On positive scalar curvature and moduli of curves

In this article we first show that any finite cover of the moduli space of closed Riemann surfaces of genus $g$ with $g\geq 2$ does not admit any Riemannian metric $ds^2$ of nonnegative scalar curvature such that $ds^2 \succ ds_{T}^2$ where $ds_{T}^2$ is the Teichm\"uller metric. Our second result is the proof that any cover $M$ of the moduli space $\mathbb{M}_{g}$ of a closed Riemann surface $S_{g}$ does not admit any complete Riemannian metric of uniformly positive scalar curvature in the quasi-isometry class of the Teichm\"uller metric, which implies a conjecture of Farb-Weinberger.Comment: J. Differential Geom, to appear; 24 page

Self-supervised Spatio-temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics

We address the problem of video representation learning without human-annotated labels. While previous efforts address the problem by designing novel self-supervised tasks using video data, the learned features are merely on a frame-by-frame basis, which are not applicable to many video analytic tasks where spatio-temporal features are prevailing. In this paper we propose a novel self-supervised approach to learn spatio-temporal features for video representation. Inspired by the success of two-stream approaches in video classification, we propose to learn visual features by regressing both motion and appearance statistics along spatial and temporal dimensions, given only the input video data. Specifically, we extract statistical concepts (fast-motion region and the corresponding dominant direction, spatio-temporal color diversity, dominant color, etc.) from simple patterns in both spatial and temporal domains. Unlike prior puzzles that are even hard for humans to solve, the proposed approach is consistent with human inherent visual habits and therefore easy to answer. We conduct extensive experiments with C3D to validate the effectiveness of our proposed approach. The experiments show that our approach can significantly improve the performance of C3D when applied to video classification tasks. Code is available at https://github.com/laura-wang/video_repres_mas.Comment: CVPR 201

The Sales Impact of Storytelling in Live Streaming E-Commerce

Live streaming e-commerce (LSE) has emerged as a popular third-party service for improving product sales. It persuades consumers through streamers’ storytelling or narratives, which encompass descriptions and depictions of their own product experiences. However, the sales impact of a story or narrative in LSEs has been overlooked in the literature. Extending the narrative transportation theory to the LSE context, we posit that the dual landscapes of narrative—the landscapes of action and the landscape of consciousness—can improve product sales through their influence on consumers’ imagination of story plotline and empathy for streamers’ product experiences. We also propose that the efficacy of the dual landscapes is contingent on streamers’ interaction response to consumer query. By collecting LSE data from the Taobao Live platform, we manually and algorithmically measured these variables and proposed to empirically examine their effects

Efficient Fully Convolution Neural Network for Generating Pixel Wise Robotic Grasps With High Resolution Images

This paper presents an efficient neural network model to generate robotic grasps with high resolution images. The proposed model uses fully convolution neural network to generate robotic grasps for each pixel using 400 $\times$ 400 high resolution RGB-D images. It first down-sample the images to get features and then up-sample those features to the original size of the input as well as combines local and global features from different feature maps. Compared to other regression or classification methods for detecting robotic grasps, our method looks more like the segmentation methods which solves the problem through pixel-wise ways. We use Cornell Grasp Dataset to train and evaluate the model and get high accuracy about 94.42% for image-wise and 91.02% for object-wise and fast prediction time about 8ms. We also demonstrate that without training on the multiple objects dataset, our model can directly output robotic grasps candidates for different objects because of the pixel wise implementation.Comment: Submitted to ROBIO 201

A Study of Single-vendor and Multiple-retailers Pricing-Ordering Strategy under Group-Buying Online Auction

The supplier and buyers, with different objectives and self-interest, are separate economic entities acting independently and opportunistically to maximize their individual profits. In this paper, a GBA model in the B2B market is studied, where one supplier faces 2 different retailers, who cooperate in the order decision making. Firstly, the optimal ordering decision of the retailers was analyzed. Then, from the perspective of the supplier, the optimal pricing strategy of the supplier is also studied. Finally, it is concluded that the group buying online auction is a useful and efficient pricing mechanism in the B2B e-market, under which, all members of the supply chain will improve their payoffs

Visual Communication and Fashion Popularity Contagion in Social Networks

Fast fashion has emerged as a prevalent retail strategy shaping fashion popularity. However, due to the lack of historical records and the dynamics of fashion trends, existing demand prediction methods do not apply to new-season fast fashion sales forecasting. We draw on the Social Contagion Theory to conceptualize a sales prediction framework for fast fashion new releases. We posit that fashion popularity contagion comes from Source Contagion and Media Contagion, which refer to the inherent infectiousness of fashion posts and the popularity diffusion in social networks, respectively. We consider fashion posts as the contagion source that visually attracts social media users with images of fashion products. Graph Convolutional Network is developed to model the dynamic fashion contagion process in the topology structure of social networks. This theory-based deep learning method can incorporate the latest social media activities to offset the deficiency of historical fashion data in new seasons

Global Positive Periodic Solutions for Periodic Two-Species Competitive Systems with Multiple Delays and Impulses

A set of easily verifiable sufficient conditions are derived to guarantee the existence and the global stability of positive periodic solutions for two-species competitive systems with multiple delays and impulses, by applying some new analysis techniques. This improves and extends a series of the well-known sufficiency theorems in the literature about the problems mentioned previously

Ecological network design based on optimizing ecosystem services:case study in the Huang-Huai-Hai region, China

In modern agricultural landscapes, constructing ‘ecological networks’ is regarded as an efficient way to conserve biodiversity and maintain ecosystem services. Here we aimed to develop an approach to design ecological corridor by employing the ecological source - resistance surface - ecological corridor framework in combination with semi-natural habitat planning and ecosystem service trade-off assessment. ‘Ecological source patches’ were identified based on a ‘Remote Sensing Ecological Index’ (RSEI) to objectively classify ecological and environmental conditions. Our resulting spatial resistance surface was further modified used based on the ‘Cultivated Land Use Intensity’ index, to derive a high accuracy and rationality of ecological corridor extraction in agriculture landscape. While planning the ecological network, key nodes and resulting semi-natural habitat (SNH) distribution were identified using Linkage Mapper tools and circuit theory. We constructed ecological network scenarios with different amounts of semi-natural habitats and calculated resulting regional ecosystem service values (ESV) using an equivalence factor method to explore optimal spatial layouts. The results showed, while regional ecosystem service values generally increased in line with semi-natural habitat area contained within the ecological network, ecological networks with forests covering 10% of the total area were predicted as an optimal scenario balancing ecosystem services with agricultural yield in the study region. Networks with mixed forest and grassland cover totaling 20% of the area represented an alternative choice that strongly enhanced regional ecosystem services while may still allowing for high agricultural productivity. In constructing corridors, identifying, restoring and protecting key ecological nodes using targeted management and habitat restoration, while protecting existing wetlands and other water bodies that support regional water cycle and supply services, should be prioritized. Regional policy measures furthermore need to promote targeted ecological network planning to help improve the overall sustainability of agricultural production