A two-year field experiment was conducted to evaluate the effects of plant density on tassel and ear differentiation, anthesissilking interval(ASI), and grain yield formation of two types of modern maize hybrids(Zhong...A two-year field experiment was conducted to evaluate the effects of plant density on tassel and ear differentiation, anthesissilking interval(ASI), and grain yield formation of two types of modern maize hybrids(Zhongdan 909(ZD909) as tolerant hybrid to crowding stress, Jidan 209(JD209) and Neidan 4(ND4) as intolerant hybrids to crowding stress) in Northeast China. Plant densities of 4.50×104(D1), 6.75×104(D2), 9.00×104(D3), 11.25×104(D4), and 13.50×104(D5) plants ha-1had no significant effects on initial time of tassel and ear differentiation of maize. Instead, higher plant density delayed the tassel and ear development during floret differentiation and sexual organ formation stage, subsequently resulting in ASI increments at the rate of 1.2–2.9 days on average for ZD909 in 2013–2014, 0.7–4.2 days for JD209 in 2013, and 0.5–3.7 days for ND4 in 2014, respectively, under the treatments of D2, D3, D4, and D5 compared to that under the D1 treatment. Total florets, silking florets, and silking rates of ear showed slightly decrease trends with the plant density increasing, whereas the normal kernels seriously decreased at the rate of 11.0–44.9% on average for ZD909 in 2013–2014, 2.0–32.6% for JD209 in 2013, and 9.7–28.3% for ND4 in 2014 with the plant density increased compared to that under the D1 treatment due to increased florets abortive rates. It was also observed that 100-kernel weight of ZD909 showed less decrease trend compared that of JD209 and ND4 along with the plant densities increase. As a consequence, ZD909 gained its highest grain yield by 13.7 t ha-1on average at the plant density of 9.00×104 plants ha-1, whereas JD209 and ND4 reached their highest grain yields by 11.7 and 10.2 t ha-1at the plant density of 6.75×104 plants ha-1, respectively. Our experiment demonstrated that hybrids with lower ASI, higher kernel number potential per ear, and relative constant 100-kernel weight(e.g., ZD909) could achieve higher yield under dense planting in high latitude area(e.g., Northeast China).展开更多
Based on G-hulls and G-kernels under the meaning of G-methods on sets, we introduce the concepts of G-hull-closed sets, G-kernel-open sets, G-kernel-neighborhoods and G-kernel-derived sets, discuss some related proper...Based on G-hulls and G-kernels under the meaning of G-methods on sets, we introduce the concepts of G-hull-closed sets, G-kernel-open sets, G-kernel-neighborhoods and G-kernel-derived sets, discuss some related properties. In particular, we define pointwise G-methods, prove the consistency of G-closed sets and G-hull-closed sets, G-open sets and Gkernel-open sets, G-neighborhoods and G-kernel-neighborhoods, G-derived sets and G-kernelderived sets under this method, and enrich some results about G-closed sets, G-open sets,G-interiors, G-neighborhoods and G-derived sets in sets. At the same time, we put forward some problems for further research.展开更多
We give heat kernel estimates on Julia sets J（f;） for quadratic polynomials f c（z） = z;+ c for c in the main cardioid or the ±1/k-bulbs where k ≥ 2. First we use external ray parametrization to construct a r...We give heat kernel estimates on Julia sets J（f;） for quadratic polynomials f c（z） = z;+ c for c in the main cardioid or the ±1/k-bulbs where k ≥ 2. First we use external ray parametrization to construct a regular, strongly local and conservative Dirichlet form on Julia set. Then we show that this Dirichlet form is a resistance form and the corresponding resistance metric induces the same topology as Euclidean metric. Finally, we give heat kernel estimates under the resistance metric.展开更多
A support vector machine time series forecasting model based on rough set data preprocessing was proposed by combining rough set attribute reduction and support vector machine regression algorithm. First, remove the r...A support vector machine time series forecasting model based on rough set data preprocessing was proposed by combining rough set attribute reduction and support vector machine regression algorithm. First, remove the redundant attribute for forecasting from condition attribute by rough set method; then use the minimum condition attribute set obtained after the reduction and the corresponding initial data, reform a new training sample set which only retain the important attributes influencing the forecasting accuracy; study and train the support vector machine with the training sample obtained after reduction, and then input the reformed testing sample set according to the minimum condition attribute and corresponding initial data. The model was tested and the mapping relation was got between the condition attribute and forecasting variable. Eventually, power supply and demand were forecasted in this model. The average absolute error rates of power consumption of the whole society and yearly maximum load are respectively 14.21% and 13.23%. It shows that RS-SVM time series forecasting model has high forecasting accuracy.展开更多
To remedy the defects of the existing research achievements,the dynamic vague region relations without kernel and the non-same-plane vague region relations without kernel based on the conception of the vague sets were...To remedy the defects of the existing research achievements,the dynamic vague region relations without kernel and the non-same-plane vague region relations without kernel based on the conception of the vague sets were studied systematically.The formalized definitions of the vague intersection set,the vague cut sets and vague region partition etc were given.Based on the vague sets,the eight vague region relations in the same plane and the ten vague region relations in the different plane were given.Furthermore,the coessential intersection and the heterogeneous intersection were proposed to simplify the representation for the dynamic vague region relations without kernel and the rotation-corresponding relations between the two kinds of the relations were also studied.The production in this paper laid the foundation for the applications and research of the vague region relations without kernel in the spatial database.展开更多
孪生支持向量机(twin support vector machine,TSVM)能有效地处理交叉或异或等类型的数据.然而,当处理集值数据时,TSVM通常利用集值对象的均值、中值等统计信息.不同于TSVM,提出能直接处理集值数据的孪生支持函数机(twin support functi...孪生支持向量机(twin support vector machine,TSVM)能有效地处理交叉或异或等类型的数据.然而,当处理集值数据时,TSVM通常利用集值对象的均值、中值等统计信息.不同于TSVM,提出能直接处理集值数据的孪生支持函数机(twin support function machine,TSFM).依据集值对象定义的支持函数,TSFM在巴拿赫空间取得非平行的超平面.为了抑制集值数据中的离群点,TSFM采用了弹球损失函数并引入了集值对象的权重.考虑到TSFM是无穷维空间的优化问题,测度采用狄拉克测度的线性组合的形式,这构建有限维空间的优化模型.为了有效地求解优化模型,利用采样策略将模型转化成二次规划(quadratic programming,QP)问题并推导出二次规划问题的对偶形式,这为判断哪些采样点是支持向量提供了理论基础.为了分类集值数据,定义集值对象到巴拿赫空间的超平面的距离并由此得出判别规则.也考虑支持函数的核化以便取得数据的非线性特征,这使得提出的模型可用于不定核函数.实验结果表明,TSFM能获取交叉类型的集值数据的内在结构,并且在离群点或集值对象包含少量高维事例的情况下取得了良好的分类性能.展开更多
Maize serves as a crucial cereal crop globally,yet the escalating frequency of drought stress during the reproductive phase poses a significant threat to grain yield by causing an irreversible loss in kernel number.En...Maize serves as a crucial cereal crop globally,yet the escalating frequency of drought stress during the reproductive phase poses a significant threat to grain yield by causing an irreversible loss in kernel number.Enhancing reproductive drought tolerance in maize requires elucidating the physiological mechanisms underlying its response to drought stress,which can then be incorporated into the development of new maize varieties through breeding programs.Additionally,innovative cultivation practices must be devised to complement these genetic improvements.In this review,the timing,duration,and severity of drought stress during the reproductive stage and their effects on maize kernel set are assessed,providing a basis for constructing a framework that links kernel setting to drought stress.Based on this framework,reproductive drought tolerance from tasseling through post-fertilization kernel establishment is subsequently examined.Evidence indicates that drought-induced fertilization failure is primarily due to delayed pollination resulting from slower silk elongation,which is caused by the loss of cell turgor and reduced carbon supply.Meanwhile,kernel abortion after fertilization is mainly triggered by carbohydrate starvation,increased ethylene emission,and the accumulation of abscisic acid(ABA).Therefore,sugar metabolism,hydraulic status,and hormone signaling collectively regulate maize's kernel setting tolerance to drought stress in a synergistic manner.Several novel gene candidates with potential for conferring drought tolerance in maize have been identified,offering promising targets for genetic improvement through genome editing combined with targeted cultivation practices to enhance maize drought tolerance and ensure stable grain yield in future crops.展开更多
基金supported by the National Basic Research Program of China (2015CB150404)the National Natural Science Foundation of China (31671642)+1 种基金the Key Program of Science and Technology Department of Jilin Province, China (LFGC14205)the Innovation Project of Chinese Academy of Agricultural Sciences (CAAS-XTCX2016008)
文摘A two-year field experiment was conducted to evaluate the effects of plant density on tassel and ear differentiation, anthesissilking interval(ASI), and grain yield formation of two types of modern maize hybrids(Zhongdan 909(ZD909) as tolerant hybrid to crowding stress, Jidan 209(JD209) and Neidan 4(ND4) as intolerant hybrids to crowding stress) in Northeast China. Plant densities of 4.50×104(D1), 6.75×104(D2), 9.00×104(D3), 11.25×104(D4), and 13.50×104(D5) plants ha-1had no significant effects on initial time of tassel and ear differentiation of maize. Instead, higher plant density delayed the tassel and ear development during floret differentiation and sexual organ formation stage, subsequently resulting in ASI increments at the rate of 1.2–2.9 days on average for ZD909 in 2013–2014, 0.7–4.2 days for JD209 in 2013, and 0.5–3.7 days for ND4 in 2014, respectively, under the treatments of D2, D3, D4, and D5 compared to that under the D1 treatment. Total florets, silking florets, and silking rates of ear showed slightly decrease trends with the plant density increasing, whereas the normal kernels seriously decreased at the rate of 11.0–44.9% on average for ZD909 in 2013–2014, 2.0–32.6% for JD209 in 2013, and 9.7–28.3% for ND4 in 2014 with the plant density increased compared to that under the D1 treatment due to increased florets abortive rates. It was also observed that 100-kernel weight of ZD909 showed less decrease trend compared that of JD209 and ND4 along with the plant densities increase. As a consequence, ZD909 gained its highest grain yield by 13.7 t ha-1on average at the plant density of 9.00×104 plants ha-1, whereas JD209 and ND4 reached their highest grain yields by 11.7 and 10.2 t ha-1at the plant density of 6.75×104 plants ha-1, respectively. Our experiment demonstrated that hybrids with lower ASI, higher kernel number potential per ear, and relative constant 100-kernel weight(e.g., ZD909) could achieve higher yield under dense planting in high latitude area(e.g., Northeast China).
基金Supported by the Special Youth Project of Ningde Normal University(Grant No.2016Q34)the National Natural Science Foundation of China(Grant No.11471153)
文摘Based on G-hulls and G-kernels under the meaning of G-methods on sets, we introduce the concepts of G-hull-closed sets, G-kernel-open sets, G-kernel-neighborhoods and G-kernel-derived sets, discuss some related properties. In particular, we define pointwise G-methods, prove the consistency of G-closed sets and G-hull-closed sets, G-open sets and Gkernel-open sets, G-neighborhoods and G-kernel-neighborhoods, G-derived sets and G-kernelderived sets under this method, and enrich some results about G-closed sets, G-open sets,G-interiors, G-neighborhoods and G-derived sets in sets. At the same time, we put forward some problems for further research.
基金Supported by National Natural Science Foundation of China(60675039)National High Technology Research and Development Program of China(863 Program)(2006AA04Z217)Hundred Talents Program of Chinese Academy of Sciences
文摘We give heat kernel estimates on Julia sets J（f;） for quadratic polynomials f c（z） = z;+ c for c in the main cardioid or the ±1/k-bulbs where k ≥ 2. First we use external ray parametrization to construct a regular, strongly local and conservative Dirichlet form on Julia set. Then we show that this Dirichlet form is a resistance form and the corresponding resistance metric induces the same topology as Euclidean metric. Finally, we give heat kernel estimates under the resistance metric.
基金Project(70373017) supported by the National Natural Science Foundation of China
文摘A support vector machine time series forecasting model based on rough set data preprocessing was proposed by combining rough set attribute reduction and support vector machine regression algorithm. First, remove the redundant attribute for forecasting from condition attribute by rough set method; then use the minimum condition attribute set obtained after the reduction and the corresponding initial data, reform a new training sample set which only retain the important attributes influencing the forecasting accuracy; study and train the support vector machine with the training sample obtained after reduction, and then input the reformed testing sample set according to the minimum condition attribute and corresponding initial data. The model was tested and the mapping relation was got between the condition attribute and forecasting variable. Eventually, power supply and demand were forecasted in this model. The average absolute error rates of power consumption of the whole society and yearly maximum load are respectively 14.21% and 13.23%. It shows that RS-SVM time series forecasting model has high forecasting accuracy.
基金Sponsored by the Science and Tecnology Research Project of Education Department Heilongjiang Province(Grant No.11551084)
文摘To remedy the defects of the existing research achievements,the dynamic vague region relations without kernel and the non-same-plane vague region relations without kernel based on the conception of the vague sets were studied systematically.The formalized definitions of the vague intersection set,the vague cut sets and vague region partition etc were given.Based on the vague sets,the eight vague region relations in the same plane and the ten vague region relations in the different plane were given.Furthermore,the coessential intersection and the heterogeneous intersection were proposed to simplify the representation for the dynamic vague region relations without kernel and the rotation-corresponding relations between the two kinds of the relations were also studied.The production in this paper laid the foundation for the applications and research of the vague region relations without kernel in the spatial database.
文摘孪生支持向量机(twin support vector machine,TSVM)能有效地处理交叉或异或等类型的数据.然而,当处理集值数据时,TSVM通常利用集值对象的均值、中值等统计信息.不同于TSVM,提出能直接处理集值数据的孪生支持函数机(twin support function machine,TSFM).依据集值对象定义的支持函数,TSFM在巴拿赫空间取得非平行的超平面.为了抑制集值数据中的离群点,TSFM采用了弹球损失函数并引入了集值对象的权重.考虑到TSFM是无穷维空间的优化问题,测度采用狄拉克测度的线性组合的形式,这构建有限维空间的优化模型.为了有效地求解优化模型,利用采样策略将模型转化成二次规划(quadratic programming,QP)问题并推导出二次规划问题的对偶形式,这为判断哪些采样点是支持向量提供了理论基础.为了分类集值数据,定义集值对象到巴拿赫空间的超平面的距离并由此得出判别规则.也考虑支持函数的核化以便取得数据的非线性特征,这使得提出的模型可用于不定核函数.实验结果表明,TSFM能获取交叉类型的集值数据的内在结构,并且在离群点或集值对象包含少量高维事例的情况下取得了良好的分类性能.
基金financially supported by the Natural Key Research and Development Program of China(2023YFD2301500)。
文摘Maize serves as a crucial cereal crop globally,yet the escalating frequency of drought stress during the reproductive phase poses a significant threat to grain yield by causing an irreversible loss in kernel number.Enhancing reproductive drought tolerance in maize requires elucidating the physiological mechanisms underlying its response to drought stress,which can then be incorporated into the development of new maize varieties through breeding programs.Additionally,innovative cultivation practices must be devised to complement these genetic improvements.In this review,the timing,duration,and severity of drought stress during the reproductive stage and their effects on maize kernel set are assessed,providing a basis for constructing a framework that links kernel setting to drought stress.Based on this framework,reproductive drought tolerance from tasseling through post-fertilization kernel establishment is subsequently examined.Evidence indicates that drought-induced fertilization failure is primarily due to delayed pollination resulting from slower silk elongation,which is caused by the loss of cell turgor and reduced carbon supply.Meanwhile,kernel abortion after fertilization is mainly triggered by carbohydrate starvation,increased ethylene emission,and the accumulation of abscisic acid(ABA).Therefore,sugar metabolism,hydraulic status,and hormone signaling collectively regulate maize's kernel setting tolerance to drought stress in a synergistic manner.Several novel gene candidates with potential for conferring drought tolerance in maize have been identified,offering promising targets for genetic improvement through genome editing combined with targeted cultivation practices to enhance maize drought tolerance and ensure stable grain yield in future crops.
