With the popularity of the Internet and improvement of information technology,digital information sharing increasingly becomes the trend.More and More universities pay attention to the digital campus,and the construct...With the popularity of the Internet and improvement of information technology,digital information sharing increasingly becomes the trend.More and More universities pay attention to the digital campus,and the construction of digital library has become the focus of digital campus.A set of manageable,authenticated and secure solutions are needed for remote access to make the campus network be a transit point for the outside users.Remote Access IPSEC Virtual Private Network gives the solution of remote access to e-library resources,networks resources and so on very safely through a public network.It establishes a safe and stable tunnel which encrypts the data passing through it with robust secured algorithms.It is to establish a virtual private network in Internet,so that the two long-distance network users can transmit data to each other in a dedicated network channel.Using this technology,multi-network campus can communicate securely in the unreliable public internet.展开更多
Security measures for a computer network system can be enhanced with better understanding the vulnerabilities and their behavior over the time. It is observed that the effects of vulnerabilities vary with the time ove...Security measures for a computer network system can be enhanced with better understanding the vulnerabilities and their behavior over the time. It is observed that the effects of vulnerabilities vary with the time over their life cycle. In the present study, we have presented a new methodology to assess the magnitude of the risk of a vulnerability as a “Risk Rank”. To derive this new methodology well known Markovian approach with a transition probability matrix is used including relevant risk factors for discovered and recorded vulnerabilities. However, in addition to observing the risk factor for each vulnerability individually we have introduced the concept of ranking vulnerabilities at a particular time taking a similar approach to Google Page Rank Algorithm. New methodology is exemplified using a simple model of computer network with three recorded vulnerabilities with their CVSS scores.展开更多
Hydrological monitoring and real-time access to data are valuable for hydrological research and water resources management. In the recent decades, rapid developments in digital technology, micro-electromechanical syst...Hydrological monitoring and real-time access to data are valuable for hydrological research and water resources management. In the recent decades, rapid developments in digital technology, micro-electromechanical systems, low power micro-sensing technologies and improved industrial manufacturing processes have resulted in retrieving real-time data through Wireless Sensor Networks (WSNs) systems. In this study, a remotely operated low-cost and robust WSN system was developed to monitor and collect real-time hydrologic data from a small agricultural watershed in harsh weather conditions and upland rolling topography of Southern Ontario, Canada. The WSN system was assembled using off-the-shelf hardware components, and an open source operating system was used to minimize the cost. The developed system was rigorously tested in the laboratory and the field and found to be accurate and reliable for monitoring climatic and hydrologic parameters. The soil moisture and runoff data for 7 springs, 19 summer, and 19 fall season rainfall events over the period of more than two years were successfully collected in a small experimental agricultural watershed situated near Elora, Ontario, Canada. The developed WSN system can be readily extended for the purpose of most hydrological monitoring applications, although it was explicitly tailored for a project focused on mapping the Variable Source Areas (VSAs) in a small agricultural watershed.展开更多
A two-stage directed Semi-Markov repairable network system is presented in this paper to model the performance of many transmission systems, such as power or oil transmission network, water or gas supply network, etc....A two-stage directed Semi-Markov repairable network system is presented in this paper to model the performance of many transmission systems, such as power or oil transmission network, water or gas supply network, etc. The availability of the system is discussed by using Markov renewal theory, Laplace transform and probability analysis methods. A numerical example is given to illustrate the results obtained in the paper.展开更多
The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchic...The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.展开更多
Objective: To assess and compare the clinical efficacy and safety of cognitive enhancers(donepezil, galantamine, rivastigmine, and memantine) on cognition, behavior, function, and global status in patients with vascul...Objective: To assess and compare the clinical efficacy and safety of cognitive enhancers(donepezil, galantamine, rivastigmine, and memantine) on cognition, behavior, function, and global status in patients with vascular cognitive impairment.Data sources: The initial literature search was performed with PubMed, EMBASE, the Cochrane Methodology Register, the Cochrane Central Register of Controlled Trials, and Cumulative Index to Nursing & Allied Health(CINAHL) from inception to January 2018 for studies regarding donepezil, galantamine, rivastigmine, and memantine for treatment of vascular cognitive impairment.Data selection: Randomized controlled trials on donepezil, galantamine, rivastigmine, and memantine as monotherapy in the treatment of vascular cognitive impairment were included. A Bayesian network meta-analysis was conducted. Outcome measures: Efficacy was assessed by changes in scores of the Alzheimer's Disease Assessment Scale, cognitive subscale, Mini-Mental State Examination, Neuropsychiatric Inventory scores and Clinician's Interview-Based Impression of Change Scale Plus Caregiver's Input, Activities of Daily Living, the Clinical Dementia Rating scale. Safety was evaluated by mortality, total adverse events(TAEs), serious adverse events(SAEs), nausea, vomiting. diarrhea, or cerebrovascular accidents(CVAs). Results: After screening 1717 citations, 12 randomized controlled trials were included. Donepezil and rivastigmine(mean difference(e) = –0.77, 95% confidence interval(CI): 0.25–1.32; MD = 1.05, 95% CI: 0.18–1.79) were significantly more effective than placebo in reducing Mini-Mental State Examination scores. Donepezil, galantamine, and memantine(MD = –1.30, 95% CI: –2.27 to –0.42; MD = –1.67, 95% CI: –3.36 to –0.06; MD = –2.27, 95% CI: –3.91 to –0.53) showed superior benefits on the Alzheimer's Disease Assessment Scale–cognitive scores compared with placebo. Memantine(MD = 2.71, 95% CI: 1.05–7.29) improved global status(Clinician's Interview-Based Impression of Change Scale Plus Caregiver's Input) more than the placebo. Safety results revealed that donepezil 10 mg(odds ratio(OR) = 3.04, 95% CI: 1.86–5.41) contributed to higer risk of adverse events than placebo. Galantamine(OR = 5.64, 95% CI: 1.31–26.71) increased the risk of nausea. Rivastigmine(OR = 16.80, 95% CI: 1.78–319.26) increased the risk of vomiting. No agents displayed a significant risk of serious adverse events, mortality, cerebrovascular accidents, or diarrhea.Conclusion: We found significant efficacy of donepezil, galantamine, and memantine on cognition. Memantine can provide significant efficacy in global status. They are all safe and well tolerated.展开更多
The service and application of a network is a behavioral process that is oriented toward its operations and tasks, whose metrics and evaluation are still somewhat of a rough comparison, This paper describes sce- nes o...The service and application of a network is a behavioral process that is oriented toward its operations and tasks, whose metrics and evaluation are still somewhat of a rough comparison, This paper describes sce- nes of network behavior as differential manifolds, Using the homeomorphic transformation of smooth differential manifolds, we provide a mathematical definition of network behavior and propose a mathe- matical description of the network behavior path and behavior utility, Based on the principle of differen- tial geometry, this paper puts forward the function of network behavior and a calculation method to determine behavior utility, and establishes the calculation principle of network behavior utility, We also provide a calculation framework for assessment of the network＇s attack-defense confrontation on the strength of behavior utility, Therefore, this paper establishes a mathematical foundation for the objective measurement and precise evaluation of network behavior,展开更多
BACKGROUND Artificial intelligence,such as convolutional neural networks(CNNs),has been used in the interpretation of images and the diagnosis of hepatocellular cancer(HCC)and liver masses.CNN,a machine-learning algor...BACKGROUND Artificial intelligence,such as convolutional neural networks(CNNs),has been used in the interpretation of images and the diagnosis of hepatocellular cancer(HCC)and liver masses.CNN,a machine-learning algorithm similar to deep learning,has demonstrated its capability to recognise specific features that can detect pathological lesions.AIM To assess the use of CNNs in examining HCC and liver masses images in the diagnosis of cancer and evaluating the accuracy level of CNNs and their performance.METHODS The databases PubMed,EMBASE,and the Web of Science and research books were systematically searched using related keywords.Studies analysing pathological anatomy,cellular,and radiological images on HCC or liver masses using CNNs were identified according to the study protocol to detect cancer,differentiating cancer from other lesions,or staging the lesion.The data were extracted as per a predefined extraction.The accuracy level and performance of the CNNs in detecting cancer or early stages of cancer were analysed.The primary outcomes of the study were analysing the type of cancer or liver mass and identifying the type of images that showed optimum accuracy in cancer detection.RESULTS A total of 11 studies that met the selection criteria and were consistent with the aims of the study were identified.The studies demonstrated the ability to differentiate liver masses or differentiate HCC from other lesions(n=6),HCC from cirrhosis or development of new tumours(n=3),and HCC nuclei grading or segmentation(n=2).The CNNs showed satisfactory levels of accuracy.The studies aimed at detecting lesions(n=4),classification(n=5),and segmentation(n=2).Several methods were used to assess the accuracy of CNN models used.CONCLUSION The role of CNNs in analysing images and as tools in early detection of HCC or liver masses has been demonstrated in these studies.While a few limitations have been identified in these studies,overall there was an optimal level of accuracy of the CNNs used in segmentation and classification of liver cancers images.展开更多
The study of the netlike earthquake distribution indicates that in the central-eastern part of Asia continent there are two network systems: the central-eastern Asia system and the southeastern China system.As interpr...The study of the netlike earthquake distribution indicates that in the central-eastern part of Asia continent there are two network systems: the central-eastern Asia system and the southeastern China system.As interpreted by the multilayer tectonic model,they might be a manifestation of the plastic-flow network systems in the lower lithosphere,including the lower crust and the mantle lid.Each network system is enclosed by different types of boundaries,including one driving boundary and some constraining and releasing boundaries.The two plastic-flow network systems with the Himalayan and Taiwan arcs as their driving boundaries play the role of controlling the intraplate tectonic deformation,stress field,seismicity,and subdivision of tectonic units.展开更多
World Data Center-D for Seismology(WDCDS)is a member of the World Data Center System under ICSU and is one of the nine World Data Centers located in China(WDC-D).During the period from 1993 to 1996,an information netw...World Data Center-D for Seismology(WDCDS)is a member of the World Data Center System under ICSU and is one of the nine World Data Centers located in China(WDC-D).During the period from 1993 to 1996,an information network system,called CSDInet,was developed in National Center for Seismic Data and Information(NCSDI)and has become the basic technical supporting system for WDC-D for Seismology.CSDInet consists of four basic parts:computer network center,LAN(Local Area Network),link to Internet,and nationwide PSTN(with dialing-up telephone line)user network.In this paper a "multi-layer multi-mode" management of data flow for this system will be explained and the data and information services will be described.展开更多
The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the ...The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the formation of deductive theory is represented as the development of a certain informational space, the elements of which are structured in the form of the orientated semantic net. This net is properly metrized and characterized by a certain system of coverings. It allows injecting net optimization parameters, regulating qualitative aspects of knowledge system under consideration. To regulate the creative processes of the formation and realization of mathematical know- edge, stochastic model of formation deductive theory is suggested here in the form of branching Markovian process, which is realized in the corresponding informational space as a semantic net. According to this stochastic model we can get correct foundation of criterion of optimization creative processes that leads to “great main points” strategy (GMP-strategy) in the process of realization of the effective control in the research work in the sphere of mathematics and its applications.展开更多
The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It has become a key part of the urban lake management. An e...The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It has become a key part of the urban lake management. An evaluation methodology system for IRSN project can provide important guidance for the selection of different water diversion schemes. However, few if any comprehensive evaluation systems have been developed to evaluate the hydrodynamics and water quality of connected lakes. This study developed a comprehensive evaluation system based on multi-indexes including aspects of water hydrodynamics, water quality and socioeconomics. A two-dimensional (2-D) mathematical hydrodynamics and water quality model was built, using NH<sub>3</sub>-N, TN and TP as water quality index. The IRSN project in Tangxun Lake group was used as a testbed here, and five water diversion schemes were simulated and evaluated. Results showed that the IRSN project can improve the water fluidity and the water quality obviously after a short time of water diversion, while the improvement rates decreased gradually as the water diversion went on. Among these five schemes, Scheme V showed the most noticeable improvement in hydrodynamics and water quality, and brought the most economic benefits. This comprehensive evaluation method can provide useful reference for the implementation of other similar IRSN projects.展开更多
A Reconfigurable Intelligent Surface(RIS)can relay signals from the transmitter to the receiver.In this regard,RISs operate similarly to traditional relays.We design a Multiple-Input-Multiple-Output(MIMO)system with a...A Reconfigurable Intelligent Surface(RIS)can relay signals from the transmitter to the receiver.In this regard,RISs operate similarly to traditional relays.We design a Multiple-Input-Multiple-Output(MIMO)system with a hybrid network of RIS and Half-Duplex(HD)Amplify-and-Forward(AF)relay.We model the system’s signal propagation and propose a new algorithm to get the system’s Achievable Rate(AR)value.We complete simulations to evaluate the performance of the RIS and HD-AF relay hybrid network system compared to the system assisted by either the RIS or HD-AF relay.The simulations indicate that many factors can considerably influence the system performance.Selecting an optimal placement for the RIS and relay can result in the best performance for the RIS and HD-AF relay hybrid network system in situations where the direct link between the receiver and transmitter is absent.展开更多
We developed L3SN, a scalable, longevous, adaptive, and internet accessible wireless sensor network system for agriculture information monitoring, which is meticulously designed to meet the requirement of thousands he...We developed L3SN, a scalable, longevous, adaptive, and internet accessible wireless sensor network system for agriculture information monitoring, which is meticulously designed to meet the requirement of thousands hectares coverage, years of time monitoring and the adverse environment. The system architecture, the agriculture sensor device, the mesh protocol, and the web-based information processing platform are introduced. We also presented some implementation experience. The mesh protocol (LayerMesh) is highlighted, in which “stair scheduling” and “distributed dynamic load-balancing” are proposed to response the scalability, longevity and adaptivity requirements. We believe the design of L3SN is useful to many other large-scale, longevous applications such as hydrologic monitoring, geological monitoring etc.展开更多
AIM:To compare the outcomes of four adjuvants used for internal limiting membrane(ILM)peeling in macular hole surgery,including indocyanine green(ICG),brilliant blue G(BBG),triamcinolone(TA)and trypan blue(TB),through...AIM:To compare the outcomes of four adjuvants used for internal limiting membrane(ILM)peeling in macular hole surgery,including indocyanine green(ICG),brilliant blue G(BBG),triamcinolone(TA)and trypan blue(TB),through systematic review and random-effects Bayesian network Meta-analysis.METHODS:PubMed,Cochrane library databases and Web of Science were searched until August 2018 for clinical trials comparing the above four adjuvants.ORs for postoperative best corrected visual acuity(BCVA)improvement and primary macular hole closure rates were compared between the different adjuvants.RESULTS:Twenty-seven eligible articles were included.For postoperative BCVA improvement,results of BBGassisted peeling were significantly more favorable than those of ICG(WMD 0.08,95%credible interval 0.01-0.16)and TA ranked highest.No significant differences were found between any other two groups in postoperative BCVA improvement.For postoperative primary macular hole closure rates,BBG ranked highest.However,no significant differences were shown between any two groups.CONCLUSION:TA and BBG are the optimum adjuvants for achieving postoperative BCVA improvement macular hole surgery with adjuvant-assisted ILM peeling.Among all adjuvants,the use of BBG is associated with the highest postoperative macular hole closure rate.展开更多
This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with...This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.展开更多
A method of system structural analysis based on decision making trial and evaluation laboratory together with interpretative structural modeling(DEMATEL-ISM) and entropy is proposed to clarify system structure of comm...A method of system structural analysis based on decision making trial and evaluation laboratory together with interpretative structural modeling(DEMATEL-ISM) and entropy is proposed to clarify system structure of communication networks and analyze mutual influencing degree between different networks.Mutual influencing degree and importance degree of elements are both considered to determine weights of elements,and the entropy of expert judgment results is used to omit unimportant influence relation and simplify system structure.Structural analysis on communication networks system shows that the proposed method can quantificationally present weights and mutual influencing degree of elements,and reasonably simplify system structure.The results indicate the rationality and feasibility of the method.展开更多
This paper presents a robust sliding mode controller for a class of unknown nonlinear discrete-time systems in the presence of fixed time delay. A neural-network approximation and the Lyapunov-Krasovskii functional th...This paper presents a robust sliding mode controller for a class of unknown nonlinear discrete-time systems in the presence of fixed time delay. A neural-network approximation and the Lyapunov-Krasovskii functional theory into the sliding-mode technique is used and a neural-network based sliding mode control scheme is proposed. Because of the novality of Chebyshev Neural Networks (CNNs), that it requires much less computation time as compare to multi layer neural network (MLNN), is preferred to approximate the unknown system functions. By means of linear matrix inequalities, a sufficient condition is derived to ensure the asymptotic stability such that the sliding mode dynamics is restricted to the defined sliding surface. The proposed sliding mode control technique guarantees the system state trajectory to the designed sliding surface. Finally, simulation results illustrate the main characteristics and performance of the proposed approach.展开更多
In this work, a total of 322 tests were taken on young volunteers by performing 10 different falls, 6 different Activities of Daily Living (ADL) and 7 Dynamic Gait Index (DGI) tests using a custom-designed Wireless Ga...In this work, a total of 322 tests were taken on young volunteers by performing 10 different falls, 6 different Activities of Daily Living (ADL) and 7 Dynamic Gait Index (DGI) tests using a custom-designed Wireless Gait Analysis Sensor (WGAS). In order to perform automatic fall detection, we used Back Propagation Artificial Neural Network (BP-ANN) and Support Vector Machine (SVM) based on the 6 features extracted from the raw data. The WGAS, which includes a tri-axial accelerometer, 2 gyroscopes, and a MSP430 microcontroller, is worn by the subjects at either T4 (at back) or as a belt-clip in front of the waist during the various tests. The raw data is wirelessly transmitted from the WGAS to a near-by PC for real-time fall classification. The BP ANN is optimized by varying the training, testing and validation data sets and training the network with different learning schemes. SVM is optimized by using three different kernels and selecting the kernel for best classification rate. The overall accuracy of BP ANN is obtained as 98.20% with LM and RPROP training from the T4 data, while from the data taken at the belt, we achieved 98.70% with LM and SCG learning. The overall accuracy using SVM was 98.80% and 98.71% with RBF kernel from the T4 and belt position data, respectively.展开更多
Protein Secondary Structure Prediction (PSSP) is considered as one of the major challenging tasks in bioinformatics, so many solutions have been proposed to solve that problem via trying to achieve more accurate predi...Protein Secondary Structure Prediction (PSSP) is considered as one of the major challenging tasks in bioinformatics, so many solutions have been proposed to solve that problem via trying to achieve more accurate prediction results. The goal of this paper is to develop and implement an intelligent based system to predict secondary structure of a protein from its primary amino acid sequence by using five models of Neural Network (NN). These models are Feed Forward Neural Network (FNN), Learning Vector Quantization (LVQ), Probabilistic Neural Network (PNN), Convolutional Neural Network (CNN), and CNN Fine Tuning for PSSP. To evaluate our approaches two datasets have been used. The first one contains 114 protein samples, and the second one contains 1845 protein samples.展开更多
文摘With the popularity of the Internet and improvement of information technology,digital information sharing increasingly becomes the trend.More and More universities pay attention to the digital campus,and the construction of digital library has become the focus of digital campus.A set of manageable,authenticated and secure solutions are needed for remote access to make the campus network be a transit point for the outside users.Remote Access IPSEC Virtual Private Network gives the solution of remote access to e-library resources,networks resources and so on very safely through a public network.It establishes a safe and stable tunnel which encrypts the data passing through it with robust secured algorithms.It is to establish a virtual private network in Internet,so that the two long-distance network users can transmit data to each other in a dedicated network channel.Using this technology,multi-network campus can communicate securely in the unreliable public internet.
文摘Security measures for a computer network system can be enhanced with better understanding the vulnerabilities and their behavior over the time. It is observed that the effects of vulnerabilities vary with the time over their life cycle. In the present study, we have presented a new methodology to assess the magnitude of the risk of a vulnerability as a “Risk Rank”. To derive this new methodology well known Markovian approach with a transition probability matrix is used including relevant risk factors for discovered and recorded vulnerabilities. However, in addition to observing the risk factor for each vulnerability individually we have introduced the concept of ranking vulnerabilities at a particular time taking a similar approach to Google Page Rank Algorithm. New methodology is exemplified using a simple model of computer network with three recorded vulnerabilities with their CVSS scores.
文摘Hydrological monitoring and real-time access to data are valuable for hydrological research and water resources management. In the recent decades, rapid developments in digital technology, micro-electromechanical systems, low power micro-sensing technologies and improved industrial manufacturing processes have resulted in retrieving real-time data through Wireless Sensor Networks (WSNs) systems. In this study, a remotely operated low-cost and robust WSN system was developed to monitor and collect real-time hydrologic data from a small agricultural watershed in harsh weather conditions and upland rolling topography of Southern Ontario, Canada. The WSN system was assembled using off-the-shelf hardware components, and an open source operating system was used to minimize the cost. The developed system was rigorously tested in the laboratory and the field and found to be accurate and reliable for monitoring climatic and hydrologic parameters. The soil moisture and runoff data for 7 springs, 19 summer, and 19 fall season rainfall events over the period of more than two years were successfully collected in a small experimental agricultural watershed situated near Elora, Ontario, Canada. The developed WSN system can be readily extended for the purpose of most hydrological monitoring applications, although it was explicitly tailored for a project focused on mapping the Variable Source Areas (VSAs) in a small agricultural watershed.
文摘A two-stage directed Semi-Markov repairable network system is presented in this paper to model the performance of many transmission systems, such as power or oil transmission network, water or gas supply network, etc. The availability of the system is discussed by using Markov renewal theory, Laplace transform and probability analysis methods. A numerical example is given to illustrate the results obtained in the paper.
文摘The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.
基金supported by the Natural Science Foundation of Liaoning Province of China,No.20170541036(to HYL)
文摘Objective: To assess and compare the clinical efficacy and safety of cognitive enhancers(donepezil, galantamine, rivastigmine, and memantine) on cognition, behavior, function, and global status in patients with vascular cognitive impairment.Data sources: The initial literature search was performed with PubMed, EMBASE, the Cochrane Methodology Register, the Cochrane Central Register of Controlled Trials, and Cumulative Index to Nursing & Allied Health(CINAHL) from inception to January 2018 for studies regarding donepezil, galantamine, rivastigmine, and memantine for treatment of vascular cognitive impairment.Data selection: Randomized controlled trials on donepezil, galantamine, rivastigmine, and memantine as monotherapy in the treatment of vascular cognitive impairment were included. A Bayesian network meta-analysis was conducted. Outcome measures: Efficacy was assessed by changes in scores of the Alzheimer's Disease Assessment Scale, cognitive subscale, Mini-Mental State Examination, Neuropsychiatric Inventory scores and Clinician's Interview-Based Impression of Change Scale Plus Caregiver's Input, Activities of Daily Living, the Clinical Dementia Rating scale. Safety was evaluated by mortality, total adverse events(TAEs), serious adverse events(SAEs), nausea, vomiting. diarrhea, or cerebrovascular accidents(CVAs). Results: After screening 1717 citations, 12 randomized controlled trials were included. Donepezil and rivastigmine(mean difference(e) = –0.77, 95% confidence interval(CI): 0.25–1.32; MD = 1.05, 95% CI: 0.18–1.79) were significantly more effective than placebo in reducing Mini-Mental State Examination scores. Donepezil, galantamine, and memantine(MD = –1.30, 95% CI: –2.27 to –0.42; MD = –1.67, 95% CI: –3.36 to –0.06; MD = –2.27, 95% CI: –3.91 to –0.53) showed superior benefits on the Alzheimer's Disease Assessment Scale–cognitive scores compared with placebo. Memantine(MD = 2.71, 95% CI: 1.05–7.29) improved global status(Clinician's Interview-Based Impression of Change Scale Plus Caregiver's Input) more than the placebo. Safety results revealed that donepezil 10 mg(odds ratio(OR) = 3.04, 95% CI: 1.86–5.41) contributed to higer risk of adverse events than placebo. Galantamine(OR = 5.64, 95% CI: 1.31–26.71) increased the risk of nausea. Rivastigmine(OR = 16.80, 95% CI: 1.78–319.26) increased the risk of vomiting. No agents displayed a significant risk of serious adverse events, mortality, cerebrovascular accidents, or diarrhea.Conclusion: We found significant efficacy of donepezil, galantamine, and memantine on cognition. Memantine can provide significant efficacy in global status. They are all safe and well tolerated.
文摘The service and application of a network is a behavioral process that is oriented toward its operations and tasks, whose metrics and evaluation are still somewhat of a rough comparison, This paper describes sce- nes of network behavior as differential manifolds, Using the homeomorphic transformation of smooth differential manifolds, we provide a mathematical definition of network behavior and propose a mathe- matical description of the network behavior path and behavior utility, Based on the principle of differen- tial geometry, this paper puts forward the function of network behavior and a calculation method to determine behavior utility, and establishes the calculation principle of network behavior utility, We also provide a calculation framework for assessment of the network＇s attack-defense confrontation on the strength of behavior utility, Therefore, this paper establishes a mathematical foundation for the objective measurement and precise evaluation of network behavior,
基金Supported by the College of Medicine Research Centre,Deanship of Scientific Research,King Saud University,Riyadh,Saudi Arabia
文摘BACKGROUND Artificial intelligence,such as convolutional neural networks(CNNs),has been used in the interpretation of images and the diagnosis of hepatocellular cancer(HCC)and liver masses.CNN,a machine-learning algorithm similar to deep learning,has demonstrated its capability to recognise specific features that can detect pathological lesions.AIM To assess the use of CNNs in examining HCC and liver masses images in the diagnosis of cancer and evaluating the accuracy level of CNNs and their performance.METHODS The databases PubMed,EMBASE,and the Web of Science and research books were systematically searched using related keywords.Studies analysing pathological anatomy,cellular,and radiological images on HCC or liver masses using CNNs were identified according to the study protocol to detect cancer,differentiating cancer from other lesions,or staging the lesion.The data were extracted as per a predefined extraction.The accuracy level and performance of the CNNs in detecting cancer or early stages of cancer were analysed.The primary outcomes of the study were analysing the type of cancer or liver mass and identifying the type of images that showed optimum accuracy in cancer detection.RESULTS A total of 11 studies that met the selection criteria and were consistent with the aims of the study were identified.The studies demonstrated the ability to differentiate liver masses or differentiate HCC from other lesions(n=6),HCC from cirrhosis or development of new tumours(n=3),and HCC nuclei grading or segmentation(n=2).The CNNs showed satisfactory levels of accuracy.The studies aimed at detecting lesions(n=4),classification(n=5),and segmentation(n=2).Several methods were used to assess the accuracy of CNN models used.CONCLUSION The role of CNNs in analysing images and as tools in early detection of HCC or liver masses has been demonstrated in these studies.While a few limitations have been identified in these studies,overall there was an optimal level of accuracy of the CNNs used in segmentation and classification of liver cancers images.
基金This Project was sponsored by the National Natural Science Foundation of China under No.49070196.
文摘The study of the netlike earthquake distribution indicates that in the central-eastern part of Asia continent there are two network systems: the central-eastern Asia system and the southeastern China system.As interpreted by the multilayer tectonic model,they might be a manifestation of the plastic-flow network systems in the lower lithosphere,including the lower crust and the mantle lid.Each network system is enclosed by different types of boundaries,including one driving boundary and some constraining and releasing boundaries.The two plastic-flow network systems with the Himalayan and Taiwan arcs as their driving boundaries play the role of controlling the intraplate tectonic deformation,stress field,seismicity,and subdivision of tectonic units.
文摘World Data Center-D for Seismology(WDCDS)is a member of the World Data Center System under ICSU and is one of the nine World Data Centers located in China(WDC-D).During the period from 1993 to 1996,an information network system,called CSDInet,was developed in National Center for Seismic Data and Information(NCSDI)and has become the basic technical supporting system for WDC-D for Seismology.CSDInet consists of four basic parts:computer network center,LAN(Local Area Network),link to Internet,and nationwide PSTN(with dialing-up telephone line)user network.In this paper a "multi-layer multi-mode" management of data flow for this system will be explained and the data and information services will be described.
文摘The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the formation of deductive theory is represented as the development of a certain informational space, the elements of which are structured in the form of the orientated semantic net. This net is properly metrized and characterized by a certain system of coverings. It allows injecting net optimization parameters, regulating qualitative aspects of knowledge system under consideration. To regulate the creative processes of the formation and realization of mathematical know- edge, stochastic model of formation deductive theory is suggested here in the form of branching Markovian process, which is realized in the corresponding informational space as a semantic net. According to this stochastic model we can get correct foundation of criterion of optimization creative processes that leads to “great main points” strategy (GMP-strategy) in the process of realization of the effective control in the research work in the sphere of mathematics and its applications.
基金National Key Research and Development Program,No.2017YFA0603704,No.2017YFC1502500
文摘The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It has become a key part of the urban lake management. An evaluation methodology system for IRSN project can provide important guidance for the selection of different water diversion schemes. However, few if any comprehensive evaluation systems have been developed to evaluate the hydrodynamics and water quality of connected lakes. This study developed a comprehensive evaluation system based on multi-indexes including aspects of water hydrodynamics, water quality and socioeconomics. A two-dimensional (2-D) mathematical hydrodynamics and water quality model was built, using NH<sub>3</sub>-N, TN and TP as water quality index. The IRSN project in Tangxun Lake group was used as a testbed here, and five water diversion schemes were simulated and evaluated. Results showed that the IRSN project can improve the water fluidity and the water quality obviously after a short time of water diversion, while the improvement rates decreased gradually as the water diversion went on. Among these five schemes, Scheme V showed the most noticeable improvement in hydrodynamics and water quality, and brought the most economic benefits. This comprehensive evaluation method can provide useful reference for the implementation of other similar IRSN projects.
文摘A Reconfigurable Intelligent Surface(RIS)can relay signals from the transmitter to the receiver.In this regard,RISs operate similarly to traditional relays.We design a Multiple-Input-Multiple-Output(MIMO)system with a hybrid network of RIS and Half-Duplex(HD)Amplify-and-Forward(AF)relay.We model the system’s signal propagation and propose a new algorithm to get the system’s Achievable Rate(AR)value.We complete simulations to evaluate the performance of the RIS and HD-AF relay hybrid network system compared to the system assisted by either the RIS or HD-AF relay.The simulations indicate that many factors can considerably influence the system performance.Selecting an optimal placement for the RIS and relay can result in the best performance for the RIS and HD-AF relay hybrid network system in situations where the direct link between the receiver and transmitter is absent.
文摘We developed L3SN, a scalable, longevous, adaptive, and internet accessible wireless sensor network system for agriculture information monitoring, which is meticulously designed to meet the requirement of thousands hectares coverage, years of time monitoring and the adverse environment. The system architecture, the agriculture sensor device, the mesh protocol, and the web-based information processing platform are introduced. We also presented some implementation experience. The mesh protocol (LayerMesh) is highlighted, in which “stair scheduling” and “distributed dynamic load-balancing” are proposed to response the scalability, longevity and adaptivity requirements. We believe the design of L3SN is useful to many other large-scale, longevous applications such as hydrologic monitoring, geological monitoring etc.
文摘AIM:To compare the outcomes of four adjuvants used for internal limiting membrane(ILM)peeling in macular hole surgery,including indocyanine green(ICG),brilliant blue G(BBG),triamcinolone(TA)and trypan blue(TB),through systematic review and random-effects Bayesian network Meta-analysis.METHODS:PubMed,Cochrane library databases and Web of Science were searched until August 2018 for clinical trials comparing the above four adjuvants.ORs for postoperative best corrected visual acuity(BCVA)improvement and primary macular hole closure rates were compared between the different adjuvants.RESULTS:Twenty-seven eligible articles were included.For postoperative BCVA improvement,results of BBGassisted peeling were significantly more favorable than those of ICG(WMD 0.08,95%credible interval 0.01-0.16)and TA ranked highest.No significant differences were found between any other two groups in postoperative BCVA improvement.For postoperative primary macular hole closure rates,BBG ranked highest.However,no significant differences were shown between any two groups.CONCLUSION:TA and BBG are the optimum adjuvants for achieving postoperative BCVA improvement macular hole surgery with adjuvant-assisted ILM peeling.Among all adjuvants,the use of BBG is associated with the highest postoperative macular hole closure rate.
基金supported by the National Natural Science Foundation of China(72101025,72271049),the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities,FRF-IDRY-24-024)the Hebei Natural Science Foundation(F2023501011)+1 种基金the Fundamental Research Funds for the Central Universities(FRF-TP-20-073A1)the R&D Program of Beijing Municipal Education Commission(KM202411232015).
文摘This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.
基金Project(20141996018)supported by Aerospace Science Foundation of ChinaProject(2012JZ8005)supported by the Natural Science Fundamental Research Planned Project of Shanxi Province,China
文摘A method of system structural analysis based on decision making trial and evaluation laboratory together with interpretative structural modeling(DEMATEL-ISM) and entropy is proposed to clarify system structure of communication networks and analyze mutual influencing degree between different networks.Mutual influencing degree and importance degree of elements are both considered to determine weights of elements,and the entropy of expert judgment results is used to omit unimportant influence relation and simplify system structure.Structural analysis on communication networks system shows that the proposed method can quantificationally present weights and mutual influencing degree of elements,and reasonably simplify system structure.The results indicate the rationality and feasibility of the method.
文摘This paper presents a robust sliding mode controller for a class of unknown nonlinear discrete-time systems in the presence of fixed time delay. A neural-network approximation and the Lyapunov-Krasovskii functional theory into the sliding-mode technique is used and a neural-network based sliding mode control scheme is proposed. Because of the novality of Chebyshev Neural Networks (CNNs), that it requires much less computation time as compare to multi layer neural network (MLNN), is preferred to approximate the unknown system functions. By means of linear matrix inequalities, a sufficient condition is derived to ensure the asymptotic stability such that the sliding mode dynamics is restricted to the defined sliding surface. The proposed sliding mode control technique guarantees the system state trajectory to the designed sliding surface. Finally, simulation results illustrate the main characteristics and performance of the proposed approach.
文摘In this work, a total of 322 tests were taken on young volunteers by performing 10 different falls, 6 different Activities of Daily Living (ADL) and 7 Dynamic Gait Index (DGI) tests using a custom-designed Wireless Gait Analysis Sensor (WGAS). In order to perform automatic fall detection, we used Back Propagation Artificial Neural Network (BP-ANN) and Support Vector Machine (SVM) based on the 6 features extracted from the raw data. The WGAS, which includes a tri-axial accelerometer, 2 gyroscopes, and a MSP430 microcontroller, is worn by the subjects at either T4 (at back) or as a belt-clip in front of the waist during the various tests. The raw data is wirelessly transmitted from the WGAS to a near-by PC for real-time fall classification. The BP ANN is optimized by varying the training, testing and validation data sets and training the network with different learning schemes. SVM is optimized by using three different kernels and selecting the kernel for best classification rate. The overall accuracy of BP ANN is obtained as 98.20% with LM and RPROP training from the T4 data, while from the data taken at the belt, we achieved 98.70% with LM and SCG learning. The overall accuracy using SVM was 98.80% and 98.71% with RBF kernel from the T4 and belt position data, respectively.
文摘Protein Secondary Structure Prediction (PSSP) is considered as one of the major challenging tasks in bioinformatics, so many solutions have been proposed to solve that problem via trying to achieve more accurate prediction results. The goal of this paper is to develop and implement an intelligent based system to predict secondary structure of a protein from its primary amino acid sequence by using five models of Neural Network (NN). These models are Feed Forward Neural Network (FNN), Learning Vector Quantization (LVQ), Probabilistic Neural Network (PNN), Convolutional Neural Network (CNN), and CNN Fine Tuning for PSSP. To evaluate our approaches two datasets have been used. The first one contains 114 protein samples, and the second one contains 1845 protein samples.
