Análisis y recomendaciones al sistema administrativo de la Universidad de El Salvador volumen II

La finalidad de este Informe es la de exponer, de un modo integral y objetivo, los diversos pormenores de la investigación científica efectuada en doce diferentes sistemas componentes del quehacer administrativo de la Universidad de El Salvado

Análisis y recomendaciones al sistema administrativo de la Universidad de El Salvador volumen I

La finalidad de este Informe es la de exponer, de un modo integral y objetivo, los diversos pormenores de la investigación científica efectuada en doce diferentes sistemas componentes del quehacer administrativo de la Universidad de El Salvador

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Damping signatures at JUNO, a medium-baseline reactor neutrino oscillation experiment

Abstract We study damping signatures at the Jiangmen Underground Neutrino Observatory (JUNO), a medium-baseline reactor neutrino oscillation experiment. These damping signatures are motivated by various new physics models, including quantum decoherence, nu(3) decay, neutrino absorption, and wave packet decoherence. The phenomenological effects of these models can be characterized by exponential damping factors at the probability level. We assess how well JUNO can constrain these damping parameters and how to disentangle these different damping signatures at JUNO. Compared to current experimental limits, JUNO can significantly improve the limits on tau(3)/m(3) in the nu(3) decay model, the width of the neutrino wave packet sigma(x), and the intrinsic relative dispersion of neutrino momentum sigma(rel)