Application of EEG multipole model in the diagnosis of Alzheimer’s disease

In order to find the electroencephalogram (EEG) characteristic parameters typical of Alzheimer’s disease (AD) and explore an effective diagnostic method, a new mobile current multipole model was proposed to simulate the AD patient’s cortical dipole source activities. The indicators of goodness of fit (GOF) and DtononD (DD) were calculated from EEG samples to evaluate the performance of this model. Relevant results showed that this multipole model with higher GOF values and larger DD change well fitted the pathological electrical activities of cortical neurons aroused by AD’s extended sulcus and gyrus in the cerebral cortex. Meanwhile, the products of DD mean & standard variance were found in a clear linear correlation with the diagnostic data of mini-mental state examination (MMSE) used in AD clinics. Furthermore, by tracing this multipole model’s indicators in typical patients and contrasting with the functional magnetic resonance image (fMRI) as AD progressed, we suggested that the DD index may be suitable for monitoring the AD developments as a new diagnostic parameter.     

Application of EEG multipole model in the diagnosis of Alzheimer''''s disease

In order to find the electroencephalogram （EEG） characteristic parameters typical of Alzheimer＇s disease （AD） and explore an effective diagnostic method, a new mobile current multipole model was proposed to simulate the AD patient＇s cortical dipole source activities. The indicators of goodness of fit （GOF） and DtononD （DD） were calculated from EEG samples to evaluate the performance of this model. Relevant results showed that this multipole model with higher GOFvalues and larger DD change well fitted the pathological electrical activities of cortical neurons aroused by AD＇s extended sulcus and gyrus in the cerebral cortex. Meanwhile, the products of DD mean ＆ standard variance were found in a clear linear correlation with the diagnostic data of mini-mental state examination （MMSE） used in AD clinics. Furthermore, by tracing this multipole model＇s indicators in typical patients and contrasting with the functional magnetic resonance image （fMRI） as AD progressed, we suggested that the DD index may be suitable for monitoring the AD developments as a new diagnostic parameter.     

Multipole BEM for 3-D Elasto-Plastic Contact with Friction

The analysis of 3-D elasto-plastic contact with friction is a highly nonlinear problem. The elements in the contact and plastic zones should be refined to obtain accurate information about the real size,displacement, and traction in the contact zone. However, the increase in the number of degrees of freedom is limited when traditional boundary element method (BEM) is used with the larger memory size and long CPU time required for the solution procedure. This paper describes the additional mathematical friction model to the 3-D elastic multipole BEM to develop a 3-D elasto-plastic contact multipole BEM. Numerical tests show that with this new method, the needed computer memory size is only 2% of the traditional BEM model with friction, which erases large-scale computing with refined meshes and improves the computational accuracy.     

Fast Multipole BEM for Simulation of 2-D Solids Containing Large Numbers of Cracks

The fast multipole method was used to solve the traction boundary integral equation for 2-D crack analysis, The use of both multipole and local expansions reduces both the computational complexity and the memory requirement to O(N). The multipole expansion uses a complex Taylor series expansion to reduce the number of multipole moments, The generalized minimum residual method solver (GMRES) was selected as the iterative solver, An improved preconditioner for GMRES was developed which uses less CPU time and less memory. A new initial candidate vector for the iterative solver was developed to further improve the efficiency, The numerical examples apply the method to the analysis of cracks in infinite 2-D space with the largest model having 900 000 degrees of freedom.     

A new quantitative relation between deformation texturesand corresponding mechanical properties of FCC metals

Quantitative analysis of deformation-induced textures and texture-induced mechanical properties is an important issue for optimal design and control of plastic forming of metals.Deformation-induced textures were predicted through the crystal plasticity finite-element method(CPFEM)in this study,and varying deformation modes,including uniaxial compression,uniaxial tension,simple shear,and plane-strain compression,were considered.The predicted textures were proven by experiments.Then,a theoretical model was proposed to build the quantitative relation between textures and the corresponding mechanical properties.This model takes into account the effects of grain’s orientation,grain’s interaction,and the property in the level of single grain.It captures the macroscopic anisotropy owing to textures and microscopic anisotropy owing to crystallographic structures.By applying this model,the macroscopic stress responses of grains’aggregate with varying textures were calculated according to grain’s orientations and the intrinsic properties of the single crystal along[100]and[111]crystallographic directions.The theoretical model is proven to have high efficiency and acceptable accuracy in the prediction of texture-induced mechanical properties comparing with CPFEM model.     

Recent 2000-year geological records of mud in the inner shelf of the East China Sea and their climatic implications

AMS^14C dating and grain-size analysis for Core DD2, located at the north of the Yangtze River-derived mud off the Zhejiang-Fujian coasts in the inner shelf of the East China Sea, provide us a high-resolution grain-size distribution curve varying with depth and time. Data in the upper mud layer of Core DD2 indicate that there are at least 9 abrupt grain-size increasing in recent 2000 years, with each corresponding very well with the low-temperature events in Chinese history, which might result from the periodical strengthening of the East Asian Winter Monsoon (EAWM), including the first-revealed maximum temperature lowering event at around 990 a BP. At the same time, the finer grain size section in Core DD2 agrees well with the Sui-Tang Warming Period (600--1000 a AD) defined previously by Zhu Kezhen, during which the climate had a warm, cold and warm fluctuation, with a dominated cooling period of 750-850 a AD. The Little Ice Age (LIA) can also be identified in the core. It starts around 1450 a AD and was followed by a subsequent cooling events at 1510, 1670 and 1840 a AD. Timing of these cold events revealed here still needs to be further verified owing to some current uncertainty of dating we used in this study.     

Information flow among neural networks with Bayesian estimation

Estimating the interaction among neural networks is an interesting issue in neuroscience. Some methods have been proposed to estimate the coupling strength among neural networks; however, few estimations of the coupling direction (information flow) among neural networks have been attempted. It is known that Bayesian estimator is based on a priori knowledge and a probability of event occurrence. In this paper, a new method is proposed to estimate coupling directions among neural networks with conditional mutual information that is estimated by Bayesian estimation. First, this method is applied to analyze the simulated EEG series generated by a nonlinear lumped-parameter model. In comparison with the conditional mutual information with Shannon entropy, it is found that this method is more successful in estimating the coupling direction, and is insensitive to the length of EEG series. Therefore, this method is suitable to analyze a short time series in practice. Second, we demonstrate how this method can be applied to the analysis of human intracranial epileptic electroencephalogram (EEG) recordings, and to indicate the coupling directions among neural networks. Therefore, this method helps to elucidate the epileptic focus localization.     

Research of Dynamic Competitive Learning in Neural Networks

Introduce a method of generation of new units within a cluster and a algorithm of generating new clusters. The model automatically builds up its dynamically growing in ternal representation structure during the learning process. Comparing model with other typical classification algorithm such as the Kohonen‘s self-organizing map. the model realizes a multilevel classification of the input pattern with an optional accuracy and gives a strong support possibility for the parallel computational main processor. The idea is suitable for the high-level storage of complex datas structures for object recognition.     

Ratio K: a New Way of Metering and Evaluating the Risk and Return of Stock Investment

Although widely used, both the Markowitz model and VAR (Value at Risk) model have some limitations in evaluating the risk and return of stock investment. By the analysis of the conceptions of risk and return, together with the three hypotheses of technological analysis, a novelty model of metering and evaluating the risk and return of stock investment is established. The major indicator of this model , risk-return ratio K, combines the characteristic indicators of risk and return. Regardless of the form of the risk-return probability density functions, this indicator K can always reflect the risk-return performances of the invested stocks clearly and accurately. How to use the model to make optimum investment and how to make portfolio combined with clustering analysis is also explained.     

Simulating a typhoon storm surge in the East Sea of China using a coupled model

A coupled numerical model with a 2’?2’ resolution grid has been developed and used to simulate five typical typhoon storm surges (5612, 7413, 7910, 8114, 9711) in the East Sea of China. Three main driving forces have been considered in this coupled model: wave radiation stress, combined wave-current bottom shear stress and wave-state dependent surface wind stress. This model has then been compared with in situ measurements of the storm set-up. The effect of different driving force components on the total storm surge has also been investigated. This study has found that the coupled model with high resolution is capable of simulating the five typical typhoons better than the uncoupled models, and that the wave-dependent surface wind stress plays an important role in typhoon storm surge-wave coupling in this area and can increase the storm set-up by 1m. The study of the five typhoon cases has shown that the general coupling effects could increase storm set-up by 20% to 32%. Thus, it is suggested that to predict typhoon storm surges in the East Sea of China, a storm surge-wave coupled model be adopted.     

A Benefit Measurement Framework for an Online Contract Change Management System

The contract change management (CCM) system is an online collaboration tool, which supports the contract change management process of new engineering contract (NEC) contract. It is currently used in practice on a wide range of civil, power, and building projects in the UK. The aim of this study is first to identify the tangible and intangible benefits of the system through a user survey; then to develop a framework to measure these benefits. A questionnaire survey is conducted, which reveals that CCM can help project teams improve process effectiveness, reduce risk of process failures, and increase the compliance with NEC requirements. Subsequently, a spreadsheet tool is developed to allow CCM users to calculate the tangible cost savings as a result of using the system. For intangible benefits, a change management maturity model (CM3) is developed, which provides a measurement framework for assessing the improvement of a project team’s capability in dealing with contract changes.     

Long-term trends in foF2 over Moscow ionosonde station: Its estimate and origins

We introduce a new approach,using the International Reference Ionosphere 2007(IRI-2007)model and observations from the Moscow ionosonde station,to analyze the long-term trends of ionospheric foF2.Possible origins,whether natural or manmade, are discussed.A small but significant residual foF2 trend is found,with-0.76 MHz over the past 50 years,but-0.2 MHz after eliminating the most variations caused by solar and geomagnetic activities and the variational earth’s magnetic field.We find that this slope depends on local time and seasons.There is a pronounced diurnal negative variation in k(annual mean slope of diurnal variations),with much larger absolute values in the morning than during afternoon or evening;the largest k is about-0.0018 per year in spring,and the smallest trend of about-0.0012 per year occurs in winter.Finally,the evidence of crucial influences of geomagnetic activity and the earth’s magnetic field on the observed trends,as emphasized by the IRI-2007 empirical model,is confirmed,and the effect of CO2 contributions to the trend is also discussed,by cooling the thermospheric temperature or recombining the electron density.     

Precise positioning of the Chang’E-3 lunar lander using a kinematic statistical method

A kinematic statistical method is proposed to determine the position for Chang’E-3(CE-3) lunar lander.This method uses both ranging and VLBI measurements to the lander for a continuous arc,combing with precise knowledge about the motion of the moon as provided by planetary ephemeris,to estimate the lander’s position on the lunar surface with high accuracy.Accuracy analyses are carried out with simulation data using the software developed at Shanghai Astronomical Observatory in this study to show that measurement errors will dominate the position accuracy.Application of lunar digital elevation model(DEM) as constraints in the lander positioning is also analyzed.Simulations show that combing range/doppler and VLBI data,single epoch positioning accuracy is at several hundred meters level,but with ten minutes data accumulation positioning accuracy is able to be achieved with several meters.Analysis also shows that the information given by DEM can provide constraints in positioning,when DEM data reduce a 3-dimensional positioning problem to 2-dimensional.Considering the Sinus Iridum,CE-3 lander’s planned landing area,has been observed with dedicated details during the CE-1 and CE-2 missions,and its regional DEM model accuracy may be higher than global models,which will certainly support CE-3’s lander positioning.     

A Designated Query Protocol for Serverless Mobile RFID Systems with Reader and Tag Privacy

Recently, a new type of Radio Frequency IDentification (RFID) system with mobile readers is introduced. In such a system, it is more desirable for mobile readers to identify tags without a back-end server, and thus it is frequently referred as a serverless mobile RFID system. In this paper, we formalize a serverless mobile RFID system model and propose a new encryption-based system that preserves the privacy of both tags and readers in the model. In addition, we define a new adversary model for the system model and show the security of the proposed system. Throughout comparisons between ours and the other alternatives, we show that our proposed system provides a stronger reader privacy and robustness against a reader forgery attack than the competitors.     

Re-mention of an old neurodegenerative disease: Alzheimer’s disease

Alzheimer’s disease(AD),the most common form of neuropsychiatric disorder,is characterized by neuronal degeneration and inexorably progressing dementia,especially in the elderly population.With a rapidly aging population in both developed and developing countries,AD has emerged as one of the largest growing problems worldwide.Current drugs improve the symptoms of AD,but do not have any profound intervention to delay its onset.Thus,understanding the molecular mechanisms underlying the genes tied to AD will be crucial to the development of therapeutic targets.This review will summarize the aetiology,pathology,and the evidence for the genetic components in AD,discuss the proposed amyloid cascade and the following tau hyperphosphorylation hypothesises,oxidative stress mediated neuronal cell death,as well as the function of Retromer complex during the developing of AD.Our laboratory’s current research progress and the challenges that still remained will be also highlighted.     

Single Production of gauge boson Z' at TeV Energy e~-γ colliders

In the context of the SU(3) simple group model and the Left-Right twin Higgs(LRTH) model,we study the single production of the new gauge boson Z' via e-γ collision and discuss the possibility to detect this new particle in the TeV energy e e-collider(LC).The results show that the production cross section of the new heavy gauge boson Z' is in the range of 10.08fb～84.5fb,and the cross section in the LRTH model is bigger than that in the SU(3) simple group model.The sufficient typical events could be assumed in future high energy LC experiments.     

Ontology-Based Semantic Multi-agent Framework for Micro-grids with Cyber Physical Concept

The distributed hierarchical control based on multi-agent system(MAS) is the main control method of micro-grids.By allowing more flexible interactions between computing components and their physical environments,cyber physical system(CPS) presents a new approach for the distributed hierarchical engineering system,with micro-grids included.The object of this paper is to integrate the CPS concept with MAS technology and propose a new control framework for micro-grids.With the analysis of the operating mode and control method of micro-grids,the cyber physical control concepts of ontologybased semantic agent are discussed.Then an MAS-based architecture of cyber physical micro-grid system and an intelligent electronic device(IED) function structure are proposed.Finally,in order to operate and test the cyber physical micro-grid concept,an integrated simulation model is presented.     

Development of an invasive brain machine interface with a monkey model

Brain-machine interfaces (BMIs) translate neural activities of the brain into specific instructions that can be carried out by external devices. BMIs have the potential to restore or augment motor functions of paralyzed patients suffering from spinal cord damage. The neural activities have been used to predict the 2D or 3D movement trajectory of monkey’s arm or hand in many studies. However, there are few studies on decoding the wrist movement from neural activities in center-out paradigm. The present study developed an invasive BMI system with a monkey model using a 10×10-microelectrode array in the primary motor cortex. The monkey was trained to perform a two-dimensional forelimb wrist movement paradigm where neural activities and movement signals were simultaneous recorded. Results showed that neuronal firing rates highly correlated with forelimb wrist movement; > 70% (105/149) neurons exhibited specific firing changes during movement and > 36% (54/149) neurons were used to discriminate directional pairs. The neuronal firing rates were also used to predict the wrist moving directions and continuous trajectories of the forelimb wrist. The four directions could be classified with 96% accuracy using a support vector machine, and the correlation coefficients of trajectory prediction using a general regression neural network were above 0.8 for both horizontal and vertical directions. Results showed that this BMI system could predict monkey wrist movements in high accuracy through the use of neuronal firing information.     

Simulation of phase transition process using lattice Boltzmann method

A new lattice Boltzmann model based on SC model, is proposed to describe the liquid-vapor phase transitions. The new model is validated through the simulation of the one-component phase transition process. Compared with the simulation results of van der Waals gas and the Maxwell equal-area construction, the results of the new model have a better agreement with the analytical solutions than those of SC and Zhang models. Since the obtained temperature range and the maximum density ratio in this model are expanded, and the magnitude of maximum spurious current is only between those of SC and Zhang models, it is believed that this new model has better stability than SC and Zhang models. Consequently, the application scope of this new model is expanded compared with the existing phase transition models. According to the principle of the corresponding states in engineering thermodynamics, the simulations of ammonia and water phase transition process were implemented using this new model with different equations of state. Compared with the experimental data of ammonia and water, the results show that the Peng-Robinson is the best equation of state to describe the phase transition process of ammonia and water. Especially, the simulation results of ammonia with Peng-Robinson equation of state have an excellent agreement with its experimental data. Therefore these simulation results have a significant influence on the real engineering applications.     

Research on Stress Testing of OSPF Protocol Implementation

The stability and robustness of routing protocol implementations (RPI) in a router are becoming more and more important with the growth of Internet scale. A novel approach named stress testing is proposed to test the properties of RPI. Compared with some traditional test techniques, stress testing is remarkably necessary to inspect and analyze RPI. The test environment is proposed and the test process of OSPF RPI is illustrated by a stochastic Petri Net model with large-scale route simulation and OSPF protocol emulation. Based on this model, the integrated performance tester (IP-TEST) is designed and developed, with which we test a CISCO2600 router. With mathematical methods, we find that the computational complexity of OSPF implementation in this router is O (lnN)^4)to the number of its routing table entries. This experiment shows that this technique can inspect the stability, the computational complexity and the sealability of RPI. Furthermore, it can also be widely used with other routing protocols, such as RIP and BGP.