The collective effect of large amounts of atoms exhibit an enhanced interaction between light and atoms. This holds great interest in quantum optics, and quantum information. When a collective excited state of a group of atoms during Rabi oscillation is varying, the oscillation exhibits rich dynamics. Here, we experimentally observe a size-reduction effect of the Rydberg collective state during Rabi oscillation in cold atomic dilute gases. The Rydberg collective state was first created by the Rydberg quantum memory, and we observed a decreased oscillation frequency effect by measuring the time traces of the retrieved light field amplitude, which exhibited chirped characteristics. This is caused by the simultaneous decay to the overall ground state and the overall loss of atoms. The observed oscillations are dependent on the effective Rabi frequency and detuning of the coupling laser, and the dephasing from inhomogeneous broadening. The reported results show the potential prospects of studying the dynamics of the collective effect of a large amount of atoms and manipulating a single-photon wave-packet based on the interaction between light and Rydberg atoms.

Quantum discord has been proposed as a resource responsible for the exponential speedup in deterministic quantum computation with one pure qubit (DQC1). Investigation of the quantum discord generated in DQC1 is of significant importance from a fundamental perspective. However, in practical applications of DQC1, qubits generally interact with the environment. Thus, it is also important to investigate the discord when DQC1 is implemented in a noisy environment. We implement DQC1 on an electron spin resonance (ESR) architecture in such an environment and nonzero quantum discord is observed. Furthermore, we find that the values of discord correspond to the values of purity α and quantum Fisher information, which reflect the power of the algorithm. Our results provide further evidence for the role of discord as a resource in DQC1 and are beneficial for understanding the origin of the power of quantum algorithms.

Environmental efficiency has become a key indicator in describing the capacity of regional resource utilization with consideration of the negative externality to nature. Notably, with the development of urban agglomerations all over the world, the role and strategy of efficiency measurement for cities should be reorganized to deal with the complex relationships among cities based on urban agglomerations. In this paper, we construct a set of data envelopment analysis (DEA) models based on a peer-evaluation mode with consideration to the cooperative relationships among cities within the same urban agglomeration together with the competitive relationships between different urban agglomerations. Then, this paper we analyze the environmental efficiency of 48 Chinese mainland cities belonging to the Beijing-Tianjin-Hebei Urban Agglomeration (BTHUA), Yangtze River Delta Urban Agglomerations (YRDUA), and Guangdong-Hong Kong-Macao Greater Bay Area (GHMGBA). This was accomplished during 2014 to 2019 by using four inputs, two desirable outputs, and two undesirable outputs. The results of efficiency scores indicate that the environmental efficiency trend increased during the time series from 2014 to 2019 while the difference on environmental efficiency among different cities and urban agglomerations are significant. The BTHUA is the best performing urban agglomeration with much higher environmental efficiency scores in all the years. Besides, this paper selected 11 influencing factors based on three different angles to analyze the internal and external environments to environmental efficiency scores for providing further inspiration to managers.

Social media has become an essential channel for increasing firm value. This study explores the impacts of social media operation (i.e., microblog and short video platforms) on firm value in the context of China. The research adopts the multi-stage propensity score matching (PSM) and differences-in-differences (DID) design, and the reseach results indicating that the operation of short video platforms for social media marketing can significantly increase firm value. However, the operation of microblogs for social media marketing insignificantly affects firm value. This means that the company’s operation of emerging social media platforms is of positive significance to firm value. Moreover, the conclusions of this study will guide the company's social media operations.

Extended t-process is robust to outliers and inherits many attractive properties from the Gaussian process. In this paper, we provide a function-on-function nonparametric random-effects model using extended t-process priors in which we consider heterogeneity of individual effect, flexible mean function, nonparametric covariance function and robustness. A likelihood-based estimation procedure is constructed to estimate parameters involved in the model. Information consistency for the parameter estimation is provided. Simulation studies and a real data example are further investigated to evaluate the performance of the developed procedures.

With the rapid reutilization of solid waste materials, it is imperative to investigate the properties of composite materials formed by the addition of solid waste materials. Basic foamed magnesium oxysulfate cementitious material(FMOCM) with and without solid waste materials were studied and compared. This study focused on the internal structures and quasi-static and dynamic mechanical properties of FMOCM. The results showed that the internal cavity structure of the FMOCM underwent significant changes, and the pore sizes became smaller owing to the addition of recycled materials and wood flour, which greatly improved the quasi-static strength of the FMOCM. It was found that the FMOCM had obvious strain rate effects. By comparing the dynamic strength factors, the dynamic strength of the regular FMOCM almost doubled, and the addition of solid waste materials weakened the strain rate effect. Only when the strain rate was lower did the FMOCM with solid waste materials show better toughness compared to the more serious fracture of the regular FMOCM. Furthermore, this study demonstrated the broad application prospects of solid waste materials in magnesium oxysulfide cementitious materials.

Visual features with high potential for generalization are critical for computer vision applications. In addition to the computational overhead associated with layer-by-layer feature stacking to produce multi-scale feature maps, existing approaches also incur high computational costs. To address this issue, we present a compact and efficient scale-in-scale convolution operator called SIS by incorporating an efficient progressive multi-scale architecture into a standard convolution operator. More precisely, the suggested operator uses the channel transform-divide-and-conquer technique to optimize conventional channel-wise computing, thereby lowering the computational cost while simultaneously expanding the receptive fields within a single convolution layer. Moreover, the proposed SIS operator incorporates weight-sharing with split-and-interact and recur-and-fuse mechanisms for enhanced variant design. The suggested SIS series is easily pluggable into any promising convolutional backbone, such as the well-known ResNet and Res2Net. Furthermore, we incorporated the proposed SIS operator series into 29-layer, 50-layer, and 101-layer ResNet as well as Res2Net variants and evaluated these modified models on the widely used CIFAR, PASCAL VOC, and COCO2017 benchmark datasets, where they consistently outperformed state-of-the-art models on a variety of major vision tasks, including image classification, key point estimation, semantic segmentation, and object detection.