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We have implemented a method based on the Feshbach formalism along with an explicitly correlated configuration interaction method to perform a systematic study on the behavior of resonance parameters (energies and lifetimes) of the autoionizing states of plasma-embedded He 1,3 S e , 1,3 P o , and 1,3 D e , as a function of the screening strength. In particular, we study the evolution of the lowest states in the series located below the He + (N = 2) ionization threshold in the unscreened case. At variance with one-electron atoms (where shape resonance widths vary monotonically with the screening strength) the evolution of the Auger width with respect to screening is found to be different for each series represented by (K,T ) A pseudoquantum numbers until resonances merge into the upper electronic continuum, when crossing the He + (2s) threshold. We conclude from our ab initio calculations that, although resonances pertaining to the same (K,T ) A series share a similar tendency in their widths against the screening strength, general propensity rules for the robustness of lifetimes, based on the isomorphic series in the (K,T ) A classification, cannot be established in plasma-embedded helium.

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A theoretical approach to obtain accurate values for autoionizing states parameters in Be-like systems is presented. The method is based on the configuration-interaction expansion of the two-active (outer) electron wavefunction in terms of correlated coordinates containing r12 explicitly and by including a model potential to represent the effect of the 1s2 core. Within our approach, 1snl core states are removed from the basis of correlated configurations by using a Phillips–Kleinman projection operator, and resonance parameters (energies and widths) are determined through the stabilization method. Illustrative examples of our implementation are given for doubly-excited states of Be and Ne6+.

The study of viral infections using live cell imaging LCI is an important area with multiple opportunities for new developments in computational cell biology. Here, this point is illustrated by the analysis of the sub-cellular distribution of mitochondrium in cell cultures infected by Dengue virus DENV and in uninfected cell cultures Mock-infections . Several videos were recorded from the overnight experiments performed in a confocal microscopy of spinning disk. The density distribution of mitochondrium around the nuclei as a function of time and space r, θ, t was numerically modeled as a smooth interpolation function from the image data and used in further analysis. " graphical study shows that the behavior of the mitochondrial density is substantially different when the infection is present. The DENV-infected cells show a more diffuse distribution and a stronger angular variation on it. This behavior can be quantified by using some usual image processing descriptors called entropy and uniformity. Interestingly, the marked difference found in the mitochondria density distribution for mock and for infected cell is present in every frame and not an evidence of time dependence was found, which indicate that from the start of the infections the cells are showing an altered subcellular pattern in mitochondrium distribution. Ulteriorly, it would be important to study by analysis of time series for clearing if there is some tendency or approximate cycles. Those findings are suggesting that using the image descriptors entropy and uniformity it is possible to create a machine learning classifier that could recognize if a single selected cell in a culture has been infected or not.