Acupuncture with twirling reducing method for tinnitus of excessive liver-fire type: a clinical observation

Objective To observe the clinical efficacy of acupuncture with twirling reducing method for tinnitus of excessive liver-fire type.Methods One hundred and one patients with tinnitus of excessive liver-fire type were randomly divided into a twirling reducing method group(35 cases),a needle retaining group(33 cases)and

Reduced Differential Transform Method for Solving Nonlinear Biomathematics Models

In this paper,we study the approximate solutions for some of nonlinear Biomathematics models via the e-epidemic SI1I2R model characterizing the spread of viruses in a computer network and SIR childhood disease model.The reduced differential transforms method(RDTM)is one of the interesting methods for finding the approximate solutions for nonlinear problems.We apply the RDTM to discuss the analytic approximate solutions to the SI1I2R model for the spread of virus HCV-subtype and SIR childhood disease model.We discuss the numerical results at some special values of parameters in the approximate solutions.We use the computer software package such as Mathematical to find more iteration when calculating the approximate solutions.Graphical results and discussed quantitatively are presented to illustrate behavior of the obtained approximate solutions.

Reduced Differential Transform Method for Solving Linear and Nonlinear Goursat Problem

In this paper a new method for solving Goursat problem is introduced using Reduced Differential Transform Method (RDTM). The approximate analytical solution of the problem is calculated in the form of series with easily computable components. The comparison of the methodology presented in this paper with some other well known techniques demonstrates the effectiveness and power of the newly proposed methodology.

Studies on Reduced Extent Method for Inhibited Thermokinetics Of Enzyme－Catalyzed Reaction──Inhibition of the laccase－catalyzed oxidation of o－dihydroxybenzene by m－dihydroxybenzene

The thermokinetic reduced extent equations of reversible inhibitions for Michaiels-Menten enzymatic reaction were deduced, and then the criteria for distingushing inhibition type was given and the methods for calculating kinetic parameters, KM,Ki and Urn were suggested. This theory was applied to inverstigate the inhibited thermokinetics of laccase-catalyzed oxidation of o-dihydroxybenzene by m-dihydroxybenzene. The experimental results show the inhibition belongs to reversible competitive type, KM=6.224×10-3 mol L-1, Ki=2. 363 × 10-2 mol. L-1.

Application of the Generalized Reduced Gradient Method in Mechanical Optimization Design

This paper presents the generalized reduced gradient method （GRG） and its realization forms. The application example of GRG in the optimization design of a single-stage cylindrical gear reducer is introduced. The algo- rithm of the GRG method is realized in Vissim software. Based on the mathematical model of the single-stage cylin- drical gear reducer, the simulation structure of the optimization design was achieved. The experiment results show that the GRG method has fewer iterations and higher precision. The GRG method is very suitable for solving mechanical optimization design.

Application of nanotechnology in a silver/graphite contact material and optimization of its physical and mechanical properties

By applying nanotechnology, a new type of silver/graphite (AgC) electricalcontact was fabricated and characterized. The AgC coating powders were obtained through high-energyball milling and reducer liquid spraying-coating method. The as-prepared powders were examined bytransmission electron microscope (TEM), scanning electron microscope (SEM), and X-ray diffraction(XRD). The results show that the thickness of graphite flakes milled for 10 h is about 50-60 nm andthe AgC coating powders exhibit flocculent structure with quite fine and homogeneous internalmicropores. XRD implies that the average crystalline size of silver in coating powders is about 50nm. The mechanical and physical properties of this newly developed AgC contact made from theabove-mentioned nanocrystalline powders by traditional powder metallurgy technique were measured.Compared with its counterparts made from other techniques, the properties of this new AgC contacthave been optimized. High surface energy and high-energy interfaces of the nanocrystalline AgCcoating powders provide powerful driving force for sintering densification. Moreover, the flocculentstructure of the powders is also an important factor to acquire fine density ratio.

Dynamical Behaviors of Nonlinear Coronavirus (COVID-19) Model with Numerical Studies

The development of mathematical modeling of infectious diseases is a key research area in various elds including ecology and epidemiology.One aim of these models is to understand the dynamics of behavior in infectious diseases.For the new strain of coronavirus(COVID-19),there is no vaccine to protect people and to prevent its spread so far.Instead,control strategies associated with health care,such as social distancing,quarantine,travel restrictions,can be adopted to control the pandemic of COVID-19.This article sheds light on the dynamical behaviors of nonlinear COVID-19 models based on two methods:the homotopy perturbation method(HPM)and the modied reduced differential transform method(MRDTM).We invoke a novel signal ow graph that is used to describe the COVID-19 model.Through our mathematical studies,it is revealed that social distancing between potentially infected individuals who are carrying the virus and healthy individuals can decrease or interrupt the spread of the virus.The numerical simulation results are in reasonable agreement with the study predictions.The free equilibrium and stability point for the COVID-19 model are investigated.Also,the existence of a uniformly stable solution is proved.

An efficient technique for recovering responses of parameterized structural dynamic problems

In this article,an effective technique is developed to efficiently obtain the output responses of parameterized structural dynamic problems.This technique is based on the conception of reduced basis method and the usage of linear interpolation principle.The original problem is projected onto the reduced basis space by linear interpolation projection,and subsequently an associated interpolation matrix is generated.To ensure the largest nonsingularity,the interpolation matrix needs to go through a timenode choosing process,which is developed by applying the angle of vector spaces.As a part of this technique,error estimation is recommended for achieving the computational error bound.To ensure the successful performance of this technique,the offline-online computational procedures are conducted in practical engineering.Two numerical examples demonstrate the accuracy and efficiency of the presented method.

Antioxidant Activity Evaluation in a Series of Heterocyclic Compounds Derived from 1,8-Diaminonaphthalene

From (2,3-dihydro-1H-perimidin-2-yl)-phenyl, the substitution of OH group in ortho or para position on the phenyl ring, allows us to synthesize the studied compounds. These three compounds have been characterized by conventional spectroscopic methods (NMR and MS). The interest of this work is to review the antioxidant activity of our compounds. The antioxidant activity screening carried out according to FRAP and DPPH methods revealed significant anti-free radical properties for compounds 1 and 2 even at low concentrations. In contrast to the compound 2, compound 3 for which the OH group is substituted in para position has the lowest activity in both cases. Therefore the para position seems to be the least sensitive position to increase the antioxidant activity of this pharmacophore.

DFT-spread combined with clipping method to reduce the PAPR in VLC-OFDM system

Orthogonal frequency division multiplexing(OFDM) is an attractive technique to realize high data rate in light emitting diodes(LEDs)-based visible light communication(VLC). However, high peak-to-average power ratio(PAPR) of OFDM makes VLC-OFDM very sensitive to the nonlinearity of LEDs. In this paper, the discrete Fourier transform-spread(DFT-spread) combined with clipping method is proposed to reduce the PAPR of OFDM signal in VLC system. Combining simulation with experiment, a performance comparison is made among conventional OFDM, DFT-spread-OFDM, and clipped DFT-spread-OFDM with different clipping ratios(CRs) in a single LED-based VLC system. The experimental results show that the proposed clipped DFT-spread-OFDM method can effectively improve the system performance compared with the other two methods. At the optimum signal peak-to-peak(PTP) value, by using the clipped DFT-spread-OFDM scheme with CR at 8 dB, the bit error rate(BER) of the system can be reduced from 0.003 7 to 0.000 287.

Multibody system transfer matrix method:The past, the present, and the future

The multibody system transfer matrix method(MSTMM),a novel dynamics approach developed during the past three decades,has several advantages compared to conventional dynamics methods.Some of these advantages include avoiding global dynamics equations with a system inertia matrix,utilizing low‐order matrices independent of system degree of freedom,high computational speed,and simplicity of computer implementation.MSTMM has been widely used in computer modeling,simulations,and performance evaluation of approximately 150 different complex mechanical systems.In this paper,the following aspects regarding MSTMM are reviewed:basic theory,algorithms,simulation and design software,and applications.Future research directions and generalization to more applications in various fields of science,technology,and engineering are discussed.

REDUCED BASIS METHOD FOR PARAMETRIZED ELLIPTIC ADVECTION-REACTION PROBLEMS

In this work we consider the Reduced Basis method for the solution of parametrized advection-reaction partial differential equations. For the generation of the basis we adopt a stabilized finite element method and we define the Reduced Basis method in the ＂primal- dual＂ formulation for this stabilized problem. We provide a priori Reduced Basis error estimates and we discuss the effects of the finite element approximation on the Reduced Basis error. We propose an adaptive algorithm, based on the a posteriori Reduced Basis error estimate, for the selection of the sample sets upon which the basis are built; the idea leading this algorithm is the minimization of the computational costs associated with the solution of the Reduced Basis problem. Numerical tests demonstrate the efficiency, in terms of computational costs, of the ＂primal-dual＂ Reduced Basis approach with respect to an ＂only primal＂ one. Parametrized advection-reaction partial differential equations, Reduced Basis method, ＂primal-dual＂ reduced basis approach, Stabilized finite element method, a posteriori error estimation.

Solution of the time-fractional generalized Burger-Fisher equation using the fractional re duce d differential transform method

“The time-fractional generalized Burger-Fisher equation(TF-GBFE)”is used in various applied sciences and physical applications,including simulation of gas dynamics,financial mathematics,fluid mechan-ics,and ocean engineering.This equation represents a concept for the coordination of reaction systems,as well as advection,and conveys the understanding of dissipation.The Fractional Reduced Differential Transform Method(FRDTM)is used to evaluate“the time-fractional generalized Burger-Fisher equation(TF-GBFE).”Todeterminethemethod’s validity,whenthesolutionsareobtained,theyarecorrelatedto exact solutions ofα=1 order,and even for various values ofα.Three-dimensional graphs are used to depict the solutions.Additionally,the analysis of exact and FRDTM solutions indicates that the proposed approach is very accurate.

换元法求解二阶常系数齐次线性微分方程

利用换元法,将二阶微分方程降为一阶微分方程,利用一阶微分方程的求解方法,得到二阶常系数齐次常系数线性微分方程的通解.

Reduced Basis Approaches in Time-Dependent Non-Coercive Settings for Modelling the Movement of Nuclear Reactor Control Rods

In this work,two approaches,based on the certified Reduced Basis method,have been developed for simulating the movement of nuclear reactor control rods,in time-dependent non-coercive settings featuring a 3D geometrical framework.In particular,in a first approach,a piece-wise affine transformation based on subdomains division has been implemented for modelling the movement of one control rod.In the second approach,a“staircase”strategy has been adopted for simulating themovement of all the three rods featured by the nuclear reactor chosen as case study.The neutron kinetics has been modelled according to the so-called multi-group neutron diffusion,which,in the present case,is a set of ten coupled parametrized parabolic equations(two energy groups for the neutron flux,and eight for the precursors).Both the reduced order models,developed according to the two approaches,provided a very good accuracy comparedwith high-fidelity results,assumed as“truth”solutions.At the same time,the computational speed-up in the Online phase,with respect to the fine“truth”finite element discretization,achievable by both the proposed approaches is at least of three orders of magnitude,allowing a real-time simulation of the rod movement and control.

Non-Intrusive Reduced OrderModeling of Convection Dominated Flows Using Artificial NeuralNetworkswithApplication to Rayleigh-Taylor Instability

.A non-intrusive reduced order model(ROM)that combines a proper orthogonal decomposition(POD)and an artificial neural network(ANN)is primarily studied to investigate the applicability of the proposed ROM in recovering the solutions with shocks and strong gradients accurately and resolving fine-scale structures efficiently for hyperbolic conservation laws.Its accuracy is demonstrated by solving a high-dimensional parametrized ODE and the one-dimensional viscous Burgers’equation with a parameterized diffusion coefficient.The two-dimensional singlemode Rayleigh-Taylor instability(RTI),where the amplitude of the small perturbation and time are considered as free parameters,is also simulated.An adaptive sampling method in time during the linear regime of the RTI is designed to reduce the number of snapshots required for POD and the training of ANN.The extensive numerical results show that the ROM can achieve an acceptable accuracy with improved efficiency in comparison with the standard full order method.

A Static Condensation Reduced Basis Element Approach for the Reynolds Lubrication Equation

In this paper,we propose a Static Condensation Reduced Basis Element(SCRBE)approach for the Reynolds Lubrication Equation(RLE).The SCRBEmethod is a computational tool that allows to efficiently analyze parametrized structures which can be decomposed into a large number of similar components.Here,we extend the methodology to allow for a more general domain decomposition,a typical example being a checkerboard-pattern assembled from similar components.To this end,we extend the formulation and associated a posteriori error bound procedure.Our motivation comes from the analysis of the pressure distribution in plain journal bearings governed by the RLE.However,the SCRBE approach presented is not limited to bearings and the RLE,but directly extends to other component-based systems.We show numerical results for plain bearings to demonstrate the validity of the proposed approach.

Tsunami wave propagation model:A fractional approach

This paper presents a fractional approach to study the mathematical model of tsunami wave propagation along a coastline of an ocean.Fractional Reduced Differential Transform Method(FRDTM)is used to analyze this model.The present model has been studied on the shallow-water assumption.It is represented by a time-fractional coupled system of non-linear partial differential equations.Solutions to the proposed model for different coastal slopes and ocean depths have been obtained.Effects of coast slope and sea depth variations on tsunami wave velocity and wave amplification have been demonstrated at different time levels and different ordersα.The obtained results are compared with Elzaki Adomian Decomposition Method(EADM)to validate the proposed method for an orderα=1.

Active Anomaly Detection Technology Based on Ensemble Learning

Anomaly detection is an important problem in various research and application fields.Researchers design reliable schemes to provide solutions for effectively detecting anomaly points.Most of the existing anomaly detection schemes are unsupervised methods,such as anomaly detection methods based on density,distance and clustering.In total,unsupervised anomaly detection methods have many limitations.For example,they cannot be well combined with prior knowledge in some anomaly detection tasks.For some nonlinear anomaly detection tasks,the modeling is complex and faces dimensional disasters,which are greatly affected by noise.Sometimes it is difficult to find abnormal events that users are interested in,and users need to customize model parameters before detection.With the wide application of deep learning technology,it has a good modeling ability to solve linear and nonlinear data relationships,but the application of deep learning technology in the field of anomaly detection has many challenges.If we regard exceptions as a supervised problem,exceptions are a few,and we usually face the problem of too few labels.To obtain a model that performs well in the anomaly detection task,it requires a high initial training set.Therefore,to solve the above problems,this paper proposes a supervised learning method with manual participation.We introduce the integrated learning model and train a supervised anomaly detection model with strong stability and high accuracy through active learning technology.In addition,this paper adopts certain strategies to maximize the accuracy of anomaly detection and minimize the cost of manual labeling.In the experimental link,we will show that our method is better than some traditional anomaly detection algorithms.