Multiple sclerosis：integration of modeling with biology,clinical and imaging measures to provide better monitoring of disease progression and prediction of outcome

Multiple Sclerosis（MS） is a major cause of neurological disability in adults and has an annual cost of approximately $28 billion in the United States. MS is a very complex disorder as demyelination can happen in a variety of locations throughout the brain; therefore, this disease is never the same in two patients making it very hard to predict disease progression. A modeling approach which combines clinical, biological and imaging measures to help treat and fight this disorder is needed. In this paper, I will outline MS as a very heterogeneous disorder, review some potential solutions from the literature, demonstrate the need for a biomarker and will discuss how computational modeling combined with biological, clinical and imaging data can help link disparate observations and decipher complex mechanisms whose solutions are not amenable to simple reductionism.

Combined Adaptive Multiple Subtraction Based on Optimized Event Tracing and Extended Wiener Filtering

The surface-related multiple elimination(SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.

Rheological Behaviour for Polymer Melts and Concentrated Solutions Part Ⅲ: A New Multiple Entanglement Model to Predict the Dependence of Linear Viscoelastic Function (η_0, Ψ_(10)~0,η_(ext)~0) on the Ranges of Primary Molecular Weights and th

It is shown theoretically that the viscoelasticity of polymer melts is determined by three combining factorst they are the primary molecular weight and its distribution, the number of entanglement sites on polymer chain and the sequence distribution of constituent chains in entanglement spacings. A unified quantity for the three combing factors is the average constrained dimensional number of constituent chains in the long entanglement spacings (v). A new relation of v to the primary molecular weight and the number of testing polymers were derived from the multiple entanglement and reptation model, and a new method for determining v was proposed. The dependences of linear viscoelastic functions on the primary molecular weight and its distribution were derived by the statistical method. When Mn=6Me to 18 Me, the values of (v) can range from 3.33 to 3.70. Their values are in a good agreement with the experiment data, and it can slightjy vary with the different species of polymers and the different ranges of molecular weight of polymers

Rheological Behaviour for Polymer Melts and Concentrated Solutions Part Ⅰ:A New Multiple Reptation Model to Predict the Nonlinear Visco-elasticity with Nagai Chain Constraints in Entangled Polymer Melts

An approach of stochastically statistical mechanics and a unified molecular theory of nonlinear viscoelasticity with constraints of Nagai chain entanglement for polymer melts have been proposed. A multimode model structure for a single polymer chain with n tail segments and N reversible entanglement sites on the test polymer chain is developed. Based on the above model structure and the mechanism of molecular flow by the dynamical reorganization of entanglement sites, the probability distribution function of the end-to-end vectr for a single polymer chain at entangled state and the viscoelastic free energy of deformation for polymer melts are calculated by using the method of the stochastically statistical mechanics. The four types of stress-strain relation and the memory function are derived from this thery. The above theoretical relations are verified by the experimentaf data for various polymer melts. These relations are found to be in good agreement with the experimental results

Multiple mobile-obstacle avoidance algorithm for redundant manipulator

In order to overcome the shortcomings of the previous obstacle avoidance algorithms,an obstacle avoidance algorithm applicable to multiple mobile obstacles was proposed.The minimum prediction distance between obstacles and a manipulator was obtained according to the states of obstacles and transformed to escape velocity of the corresponding link of the manipulator.The escape velocity was introduced to the gradient projection method to obtain the joint velocity of the manipulator so as to complete the obstacle avoidance trajectory planning.A7-DOF manipulator was used in the simulation,and the results verified the effectiveness of the algorithm.

Investigating fatigue behavior of gear components with the acoustic emission technique

A novel method is presented to evaluate the complicated fatigue behavior of gears made of20Cr2Ni4 A.Fatigue tests are conducted in a high-frequency push-pull fatigue tester,and acoustic emission（AE）technique is used to acquire metal fatigue signals.After analyzing large number of AE frequency spectrum,we find that：the crack extension can be expressed as the energy of specific frequency band,which is abbreviated as F-energy.To further validate the fatigue behavior,some correlation analysis is applied between F-energy and some AE parameters.Experimental results show that there is significant correlation among the Fenergy,root mean square（RMS）,relative energy,and hits.The findings can be used to validate the effectiveness of the F-energy in predicting fatigue crack propagation and remaining life for parts in-service.F-energy,as a new AE parameter,is first put forward in the area of fatigue crack growth.