|
Albertus, C., Hernandez, E., & Nieves, J. (2011). Exclusive c -> s, d semileptonic decays of ground-state spin-1/2 doubly charmed baryons. Phys. Lett. B, 704(5), 499–509.
Abstract: We evaluate exclusive semileptonic decays of ground-state spin-1/2 doubly heavy charmed baryons driven by a c -> s, d transition at the quark level. Our results for the form factors are consistent with heavy quark spin symmetry constraints which are valid in the limit of an infinitely massive charm quark and near zero recoil. Only a few exclusive semileptonic decay channels have been theoretically analyzed before. For those cases we find that our results are in a reasonable agreement with previous calculations.
|
|
|
Albertus, C., Hernandez, E., & Nieves, J. (2012). Exclusive c -> s, d semileptonic decays of ground-state spin-1/2 and spin-3/2 doubly heavy cb baryons. Phys. Rev. D, 85(9), 094035–21pp.
Abstract: We evaluate exclusive semileptonic decays of ground-state spin-1/2 and spin-3/2 doubly heavy cb baryons driven by a c --> s, d transition at the quark level. We check our results for the form factors against heavy quark spin symmetry constraints obtained in the limit of very large heavy quark masses and near zero recoil. Based on those constraints we make model-independent, though approximate, predictions for ratios of decay widths.
|
|
|
Albertus, C., Hernandez, E., & Nieves, J. (2014). B -> rho semileptonic decays and vertical bar V-ub vertical bar. Phys. Rev. D, 90(1), 013017–11pp.
Abstract: We reevaluate the B -> rho l(+) nu(l) decay width as a full B. pi pi iota(+)nu iota four-particle decay, in which the two final pions are produced via an intermediate. meson. The decay width can be written as a convolution of the B -> rho l(+) nu(l) decay width, for an off-shell., with the.. pp line shape. This allows us to fully incorporate the effects of the finite. meson width and a better comparison with actual experiments. We use an Omn s representation to provide the dependence of the B.. semileptonic form factors on q2. The Omn s subtraction constants and the overall normalization parameter jVubj are fitted to light cone sum rules and lattice QCD theoretical form-factor calculations, in the low and high q2 regions, respectively, together to the CLEO, BABAR, and Belle experimental partial branching fraction distributions. The extracted value from this global fit is jVubj d3.40 +/- 0.15_ x 10-3, in agreement with jVubj extracted using all other inputs in Cabibbo-Kobayashi-Maskawa fits and the exclusive semileptonic B. p channel, but showing a clear disagreement with jVubj extracted from inclusive semileptonic b. u decays. As estimated by [U.-G. Mei beta ner andW. Wang, J. High Energy Phys. 01 (2014) 107], taking into account the. meson width effects and the actual acceptance of the experiments is essential to render the jVubj determinations from exclusive B. p and B.. decays totally compatible.
|
|
|
Albertus, C., Hernandez, E., & Nieves, J. (2014). Exclusive c -> s, d Semileptonic Decays of Spin-1/2 and Spin-3/2 cb Baryons. Few-Body Syst., 55(8-10), 767–771.
Abstract: We present results for exclusive semileptonic decay widths of ground state spin-1/2 and spin-3/2 cb baryons corresponding to a c -> s, d transition at the quark level. The relevance of hyperfine mixing in spin-1/2 cb baryons is shown. Our form factors are compatible with heavy quark spin symmetry constraints obtained in the infinite heavy quark mass limit.
|
|
|
Albiol, A., Albiol, F., Paredes, R., Plasencia-Martinez, J. M., Blanco Barrio, A., Garcia Santos, J. M., et al. (2022). A comparison of Covid-19 early detection between convolutional neural networks and radiologists. Insights Imaging, 13(1), 122–12pp.
Abstract: Background The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists. In this paper, the performance of a deep learning algorithm on the first clinical encounter is evaluated and compared with a group of radiologists with different years of experience. Methods The algorithm uses an ensemble of four deep convolutional networks, Ensemble4Covid, trained to detect COVID-19 on frontal chest radiographs. The algorithm was tested using images from the first clinical encounter of positive and negative cases. Its performance was compared with five radiologists on a smaller test subset of patients. The algorithm's performance was also validated using the public dataset COVIDx. Results Compared to the consensus of five radiologists, the Ensemble4Covid model achieved an AUC of 0.85, whereas the radiologists achieved an AUC of 0.71. Compared with other state-of-the-art models, the performance of a single model of our ensemble achieved nonsignificant differences in the public dataset COVIDx. Conclusion The results show that the use of images from the first clinical encounter significantly drops the detection performance of COVID-19. The performance of our Ensemble4Covid under these challenging conditions is considerably higher compared to a consensus of five radiologists. Artificial intelligence can be used for the fast diagnosis of COVID-19.
|
|