A three-loop radiative neutrino mass model with dark matter

We present a model that generates small neutrino masses at three-loop level due to the existence of Majorana fermionic dark matter, which is stabilized by a Z2 symmetry. The model predicts that the lightest neutrino is massless. We show a prototypical parameter choice allowed by relevant experimental data, which favors the case of normal neutrino mass spectrum and the dark matter with m \sim 50-135 GeV and a sizable Yukawa coupling. It means that new particles can be searched for in future e+e- collisions.Comment: 7 pages, 3 figure

2.5D multi-view gait recognition based on point cloud registration

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM

Formal and Informal Credit Markets and Rural Credit Demand in China

Credit markets are an essential economic institution. In developing countries, particularly in countries undergoing rapid social and economic transition, it is important to identify emerging credit demand and institute credit supply in a timely manner to facilitate economic transformation. This research focuses on the evolving rural credit market in China, where borrowing from the social network has been common but the recent economic transition has made this informal credit market inadequate in addressing rural credit needs. This research is aimed at identifying the social and economic factors that explain the farmers’ credit constraint and influence farmers’ decisions to switch from informal to formal credit markets. Using data from a household survey, we estimated both binary choice probit models and a multinomial probit model to explore the determinants of credit market choice and credit constraints. We found that the credit demand is significantly affected by household’s production capacity as supported by the fact that household size, land size, head’s education all significantly increase household’s probability to borrow, but the impact of these factors varies considerably by credit market. Transaction costs have a significant, negative effect on formal credit demand. The credit constraints analysis suggest that off-farm employment, land size and the cost of the credit are the three most important factors that increase the probability of being constrained.Formal Credit, Informal Credit, Credit Markets, Rural Credit, China, Agricultural Finance, Farm Management,