Discussion on Green Development of Fenlong for Yield Increase, Quality Enhancing, Water Retaining and Multiple Use of Natural Resources

Fenlong green ecological agriculture technology （Fenlong technology）, a new smash ridging farming method developed by Guangxi Academy of Agdcultural Sciences, has been elected as the recommended cultivation technique by the Ministry of Agriculture of China. It replaces the traditional plowshare with spiral drill, and its tilth depth is twice deeper than that by tractor tilthing. It also extends soil nutrient, moisture, oxygen and microorganism, the so-called ＂Four pools＂. Soil nutrient, oxygen, microorganism, light and rainfall use ratio is increased by 10%-100%, creating a platform for natural increase of more than 10% of crop yield. Its application to over 20 kinds of crops in 21 provinces has proved that the yield increases 10-30% with quality enhancing 5% and double water retaining capacity but no more input. When the application area of Fenlong could reach 67 million hm2, the amount of fertilizer can be reduced by 40-50 billion kg, saving 120-150 billion Yuan. In this paper, we put forward the strategy of ＂4＋1＂ （arable, saline-alkali soil, grasslands, Sponge City ＋ rivers） green development in China, and deepened the Fenlong cultivated tilled layer from 16.5 cm to 35 cm for 67 million hm2 arable land, ridged 13.3 million hm2 of saline-alkali soil for 35 cm, and also 35 cm for 67 million hm2 degraded steppe, which could have the following 3 effects： first, the 147 million hm2 of land with Fenlong cultivation could increase loosing soil to 315.491 billion m3, in＊ creasing by 159.26% for 120 million hm2 of arable land with the average tilled layer of 16.5 cm, which has loosing soil of only 198.1 billion m3, that is, the space of the land increases 1.6 times. Second, every hectare of plowland could store up to 450 m3/hm2 of natural rainfall, and the unused 60 m3 of saline-alkali soil and grasslands could store water of 102 billion m3, showing an increase of over 88.89% for the current plowland storage of 54 billion m3 at now, that is, double the natural rainfall storage capacity. Third, the two multiple increase of natural resources application can bring trillions of resource activation, environmental cleaning, food security, citizens, health, economic, ecological and social benefits, and makes the Chinese nation move forward in green development. Its application in ＂big scientific research＂ and ＂One Belt And One Road＂ will contribute Chinese strength to the world.

Numerical investigation for anisotropy of compressive strength of rock mass with multiple natural joints

Based on Rock Failure Process Analysis model RFPA2D, the evolutionary proc- esses of failure process of rock mass with multiple natural joints were simulated. Numeri- cal simulations show that anisotropy of compressive strength of jointed rock mass varies with the number of natural joints and inclination of natural joints. As the number of natural joints in rock mass increases, the anisotropy becomes less and less. It is justifiable to treat approximately rock mass containing six or more natural joints instead of four or more joints that was described in literature of Hoek and Brown as isotropy.

A Multiple Feature Approach for Disorder Normalization in Clinical Notes

In this paper we propose a multiple feature approach for the normalization task which can map each disorder mention in the text to a unique unified medical language system（UMLS）concept unique identifier（CUI）. We develop a two-step method to acquire a list of candidate CUIs and their associated preferred names using UMLS API and to choose the closest CUI by calculating the similarity between the input disorder mention and each candidate. The similarity calculation step is formulated as a classification problem and multiple features（string features,ranking features,similarity features,and contextual features） are used to normalize the disorder mentions. The results show that the multiple feature approach improves the accuracy of the normalization task from 32.99% to 67.08% compared with the Meta Map baseline.