We study the semileptonic decaysBc-→(ηc,J/ψ)l-■lusing the PQCD factorization approach with the newly defined distribution amplitudes of the B c meson and a new kind of parametrization for extrapolating the form fa...
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We study the semileptonic decaysBc-→(ηc,J/ψ)l-■lusing the PQCD factorization approach with the newly defined distribution amplitudes of the B c meson and a new kind of parametrization for extrapolating the form factors which takes into account the recent lattice QCD *** find the following main results:(a)the PQCD predictions of the branching ratios of theBc→(ηc,J/ψ)l■decays are smaller by about 5%-16%when the lattice results are taken into account in the extrapolation of the relevant form factors;(b)the PQCD predictions of the ratio Rηc,RJ/ψand of the longitudinal polarization PτareRηc=0.34±0.01,RJ/ψ=0.28±0.01,Pτ(ηc)=0.37±0.01and Pτ(J/ψ)=-0.55±0.01;and(c)after including the lattice results,the theoretical predictions slightly change:Rηc=0.31±0.01,RJ/ψ=0.27±0.01,Pτ(ηc)=0.36±0.01andPτ(J/ψ)=-0.53±*** theoretical predictions of RJ/ψagree with the measurements within the *** other predictions could be tested by the LHCb experiment in the near future.
Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to direct...
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Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.
We study the effects of infinite-range (IR) interaction on the localization properties of one-dimensional disordered harmonic chains. Two kinds of disordered models are considered: one is with disordered masses, but c...
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We study the effects of infinite-range (IR) interaction on the localization properties of one-dimensional disordered harmonic chains. Two kinds of disordered models are considered: one is with disordered masses, but constant spring coefficient (mass model), and the other is with disordered spring coefficient, but constant mass (spring model). It is found that the IR interaction induces a gap between the ω=0 and the excited frequency band for both types of disordered models, and their gaps are both proportional to the IR interaction coefficient γ for larger γ. In addition, the width of the excited frequency band of the mass model is also proportional to γ for larger γ, while that of the spring model is independent of γ. By employing the normalized participation ratio, we find that the low-frequency modes of the mass model except for the lowest frequency change from extended to localized states, while the localized properties of the spring model modes remain unchanged. We also discuss the effects of IR interaction on the dynamic behaviors of the two kinds of disordered models.
With the development of urbanization,the number of residents' motor vehicles has increased sharply,and traffic congestion problem has become increasingly *** construction of Intelligent Traffic System(ITS) has bec...
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With the development of urbanization,the number of residents' motor vehicles has increased sharply,and traffic congestion problem has become increasingly *** construction of Intelligent Traffic System(ITS) has become the main means to alleviate traffic ***-term traffic flow prediction has guiding significance for residents' travel planning and intelligent management of transportation,and has become one of the research hotspots in intelligent transportation ***,A short-term traffic flow prediction method based on the spatio-temporal characteristics of complex road networks is proposed to further improve the prediction accuracy and reduce the prediction ***,a graph convolutional network(GCN) capable of processing non-Euclidean data structures is used to extract the spatial characteristics of traffic flow ***,the long and short-term memory(LSTM) neural network is used to process the time ***,the two are combined to realize the effective processing of the spatio-temporal characteristics of traffic flow *** results on the real traffic flow dataset prove the feasibility and effectiveness of the proposed method,and can provide a basis for intelligent traffic control and smart city construction.
We explore the eigenenergy distribution, localization transition, and topological property of a one-dimensional non-Hermitian lattice with a slowly varying potential, which does not possess parity-time (PT) symmetry. ...
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We explore the eigenenergy distribution, localization transition, and topological property of a one-dimensional non-Hermitian lattice with a slowly varying potential, which does not possess parity-time (PT) symmetry. We found that, in contrast to PT-symmetric systems whose eigenenergies can stay real until the PT-symmetry breaking point, the eigenenergies in the present system are fully complex and their distribution in the complex plane depends on the parameters. As non-Hermiticity is introduced into the system, also depending on the parameters, the eigenstates may show a crossover behavior from fully extended to fully localized as non-Hermiticity is increased, or there will be a sharp localization transition at finite non-Hermiticity. Nevertheless, this non-Hermitian system is proven to be topologically trivial, thus we conclude that in general non-Hermitian systems, the localization transition is not always of a topological nature.
This study aims to explore the effects of different human-machine interfaces, system performance, and robot interaction modalities on over-trust in chat companion robot systems. We designed and implemented three types...
ISBN:
(纸本)9798400708831
This study aims to explore the effects of different human-machine interfaces, system performance, and robot interaction modalities on over-trust in chat companion robot systems. We designed and implemented three types of interfaces: 2D Virtual Interface + Virtual Robot, 3D Augmented Reality Interface + AR-based Virtual Robot, and 3D Real World + NAO Physical Robot. We also manipulated the system performance (high or low) and the robot interaction modality (language, gesture, or both). We conducted a user study with 30 participants, who interacted with the chat companion robot under different conditions and rated their trust, distrust, and human-robot distance. We also measured the user experience in terms of usefulness and ease of use. The results showed that the type of interface significantly influenced the trust, distrust, and human-robot distance of the users, and that the 3D augmented reality interface was the most effective in enhancing trust and reducing distrust and distance. The performance of the system also affected the trust and distance of the users, and the gesture interface was the most sensitive to the performance variation. The modality of the interaction did not have a significant impact on the dependent variables. The user experience ratings also indicated that the 3D augmented reality interface was the most useful and easy to use. The implications and limitations of these findings are discussed in the paper.
The phase behavior of symmetric diblock copolymers under three-dimensional (3D) soft confinement is investigated using the self-consistent field theory. The soft confinement is realized in binary blends composed AB di...
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The contribution of our paper is a new simple method for transfer-function matrices derivation in two-dimensional digital systems from Roesser’s model is given. The main idea of this method is changing the form of th...
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We study the quantum phase transitions (QPTs) in extended Kitaev chains with long-range (1/rα) hopping. Formally, there are two QPT points at µ = µ0(α) and µπ(α) (µ is the chemical potential) w...
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A wide part of scientific research in the food-packaging sector has shown interesting challenges in assuring food shelf-life extension. Conventional plastic is mostly used for food packaging, hence has major environme...
A wide part of scientific research in the food-packaging sector has shown interesting challenges in assuring food shelf-life extension. Conventional plastic is mostly used for food packaging, hence has major environmental drawbacks by being non-degradable and accumulating over the years due to its elimination process. Biodegradable food packaging polymers have contributed to overcoming these challenges and diverted from the environmental concern. In the light of the sustainable development goals, implementing green technology in current industries help secure the consumer's safety by minimizing food loss and reducing plastic waste, thus attaining environmental sustainability. Whey protein isolate (WPI) has been considerably investigated lately and used in packaging formulation for its functional properties. This work aims to produce a biopolymer film destined for food packaging based on the crosslinking of whey protein isolate using glycerol as a plasticizer. The thermal properties of the film samples were investigated. Other aspects of the WPI biopolymer can be studied for other potential uses, more additives can be added to develop further properties depending on the final use of the film. The developed polymer can potentially be used in the food packaging industry under various conservation conditions.
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