Aharonov-Bohm effect in monolayer black phosphorus (phosphorene) nanorings

This work presents theoretical demonstration of Aharonov-Bohm (AB) effect in monolayer phosphorene nanorings (PNR). Atomistic quantum transport simulations of PNR are employed to investigate the impact of multiple modulation sources on the sample conductance. In presence of a perpendicular magnetic field, we find that the conductance of both armchair and zigzag PNR oscillate periodically in a low-energy window as a manifestation of the AB effect. Our numerical results have revealed a giant magnetoresistance (MR) in zigzag PNR (with a maximum magnitude approaching two thousand percent). It is attributed to the AB effect induced destructive interference phase in a wide energy range below the bottom of the second subband. We also demonstrate that PNR conductance is highly anisotropic, offering an additional way to modulate MR. The giant MR in PNR is maintained at room temperature in the presence of thermal broadening effect.Comment: 7 pages, 7 figure

Global-Scale Resource Survey and Performance Monitoring of Public OGC Web Map Services

One of the most widely-implemented service standards provided by the Open Geospatial Consortium (OGC) to the user community is the Web Map Service (WMS). WMS is widely employed globally, but there is limited knowledge of the global distribution, adoption status or the service quality of these online WMS resources. To fill this void, we investigated global WMSs resources and performed distributed performance monitoring of these services. This paper explicates a distributed monitoring framework that was used to monitor 46,296 WMSs continuously for over one year and a crawling method to discover these WMSs. We analyzed server locations, provider types, themes, the spatiotemporal coverage of map layers and the service versions for 41,703 valid WMSs. Furthermore, we appraised the stability and performance of basic operations for 1210 selected WMSs (i.e., GetCapabilities and GetMap). We discuss the major reasons for request errors and performance issues, as well as the relationship between service response times and the spatiotemporal distribution of client monitoring sites. This paper will help service providers, end users and developers of standards to grasp the status of global WMS resources, as well as to understand the adoption status of OGC standards. The conclusions drawn in this paper can benefit geospatial resource discovery, service performance evaluation and guide service performance improvements.Comment: 24 pages; 15 figure

Two sufficient conditions in frequency domain for Gabor frames

AbstractTwo sufficient conditions for the Gabor system to be a frame for L2(R) are presented in this note. The conditions proposed are stated in terms of the Fourier transforms of the Gabor system’s generating functions. It is also shown that these conditions are better than the known result

HIPPOCAMPAL REPLAY IN A NOVEL ENVIRONMENT: INFORMATION CONTENT AND INTERACTION WITH PREFRONTAL NEURONAL ACTIVITIES

Hippocampal place-cell replay has been proposed as a fundamental mechanism of learning and memory, which might support navigational learning and planning. An important hypothesis of relevance to these proposed functions is that the information encoded in replay should reflect the topological structure of experienced environments, that is, which places in the environment are connected with which others. Here we report several attributes of replay observed in rats exploring a novel forked environment that support the hypothesis. First, we observed that spatially overlapping replays depicting divergent trajectories through the fork recruited the same population of cells with the same firing rates to represent the common portion of the trajectories. Second, replay tended to be directional and to flip the represented direction at the fork. Third, replay-associated sharp-wave-ripple events in the local field potential exhibited substructure that mapped onto the maze topology. Thus the spatial complexity of our recording environment was accurately captured by replay: the underlying neuronal activities reflected the bifurcating shape, and both directionality and associated ripple structure reflected the segmentation of the maze. Moreover, we observed that replays occurred rapidly after small numbers of experiences. To further investigate the potential role of sequence replay in cross-structural network functions, we addressed the question of whether and how hippocampal replay interacts with prefrontal processes. We found strong modulations of simultaneously recorded medial prefrontal neuronal activities by running direction on track arms as well as reward conditions at arm ends, indicating their active involvement in task performance. Importantly, prefrontal neurons exhibited substantial firing-rate changes consistently at the occurrences of hippocampal replay, with a subset of neurons showing significantly different response patterns to replays representing different arms of the maze. Our results suggest that hippocampal replay rapidly captures learned information about environmental topology to support a role in navigation, possibly through informing prefrontal activities in spatial decision making processes

DI-Net : Decomposed Implicit Garment Transfer Network for Digital Clothed 3D Human

3D virtual try-on enjoys many potential applications and hence has attracted wide attention. However, it remains a challenging task that has not been adequately solved. Existing 2D virtual try-on methods cannot be directly extended to 3D since they lack the ability to perceive the depth of each pixel. Besides, 3D virtual try-on approaches are mostly built on the fixed topological structure and with heavy computation. To deal with these problems, we propose a Decomposed Implicit garment transfer network (DI-Net), which can effortlessly reconstruct a 3D human mesh with the newly try-on result and preserve the texture from an arbitrary perspective. Specifically, DI-Net consists of two modules: 1) A complementary warping module that warps the reference image to have the same pose as the source image through dense correspondence learning and sparse flow learning; 2) A geometry-aware decomposed transfer module that decomposes the garment transfer into image layout based transfer and texture based transfer, achieving surface and texture reconstruction by constructing pixel-aligned implicit functions. Experimental results show the effectiveness and superiority of our method in the 3D virtual try-on task, which can yield more high-quality results over other existing methods