507 research outputs found
Rigorous numerics for NLS: bound states, spectra, and controllability
In this paper it is demonstrated how rigorous numerics may be applied to the
one-dimensional nonlinear Schr\"odinger equation (NLS); specifically, to
determining bound--state solutions and establishing certain spectral properties
of the linearization. Since the results are rigorous, they can be used to
complete a recent analytical proof [6] of the local exact controllability of
NLS.Comment: 30 pages, 2 figure
Existence and instability of steady states for a triangular cross-diffusion system: a computer-assisted proof
In this paper, we present and apply a computer-assisted method to study
steady states of a triangular cross-diffusion system. Our approach consist in
an a posteriori validation procedure, that is based on using a fxed point
argument around a numerically computed solution, in the spirit of the
Newton-Kantorovich theorem. It allows us to prove the existence of various non
homogeneous steady states for different parameter values. In some situations,
we get as many as 13 coexisting steady states. We also apply the a posteriori
validation procedure to study the linear stability of the obtained steady
states, proving that many of them are in fact unstable
Learning the structure of Bayesian Networks: A quantitative assessment of the effect of different algorithmic schemes
One of the most challenging tasks when adopting Bayesian Networks (BNs) is
the one of learning their structure from data. This task is complicated by the
huge search space of possible solutions, and by the fact that the problem is
NP-hard. Hence, full enumeration of all the possible solutions is not always
feasible and approximations are often required. However, to the best of our
knowledge, a quantitative analysis of the performance and characteristics of
the different heuristics to solve this problem has never been done before.
For this reason, in this work, we provide a detailed comparison of many
different state-of-the-arts methods for structural learning on simulated data
considering both BNs with discrete and continuous variables, and with different
rates of noise in the data. In particular, we investigate the performance of
different widespread scores and algorithmic approaches proposed for the
inference and the statistical pitfalls within them
A method to rigorously enclose eigenpairs of complex interval matrices
summary:In this paper, a rigorous computational method to enclose eigenpairs of complex interval matrices is proposed. Each eigenpair x=(\lambda,\rv) is found by solving a nonlinear equation of the form via a contraction argument. The set-up of the method relies on the notion of {\em radii polynomials}, which provide an efficient mean of determining a domain on which the contraction mapping theorem is applicable
A stacking-based artificial intelligence framework for an effective detection and localization of colon polyps
Albuquerque, C., Henriques, R., & Castelli, M. (2022). A stacking-based artificial intelligence framework for an effective detection and localization of colon polyps. Scientific Reports, 12, 1-12. [17678]. https://doi.org/10.21203/rs.3.rs-1862362/v1, https://doi.org/10.1038/s41598-022-21574-w ------- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.Polyp detection through colonoscopy is a widely used method to prevent colorectal cancer. The automation of this process aided by artificial intelligence allows faster and improved detection of polyps that can be missed during a standard colonoscopy. In this work, we propose implementing different object detection algorithms for polyp detection. To improve the mean average precision (mAP) of the detection, we combine the baseline models through a stacking approach. The experiments demonstrate the potential of this new methodology, which can reduce the workload for oncologists and increase the precision of the localization of polyps. Our proposal achieves an mAP of 0.86, translated into an improvement of 34.9% compared to the best baseline model and 28.8% with respect to the weighted boxes fusion ensemble technique.preprintpublishersversionepub_ahead_of_prin
Argomenti di giurisprudenza e di scienze politiche sui quali dopo sostenuti gli esami rigorosi per ottenere la laurea in ambe le leggi nell' I. R. Università di Pavia disputerà pubblicamente Castelli Roberto di Pavia il giorno di Lunedì 30 Agosto 1858
Analytic enclosure of the fundamental matrix solution
This work describes a method to rigorously compute the real Floquet normal form decomposition of the fundamental matrix solution of a system of linear ODEs having periodic coefficients. The Floquet normal form is validated in the space of analytic functions. The technique combines analytical estimates and rigorous numerical computations and no rigorous integration is needed. An application to the theory of dynamical system is presented, together with a comparison with the results obtained by computing the enclosure in the C s category
Influenza B-cells protective epitope characterization: a passkey for the rational design of new broad-range anti-influenza vaccines
The emergence of new influenza strains causing pandemics represents a serious threat to human health. From 1918, four influenza pandemics occurred, caused by H1N1, H2N2 and H3N2 subtypes. Moreover, in 1997 a novel influenza avian strain belonging to the H5N1 subtype infected humans. Nowadays, even if its transmission is still circumscribed to avian species, the capability of the virus to infect humans directly from avian reservoirs can result in fatalities. Moreover, the risk that this or novel avian strains could adapt to inter-human transmission, the development of resistance to anti-viral drugs and the lack of an effective prevention are all incumbent problems for the world population. In this scenario, the identification of broadly neutralizing monoclonal antibodies (mAbs) directed against conserved regions shared among influenza isolates has raised hopes for the development of monoclonal antibody-based immunotherapy and “universal” anti-influenza vaccines
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