Natural conditions and cropping regionalization of rice area in China

The formation of rice distribution is based on certain natural ecological conditions and social economic environments. In China, rice cropping is distributed in a vast area extending across 5 tempera ture belts, the northernmost of rice growing area in the world being in China. Distribution of rice cropping is characterized by a gradual decrease from south to north, from large and concentrated regions in Southeast to small and separated areas in Northwest. Natural conditions in rice regions differ in China with a varied topography, high in the west and low in the east. Rice fields in the west are mostly distributed on flatlands on plains, valleys among mountains, tablelands in river valleys, yellow-soil plains and basins in low valleys, alluvial plains, plains in river valleys, while those in the east are mainly distributed on alluvial plains, hilly areas among low mountains, coastal plains, along rivers and lakes and in basins among mountains.

Agricultural production structure,market conditions and farmers’nutritional intake in rural China

Nutrition poverty alleviation is an effective measure to improve the nutritional status of economically disadvantaged individuals,fundamentally improving their health and reducing poverty.Based on the Entitlement Theory and using the China Health and Nutrition Survey(CHNS)data,this paper examines the relationship between farmers’nutritional intake,production structure and regional market conditions.Results show that farmers with diversified production have better nutritional intake than those who specialize.Furthermore,the correlation between regional market conditions and nutritional intake varies between economically disadvantaged and non-economically disadvantaged households.Market conditions significantly influence the carbohydrate and fat intake of economically disadvantaged households and are positively associated with the dietary structure and nutritional intake of non-economically disadvantaged ones.Moreover,income is positively correlated with the nutritional intake of non-economically disadvantaged households but not with economically disadvantaged ones.

An Image Segmentation Algorithm Based on a Local Region Conditional Random Field Model

To reduce the computation cost of a combined probabilistic graphical model and a deep neural network in semantic segmentation, the local region condition random field (LRCRF) model is investigated which selectively applies the condition random field (CRF) to the most active region in the image. The full convolutional network structure is optimized with the ResNet-18 structure and dilated convolution to expand the receptive field. The tracking networks are also improved based on SiameseFC by considering the frame relations in consecutive-frame traffic scene maps. Moreover, the segmentation results of the greyscale input data sets are more stable and effective than using the RGB images for deep neural network feature extraction. The experimental results show that the proposed method takes advantage of the image features directly and achieves good real-time performance and high segmentation accuracy.

The Sensitive Regions Identified by CNOPs of Three Typhoon Events

In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts.

A Novel Risk Informatization Assessment System for In-Service Highway Slope Based on Network

Aiming at the information evaluation of traffic infrastructure in-service roadside slope risk assessment,the method of risk assessment for highway slope engineering is proposed by using the combination of quantitative and qualitative methods,and a new risk assessment method is proposed and improved.The system,in order to prevent the risks in slope engineering,serves the scientific decision-making of the maintenance,operation and management of the in-service road slopes.Based on the analysis of the special geological conditions,complex surrounding environment and construction schemes of existing highway slopes in China,this paper establishes an in-service slope evaluation model for in-service roads,and designs the scheme diagram of the in-service road slope evaluation system based on the networked Internet platform.Moreover,a set of in-service roadside slope risk assessment system software,the system component block diagram and the main design interface are given.This system can meet the needs of comprehensive evaluation of multi-factors in service road slopes.