15 research outputs found

    Ground-state phase diagram of two-component interacting bosons on a two-leg ladder

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    Using the cluster Gutzwiller mean-field method, we numerically study the ground-state phase diagram of the non-hard-core two-component interacting bosons trapped in a two-leg ladder with and without an artificial magnetic field. Interestingly, several loophole supercounterfluid (SCF) phases are observed at a sufficiently small intra- to inter-leg hopping ratio when the magnetic flux is absent. While if the ratio is not too small, the loophole SCF phases can be induced by the effect of the magnetic flux as well. Additionally, we also find that the presence of the magnetic flux leads to an enlargement of the Mott insulator lobe and the conventional SCF lobe. We hope these results can improve the understanding of the interplay between lattice gases, gauge fields, and bosonic ladder systems.Comment: 9 pages, 5 figure

    Sweeping cluster algorithm for quantum spin systems with strong geometric restrictions

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    Quantum spin systems with strong geometric restrictions give rise to rich quantum phases such as valence bond solids and spin liquid states. However, the geometric restrictions often hamper the application of sophisticated numerical approaches. Based on the stochastic series expansion method, we develop an efficient and exact quantum Monte Carlo "sweeping cluster" algorithm which automatically satisfies the geometrical restrictions. Here we use the quantum dimer model as a benchmark to demonstrate the reliability and power of this algorithm. Comparing to existing numerical methods, we can obtain higher accuracy results for a wider parameter region and much more substantial system sizes

    Ground state properties of a multi-component bosonic mixture: a Gutzwiller mean-field study

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    Using the single-site Gutzwiller method, we theoretically study the ground state and the interspecies entanglement properties of interexchange symmetric multi-component (two- and three-) bosonic mixtures in an optical lattice, and the results are generalized to an nn-component (n=2,3,4,⋯n=2,3,4,\cdots) system. We compute the mean-field phase diagram, the interspecies entanglement entropy, and the ground state spectral decomposition. Three phases namely the nn-component Superfluid state (nSF), the nn-component Mott insulator state (nMI), and the Super-counter-fluid state (SCF) are observed. Interestingly, we find that there are n−1n-1 SCF lobes to separate every two neighboring nMI lobes in the phase diagram. More importantly, we derive the exact general expression of the interspecies entanglement entropy for the SCF phase. In addition, we also investigate the demixing effect of an n-component mixture and demonstrate that the mixing-demixing critical point is independent of n.Comment: 12 pages, 6 figure

    Ginsenosides on stem cells fate specification—a novel perspective

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    Recent studies have demonstrated that stem cells have attracted much attention due to their special abilities of proliferation, differentiation and self-renewal, and are of great significance in regenerative medicine and anti-aging research. Hence, finding natural medicines that intervene the fate specification of stem cells has become a priority. Ginsenosides, the key components of natural botanical ginseng, have been extensively studied for versatile effects, such as regulating stem cells function and resisting aging. This review aims to summarize recent progression regarding the impact of ginsenosides on the behavior of adult stem cells, particularly from the perspective of proliferation, differentiation and self-renewal

    NcPuf1 Is a Key Virulence Factor in Neospora caninum

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    Background: Neospora caninum is an apicomplexan parasite that infects many mammals and particularly causes abortion in cattle. The key factors in its wide distribution are its virulence and ability to transform between tachyzoite and bradyzoite forms. However, the factors are not well understood. Although Puf protein (named after Pumilio from Drosophila melanogaster and fem-3 binding factor from Caenorhabditis elegans) have a functionally conserved role in promoting proliferation and inhibiting differentiation in many eukaryotes, the function of the Puf proteins in N. caninum is poorly understood. Methods: The CRISPR/CAS9 system was used to identify and study the function of the Puf protein in N. caninum. Results: We showed that N. caninum encodes a Puf protein, which was designated NcPuf1. NcPuf1 is found in the cytoplasm in intracellular parasites and in processing bodies (P-bodies), which are reported for the first time in N. caninum in extracellular parasites. NcPuf1 is not needed for the formation of P-bodies in N. caninum. The deletion of NcPuf1 (ΔNcPuf1) does not affect the differentiation in vitro and tissue cysts formation in the mouse brain. However, ΔNcPuf1 resulted in decreases in the proliferative capacity of N. caninum in vitro and virulence in mice. Conclusions: Altogether, the disruption of NcPuf1 does not affect bradyzoites differentiation, but seriously impairs tachyzoite proliferation in vitro and virulence in mice. These results can provide a theoretical basis for the development of attenuated vaccines to prevent the infection of N. caninum

    Cloud Storage Strategy of Blockchain Based on Genetic Prediction Dynamic Files

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    With the rapid expansion of data volume, traditional data storage methods have been unable to meet the practical application requirements of blockchain cloud storage. Aiming for the cloud storage problem of blockchain, a new storage access method for predicting dynamic file load is proposed. By predicting the load status of cloud storage files in advance, the load of each blockchain data node at the next moment is first estimated. A hierarchical genetic algorithm is used to construct the connection weights between the hidden layer and the output layer, which makes the data network converge faster and more accurate, thereby effectively predicting the node load. In addition, based on the file allocation, an evaluation analysis model is constructed to obtain the time response capability of each file during the allocation process. The node’s periodic load prediction value is used to calculate the corresponding weight of the node and it is continuously updated, retaining the advantages of the static weighted polling algorithm. Combined with the genetic algorithm to help predict the file assignment access strategy of the later load of each node, it can meet the system requirements under complex load conditions and provide a reasonable and effective cloud storage method. The experimental evaluation of the proposed new strategy and new algorithm verifies that the new storage method has a faster response time, more balanced load, and greatly reduced energy consumption

    Real-Time Location-Based Rendering of Urban Underground Pipelines

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    The concealment and complex spatial relationships of urban underground pipelines present challenges in managing them. Recently, augmented reality (AR) has been a hot topic around the world, because it can enhance our perception of reality by overlaying information about the environment and its objects onto the real world. Using AR, underground pipelines can be displayed accurately, intuitively, and in real time. We analyzed the characteristics of AR and their application in underground pipeline management. We mainly focused on the AR pipeline rendering procedure based on the BeiDou Navigation Satellite System (BDS) and simultaneous localization and mapping (SLAM) technology. First, in aiming to improve the spatial accuracy of pipeline rendering, we used differential corrections received from the Ground-Based Augmentation System to compute the precise coordinates of users in real time, which helped us accurately retrieve and draw pipelines near the users, and by scene recognition the accuracy can be further improved. Second, in terms of pipeline rendering, we used Visual-Inertial Odometry (VIO) to track the rendered objects and made some improvements to visual effects, which can provide steady dynamic tracking of pipelines even in relatively markerless environments and outdoors. Finally, we used the occlusion method based on real-time 3D reconstruction to realistically express the immersion effect of underground pipelines. We compared our methods to the existing methods and concluded that the method proposed in this research improves the spatial accuracy of pipeline rendering and the portability of the equipment. Moreover, the updating of our rendering procedure corresponded with the moving of the user’s location, thus we achieved a dynamic rendering of pipelines in the real environment
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