together with those of two previous experiments (which evidenced changes in concentration of stable elements and production of transuranic elements induced by cavitation), seems to support sononuclear reactions (in particular sononuclear fusion). We propose some possible classical mechanisms for the explanation of these findings

Inspired by the dissipative quantum model of brain, we model the states of neural nets in terms of collective modes by the help of the formalism of Quantum Field Theory. We exhibit an explicit neural net model which allows to memorize a sequence of several informations without reciprocal destructive interference, namely we solve the overprinting problem in such a way last registered information does not destroy the ones previously registered. Moreover, the net is able to recall not only the last registered information in the sequence, but also anyone of those previously registered.The quantum model of brain by Umezawa and Ricciardi [1,2,3,4] has attracted much attention in recent years. Moreover, its extension to dissipative dynamics [5], aimed to solve the long standing problem of memory capacity, provides an interesting framework to study consciousness related mechanisms. On the other hand, computational neuroscience mostly relies on specific activity of neural cells and of their networks, thus leading to a number of models and simulations of the brain activity in terms of neural nets, mostly based on modern methods of statistical mechanics and of spin glass theory [6,7]. Besides, there is an increasing interest in the study of quantum features of network dynamics, either in connection with information processing in biological systems, or in relation with a computational strategy based on the system quantum evolution (quantum computation).Inspired thus by the papers [1, 2, 3] and [5] (see also [8,9, 10]), we explore the possibility of modeling the states of neural nets in terms of collective modes by the help of the formalism of Quantum Field Theory (QFT).We show that the classical limit of the dissipative quantum brain dynamics (DQBD)[5] provides a representation of a neural net characterized by long range correlations among the net's units. In this way we exhibit a link between DQBD and neural net dynamics [11].We present an explicit neural net model which allows to memorize a sequence of several informations without reciprocal destructive interference, namely we solve the overprinting problem, i.e. last registered information does not destroy the ones previously registered. The net is also able to recall informations registered prior to the last registered one in the sequence.In the following we will first introduce the general theoretical background on which our neural net is modeled and then we will present some of its specific features and the results, which, although preliminary, confirm our expectations.

We discuss some features of the dissipative quantum model of brain in the frame of the formalism of quantum dissipation. Such a formalism is based on the doubling of the system degrees of freedom. We show that the doubled modes account for the quantum noise in the fluctuating random force in the system-environment coupling. Remarkably, such a noise manifests itself through the coherent structure of the system ground state. The entanglement of the system modes with the doubled modes is shown to be permanent in the infinite volume limit. In such a limit the trajectories in the memory space are classical chaotic trajectories.