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.
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Balazs, C. et al, Mamuzic, J., & Ruiz de Austri, R. (2021). A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications. J. High Energy Phys., 05(5), 108–46pp.
Abstract: Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms.
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Baker, M. J., Bordes, J., Hong-Mo, C., & Tsun, T. S. (2013). A comprehensive mechanism reproducing the mass and mixing parameters of quarks and leptons. Int. J. Mod. Phys. A, 28(16), 1350070–29pp.
Abstract: It is shown that if, from the starting point of a universal rank-one mass matrix long favored by phenomenologists, one adds the assumption that it rotates (changes its orientation in generation space) with changing scale, one can reproduce, in terms of only six real parameters, all the 16 mass ratios and mixing parameters of quarks and leptons. Of these 16 quantities so reproduced, 10 for which data exist for direct comparison (i.e. the CKM elements including the CP-violating phase, the angles theta(12), theta(13), theta(23) in nu-oscillation, and the masses m(c), m(mu), m(e)) agree well with experiment, mostly to within experimental errors; four others (m(s), m(u), m(d), m(nu 2)), the experimental values for which can only be inferred, agree reasonably well; while two others (m(nu 1), delta(CP) for leptons), not yet measured experimentally, remain as predictions. In addition, one gets as bonuses, estimates for (i) the right-handed neutrino mass m(nu R) and (ii) the strong CP angle theta inherent in QCD. One notes in particular that the output value for sin(2) 2 theta(13) from the fit agrees very well with recent experiments. By inputting the current experimental value with its error, one obtains further from the fit two new testable constraints: (i) that theta(23) must depart from its “maximal” value: sin(2) 2 theta(23) similar to 0.935 +/- 0.021, (ii) that the CP-violating (Dirac) phase in the PMNS would be smaller than in the CKM matrix: of order only vertical bar sin delta(CP)vertical bar <= 0.31 if not vanishing altogether.
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Zhai, Y. J., Giare, W., van de Bruck, C., Di Valentino, E., Mena, O., & Nunes, R. C. (2023). A consistent view of interacting dark energy from multiple CMB probes. J. Cosmol. Astropart. Phys., 07(7), 032–16pp.
Abstract: We analyze a cosmological model featuring an interaction between dark energy and dark matter in light of the measurements of the Cosmic Microwave Background released by three independent experiments: the most recent data by the Planck satellite and the Atacama Cosmology Telescope, and WMAP (9-year data). We show that different combinations of the datasets provide similar results, always favoring an interacting dark sector with a 95% C.L. significance in the majority of the cases. Remarkably, such a preference remains consistent when cross-checked through independent probes, while always yielding a value of the expansion rate H0 consistent with the local distance ladder measurements. We investigate the source of this preference by scrutinizing the angular power spectra of temperature and polarization anisotropies as measured by different experiments.
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Hirsch, M., Krauss, M. E., Opferkuch, T., Porod, W., & Staub, F. (2016). A constrained supersymmetric left-right model. J. High Energy Phys., 03(3), 009–22pp.
Abstract: We present a supersymmetric left-right model which predicts gauge coupling unification close to the string scale and extra vector bosons at the TeV scale. The subtleties in constructing a model which is in agreement with the measured quark masses and mixing for such a low left-right breaking scale are discussed. It is shown that in the constrained version of this model radiative breaking of the gauge symmetries is possible and a SM-like Higgs is obtained. Additional CP-even scalars of a similar mass or even much lighter are possible. The expected mass hierarchies for the supersymmetric states differ clearly from those of the constrained MSSM. In particular, the lightest down-type squark, which is a mixture of the sbottom and extra vector-like states, is always lighter than the stop. We also comment on the model's capability to explain current anomalies observed at the LHC.
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