Favella e il più antico Neolitico in Italia

News release announces that the University of Dayton ranks among the top Catholic universities and colleges in the country, according to the new issue of America\u27s Best Colleges from U.S. News and World Report

Predicting Thermodynamic Properties from Molecular Structures by Recursive Neural Networks. Comparison with Classical Group Contributions Methods.

The recursive neural networks deal with prediction tasks for compounds represented in a structured domain. These approaches allow combining, in a learning system, the flexibility and general advantages of a neural network model with the representational power of a structured domain. As a result a completely new approach to QSPR/QSAR analysis is obtained through the adaptive processing of molecular graphs whose performance is even better than that of traditional approaches. In this paper a Recursive Cascade Correlation model (RecCC) has been applied to the analysis of the Gibbs free energies of solvation in water of 179 monofunctional open chain organic compounds. An original representation of the molecules in terms of labeled directed positional acyclic graphs has been developed by individuating a limited set of constituent atomic groups and representation rules. The descriptive and predictive abilities of the RecCC model have been tested and compared with those of a traditional group contributions method. The inherent ability of the RecCC model to abstract chemical knowledge through the adaptive learning process have been investigated by Principal Components Analysis of the internal representations developed by the neural network, finding that the model recognizes the chemical compounds on the basis of a not trivial combination of their chemical structure and target property

Caratterizzazione del campo di induzione magnetica prodotto da cabine secondarie

L’articolo presenta una metodologia per la caratterizzazione del campo di induzione magnetica nei pressi di cabine secondarie di tipo a box prefabbricato in cemento armato vibrato, che costituisce un valido strumento per la verifica del rispetto degli obiettivi di qualità imposti dalla legislazione vigente

Metrological performances of voltage and current instrument transformers in harmonics measurements

In the new electrical system scenario, the increasing presence of non-linear loads and renewable energy sources makes the measurement of harmonics an essential task. The accuracy of harmonic measurement firstly depends on the used instrument transformers for voltage and current sensing. Since the behavior of instrument transformers in non-sinusoidal conditions is not always well defined, this paper presents an experimental study on the metrological performances of current and voltage instrument transformers (CTs and VTs) in the presence of harmonics. Proper tests procedures are defined and measurement setups are developed for both CTs and VTs calibration. The analysis is carried out by using test waveforms composed of a fundamental and one harmonic component. The harmonic ratio and phase errors are evaluated; the distortion effects on the errors on the fundamental component measurement are also investigated. The obtained results show how the metrological performances in harmonics measurement are influenced by both amplitude and phase shift of the harmonics