Consistent performance measurement of a system to detect masses in mammograms based on blind feature extraction

BACKGROUND: Breast cancer continues to be a leading cause of cancer deaths among women, especially in Western countries. In the last two decades, many methods have been proposed to achieve a robust mammography‐based computer aided detection (CAD) system. A CAD system should provide high performance over time and in different clinical situations. I.e., the system should be adaptable to different clinical situations and should provide consistent performance. METHODS: We tested our system seeking a measure of the guarantee of its consistent performance. The method is based on blind feature extraction by independent component analysis (ICA) and classification by neural networks (NN) or SVM classifiers. The test mammograms were from the Digital Database for Screening Mammography (DDSM). This database was constructed collaboratively by four institutions over more than 10 years. We took advantage of this to train our system using the mammograms from each institution separately, and then testing it on the remaining mammograms. We performed another experiment to compare the results and thus obtain the measure sought. This experiment consists in to form the learning sets with all available prototypes regardless of the institution in which them were generated, obtaining in that way the overall results. RESULTS: The smallest variation from comparing the results of the testing set in each experiment (performed by training the system using the mammograms from one institution and testing with the remaining) with those of the overall result, considering the success rate for an intermediate decision maker threshold, was roughly 5%, and the largest variation was roughly 17%. But, if we considere the area under ROC curve, the smallest variation was close to 4%, and the largest variation was about a 6%. CONCLUSIONS: Considering the heterogeneity in the datasets used to train and test our system in each case, we think that the variation of performance obtained when the results are compared with the overall results is acceptable in both cases, for NN and SVM classifiers. The present method is therefore very general in that it is able to adapt to different clinical situations and provide consistent performance

Updated Knowledge on Floods and Risk Management in the Middle Ebro River: the “Anthropocene” Context and River Resilience

The floods of 2015 and 2018 in the Middle Ebro River have led to a rethinking and updating of the forecasting and management systems. The improvements in the flow measurement systems applied in this type of extreme phenomena have led to questioning the values that were recorded in the past, officially changing the maximum flow rates of some historical floods. This has called for the need to update the knowledge/information of those recorded in the middle Ebro River, for example changing the return periods and making previous scientific studies obsolete. Updated data are applied, trying to re-characterize the floods of Ebro River since 1950, date in which the beginning of the "Anthropocene" is evident in the river management of the mainstream and its basin. At the same time, in the proposed risk management plans compliant with 2007/60/EC Directive, the structural measures are being replaced by more respectful and better adapted prevention systems for the river. The two processes interact and are essential for educating the population on risk, adopting preventive measures that are sustainable and consistent with the authentic ( corrected) characteristics of the river and its floods. Thus, scientific knowledge has been consolidated as a tool to display corrected data, or, the river's updated reality, and also to make the affected inhabitants aware of the need to follow new management protocols, focused on river resilience and social strategies.This study is integrated within project CGL2017-83866-C3-1-R, financed by the Ministry of Economy and Competitiveness (Spain

Analytic structure of the S-matrix for singular quantum mechanics

The analytic structure of the S-matrix of singular quantum mechanics is examined within a multichannel framework, with primary focus on its dependence with respect to a parameter (Ω) that determines the boundary conditions. Specifically, a characterization is given in terms of salient mathematical and physical properties governing its behavior. These properties involve unitarity and associated current-conserving Wronskian relations, time-reversal invariance, and Blaschke factorization. The approach leads to an interpretation of effective nonunitary solutions in singular quantum mechanics and their determination from the unitary family.Fil: Camblong, Horacio E.. University of San Francisco; Estados UnidosFil: Epele, Luis Nicolas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Física. Laboratorio de Física Teórica; ArgentinaFil: Fanchiotti, Huner. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Física. Laboratorio de Física Teórica; ArgentinaFil: García Canal, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Física. Laboratorio de Física Teórica; Argentin

Spiking Central Pattern Generators through Reverse Engineering of Locomotion Patterns

In robotics, there have been proposed methods for locomotion of nonwheeled robots based on artificial neural networks; those built with plausible neurons are called spiking central pattern generators (SCPGs). In this chapter, we present a generalization of reported deterministic and stochastic reverse engineering methods for automatically designing SCPG for legged robots locomotion systems; such methods create a spiking neural network capable of endogenously and periodically replicating one or several rhythmic signal sets, when a spiking neuron model and one or more locomotion gaits are given as inputs. Designed SCPGs have been implemented in different robotic controllers for a variety of robotic platforms. Finally, some aspects to improve and/or complement these SCPG-based locomotion systems are pointed out

Effective Field Theory Program for Conformal Quantum Anomalies

The emergence of conformal states is established for any problem involving a domain of scales where the long-range, SO(2,1) conformally invariant interaction is applicable. Whenever a clear-cut separation of ultraviolet and infrared cutoffs is in place, this renormalization mechanism produces binding in the strong-coupling regime. A realization of this phenomenon, in the form of dipole-bound anions, is discussed.Comment: 15 pages. Expanded, with additional calculational details. To be published in Phys. Rev.

Surface Reconstruction and Decahedral Structure of Bimetallic Nanoparticles

We report on energetic surface reconstruction phenomena observed on bimetallic nanoparticle systems of AuPd and AuCu, similar to a resolidification effect observed during the cooling process in lead clusters. These binary alloy nanoparticles show the fivefold edges truncated, resulting in { 100 } facets on decahedral structures, an effect largely envisioned and reported theoretically, with no experimental evidence so far. We demonstrate experimentally as well as by computational simulations that this new eutectic structure is favored in such nanoalloy systems.Fil: Rodríguez López J. L.. Instituto Potosino de Investigación Científica y Tecnológica ; MéxicoFil: Montejano Carrizales, J. M.. Universidad Autónoma de San Luis Potosí; MéxicoFil: Pal, U.. Universidad Auto´noma de Puebla; MéxicoFil: Sánchez Ramírez, J. F.. Universidad Auto´noma de Puebla; MéxicoFil: Troiani, Horacio Esteban. Comision Nacional de Energía Atómica. Gerencia de Área Investigaciones y Aplicaciones no Nucleares. Gerencia de Física (Centro Atómico Bariloche). División Física de Metales; ArgentinaFil: García, D.. The University of Texas; Estados UnidosFil: Miki Yoshida, M.. The University of Texas; Estados UnidosFil: José Yacamán, Miguel. The University of Texas; Estados Unido

Nonequilibrium phase transitions induced by multiplicative noise: effects of self-correlation

A recently introduced lattice model, describing an extended system which exhibits a reentrant (symmetry-breaking, second-order) noise-induced nonequilibrium phase transition, is studied under the assumption that the multiplicative noise leading to the transition is colored. Within an effective Markovian approximation and a mean-field scheme it is found that when the self-correlation time of the noise is different from zero, the transition is also reentrant with respect to the spatial coupling D. In other words, at variance with what one expects for equilibrium phase transitions, a large enough value of D favors disorder. Moreover, except for a small region in the parameter subspace determined by the noise intensity and D, an increase in the self-correlation time usually preventsthe formation of an ordered state. These effects are supported by numerical simulations.Comment: 15 pages. 9 figures. To appear in Phys.Rev.

Resonant phenomena in extended chaotic systems subject to external noise: the Lorenz'96 model case

We investigate the effects of a time-correlated noise on an extended chaotic system. The chosen model is the Lorenz'96, a kind of "toy" model used for climate studies. Through the analysis of the system's time evolution and its time and space correlations, we have obtained numerical evidence for two stochastic resonance-like behavior. Such behavior is seen when both, the usual and a generalized signal-to-noise ratio function are depicted as a function of the external noise intensity or the system size. The underlying mechanism seems to be associated to a "noise-induced chaos reduction". The possible relevance of these and other findings for an "optimal" climate prediction are discussed.Comment: Submitted to Europhysics Letters (LaTex, 12 pgs, 5 figures