This research inquires some dimensions implied in the “graphical facilitation effect” on probabilistic reasoning, considering the associations of performance with contextual and individual features. Indeed, many authors highlighted that graphical representations might enhance problem solving in probabilistic reasoning; however, the cognitive processes underpinning these aspects have to be further deepened. Specifically, the role and the interaction between contextual and individual dimensions are not yet clearly defined. We aim to enlighten the influence of these kinds of dimensions, comparing the probabilistic reasoning applied by the same undergraduate in similar problems presented in verbal-numerical and graphicalpictorial formats. These assessments were conducted by controlling the effects on performance of numerical and visuo spatial abilities, attitudes towards statistics, statistical anxiety, and metacognitive awareness of the correctness of response (confidence); furthermore, we considered the influence of time pressure (presence versus absence) and of the type of university course enrolled (Psychology versus Business and Economics). Three hundred and forty-five Italian first year undergraduates, lacking statistical expertise, fulfilled a protocol composed by standardized instruments of assessment. The evaluation of accuracy on the solution in both formats have been related to the aforementioned contextual variables (time pressure, university course enrolled) and individual variables (abilities, anxiety, attitudes and confidence). At first, Hierarchical Linear Regressions were carried out separately to identify the individual variables affecting performance. Two formats of problem presentation were used. Then, the Analysis of Covariance with Mixed Design was applied, in order to highlight the effects of covariates (identified as the significant predictors distinguished in the previous regressions), the effects of the between factors (time pressure and university course) on the performance in two formats (considered as repeated measures). It was observed that confidence is the finest predictor of performance accuracy in both formats; it means that the metacognitive dimension strongly affects accuracy. Furthermore, the effect of format was underlined (“graphical facilitation” was highlighted) and the effect of time pressure was emphasised (the presence of time limits significantly enhances performance). No differences were found between the undergraduates enrolled in two university courses (Psychology and Business and Economics). In summary, “graphical facilitation” might be the after effect of multifactorial relations between different variables. Furthermore, these findings might be considered as an evidence of the key role of individual differences in probabilistic reasoning, which, by interacting with contextual dimensions, might influence the application of strategies useful to solve probabilistic problems, specifically in undergraduates without any statistical knowledge.

Starting from the Eighties, there has been a fluorishing of models of memorization and learning processes, based on neural networks. As shown by McCloskey e Cohen (1989), and Ratcliff (1990), the ones characterized by a multilayer feedforward architecture and the supervised back-propagation learning rule are plagued by the so-called catastrophic interference problem. This latter arises when, after a network learned a certain number of items belonging to a suitable learning set, the same network is submitted to a second learning process with a new learning set.

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 138Eu. 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.

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.

We discuss the possible effects of gravitational-wave stochastic background on the performance of a pendulum device such those used in precise measurements of the gravitational constant G. The variation ΔQ of the quality factor Q of the pendulum induced by the stochastic background is evaluated, by using as numerical input the results obtained in gravitational antennas experiments. It is found |ΔQ|∼10−10, completely negligible with respect to a typical value Q∼105.

In this paper we review the evidence for quantum phenomena underlying neuropsychiatric disorders. Existing data can be explained only by resorting to non-local correlations within brain activity, such as the ones predicted by quantum theory. Such a situation suggests that perhaps a quantum description may be the best description of interrelationships between neural and cognitive phenomena.

We carry out a critical analysis of the Maxwell electromagnetic theory, with emphasis on ifs "geometrical" features and gauge-theoretical properties. This allows us to single out five fundamental principles, which are at the very foundation of electromagnetism and can be used to build up any (electromagnetic-like) unified-gauge theory Such principles are essentially based on the different order of commutators among covariant derivatives, and are connected in a natural way to the commutative diagrams of various orders, which relate the relevant operators involved in the electromagnetic theory. An application of this general procedure is given by considering general relativity, whose basic equations can also be derived from the five basic postulates. Moreover, the equations satisfied by the sources of the gauge field can be derived from a fundamental invariant by imposing that the continuity equation for the current be satisfied. Such an electromagnetic-like generation scheme permits us to obtain a family of unified-gauge theories, hierarchically arranged by increasing complexity.

Recognizing that syntactic and semantic structures of classical logic are not sufficient to understand the meaning of quantum phenomena, we propose in this paper a new interpretation of quantum mechanics based on evidence theory. The connection between these two theories is obtained through a new language, quantum set theory, built on a suggestion by J. Bell. Further, we give a modal logic interpretation of quantum mechanics and quantum set theory by using Kripke's semantics of modal logic based on the concept of possible worlds. This is grounded on previous work of a number of researchers (Resconi, Klir, Harmanec) who showed how to represent evidence theory and other uncertainty theories in terms of modal logic. Moreover, we also propose a reformulation of the many-worlds interpretation of quantum mechanics in terms of Kripke's semantics. We thus show how three different theories — quantum mechanics, evidence theory, and modal logic — are interrelated. This opens, on one hand, the way to new applications of quantum mechanics within domains different from the traditional ones, and, on the other hand, the possibility of building new generalizations of quantum mechanics itself.

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.

We show that particular features of prosopagnosic impairment can be simulated by a connectionist model trained with an unsupervised learning procedure. In particular we describe a Kohonen's neural network which is able to correctly recognize and categorize a series of digitized pictures of faces when learning is characterized by certain parameter values, but which shows a prosopagnosic behavior when lateral connections are leasioned. We discuss the relationship between this result and some neurophysiological hypotheses about prosopagnosia.