Edge States and Quantum Hall Effect in Graphene under a Modulated Magnetic Field

Graphene properties can be manipulated by a periodic potential. Based on the tight-binding model, we study graphene under a one-dimensional (1D) modulated magnetic field which contains both a uniform and a staggered component. New chiral current-carrying edge states are generated at the interfaces where the staggered component changes direction. These edge states lead to an unusual integer quantum Hall effect (QHE) in graphene, which can be observed experimentally by a standard four-terminal Hall measurement. When Zeeman spin splitting is considered, a novel state is predicted where the electron edge currents with opposite polarization propagate in the opposite directions at one sample boundary, whereas propagate in the same directions at the other sample boundary.Comment: 5 pages, 4 figure

Value co-creation characteristics and creativity-oriented customer citizenship behavior

For the competitive advantage of service organization, it is important to improve the creative performance of human resources in the organization. For example, when employees perform creatively, in other words, if they generate novel and useful ideas, it will contribute to organizational competiveness. Therefore, there has been an increased focus in identifying its antecedents and consequences. Unfortunately, little is known about the creative performance of customers. According to service-centered dominant logic, customer is the value co-creator, it emphasizes co-opting customer involvement in the value creation process as an additional human resource. In addition, customers can be a valuable resource for service improvement efforts for firms. For instance, companies might benefit greatly from customer feedback and complaints regarding their offerings and can enhance their productivity in terms of quality and quantity. In this paper, the type of novel, creative-oriented customer behaviors highlighted in the preceding paragraph are referred to as creativity-oriented customer citizenship behaviors (CCBs). In the customer value co-creation context, creative-oriented CCBs refer to extra-role efforts by customers with regards the development of ideas about products, practices, services, and procedures that are novel and potentially useful to a firm. According to the intrinsic motivation perspective, the context in which customers create values, influences their intrinsic motivation, which in turn affects creativity-oriented CCBs. The intrinsic motivation perspective suggests that high intrinsic motivation is affected by information from both task characteristics (i.e., autonomy) and social characteristics (e.g., supplier support). Specifically, complex and challenging task characteristics such as high levels of variety, identity, significance, autonomy, and feedback are expected to increase customer intrinsic motivation. Under these conditions, customers should increase the likelihood of creativity-oriented CCBs. Therefore, customers are expected to be most creative when they experience a high level of intrinsic motivation. In contrast, complex and challenging task and social characteristics can have the opposite effect to customers. For example, in a high level of variety task, increased autonomy can lead to increased workload because they must take on related extra responsibilities and accountability. Increased workload, in turn, is expected to lead to decreased likelihood of creativity-oriented CCBs. Therefore, this study attempts to explore the impact of task characteristics and social characteristics on creativity-oriented CCBs. Furthermore, a substantial body of research has examined the possibility that creativity is affected by personal characteristics. As such, in addition to the relevant task and social characteristics, the moderating influence of several trait variables is also considered. This article makes several contributions. First, this study investigates the trade-off effect of the customer value co-creation related task and social characteristics by examining the underlying opposing mechanism of motivation and work overload. Second, this research provides a deeper understanding of contingency factors that systematically strengthen the relationships under consideration. Third, this study may indicate that companies seek to promote the creativity of their industrial customers and should design the tasks and social characteristics of their industrial customers in a way that maximizes their creativity. But, companies should be aware of the negative impact of specific tasks and social characteristics that may minimize the creativity of industrial customers

Phase control of spatial interference from two duplicated two-level atoms

We report the phase control of spatial interference of resonance fluorescence from two duplicated two-level atoms, driving by two orthogonally polarized fields. In this closed-loop system, the relative phase is of crucial importance to the recovery of the interference patten in the fluorescence light even with strong driving.In order to improve the experimental realizability, we propose a scheme to recover the visibility with fixed relative phase by adjusting the relative intensities between the two driving fields or alternatively by using a standing-wave field.Comment: 5 pages, 3 figure

White Matter Hyperintensity and Multi-region Brain MRI Segmentation Using Convolutional Neural Network

Accurate segmentation of WMH (white matter hyperintensity) from the magnetic resonance image is a prerequisite for many precise medical procedures, especially for the diagnosis of vascular dementia. Brain segmentation has important research significance and clinical application prospects especially for early detection of Alzheimer’s disease. In order to effectively perform accurate segmentation according to the MRI characteristics of different regions of the brain, this thesis proposed an optimized 3D u-net and used WHM segmentation as a pre-experiment to select the good hyperparameters (i.e. network depth, image fusion method, and the implementation of loss function) to construct an image feature learning network with both long and short skip connections. Soft voting is used as the postprocessing procedure. Our model is evaluated by a 10-fold cross-validation and achieved a dice score of 0.78 for binary segmentation (WMH segmentation) and accuracy of 0.96 for multi-class segmentation (139 regions brain segmentation), outperforming other methods