Chinese Rural Financial Exclusion

Financial exclusion is a social problem. It will affect the economic and social development, causing Matthew Effect and regional financial desertification. There is a serious financial exclusion phenomenon in Chinese rural areas, such as few outlets of financial institutions network, harsh financing conditions, high interest rates and serious gap in marketing. All these problems’ genesis is low income of farmers and the lagging of economic development. Specifically, it can be accounted for the agricultural production risks, farmers’ lacking of financial knowledge. At present, the rural financial exclusion can be eased mainly by strengthening of government financial supervision, popularization of farmers’ financial knowledge, development of micro financing institutions and the coordinated development of the rural economy

A New Arctic Ice-Ocean Prediction System

LONG-TERM GOALS: The long term goal of the project is to produce a new operational Arctic ice-ocean prediction system that improves on the earlier PIPS 1.0 and PIPS 2.0 systems, as measured in terms of forecasting skill.Award #: N0001499WR3013

クライオ電子顕微鏡単粒子解析によるヒトカルシウムATPase SERCA2bの構造および機構に関する研究

要約のみTohoku University稲葉謙次課

The Relationship Between Nitrogen Content in Soybean Leaves and Infestation Severity of Aphis glycines Mutsumura

Changes in nitrogen content of leaves in different soybean species during the infestation by Aphis glycines Mutsumura was determined. A correlation between the nitrogen content of soybean leaves and infestation severity of Aphis glycines Mutsumura was found. Therefore, the nitrogen content of soybean leaves could be regarded as one of the ecological factors used in prediction of infestation severity of Aphis glycines Mutsumura.Originating text in Chinese.Citation: Hu, Qi, Zhang, Weiqun, Yao, Yuxia, Yan, Shuqin. (1992). The Relationship Between Nitrogen Content in Soybean Leaves and Infestation Severity of Aphis glycines Mutsumura. Journal of Jilin Agricultural University, 14(4), 103-104

Successive one-sided Hodrick-Prescott filter with incremental filtering algorithm for nonlinear economic time series

We propose a successive one-sided Hodrick-Prescott (SOHP) filter from multiple time scale decomposition perspective to derive trend estimate for a time series. The idea is to apply the one-sided HP (OHP) filter recursively on the updated cyclical component to extract the trend residual on multiple time scales, thereby to improve the trend estimate. To address the issue of optimization with a moving horizon as that of the SOHP filter, we present an incremental HP filtering algorithm, which greatly simplifies the involved inverse matrix operation and reduces the computational demand of the basic HP filtering. Actually, the new algorithm also applies effectively to other HP-type filters, especially for large-size or expanding data scenario. Numerical examples on real economic data show the better performance of the SOHP filter in comparison with other known HP-type filters