Topologically protected mid-gap states induced by impurity in one-dimensional superlattices

Based on the discovery of the nontrivial topology of one-dimensional superlattices, we show that midgap states will emerge in such systems induced by a single on-site impurity. Besides the trivial bound state located at the impurity site, these midgap states are localized at the adjacent sides of the impurity, carrying the information of the topology and behaving like the effect of the open boundary conditions in the limit of a large attractive or repulsive impurity potential. Using this feature, the impurity can be used to detect the topology of the superlattice system and to realize the adiabatic pumping between the opposite sides of the impurity in cold-atom experiments or in photonic crystals.Comment: 5 pages, 6 figure

Generalized fuzzy rough sets based on fuzzy coverings

This paper further studies the fuzzy rough sets based on fuzzy coverings. We first present the notions of the lower and upper approximation operators based on fuzzy coverings and derive their basic properties. To facilitate the computation of fuzzy coverings for fuzzy covering rough sets, the concepts of fuzzy subcoverings, the reducible and intersectional elements, the union and intersection operations are provided and their properties are discussed in detail. Afterwards, we introduce the concepts of consistent functions and fuzzy covering mappings and provide a basic theoretical foundation for the communication between fuzzy covering information systems. In addition, the notion of homomorphisms is proposed to reveal the relationship between fuzzy covering information systems. We show how large-scale fuzzy covering information systems and dynamic fuzzy covering information systems can be converted into small-scale ones by means of homomorphisms. Finally, an illustrative example is employed to show that the attribute reduction can be simplified significantly by our proposed approach

Collaborative Self-Attention for Recommender Systems

Recommender systems (RS), which have been an essential part in a wide range of applications, can be formulated as a matrix completion (MC) problem. To boost the performance of MC, matrix completion with side information, called inductive matrix completion (IMC), was further proposed. In real applications, the factorized version of IMC is more favored due to its efficiency of optimization and implementation. Regarding the factorized version, traditional IMC method can be interpreted as learning an individual representation for each feature, which is independent from each other. Moreover, representations for the same features are shared across all users/items. However, the independent characteristic for features and shared characteristic for the same features across all users/items may limit the expressiveness of the model. The limitation also exists in variants of IMC, such as deep learning based IMC models. To break the limitation, we generalize recent advances of self-attention mechanism to IMC and propose a context-aware model called collaborative self-attention (CSA), which can jointly learn context-aware representations for features and perform inductive matrix completion process. Extensive experiments on three large-scale datasets from real RS applications demonstrate effectiveness of CSA.Comment: There are large modification

Linear temperature behavior of thermopower and strong electron-electron scattering in thick F-doped SnO2_{2} films

Both the semi-classical and quantum transport properties of F-doped SnO$_2$ thick films ($\sim$1\,$\mu$m) were investigated experimentally. It is found that the resistivity caused by the thermal phonons obeys Bloch-Gr\"{u}neisen law from $\sim$90 to 300\,K, while only the diffusive thermopower, which varies linearly with temperature from 300 down to 10\,K, can be observed.The phonon-drag thermopower is completely suppressed due to the long electron-phonon relaxation time in the compound. These observations, together with the temperature independent characteristic of carrier concentration, indicate that the conduction electron in F-doped SnO$_2$ films behaves essentially like a free electron. At low temperatures, the electron-electron scattering dominates over the electron-phonon scattering and governs the inelastic scattering process. The theoretical predicated scattering rates for both large- and small-energy-transfer electron-electron scattering processes, which are negligibly weak in three-dimensional disordered conventional conductors, are quantitatively tested in this lower carrier concentration and free-electron-like highly degenerate semiconductor

Market Dynamics and Indirect Network Effects in Electric Vehicle Diffusion

The diffusion of electric vehicles (EVs) is studied in a two-sided market framework consisting of EVs on the one side and EV charging stations (EVCSs) on the other. A sequential game is introduced as a model for the interactions between an EVCS investor and EV consumers. A consumer chooses to purchase an EV or a conventional gasoline alternative based on the upfront costs of purchase, the future operating costs and the availability of charging stations. The investor, on the other hand, maximizes his profit by deciding whether to build charging facilities at a set of potential EVCS sites or to defer his investments. The solution of the sequential game characterizes the EV-EVCS market equilibrium. The market solution is compared with that of a social planner who invests in EVCSs with the goal of maximizing the social welfare. It is shown that the market solution underinvests EVCSs, leading to slower EV diffusion. The effects of subsidies for EV purchase and EVCSs are also considered.Comment: 20 pages, 8 figures, journal pape

Drug-drug interaction prediction based on co-medication patterns and graph matching

Background: The problem of predicting whether a drug combination of arbitrary orders is likely to induce adverse drug reactions is considered in this manuscript. Methods: Novel kernels over drug combinations of arbitrary orders are developed within support vector machines for the prediction. Graph matching methods are used in the novel kernels to measure the similarities among drug combinations, in which drug co-medication patterns are leveraged to measure single drug similarities. Results: The experimental results on a real-world dataset demonstrated that the new kernels achieve an area under the curve (AUC) value 0.912 for the prediction problem. Conclusions: The new methods with drug co-medication based single drug similarities can accurately predict whether a drug combination is likely to induce adverse drug reactions of interest. Keywords: drug-drug interaction prediction; drug combination similarity; co-medication; graph matchin

Large time behavior of solutions for a Cauchy problem on nonlinear conservation laws with large initial data in the whole space

We consider the Cauchy problem on a nonlinear conversation law with large initial data. By Green's function methods, energy methods, Fourier analysis, frequency decomposition, pseudo-differential operators, we obtain the global existence and the optimal decay estimate of $t$.Comment: 32 page

Multi-interactive Dual-decoder for RGB-thermal Salient Object Detection

RGB-thermal salient object detection (SOD) aims to segment the common prominent regions of visible image and corresponding thermal infrared image that we call it RGBT SOD. Existing methods don't fully explore and exploit the potentials of complementarity of different modalities and multi-type cues of image contents, which play a vital role in achieving accurate results. In this paper, we propose a multi-interactive dual-decoder to mine and model the multi-type interactions for accurate RGBT SOD. In specific, we first encode two modalities into multi-level multi-modal feature representations. Then, we design a novel dual-decoder to conduct the interactions of multi-level features, two modalities and global contexts. With these interactions, our method works well in diversely challenging scenarios even in the presence of invalid modality. Finally, we carry out extensive experiments on public RGBT and RGBD SOD datasets, and the results show that the proposed method achieves the outstanding performance against state-of-the-art algorithms. The source code has been released at:https://github.com/lz118/Multi-interactive-Dual-decoder.Comment: Accepted by IEEE TI

The \sigma law of evolutionary dynamics in community-structured populations

Evolutionary game dynamics in finite populations provides a new framework to understand the selection of traits with frequency-dependent fitness. Recently, a simple but fundamental law of evolutionary dynamics, which we call {\sigma} law, describes how to determine the selection between two competing strategies: in most evolutionary processes with two strategies, A and B, strategy A is favored over B in weak selection if and only if {\sigma}R + S > T + {\sigma}P. This relationship holds for a wide variety of structured populations with mutation rate and weak selection under certain assumptions. In this paper, we propose a model of games based on a community-structured population and revisit this law under the Moran process. By calculating the average payoffs of A and B individuals with the method of effective sojourn time, we find that {\sigma} features not only the structured population characteristics but also the reaction rate between individuals. That's to say, an interaction between two individuals are not uniform, and we can take {\sigma} as a reaction rate between any two individuals with the same strategy. We verify this viewpoint by the modified replicator equation with non-uniform interaction rates in a simplified version of the prisoner's dilemma game (PDG).Comment: 11 pages, 3 figures;Accepted by JT

Chiral d-wave superfluid in periodically driven lattices

Chiral d-wave superfluid is a preliminary example of topological matters that intrinsically encodes interaction effects. It exhibits fascinating properties including a finite Chern number in the bulk and topologically protected edge states, which have been invoking physicists for decades. However, unlike s-wave superfluids prevalent in nature, its existence requires a strong interaction in the d-wave channel, a criterion that is difficult to access in ordinary systems. So far, such an unconventional superfluid has not been discovered in experiments. Here, we present a new principle for creating a two-dimensional chiral d-wave superfluid using periodically driven lattices. Due to an imprinted two-dimensional pseudospin-orbit coupling, where the sublattice index serves as the pseudospin, s-wave interaction between two hyperfine spin states naturally creates a chiral d-wave superfluid. This scheme also allows physicists to study the phase transition between the topologically distinct s- and d-wave superfluids by controlling the driving field or the particle density.Comment: 10pages, 7figure