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It has been found in previous works [M. Baldo and K. Fukukawa, Phys. Rev. Lett.113, 241501 (2014); K. Fukukawa, M. Baldo, G. F. Burgio, L. Lo Monaco and H.-J. Schulze, Phys. Rev.92, 065802 (2015)] that the nucleon–nucleon potential of [Y. Fujiwara, M. Kohno, C. Nakamoto and Y. Suzuki Phys. Rev. C64, 054001 (2001); Y. Fujiwara et al., Phys. Rev. C65, 014002 (2001)] gives an accurate saturation point in symmetric nuclear matter once the three hole-line contributions are included in the Brueckner–Bethe–Goldstone expansion without the addition of three-body forces in the nuclear Hamiltonian. The potential is based on a quark model of nucleons and on the quark–quark interaction together with quark exchange processes. These features introduce an intrinsic nonlocality of the nucleon–nucleon interaction. In order to clarify the role of the quark degrees of freedom and of the nonlocality in the saturation, we perform a comparative study of this potential and the traditional meson exchange models, exemplified in the CD-Bonn potential. We find that at the Brueckner–Hartree–Fock approximation, which corresponds to the two hole-line level of approximation, the dominant modification of the nucleon–nucleon interaction with respect to CD-Bonn is incorporated in the s-wave channels, where the quark degrees of freedom should be more relevant, in particular for the short range quark exchange processes. However, when the three hole-line contribution is included, we find that the higher partial waves play a relevant role, mainly in the term that describes the effect of the medium on the off-shell propagation of the nucleon. [ABSTRACT FROM AUTHOR]

Electroencephalogram (EEG) is a fundamental and unique tool for exploring human brain activity in general and epileptic mechanism in particular. It offers significant information about epileptic seizures source known as epileptogenic area. However, it is often complicated to detect critical changes in EEG signals by visual examination, since this signal aspect of epileptic persons seems to be normal out of the seizure. Thus, the challenge is to design such a robust and automatic system to detect these unseen changes and use them for diagnosis. In this research, we apply the Artificial Metaplasticity Multi-Layer Perceptron (AMMLP) together with discrete wavelet transform (DWT) to Bonn EEG signals for seizure detection goal. Significant features were then extracted from the well-known EEG brainwaves. Aiming to decrease the computational time and improve classification accuracy, we performed a features ranking and selection employing the Relief algorithm. The obtained AMMLP classification accuracy of 98.97% proved the effctiveness of the applied approach. Our results were compared to recent researches results on the same database, proving to be superior or at least an interesting alternative for seizures detection within EEG signals. [ABSTRACT FROM AUTHOR]

Feature selection plays a vital role in the detection and discrimination of epileptic seizures in electroencephalogram (EEG) signals. The state-of-the-art EEG classification techniques commonly entail the extraction of the multiple features that would be fed into classifiers. For some techniques, the feature selection strategies have been used to reduce the dimensionality of the entire feature space. However, most of these approaches focus on the performance of classifiers while neglecting the association between the feature and the EEG activity itself. To enhance the inner relationship between the feature subset and the epileptic EEG task with a promising classification accuracy, we propose a machine learning-based pipeline using a novel feature selection algorithm built upon a knockoff filter. First, a number of temporal, spectral, and spatial features are extracted from the raw EEG signals. Second, the proposed feature selection algorithm is exploited to obtain the optimal subgroup of features. Afterwards, three classifiers including k -nearest neighbor (KNN), random forest (RF) and support vector machine (SVM) are used. The experimental results on the Bonn dataset demonstrate that the proposed approach outperforms the state-of-the-art techniques, with accuracy as high as 99.93% for normal and interictal EEG discrimination and 98.95% for interictal and ictal EEG classification. Meanwhile, it has achieved satisfactory sensitivity (95.67% in average), specificity (98.83% in average), and accuracy (98.89% in average) over the Freiburg dataset. [ABSTRACT FROM AUTHOR]

The properties of neutron star are studied in the framework of relativistic Hartree–Fock (RHF) model with realistic nucleon–nucleon (NN) interactions, i.e., Bonn potentials. The strong repulsion of NN interaction at short range is properly removed by the unitary correlation operator method (UCOM). Meanwhile, the tensor correlation is neglected due to the very rich neutron environment in neutron star, where the total isospin of two nucleons can be approximately regarded as T = 1. The equations of state of neutron star matter are calculated in β equilibrium and charge neutrality conditions. The properties of neutron star, such as mass, radius and tidal deformability, are obtained by solving the Tolman–Oppenheimer–Volkoff equation and tidal equation. The maximum masses of neutron from Bonn A, B, C potentials are around 2. 2 M ⊙ . The radius are 1 2. 4 0 − 1 2. 9 1 km at 1. 4 M ⊙ , respectively. The corresponding tidal deformabilities are Λ 1. 4 = 2 9 3 − 3 5 5. All of these properties are satisfied with the recent observables from the astronomical and gravitational wave devices and are consistent with the results from the relativistic Brueckner–Hartree–Fock model. [ABSTRACT FROM AUTHOR]

We investigate the equation of state (EOS) and the corresponding sound velocity of the dense matter in hybrid neutron stars. For the hadron matter, the Bruckner–Hartree–Fock (BHF) many-body theory with Bonn-B potential is adopted. For the quark matter, the Dyson–Schwinger quark model is adopted, with the rainbow approximation and the Gaussian type effective interaction for quark–gluon vertex and gluon propagator. The phase transition is considered with both Maxwell condition and Gibbs condition. Then, the sound velocity in the pure hadron phase, pure quark phase and the mixed phase are obtained. The causality requirement c s 2 ≤ 1 puts a strong constraint on the EOS from BHF theory. In quark matter, it is found that c s 2 ≤ 1 / 3 and varies slowly. In the mixed phase with Gibbs condition, the sound velocity varies strongly and nonmonotonically. [ABSTRACT FROM AUTHOR]