Calcium ferrite(CF)is recognized as a potential green and efficient functional material because of its advantages of magnetism,electrochemistry,catalysis,and biocompatibility in the fields of materials chemistry,envir...Calcium ferrite(CF)is recognized as a potential green and efficient functional material because of its advantages of magnetism,electrochemistry,catalysis,and biocompatibility in the fields of materials chemistry,environmental engineering,and biomedicine.There-fore,the obtained research results need to be systematically summarized,and new perspectives on CF and its composite materials need to be analyzed.Based on the presented studies of CF and its composite materials,the types and structures of the crystal are summarized.In addition,the current application technologies and theoretical mechanisms with various properties in different fields are elucidated.Moreover,the various preparation methods of CF and its composite materials are elaborated in detail.Most importantly,the advantages and disadvantages of the synthesis methods of CF and its composite materials are discussed,and the existing problems and emerging challenges in practical production are identified.Furthermore,the key future research directions of CF and its composite materials have been prospected from the potential application technologies to provide references for its synthesis and efficient utilization.展开更多
Software defect feature selection has problems of feature space dimensionality reduction and large search space.This research proposes a defect prediction feature selection framework based on improved shuffled frog le...Software defect feature selection has problems of feature space dimensionality reduction and large search space.This research proposes a defect prediction feature selection framework based on improved shuffled frog leaping algorithm(ISFLA).Using the two-level structure of the framework and the improved hybrid leapfrog algorithm's own advantages,the feature values are sorted,and some features with high correlation are selected to avoid other heuristic algorithms in the defect prediction that are easy to produce local The case where the convergence rate of the optimal or parameter optimization process is relatively slow.The framework improves generalization of predictions of unknown data samples and enhances the ability to search for features related to learning tasks.At the same time,this framework further reduces the dimension of the feature space.After the contrast simulation experiment with other common defect prediction methods,we used the actual test data set to verify the framework for multiple iterations on Internet of Things(IoT)system platform.The experimental results show that the software defect prediction feature selection framework based on ISFLA is very effective in defect prediction of IoT communication software.This framework can save the testing time of IoT communication software,effectively improve the performance of software defect prediction,and ensure the software quality.展开更多
Monitoring,understanding and predicting Origin-destination(OD)flows in a city is an important problem for city planning and human activity.Taxi-GPS traces,acted as one kind of typical crowd sensed data,it can be used ...Monitoring,understanding and predicting Origin-destination(OD)flows in a city is an important problem for city planning and human activity.Taxi-GPS traces,acted as one kind of typical crowd sensed data,it can be used to mine the semantics of OD flows.In this paper,we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China.The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows.Then based on a novel complex network model,a semantics mining method of OD flows is proposed through compounding Points of Interests(POI)network and public transport network to the OD flows network.The propose method would offer a novel way to predict the location characteristic and future traffic conditions accurately.展开更多
Plant metabolites are dynamically modified and distributed in response to environmental changes.How-ever,it is poorly understood how metabolic change functions in plant stress responses.Maintaining ion ho-meostasis un...Plant metabolites are dynamically modified and distributed in response to environmental changes.How-ever,it is poorly understood how metabolic change functions in plant stress responses.Maintaining ion ho-meostasis under salt stress requires coordinated activation of two types of central regulators:plasma membrane(PM)H^(+)-ATPase and Na^(+)/H^(+) antiporter.In this study,we used a bioassay-guided isolation approach to identify endogenous small molecules that affect PM H^(+)-ATPase and Na^(+)/H^(+) antiporter activities and identified phosphatidylinositol(PI),which inhibits PM H^(+)-ATPase activity under non-stress conditions in Arabidopsis by directly binding to the C terminus of the PM H^(+)-ATPase AHA2.Under salt stress,the phosphatidylinositol 4-phosphate-to-phosphatidylinositol(PI4P-to-PI)ratio increased,and PI4P bound and activated the PM Na^(+)/H^(+) antiporter.PI prefers binding to the inactive form of PM H^(+)-ATPase,while PI4P tends to bind to the active form of the Na^(+)/H^(+) antiporter.Consistent with this,pis1 mutants,with reduced levels of PI,displayed increased PM H^(+)-ATPase activity and salt stress toler-ance,while the pi4kβ1 mutant,with reduced levels of PI4P,displayed reduced PM Na^(+)/H^(+) antiporter activity and salt stress tolerance.Collectively,our results reveal that the dynamic change between PI and PI4P in response to salt stress in Arabidopsis is crucial for maintaining ion homeostasis to protect plants from un-favorable environmental conditions.展开更多
基金supported by the National Natural Science Foundation of China(No.51574105)the Science and Technology Program of Hebei Province,China(No.23564101D)+2 种基金the Natural Science Foundation of Hebei Province,China(No.E2021209147)the Key Research Project of North China University of Science and Technology(No.ZD-ST-202308)the Postgraduate Innovation Funding Project of Hebei Province,China(No.CXZZBS2024135).
文摘Calcium ferrite(CF)is recognized as a potential green and efficient functional material because of its advantages of magnetism,electrochemistry,catalysis,and biocompatibility in the fields of materials chemistry,environmental engineering,and biomedicine.There-fore,the obtained research results need to be systematically summarized,and new perspectives on CF and its composite materials need to be analyzed.Based on the presented studies of CF and its composite materials,the types and structures of the crystal are summarized.In addition,the current application technologies and theoretical mechanisms with various properties in different fields are elucidated.Moreover,the various preparation methods of CF and its composite materials are elaborated in detail.Most importantly,the advantages and disadvantages of the synthesis methods of CF and its composite materials are discussed,and the existing problems and emerging challenges in practical production are identified.Furthermore,the key future research directions of CF and its composite materials have been prospected from the potential application technologies to provide references for its synthesis and efficient utilization.
基金This work was supported by Liaoning Natural Fund Guidance Plan Project(No.20180550021)Dalian Science and Technology Star Project(No.2017RQ021)2019 Qingdao Binhai University-level Science and Technology Plan Research Project(No.2019KY09).
文摘Software defect feature selection has problems of feature space dimensionality reduction and large search space.This research proposes a defect prediction feature selection framework based on improved shuffled frog leaping algorithm(ISFLA).Using the two-level structure of the framework and the improved hybrid leapfrog algorithm's own advantages,the feature values are sorted,and some features with high correlation are selected to avoid other heuristic algorithms in the defect prediction that are easy to produce local The case where the convergence rate of the optimal or parameter optimization process is relatively slow.The framework improves generalization of predictions of unknown data samples and enhances the ability to search for features related to learning tasks.At the same time,this framework further reduces the dimension of the feature space.After the contrast simulation experiment with other common defect prediction methods,we used the actual test data set to verify the framework for multiple iterations on Internet of Things(IoT)system platform.The experimental results show that the software defect prediction feature selection framework based on ISFLA is very effective in defect prediction of IoT communication software.This framework can save the testing time of IoT communication software,effectively improve the performance of software defect prediction,and ensure the software quality.
基金This work is supported by Shandong Provincial Natural Science Foundation,China under Grant No.ZR2017MG011This work is also supported by Key Research and Development Program in Shandong Provincial(2017GGX90103).
文摘Monitoring,understanding and predicting Origin-destination(OD)flows in a city is an important problem for city planning and human activity.Taxi-GPS traces,acted as one kind of typical crowd sensed data,it can be used to mine the semantics of OD flows.In this paper,we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China.The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows.Then based on a novel complex network model,a semantics mining method of OD flows is proposed through compounding Points of Interests(POI)network and public transport network to the OD flows network.The propose method would offer a novel way to predict the location characteristic and future traffic conditions accurately.
基金supported by grants ofrom the National Natural Science Foundation of China(31430012,31872659,32070301,U1706201,31921001,31861133005,21625201,21961142010,21661140001,91853202,and 21521003)the National Key Research and Development Program of China(2017YFA0505200)the Beijing Outstanding Young Scientist Program(BJJWZYJH01201910001001).
文摘Plant metabolites are dynamically modified and distributed in response to environmental changes.How-ever,it is poorly understood how metabolic change functions in plant stress responses.Maintaining ion ho-meostasis under salt stress requires coordinated activation of two types of central regulators:plasma membrane(PM)H^(+)-ATPase and Na^(+)/H^(+) antiporter.In this study,we used a bioassay-guided isolation approach to identify endogenous small molecules that affect PM H^(+)-ATPase and Na^(+)/H^(+) antiporter activities and identified phosphatidylinositol(PI),which inhibits PM H^(+)-ATPase activity under non-stress conditions in Arabidopsis by directly binding to the C terminus of the PM H^(+)-ATPase AHA2.Under salt stress,the phosphatidylinositol 4-phosphate-to-phosphatidylinositol(PI4P-to-PI)ratio increased,and PI4P bound and activated the PM Na^(+)/H^(+) antiporter.PI prefers binding to the inactive form of PM H^(+)-ATPase,while PI4P tends to bind to the active form of the Na^(+)/H^(+) antiporter.Consistent with this,pis1 mutants,with reduced levels of PI,displayed increased PM H^(+)-ATPase activity and salt stress toler-ance,while the pi4kβ1 mutant,with reduced levels of PI4P,displayed reduced PM Na^(+)/H^(+) antiporter activity and salt stress tolerance.Collectively,our results reveal that the dynamic change between PI and PI4P in response to salt stress in Arabidopsis is crucial for maintaining ion homeostasis to protect plants from un-favorable environmental conditions.
