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Articles you may be interested inNSDann2BS, a neutron spectrum unfolding code based on neural networks technology and two bonner spheres AIP Conf.Abstract. In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetry with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user´s philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural net approach it is possible to reduce the rate counts used to unfold the neutron spectrum. To evaluate these codes a computer tool called Neutron Spectrometry and dosimetry computer tool was designed. The results obtained with this package are showed. The codes here mentioned are freely available upon request to the authors.

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En este trabajo, se comparó el comportamiento experimental presión-temperatura en la transición de fase Isotrópico-Nemático para el Cristal Líquido 4-4´-bis(heptyloxy)azoxybenzene (HOAOB) a 1 atm utilizando un desarrollo del Modelo Convex Peg HERSW. Se calcularon los valores de los volúmenes moleculares para la coraza dura y atractiva respectivamente, por medio de cálculos mecano cuánticos a los niveles de teoría y precisión numérica PM3, PM6, Teoría de funcionales de la Densidad al nivel de teoría y precisión numérica B3LYP/6-311++G(d,p) y B3LYP/6-311++G(d,p)//PM6 considerando las interacciones intermoleculares entre monómeros (de moléculas de HOAOB) de un heptámetro (HOAOB)7. Se encontró que la mejor predicción teórica de los datos experimentales se encuentra cuando se incorpora el efecto de la correlación electrónica al cálculo del volumen con el modelo IPCM.