Calculation of electron correlation energy in molecules involves a very important computational effort, even in the simplest cases. Nowadays, using the new parallel libraries (PETSc and SLEPc) and MPI, we can resolve this calculation faster and with very big molecules. This result is a very important advance in chemical computation.

We study the correlation energy associated with the pair fluctuations in BCS theory. We use a schematic two-level pairing model and discuss the behavior of the correlation energy across shell closures, including the even-odd differences. It is shown that the random phase approximation (RPA) to the ground state energy reproduces the exact solutions quite well both in the normal fluid and in the ...

The extraction of Green’s functions by cross correlation of continuous seismic records at station pairs is best achieved in a diffuse wave field, where energies radiated by random sources have equal power. To partially satisfy the diffuse wave-field condition, original seismic records must be normalized as they are highly nonstationary and may have amplitude variations of orders of magnitude wi...

We present an interactive IDL program for viewing and analyzing astronomical spectra in the context of modern imaging surveys. SpecPro’s interactive design lets the user simultaneously view spectroscopic, photometric, and imaging data, allowing for rapid object classification and redshift determination. The spectroscopic redshift can be determined with automated cross-correlation against a vari...

Background: The study was conducted to assess reliability of modified semi-quantitative food frequency questionnaire (SQFFQ) as a part of the Amirkola Health and Aging Project (AHAP). Methods: The study was carried out in a sample of 200 men and women aged 60 years and older. A 138-item SQFFQ and two 24-hour dietary recalls were completed. The reliability of SQFFQ was evaluated by comparing ei...

  Objective(s): A fast and reliable evaluation of the binding energy from a single conformation of a molecular complex is an important practical task. Artificial neural networks (ANNs) are strong tools for predicting nonlinear functions which are used in this paper to predict binding energy. We proposed a structure that obtains binding energy using physicochemical molecular descripti...