Background With an aggravated social ageing level, the number of patients with Alzheimer's disease (AD) is gradually increasing, and mild cognitive impairment (MCI) is considered to be an early form of Alzheimer&#...Background With an aggravated social ageing level, the number of patients with Alzheimer's disease (AD) is gradually increasing, and mild cognitive impairment (MCI) is considered to be an early form of Alzheimer's disease. How to distinguish diseases in the early stage for the purposes of early diagnosis and treatment is an important topic. Aims The purpose of our study was to investigate the differences in brain cortical thickness and surface area among elderly patients with AD, elderly patients with amnestic MCI (aMCI) and normal controls (NC). Methods 20 AD patients, 21 aMCIs and 25 NC were recruited in the study. FreeSurfer software was used to calculate cortical thickness and surface area among groups. Results The patients with AD had less cortical thickness both in the left and right hemisphere in 17 of the 36 brain regions examined than the patients with aMCI or NC. The patients with AD also had smaller cerebral surface area both in the left and right hemisphere in 3 of the 36 brain regions examined than the patients with aMCI or NC. Compared with the NC, the patients with aMCI only had slight atrophy in the inferior parietal lobe of the left hemisphere, and no significant difference was found. Conclusion AD, as well as aMCI (to a lesser extent), is associated with reduced cortical thickness and surface area in a few brain regions associated with cognitive impairment. These results suggest that cortical thickness and surface area could be used for early detection of AD.展开更多
An adaptive learning rule of synapses is proposed for a general asymmetric non-identical neural network.Its feasibility is proved by the Lasalle principle.Numerical simulation results show that synaptic connection wei...An adaptive learning rule of synapses is proposed for a general asymmetric non-identical neural network.Its feasibility is proved by the Lasalle principle.Numerical simulation results show that synaptic connection weight can converge to an appropriate strength and the identical network comes to synchronization.Furthermore,by this approach of learning,a non-identical neural population can still reach synchronization.This means that the learning rule has robustness on mismatch parameters.The firing rhythm of the neural population is totally dependent on topological properties,which promotes our understanding of neuron population activities.展开更多
We present an analytical solution of two solitons of Bose-Einstein condensates trapped in a double-barrier potential by using a multiple-scale method. In the linear case, we find that the stable spots of the soliton f...We present an analytical solution of two solitons of Bose-Einstein condensates trapped in a double-barrier potential by using a multiple-scale method. In the linear case, we find that the stable spots of the soliton formation are at the top of the barrier potential and at the region of barrier potential absence. For weak nonlinearity, it is shown that the height of the barrier potential has an important effect on the dark soliton dynamical properties. Especially, in the case of regarding a double-barrier potential as the output source of the solitons, the collision spots between two dark solitons can be controlled by the height of the barrier potential.展开更多
We first present an analytical solution of the single and double solitions of Bose-Einstein condensates trapped in a double square well potential using the multiple-scale method. Then, we show by numerical calculation...We first present an analytical solution of the single and double solitions of Bose-Einstein condensates trapped in a double square well potential using the multiple-scale method. Then, we show by numerical calculation that a dark soliton can be transmitted through the square well potential. With increasing depth of the square well potential, the amplitude of the dark soliton becomes larger, and the soliton propagates faster. In particular, we treat the collision behaviour of the condensates trapped in either equal or different depths of the double square well potential. If we regard the double square well potential as the output source of the solitons, the collision locations （position and time） between two dark solitons can be controlled by its depth.展开更多
With the continuous expansion of software applications,people’s requirements for software quality are increasing.Software defect prediction is an important technology to improve software quality.It often encodes the ...With the continuous expansion of software applications,people’s requirements for software quality are increasing.Software defect prediction is an important technology to improve software quality.It often encodes the software into several features and applies the machine learning method to build defect prediction classifiers,which can estimate the software areas is clean or buggy.However,the current encoding methods are mainly based on the traditional manual features or the AST of source code.Traditional manual features are difficult to reflect the deep semantics of programs,and there is a lot of noise information in AST,which affects the expression of semantic features.To overcome the above deficiencies,we combined with the Convolutional Neural Networks(CNN)and proposed a novel compiler Intermediate Representation(IR)based program encoding method for software defect prediction(CIR-CNN).Specifically,our program encoding method is based on the compiler IR,which can eliminate a large amount of noise information in the syntax structure of the source code and facilitate the acquisition of more accurate semantic information.Secondly,with the help of data flow analysis,a Data Dependency Graph(DDG)is constructed on the compiler IR,which helps to capture the deeper semantic information of the program.Finally,we use the widely used CNN model to build a software defect prediction model,which can increase the adaptive ability of the method.To evaluate the performance of the CIR-CNN,we use seven projects from PROMISE datasets to set up comparative experiments.The experiments results show that,in WPDP,with our CIR-CNN method,the prediction accuracy was improved by 12%for the AST-encoded CNN-based model and by 20.9%for the traditional features-based LR model,respectively.And in CPDP,the AST-encoded DBNbased model was improved by 9.1%and the traditional features-based TCA+model by 19.2%,respectively.展开更多
As nanoscale processing becomes the mainstream in IC manufacturing,the crosstalk problem rises as a serious challenge,not only for energy-efficiency and performance but also for security requirements.In this paper,we ...As nanoscale processing becomes the mainstream in IC manufacturing,the crosstalk problem rises as a serious challenge,not only for energy-efficiency and performance but also for security requirements.In this paper,we propose a register reallocation algorithm called Nearby Access based Register Reallocation(NARR)to reduce the crosstalk between instruction buses.The method includes construction of the software Nearby Access Aware Interference Graph(NAIG),using data flow analysis at assembly level,and reallocation of the registers to the software.Experimental results show that the crosstalk could be dramatically minimized,especially for 4C crosstalk,with a reduction of 80.84%in average,and up to 99.99%at most.展开更多
Timing speculative(TS)architecture is promising for improving the energy efficiency of microprocessors.Error recovery units,designed for tolerating occasional timing errors,have been used to support a wider range of v...Timing speculative(TS)architecture is promising for improving the energy efficiency of microprocessors.Error recovery units,designed for tolerating occasional timing errors,have been used to support a wider range of voltage scaling,therefore to achieve a better energy efficiency.More specifically,the timing error rate,influenced mainly by data forwarding,is the bottleneck for voltage down-scaling in TS processors.In this paper,a new Timing Error Aware Register Allocation method is proposed.First,we designed the Dependency aware Interference Graph(DIG)construction to get the information of Read after Write(RAW)in programs.To build the construction,we get the disassemble code as input and suppose that there are unlimited registers,the same way as so-called virtual registers in many compilers.Then we change the disassemble codes to the SSA form for each basic block to make sure the registers are defined only once.Based on the DIG construction,registers were real-located to eliminate the timing error,by loosening the RAW dependencies.We con-struct the DIG for each function of the program and sort the edge of DIG by an increasing weight order.Since a smaller weighted-edge value means that its owner nodes have more frequent access in instruction flows,we expect it in different registers with no read-write dependency.At the same time,we make sure that there are no additional new spill codes emerging in our algorithm to minimize the rate of spill code.A high rate of spill code will not only decrease the performance of the system but also increase the unexpected read-write dependency.Next,we reallocate the reg-isters by weight order in turn to loosen the RAW dependencies.Furthermore,we use the NOP operation to pad the instructions with a minimal distance value of 2.Experiment results showed that the average distance of RAW dependencies was increased by over 20%.展开更多
With the rapid development of information technology,audit objects and audit itself are more and more inseparable from software.As an important means of software security audit,code security audit will become an impor...With the rapid development of information technology,audit objects and audit itself are more and more inseparable from software.As an important means of software security audit,code security audit will become an important aspect of future audit that cannot be ignored.However,the existing code security audit ismainly based on source code,which is difficult to meet the audit needs of more and more programming languages and binary commercial software.Based on the idea of normalized transformation,this paper constructs a cross language code security audit framework(CLCSA).CLCSA first uses compile/decompile technology to convert different highlevel programming languages and binary codes into normalized representation,and then usesmachine learning technology to build a cross language code security audit model based on normalized representation to evaluate code security and find out possible code security vulnerabilities.Finally,for the discovered vulnerabilities,the heuristic search strategy will be used to find the best repair scheme from the existing normalized representation sample library for automatic repair,which can improve the effectiveness of code security audit.CLCSA realizes the normalized code security audit of different types and levels of code,which provides a strong support for improving the breadth and depth of code security audit.展开更多
基金Collaborative Innovation Center for Translational Medicine at Shanghai Jiao Tong University School of Medicine TM201728National Nature Science Foundation of China 81571298+2 种基金Shanghai health system excellent talent training program (excellent subject leader) project 2017BR054Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support 20172029Shanghai Pujiang Program 17PJD038.
文摘Background With an aggravated social ageing level, the number of patients with Alzheimer's disease (AD) is gradually increasing, and mild cognitive impairment (MCI) is considered to be an early form of Alzheimer's disease. How to distinguish diseases in the early stage for the purposes of early diagnosis and treatment is an important topic. Aims The purpose of our study was to investigate the differences in brain cortical thickness and surface area among elderly patients with AD, elderly patients with amnestic MCI (aMCI) and normal controls (NC). Methods 20 AD patients, 21 aMCIs and 25 NC were recruited in the study. FreeSurfer software was used to calculate cortical thickness and surface area among groups. Results The patients with AD had less cortical thickness both in the left and right hemisphere in 17 of the 36 brain regions examined than the patients with aMCI or NC. The patients with AD also had smaller cerebral surface area both in the left and right hemisphere in 3 of the 36 brain regions examined than the patients with aMCI or NC. Compared with the NC, the patients with aMCI only had slight atrophy in the inferior parietal lobe of the left hemisphere, and no significant difference was found. Conclusion AD, as well as aMCI (to a lesser extent), is associated with reduced cortical thickness and surface area in a few brain regions associated with cognitive impairment. These results suggest that cortical thickness and surface area could be used for early detection of AD.
基金Supported by the National Natural Science Foundation of China under Grant No 10872068the Fundamental Research Funds for the Central Universities,Youth Cultivating Foundation of Hangzhou Normal University under Grant No 2010QN02the Key Program of National Natural Science Foundation of China under Grant No 11232005(on neurodynamics research and experimental analysis of perceptual cognition and decision making)。
文摘An adaptive learning rule of synapses is proposed for a general asymmetric non-identical neural network.Its feasibility is proved by the Lasalle principle.Numerical simulation results show that synaptic connection weight can converge to an appropriate strength and the identical network comes to synchronization.Furthermore,by this approach of learning,a non-identical neural population can still reach synchronization.This means that the learning rule has robustness on mismatch parameters.The firing rhythm of the neural population is totally dependent on topological properties,which promotes our understanding of neuron population activities.
基金Project supported by the Science Research Foundation of the Education Bureau of Hunan Province of China (Grant No.09C227)
文摘We present an analytical solution of two solitons of Bose-Einstein condensates trapped in a double-barrier potential by using a multiple-scale method. In the linear case, we find that the stable spots of the soliton formation are at the top of the barrier potential and at the region of barrier potential absence. For weak nonlinearity, it is shown that the height of the barrier potential has an important effect on the dark soliton dynamical properties. Especially, in the case of regarding a double-barrier potential as the output source of the solitons, the collision spots between two dark solitons can be controlled by the height of the barrier potential.
基金supported by the Science Research Foundation of the Education Bureau of Hunan Province of China (Grant No. 09C227)
文摘We first present an analytical solution of the single and double solitions of Bose-Einstein condensates trapped in a double square well potential using the multiple-scale method. Then, we show by numerical calculation that a dark soliton can be transmitted through the square well potential. With increasing depth of the square well potential, the amplitude of the dark soliton becomes larger, and the soliton propagates faster. In particular, we treat the collision behaviour of the condensates trapped in either equal or different depths of the double square well potential. If we regard the double square well potential as the output source of the solitons, the collision locations （position and time） between two dark solitons can be controlled by its depth.
基金This work was supported by the Universities Natural Science Research Project of Jiangsu Province under Grant 20KJB520026 and 20KJA520002the Foundation for Young Teachers of Nanjing Auditing University under Grant 19QNPY018the National Nature Science Foundation of China under Grant 71972102 and 61902189.
文摘With the continuous expansion of software applications,people’s requirements for software quality are increasing.Software defect prediction is an important technology to improve software quality.It often encodes the software into several features and applies the machine learning method to build defect prediction classifiers,which can estimate the software areas is clean or buggy.However,the current encoding methods are mainly based on the traditional manual features or the AST of source code.Traditional manual features are difficult to reflect the deep semantics of programs,and there is a lot of noise information in AST,which affects the expression of semantic features.To overcome the above deficiencies,we combined with the Convolutional Neural Networks(CNN)and proposed a novel compiler Intermediate Representation(IR)based program encoding method for software defect prediction(CIR-CNN).Specifically,our program encoding method is based on the compiler IR,which can eliminate a large amount of noise information in the syntax structure of the source code and facilitate the acquisition of more accurate semantic information.Secondly,with the help of data flow analysis,a Data Dependency Graph(DDG)is constructed on the compiler IR,which helps to capture the deeper semantic information of the program.Finally,we use the widely used CNN model to build a software defect prediction model,which can increase the adaptive ability of the method.To evaluate the performance of the CIR-CNN,we use seven projects from PROMISE datasets to set up comparative experiments.The experiments results show that,in WPDP,with our CIR-CNN method,the prediction accuracy was improved by 12%for the AST-encoded CNN-based model and by 20.9%for the traditional features-based LR model,respectively.And in CPDP,the AST-encoded DBNbased model was improved by 9.1%and the traditional features-based TCA+model by 19.2%,respectively.
基金This work was supported by the General Project of Humanities and Social Sciences Research of the Ministry of Education(16YJA740039)the Foundation Project of Philosophy and Social Science of Hunan(17YBA115).
文摘As nanoscale processing becomes the mainstream in IC manufacturing,the crosstalk problem rises as a serious challenge,not only for energy-efficiency and performance but also for security requirements.In this paper,we propose a register reallocation algorithm called Nearby Access based Register Reallocation(NARR)to reduce the crosstalk between instruction buses.The method includes construction of the software Nearby Access Aware Interference Graph(NAIG),using data flow analysis at assembly level,and reallocation of the registers to the software.Experimental results show that the crosstalk could be dramatically minimized,especially for 4C crosstalk,with a reduction of 80.84%in average,and up to 99.99%at most.
基金This work was supported by the General Project of Humanities and Social Sciences Research of the Ministry of Education(16YJA740039,Sheng Xiao,2016)the Foundation Project of Philosophy and Social Science of Hunan(17YBA115,Sheng Xiao,2018).
文摘Timing speculative(TS)architecture is promising for improving the energy efficiency of microprocessors.Error recovery units,designed for tolerating occasional timing errors,have been used to support a wider range of voltage scaling,therefore to achieve a better energy efficiency.More specifically,the timing error rate,influenced mainly by data forwarding,is the bottleneck for voltage down-scaling in TS processors.In this paper,a new Timing Error Aware Register Allocation method is proposed.First,we designed the Dependency aware Interference Graph(DIG)construction to get the information of Read after Write(RAW)in programs.To build the construction,we get the disassemble code as input and suppose that there are unlimited registers,the same way as so-called virtual registers in many compilers.Then we change the disassemble codes to the SSA form for each basic block to make sure the registers are defined only once.Based on the DIG construction,registers were real-located to eliminate the timing error,by loosening the RAW dependencies.We con-struct the DIG for each function of the program and sort the edge of DIG by an increasing weight order.Since a smaller weighted-edge value means that its owner nodes have more frequent access in instruction flows,we expect it in different registers with no read-write dependency.At the same time,we make sure that there are no additional new spill codes emerging in our algorithm to minimize the rate of spill code.A high rate of spill code will not only decrease the performance of the system but also increase the unexpected read-write dependency.Next,we reallocate the reg-isters by weight order in turn to loosen the RAW dependencies.Furthermore,we use the NOP operation to pad the instructions with a minimal distance value of 2.Experiment results showed that the average distance of RAW dependencies was increased by over 20%.
基金This work was supported by the Universities Natural Science Research Project of Jiangsu Province under Grant 20KJB520026the Natural Science Foundation of Jiangsu Province under Grant BK20180821.
文摘With the rapid development of information technology,audit objects and audit itself are more and more inseparable from software.As an important means of software security audit,code security audit will become an important aspect of future audit that cannot be ignored.However,the existing code security audit ismainly based on source code,which is difficult to meet the audit needs of more and more programming languages and binary commercial software.Based on the idea of normalized transformation,this paper constructs a cross language code security audit framework(CLCSA).CLCSA first uses compile/decompile technology to convert different highlevel programming languages and binary codes into normalized representation,and then usesmachine learning technology to build a cross language code security audit model based on normalized representation to evaluate code security and find out possible code security vulnerabilities.Finally,for the discovered vulnerabilities,the heuristic search strategy will be used to find the best repair scheme from the existing normalized representation sample library for automatic repair,which can improve the effectiveness of code security audit.CLCSA realizes the normalized code security audit of different types and levels of code,which provides a strong support for improving the breadth and depth of code security audit.
