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Neonatal epilepsy is a common emergency phenomenon in neonatal intensive care units (NICUs), which requires timely attention, early identification, and treatment. Traditional detection methods mostly use supervised learning with enormous labeled data. Hence, this study offers a semi-supervised hybrid architecture for detecting seizures, which combines the extracted electroencephalogram (EEG) feature dataset and convolutional autoencoder, called Fd-CAE. First, various features in the time domain and entropy domain are extracted to characterize the EEG signal, which helps distinguish epileptic seizures subsequently. Then, the unlabeled EEG features are fed into the convolutional autoencoder (CAE) for training, which effectively represents EEG features by optimizing the loss between the input and output features. This unsupervised feature learning process can better combine and optimize EEG features from unlabeled data. After that, the pre-trained encoder part of the model is used for further feature learning of labeled data to obtain its low-dimensional feature representation and achieve classification. This model is performed on the neonatal EEG dataset collected at the University of Helsinki Hospital, which has a high discriminative ability to detect seizures, with an accuracy of 92.34%, precision of 93.61%, recall rate of 98.74%, and F1-score of 95.77%, respectively. The results show that unsupervised learning by CAE is beneficial to the characterization of EEG signals, and the proposed Fd-CAE method significantly improves classification performance. [ABSTRACT FROM AUTHOR]

We investigate the dual-band unidirectional reflectionless phenomenon and near perfect absorption using high-order plasmon resonators at exceptional points based on near-field coupling in plasmonic waveguide system. The system consists of two high-order plasmon resonators end-coupled to a metal-insulator-metal plasmonic waveguide. The reflection for forward (backward) direction is close to 0.85 (0.74), while for backward (forward) direction is approximate to 0 (0) at a frequency of 199.8 THz (206.1 THz), and the quality factor of absorption spectrum is about 257.6 (217.2) at 206.1 THz (199.8 THz) for forward (backward) direction. [ABSTRACT FROM AUTHOR]

Tensor Robust Principal Component Analysis (TRPCA) has achieved promising results in the analysis of genomics data. However, the TRPCA model under the existing tensor singular value decomposition (t -SVD) framework insufficiently extracts the potential low-rank structure of the data, resulting in suboptimal restored components. Simultaneously, the tensor nuclear norm (TNN) defined based on t -SVD uses the same standard to handle various singular values. TNN ignores the difference of singular values, leading to the failure of the main information that needs to be well preserved. To preserve the heterogeneous structure in the low-rank information, we propose a novel TNN and extend it to the TRPCA model. Potential low-rank space may contain important information. We learn the low-rank structural information from the core tensor. The singular value space contains the association information between genes and cancers. The p -shrinkage generalized threshold function is utilized to preserve the low-rank properties of larger singular values. The optimization problem is solved by the alternating direction method of the multiplier (ADMM) algorithm. Clustering and feature selection experiments are performed on the TCGA data set. The experimental results show that the proposed model is more promising than other state-of-the-art tensor decomposition methods. [ABSTRACT FROM AUTHOR]

Epidemics usually spread widely and can cause a great deal of loss to humans. In the real world, vaccination is the principal method for suppressing the spread of infectious diseases. The Susceptible-Infected-Susceptible (SIS) model suggests that voluntary vaccination may affect the spread of an epidemic. Most studies to date have argued that the infection rates of nodes in the SIS model are not heterogeneous. However, in reality, there exist differences in the neighbor network structure and the number of contacts, which may affect the spread of infectious diseases in society. As a consequence, it can be reasonably assumed that the infection rate of the nodes is heterogeneous because of the amount of contact among people. Here, we propose an improved SIS model with heterogeneity in infection rates, proportional to the degree of nodes. By conducting simulations, we illustrate that almost all vaccinated nodes have high degrees when the infection rate is positively correlated with the degree of a node. These vaccinated nodes can divide the whole network into many connected sub-graphs, which significantly slows down the propagation of an epidemic; the heterogeneity of infection rates has a strong inhibitory effect on epidemic transmission. On the other hand, when the infection rate is negatively related to the degrees of the infection rate nodes, it is difficult for most nodes to meet the inoculation conditions, and the number of inoculations is close to zero. [ABSTRACT FROM AUTHOR]

Non-negative Matrix Factorization (NMF) is a popular data dimension reduction method in recent years. The traditional NMF method has high sensitivity to data noise. In the paper, we propose a model called Sparse Robust Graph-regularized Non-negative Matrix Factorization based on Correntropy (SGNMFC). The maximized correntropy replaces the traditional minimized Euclidean distance to improve the robustness of the algorithm. Through the kernel function, correntropy can give less weight to outliers and noise in data but give greater weight to meaningful data. Meanwhile, the geometry structure of the high-dimensional data is completely preserved in the low-dimensional manifold through the graph regularization. Feature selection and sample clustering are commonly used methods for analyzing genes. Sparse constraints are applied to the loss function to reduce matrix complexity and analysis difficulty. Comparing the other five similar methods, the effectiveness of the SGNMFC model is proved by selection of differentially expressed genes and sample clustering experiments in three The Cancer Genome Atlas (TCGA) datasets. [ABSTRACT FROM AUTHOR]

We design a structure to achieve a function of polarization-independent multi-band unidirectional reflectionlessness in a non-Hermitian metamaterial system based on the Fabry-Pérot resonance. All contrast ratios of reflectance at 198 THz, 214.2 THz, and 232.65 THz are 0.99. The unidirectional reflectionless peak position remains almost unchanged with increasing polarization angles. Besides, the structure can also be used to realize the unidirectional reflectionless phenomenon in the incident angle range of 0–30 ∘ , which may provide great convenience for experimental operations. [ABSTRACT FROM AUTHOR]

We investigate the strong gravitational lensing of spherically symmetric black holes in the novel Einstein–Gauss–Bonnet (EGB) gravity surrounded by unmagnetized plasma medium. The deflection angle in the strong deflection limit in EGB spacetime with homogeneous plasma is derived. We find that both the coupling constant α in the novel EGB gravity and the presence of plasma can affect the radius of photon sphere, strong field limit coefficient and other lensing observables significantly, while plasma has little effect on the angular image separation and the relative magnifications as α / M 2 → − 8 and α / M 2 → 1 , respectively. [ABSTRACT FROM AUTHOR]

Dual-band unidirectional reflectionlessness is investigated in a system consisting of three stub resonators side-coupled to a metal-insulator-metal plasmonic waveguide based on near-field coupling in terahertz domain. Reflectivities of ∼ 0 (∼ 0. 6 5) and ∼ 0 (∼ 0. 9 7) , respectively, at two exceptional points 4.11 THz and 4.695 THz are obtained for forward (backward) direction. More than that multi-band unidirectional reflectionlessness is demonstrated based on multi-stub resonators side-coupled to an MIM plasmonic waveguide. [ABSTRACT FROM AUTHOR]

We demonstrate the unidirectional reflectionlessness at exceptional points (EPs) and nonreciprocal perfect absorption near EPs based on phase coupling between two photonic crystal cavities (PCCs) in optical waveguide. In our scheme, when distance nm (nm), the reflectivities for forward and backward (backward and forward) directions are closed to and ( and ), respectively, and absorptances of the nonreciprocal perfect absorptions for forward and backward directions are and with the high quality factors of and , respectively. [ABSTRACT FROM AUTHOR]

We propose a narrow-dual-band metamaterial perfect absorber (MPA) made of metal-insulator-metal multilayer composite based on the coupling of two resonators. The absorptance of dual resonant peak all exceeding 95% at nm and 98% at nm ( is the length of 'left'-'right' pair), respectively, where the full absorption width at half-maximum is about 3% (low frequency) and 5% (high frequency). The narrow distance of dual resonant peak is 31.4THz together with 43.6THz when nm and 290nm, respectively. In addition, we demonstrate that the MPA can work as a sensitive sensor for refractive index sensing. The figure of merit FOM* reaches 197.7 (low frequency) and 274.8 (high frequency) when nm. The narrow-dual-band peak position can be controlled by changing as well. [ABSTRACT FROM AUTHOR]

Solitons in one-dimensional FPU- lattice chains were studied by the Jacobi elliptic function expansion method under the condition of quasi-continuum approximation. It is found that there exhibits a novel nonlinear elementary excitation, i.e. exact solitary solutions. On the basis of the above, the influence of the nonlinear intensity on the solitons was analyzed. It is found that the modulation amplitude of soliton is related closely to the nonlinear parameter also. [ABSTRACT FROM AUTHOR]

We demonstrate an, ultra-narrow-band perfect absorber based on high-order magnetic plasmonic resonance, which is polarization independent because of the ring element in the structure. When the thickness of MgF2 is 60nm, the absorption at frequency 424.5THz is close to 1, its full width at half maximum (FWHM) is 13nm. In our structure, a wavelength sensitivity about 190nm/RIU is achieved by utilizing the absorption peaks alter upon the refractive index change. In addition, we also discuss the figure of merit (FOM*) under different reflective index of sample surface. Therefore, the ultra-narrow-band perfect absorber will provide the great potential applications to filters and plasmonic refractive index sensors. [ABSTRACT FROM AUTHOR]

The classical electromagnetically-induced transparency (EIT)-like switching in metamaterials was experimentally demonstrated in the microwave-frequency region. The metameterial unit cell consists of two identical split-ring resonators, which are arranged on both sides of a dielectric substrate with 90°-rotation asymmetry. In our scheme, the classical EIT-like switching can be achieved by changing the polarization of the incident electromagnetic wave. [ABSTRACT FROM AUTHOR]

A modified form of nonlocally corrected theory of gravity is investigated in the context of cosmology and the Newtonian limit. This form of nonlocal correction to classic Einstein-Hilbert action can be locally represented by a triple-scalar-tensor theory in which one of the scalar degrees of freedom is phantom-like and the other two are quintessence-like. We show that there exists a stable de Sitter solution for the cosmological dynamics if a suitable form of potential function V(ϕ) (or equivalently, f(R)) is selected. However, no matter what a potential function is selected, there is always an early time repeller solution corresponding to a radiation dominated universe. Besides, the equations for linear scalar perturbations are presented and it is shown that the form of potential function V(ϕ) is stringently constrained by the solar system test, although the post-Newtonian parameter γ is not directly affected by this function. [ABSTRACT FROM AUTHOR]

Heat conduction in Fermi-Pasta-Ulam (FPU) dielectric atomic chains were studied by extended FKM formalism. We found that the FPU interactions between atoms have played an important role in quantum thermal transport. For small systems, the numerical simulations indicate that the heat current exhibits a kind of Fourier-like behaviors. In particular, the current is almost unaffected by the massive disorder at the fixed-free boundaries. [ABSTRACT FROM AUTHOR]

Heat conduction in dielectric atomic chains with on-site potential were studied by means of FKM formalism. Using numerical simulation we found that the on-site potential plays an important role in quantum thermal transport. As special cases, the "Fourier-like behavior" J ∝ 1/N was obtained also for different boundary conditions. The influence of boundaries can be regulated by the coupling strength coefficient of the on-site potential. [ABSTRACT FROM AUTHOR]

Thermal entanglement of a two-qubit Heisenberg XXZ chain in the presence of different Dzyaloshinskii–Moriya (DM) anisotropic antisymmetric interactions and entanglement teleportation using two independent Heisenberg chains as quantum channel are investigated. It is found that the anisotropic coupling coefficient Jz (z-component exchange constant) and DM interactions can excite the entanglement, and x-component DM interaction Dx has a more remarkable influence than the z-axis DM interaction Dz for exchange constant J > 0 (antiferromagnetic) case, which is contrary to coupling coefficient J < 0 (ferromagnetic) case. The output entanglement and fidelity increase with increasing z-axis coupling parameter Jz for both the antiferromagnetic J > 0 case and ferromagnetic J < 0 case. By introducing the different DM interactions, it is superior to teleportate initial state by using the Dz interaction in the model for J > 0 case. But for J < 0 case, the Dx interaction is better, and the output concurrence and fidelity can reach the maximum value 1 with suitable Dx. [ABSTRACT FROM AUTHOR]

We give a complete numerical classification for pairs (S, G) consisting of complex nonsingular projective surfaces S of general type with a fibration of genus 2 and non-trivial subgroups G of automorphisms of S inducing trivial actions on H2(S, ℚ). [ABSTRACT FROM AUTHOR]

Although the density peak clustering (DPC) algorithm can effectively distribute samples and quickly identify noise points, it lacks adaptability and cannot consider the local data structure. In addition, clustering algorithms generally suffer from high time complexity. Prior research suggests that clustering algorithms grounded in P systems can mitigate time complexity concerns. Within the realm of membrane systems (P systems), spiking neural P systems (SN P systems), inspired by biological nervous systems, are third-generation neural networks that possess intricate structures and offer substantial parallelism advantages. Thus, this study first improved the DPC by introducing the maximum nearest neighbor distance and K-nearest neighbors (KNN). Moreover, a method based on delayed spiking neural P systems (DSN P systems) was proposed to improve the performance of the algorithm. Subsequently, the DSNP-ANDPC algorithm was proposed. The effectiveness of DSNP–ANDPC was evaluated through comprehensive evaluations across four synthetic datasets and 10 real-world datasets. The proposed method outperformed the other comparison methods in most cases. [ABSTRACT FROM AUTHOR]