Soil salinity is a worldwide problem that adversely affects plant growth and crop productivity. The salt overly sensitive (SOS) pathway is evolutionarily conserved and essential for plant salt tolerance. In this study...Soil salinity is a worldwide problem that adversely affects plant growth and crop productivity. The salt overly sensitive (SOS) pathway is evolutionarily conserved and essential for plant salt tolerance. In this study, we reveal how the maize shaggy/glycogen synthase kinase 3-like kinases ZmSK3 and ZmSK4, orthologs of brassinosteroid insensitive 2 in Arabidopsis thaliana, regulate the maize SOS pathway. ZmSK3 and ZmSK4 interact with and phosphorylate ZmSOS2, a core member of the maize SOS pathway. The mutants defective in ZmSK3 or ZmSK4 are hyposensitive to salt stress, with higher salt-induced activity of ZmSOS2 than that in the wild type. Furthermore, the Ca^(2+) sensors ZmSOS3 and ZmSOS3-like calcium binding protein 8 (ZmSCaBP8) activate ZmSOS2 to maintain Na^(+)/K^(+) homeostasis under salt stress and may participate in the regulation of ZmSOS2 by ZmSK3 and ZmSK4. These findings discover the regulation of the maize SOS pathway and provide important gene targets for breeding salt-tolerant maize.展开更多
Electricity plays a vital role in daily life and economic development.The status of the indicator lights of the power plant needs to be checked regularly to ensure the normal supply of electricity.Aiming at the proble...Electricity plays a vital role in daily life and economic development.The status of the indicator lights of the power plant needs to be checked regularly to ensure the normal supply of electricity.Aiming at the problem of a large amount of data and different sizes of indicator light detection,we propose an improved You Only Look Once vision 5(YOLOv5)power plant indicator light detection algorithm.The algorithm improves the feature extraction ability based on YOLOv5s.First,our algorithm enhances the ability of the network to perceive small objects by combining attention modules for multi-scale feature extraction.Second,we adjust the loss function to ensure the stability of the object frame during the regression process and improve the conver-gence accuracy.Finally,transfer learning is used to augment the dataset to improve the robustness of the algorithm.The experimental results show that the average accuracy of the proposed squeeze-and-excitation YOLOv5s(SE-YOLOv5s)algorithm is increased by 4.39%to 95.31%compared with the YOLOv5s algorithm.The proposed algorithm can better meet the engineering needs of power plant indicator light detection.展开更多
In recent years,pedestrian detection is a hot research topic in the field of computer vision and artificial intelligence,it is widely used in the field of security and pedestrian analysis.However,due to a large amount...In recent years,pedestrian detection is a hot research topic in the field of computer vision and artificial intelligence,it is widely used in the field of security and pedestrian analysis.However,due to a large amount of calculation in the traditional pedestrian detection technology,the speed of many systems for pedestrian recognition is very limited.But in some restricted areas,such as construction hazardous areas,real-time detection of pedestrians and cross-border behaviors is required.To more conveniently and efficiently detect whether there are pedestrians in the restricted area and cross-border behavior,this paper proposes a pedestrian cross-border detection method based on HOG(Histogram of Oriented Gradient)and SVM(Support Vector Machine).This method extracts the moving target through the GMM(Gaussian Mixture Model)background modeling and then extracts the characteristics of the moving target through gradient HOG.Finally,it uses SVM training to distinguish pedestrians from non-pedestrians,completes the detection of pedestrians,and labels the targets.The test results show that only the HOG feature extraction of the candidate area can greatly reduce the amount of calculation and reduce the time of feature extraction,eliminate background interference,thereby improving the efficiency of detection,and can be applied to occasions with real-time requirements.展开更多
Existing temporal segmentation methods suffer from the problems of high computational complexity and complicated steps. To address this issue, we present a method that combines the binary tree and spatio-temporal tunn...Existing temporal segmentation methods suffer from the problems of high computational complexity and complicated steps. To address this issue, we present a method that combines the binary tree and spatio-temporal tunnel(STT) for temporal segmentation of rough videos. First, we compute initial cumulative spatio-temporal flow to determine flow overflow of sub-video which is divided from a rough video. Second, the decision tree is generated by combining binary tree and balance factor to dynamically adjust the sampling line of the STT. Finally, pixels on the sampling line are extracted to generate an adaptive STT for temporal proposals. Experimental results show that the computational complexity of the proposed method is significantly better than that of the comparison methods while ensuring accuracy.展开更多
In the field of educational examination,automatic marking technology plays an essential role in improving the efficiency of marking and liberating the labor force.At present,the implementation of the policy of expandi...In the field of educational examination,automatic marking technology plays an essential role in improving the efficiency of marking and liberating the labor force.At present,the implementation of the policy of expanding erolments has caused a serious decline in the teacher-student ratio in colleges and universities.The traditional marking system based on Optical Mark Reader technology can no longer meet the requirements of liberating the labor force of teachers in small and medium-sized examinations.With the development of image processing and artificial neural network technology,the recognition of handwritten character in the field of pattern recognition has attracted the attention of many researchers.In this paper,filtering and de-noise processing and binary processing are used as preprocessing methods for handwriting recognition.Extract the pixel feature of handwritten characters through digital image processing of handwritten character pictures,and then,get the feature vector from these feature fragments and use it as the description of the character.The extracted feature values are used to train the neural network to realize the recognition of handwritten English letters and numerical characters.Experimental results on Chars74K and MNIST data sets show that the recognition accuracy of some handwritten English letters and numerical characters can reach 90%and 99%,respectively.展开更多
Since the discovery of the structure of DNA and the statement by Francis Crick that DNA is“…so precious that probably many distinct repair mechanisms would exist”,1 a plethora of DNA alterations induced by exogenou...Since the discovery of the structure of DNA and the statement by Francis Crick that DNA is“…so precious that probably many distinct repair mechanisms would exist”,1 a plethora of DNA alterations induced by exogenous and endogenous genotoxins has been identified,together with complex cellular processes that sense the damage,remove it from the macromolecule or tolerate it during replication.Kinase-driven pathways signal downstream to complex networks,which regulate the balance between survival and death,and are collectively referred to as the DNA damage response(DDR).The classical DNA repair and DDR pathways have been elucidated in detail and a tight entanglement has been uncovered between ATM-ATR-DNA-PK driven pathways,chromatin remodeling,damage recruiting factors,and mechanisms removing or tolerating DNA damage in a simple(damage reversal)or more complex way(Fig.1).展开更多
基金This work was supported by grants from the National Key R&D Program of China(2022YFF1001601 and 2022YFA1303400)supported by grants from the National Natural Science Foundation of China(32100234 and 31921001).
文摘Soil salinity is a worldwide problem that adversely affects plant growth and crop productivity. The salt overly sensitive (SOS) pathway is evolutionarily conserved and essential for plant salt tolerance. In this study, we reveal how the maize shaggy/glycogen synthase kinase 3-like kinases ZmSK3 and ZmSK4, orthologs of brassinosteroid insensitive 2 in Arabidopsis thaliana, regulate the maize SOS pathway. ZmSK3 and ZmSK4 interact with and phosphorylate ZmSOS2, a core member of the maize SOS pathway. The mutants defective in ZmSK3 or ZmSK4 are hyposensitive to salt stress, with higher salt-induced activity of ZmSOS2 than that in the wild type. Furthermore, the Ca^(2+) sensors ZmSOS3 and ZmSOS3-like calcium binding protein 8 (ZmSCaBP8) activate ZmSOS2 to maintain Na^(+)/K^(+) homeostasis under salt stress and may participate in the regulation of ZmSOS2 by ZmSK3 and ZmSK4. These findings discover the regulation of the maize SOS pathway and provide important gene targets for breeding salt-tolerant maize.
基金supported by the National Natural Science Foun-dation of China(Nos.61702347,62027801)the Natural Sci-ence Foundation of Hebei Province(Nos.F2022210007,F2017210161)+1 种基金the Science and Technology Project of Hebei Education Department(Nos.ZD2022100,QN2017132)the Central Guidance on Local Science and Technology Development Fund(No.226Z0501G)。
文摘Electricity plays a vital role in daily life and economic development.The status of the indicator lights of the power plant needs to be checked regularly to ensure the normal supply of electricity.Aiming at the problem of a large amount of data and different sizes of indicator light detection,we propose an improved You Only Look Once vision 5(YOLOv5)power plant indicator light detection algorithm.The algorithm improves the feature extraction ability based on YOLOv5s.First,our algorithm enhances the ability of the network to perceive small objects by combining attention modules for multi-scale feature extraction.Second,we adjust the loss function to ensure the stability of the object frame during the regression process and improve the conver-gence accuracy.Finally,transfer learning is used to augment the dataset to improve the robustness of the algorithm.The experimental results show that the average accuracy of the proposed squeeze-and-excitation YOLOv5s(SE-YOLOv5s)algorithm is increased by 4.39%to 95.31%compared with the YOLOv5s algorithm.The proposed algorithm can better meet the engineering needs of power plant indicator light detection.
基金This work was supported by the National Nature Science Foundation of China(Grant Nos.61702347,61972267,61772225)Natural Science Foundation of Hebei Province(Grant Nos.F2017210161,F2018210148)。
文摘In recent years,pedestrian detection is a hot research topic in the field of computer vision and artificial intelligence,it is widely used in the field of security and pedestrian analysis.However,due to a large amount of calculation in the traditional pedestrian detection technology,the speed of many systems for pedestrian recognition is very limited.But in some restricted areas,such as construction hazardous areas,real-time detection of pedestrians and cross-border behaviors is required.To more conveniently and efficiently detect whether there are pedestrians in the restricted area and cross-border behavior,this paper proposes a pedestrian cross-border detection method based on HOG(Histogram of Oriented Gradient)and SVM(Support Vector Machine).This method extracts the moving target through the GMM(Gaussian Mixture Model)background modeling and then extracts the characteristics of the moving target through gradient HOG.Finally,it uses SVM training to distinguish pedestrians from non-pedestrians,completes the detection of pedestrians,and labels the targets.The test results show that only the HOG feature extraction of the candidate area can greatly reduce the amount of calculation and reduce the time of feature extraction,eliminate background interference,thereby improving the efficiency of detection,and can be applied to occasions with real-time requirements.
基金supported by the National Natural Science Foundation of China(Nos.61702347 and 62027801)the Natural Science Foundation of Hebei Province(Nos.F2022210007 and F2017210161)+1 种基金the Science and Technology Project of Hebei Education Department(Nos.ZD2022100 and QN2017132)the Central Guidance on Local Science and Technology Development Fund(No.226Z0501G)。
文摘Existing temporal segmentation methods suffer from the problems of high computational complexity and complicated steps. To address this issue, we present a method that combines the binary tree and spatio-temporal tunnel(STT) for temporal segmentation of rough videos. First, we compute initial cumulative spatio-temporal flow to determine flow overflow of sub-video which is divided from a rough video. Second, the decision tree is generated by combining binary tree and balance factor to dynamically adjust the sampling line of the STT. Finally, pixels on the sampling line are extracted to generate an adaptive STT for temporal proposals. Experimental results show that the computational complexity of the proposed method is significantly better than that of the comparison methods while ensuring accuracy.
基金This work was supported by the National Nature Science Foundation of China(Grant No.61702347).
文摘In the field of educational examination,automatic marking technology plays an essential role in improving the efficiency of marking and liberating the labor force.At present,the implementation of the policy of expanding erolments has caused a serious decline in the teacher-student ratio in colleges and universities.The traditional marking system based on Optical Mark Reader technology can no longer meet the requirements of liberating the labor force of teachers in small and medium-sized examinations.With the development of image processing and artificial neural network technology,the recognition of handwritten character in the field of pattern recognition has attracted the attention of many researchers.In this paper,filtering and de-noise processing and binary processing are used as preprocessing methods for handwriting recognition.Extract the pixel feature of handwritten characters through digital image processing of handwritten character pictures,and then,get the feature vector from these feature fragments and use it as the description of the character.The extracted feature values are used to train the neural network to realize the recognition of handwritten English letters and numerical characters.Experimental results on Chars74K and MNIST data sets show that the recognition accuracy of some handwritten English letters and numerical characters can reach 90%and 99%,respectively.
文摘Since the discovery of the structure of DNA and the statement by Francis Crick that DNA is“…so precious that probably many distinct repair mechanisms would exist”,1 a plethora of DNA alterations induced by exogenous and endogenous genotoxins has been identified,together with complex cellular processes that sense the damage,remove it from the macromolecule or tolerate it during replication.Kinase-driven pathways signal downstream to complex networks,which regulate the balance between survival and death,and are collectively referred to as the DNA damage response(DDR).The classical DNA repair and DDR pathways have been elucidated in detail and a tight entanglement has been uncovered between ATM-ATR-DNA-PK driven pathways,chromatin remodeling,damage recruiting factors,and mechanisms removing or tolerating DNA damage in a simple(damage reversal)or more complex way(Fig.1).
