In order to determine the physiological mechanism of drought resistance of northern wheat in China,six drought resistant wheat and one sensitivity to drought wheat were planted in pots.They were subjected to drought t...In order to determine the physiological mechanism of drought resistance of northern wheat in China,six drought resistant wheat and one sensitivity to drought wheat were planted in pots.They were subjected to drought treatment and normal water when the plants grew to the 3-leaf stage.Samples were collected at 10,20,30,and 40 days after the drought treatment,respectively.The electrical conductivity,photosynthetic parameters,chlorophyll fluorescence parameters,sugar content,proline content,protein content,and active oxygen scavenging enzyme activity of the plants were detected,and the agronomic traits of the wheat varieties were investigated at maturity.The results indicated that the phenotype and yield-related factors of Darkhan 144 changed little under the drought stress.The relative electrical conductivity of Kefeng 6 and Darkhan 166 was lower under the drought stress,and their cell membrane was less damaged.The Darkhan 144 and Darkhan 166 had higher drought resistance coefficients,and were the wheat varieties with stronger drought resistance.However,the physiological mechanisms of drought resistance of these three wheat were different:Darkhan 144 maintained a higher photosynthetic activity under the drought stress;Darkhan 166 maintained a higher protein content,photosynthetic activity and active oxygen scavenging enzyme activity.In addition,other drought-resistant varieties Kefeng 6,Kefeng 10 and Longmai 26 had a higher content of osmoregulatory substances under the drought stress.展开更多
The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distanc...The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distance and Tukey M-estimator.Firstly,we propose a k-distancebased method to compute user suspicion degree(USD).The reliable neighbor model can be constructed through incorporating the user suspicion degree into user neighbor model.The influence of attack profiles on the recommendation results is reduced through adjusting similarities among users.Then,Tukey M-estimator is introduced to construct robust matrix factorization model,which can realize the robust estimation of user feature matrix and item feature matrix and reduce the influence of attack profiles on item feature matrix.Finally,a robust collaborative recommendation algorithm is devised by combining the reliable neighbor model and robust matrix factorization model.Experimental results show that the proposed algorithm outperforms the existing methods in terms of both recommendation accuracy and robustness.展开更多
基金the National Ministry of Science and Technology Key Project(2018YFE0123300)the National Modern Agricultural Wheat Industry Technology System Keshan Comprehensive Test Station(CARS‒03‒54)the Collaborative Innovation and Extension System of Modern Agricultural Wheat in Heilongjiang Province。
文摘In order to determine the physiological mechanism of drought resistance of northern wheat in China,six drought resistant wheat and one sensitivity to drought wheat were planted in pots.They were subjected to drought treatment and normal water when the plants grew to the 3-leaf stage.Samples were collected at 10,20,30,and 40 days after the drought treatment,respectively.The electrical conductivity,photosynthetic parameters,chlorophyll fluorescence parameters,sugar content,proline content,protein content,and active oxygen scavenging enzyme activity of the plants were detected,and the agronomic traits of the wheat varieties were investigated at maturity.The results indicated that the phenotype and yield-related factors of Darkhan 144 changed little under the drought stress.The relative electrical conductivity of Kefeng 6 and Darkhan 166 was lower under the drought stress,and their cell membrane was less damaged.The Darkhan 144 and Darkhan 166 had higher drought resistance coefficients,and were the wheat varieties with stronger drought resistance.However,the physiological mechanisms of drought resistance of these three wheat were different:Darkhan 144 maintained a higher photosynthetic activity under the drought stress;Darkhan 166 maintained a higher protein content,photosynthetic activity and active oxygen scavenging enzyme activity.In addition,other drought-resistant varieties Kefeng 6,Kefeng 10 and Longmai 26 had a higher content of osmoregulatory substances under the drought stress.
基金National Natural Science Foundation of China under Grant No.61379116，Natural Science Foundation of Hebei Province under Grant No.F2015203046 and No.F2013203124，Key Program of Research on Science and Technology of Higher Education Institutions of Hebei Province under Grant No.ZH2012028
文摘The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distance and Tukey M-estimator.Firstly,we propose a k-distancebased method to compute user suspicion degree(USD).The reliable neighbor model can be constructed through incorporating the user suspicion degree into user neighbor model.The influence of attack profiles on the recommendation results is reduced through adjusting similarities among users.Then,Tukey M-estimator is introduced to construct robust matrix factorization model,which can realize the robust estimation of user feature matrix and item feature matrix and reduce the influence of attack profiles on item feature matrix.Finally,a robust collaborative recommendation algorithm is devised by combining the reliable neighbor model and robust matrix factorization model.Experimental results show that the proposed algorithm outperforms the existing methods in terms of both recommendation accuracy and robustness.
