“程序法”在解高考压轴题中的应用

高考物理压轴题是以能力考查为主的综合试题,它涉及到的物理概念、规律等知识点较多,所设置的物理过程或状态往往比较复杂.如果考生用其它方法不能在短时间内找到分析问题的突破口,不妨试一试用"程序法"进行解答.

Methods of Validating Simulation Model and Program Design

Validating simulation model is one of the important aspects for modeling and simulation. Some methods of validating model are compared and analyzed. Several typical methods, such as TIC’s inequality coefficient, gray interconnected analysis, direct spectrum estimation, maximum entropy spectral estimation based on Burg or Marple, are chosen and programmed in C language. Some examples by using the program are given. The results show that the program is available and it is best to adopt multi methods for validating models.

Flow Cytometric Evidence for Hydroxyl Radical-induced Apoptosis in Tobacco Protoplasts

Protoplasts prepared from tobacco (Nicotiana tabacum L., cultivar BY-2) suspension cells have similar morphological characteristics to those in animal cells. The hallmarks of apoptosis such as condensation and peripheral distribution of nuclei, TUNEL positive reaction, and DNA ladders were observed when tobacco protoplasts were treated with the hydroxyl radical generating system (1.0 mmol/L FeSO4/0.5 mmol/L H2O2). In animals, the loss of transmembrane potential (DeltaPsi(m)) and the exposure of phospholipid phosphatidylserine (PS) are believed to be the main apoptosis events. To test whether these significant processes take place in plants, flow cytometry was used to detect annexin V binding and changes in DeltaPsi(m). Results showed that the PS turned out from inner membrane and DeltaPsi(m) gradually decreased during the apoptosis. All these apoptotic characteristics proved that hydroxyl radicals can cause typical programmed cell death (PCD) in tobacco protoplasts and this design can be served as an effective experiment system to explore the mechanism of plant apoptosis.

Shrek:a dynamic object-oriented programming language

From a perspective of theoretical study, there are some faults in the models of the existing object-oriented programming languages. For example, C# does not support metaclasses, the primitive types of Java and C# are not objects, etc. So, this paper designs a programming language, Shrek, which integrates many language features and constructions in a compact and consistent model. The Shrek language is a class-based purely object-oriented language. It has a dynamical strong type system, and adopts a single-inheritance mechanism with Mixin as its complement. It has a consistent class instantiation and inheritance structure, and the ability of intercessive structural computational reflection, which enables it to support safe metaclass programming. It also supports multi-thread programming and automatic garbage collection, and enforces its expressive power by adopting a native method mechanism. The prototype system of the Shrek language is implemented and anticipated design goals are achieved.

Prediction of Injection-Production Ratio with BP Neural Network

Injection of water to enhance oil production is commonplace, and improvements in understanding the process are economically important. This study examines predictive models of the injection-to-production ratio. Firstly, the error between the fitting and actual injection-production ratio is calculated with such methods as the injection-production ratio and water-oil ratio method, the material balance method, the multiple regression method, the gray theory GM (1,1) model and the back-propogation (BP) neural network method by computer applications in this paper. The relative average errors calculated are respectively 1.67%, 1.08%, 19.2%, 1.38% and 0.88%. Secondly, the reasons for the errors from different prediction methods are analyzed theoretically, indicating that the prediction precision of the BP neural network method is high, and that it has a better self-adaptability, so that it can reflect the internal relationship between the injection-production ratio and the influencing factors. Therefore, the BP neural network method is suitable to the prediction of injection-production ratio.

Elastoplastic solutions for single piles under combined vertical and lateral loads

In order to improve the reliability of the design and calculation of single piles under the combined vertical and lateral loads, the solutions were presented based on the subgrade reaction method, in which the ultimate soil resistance was considered and the coefficient of subgrade reaction was assumed to be a constant. The corresponding computational program was developed using FORTRAN language. A comparison between the obtained solutions and the model test results was made to show the validity of the obtained solutions. The calculation results indicate that both the maximum lateral displacement and bending moment increase with the increase of the vertical and lateral loads and the pile length above ground, while decrease as the pile stiffness, the coefficient of subgrade reaction and the yielding displacement of soil increase. It is also shown that the pile head condition controls the pile responses and the vertical load may cause the instability problem to the pile. In general, the proposed method can be employed to calculate the pile responses independent of the magnitude of the pile deflection.

Application of Decision Tree Algorithm in Stamping Process

Various process parameters exert different effects in stamping process. In order to study the relationships among the process parameters of box stamping process, including the blank holder force, friction coefficient, depth of drawbead, offset and length of drawbead, the decision tree algorithm C4.5 was performed to generate the decision tree using the result data of the box stamping simulation. The design and improvement methods of the decision tree were presented. Potential and valuable rules were generated by traversing the decision tree, which plays an instructive role on the practical design. The rules show that the correct combination of blank holder force and setting of drawbead are the dominant contribution for controlling the cracking and wrinkling in box stamping process. In order to validate the rules, the stamping process for box was also performed. The experiment results show good agreement with the generated rules.

Parallel Image Processing Technology of Surface Detection System

To improve image processing speed and detection precision of a surface detection system on a strip surface,based on the analysis of the characteristics of image data and image processing in detection system on the strip surface,the design of parallel image processing system and the methods of algorithm implementation have been studied. By using field programmable gate array(FPGA) as hardware platform of implementation and considering the characteristic of detection system on the strip surface,a parallel image processing system implemented by using multi IP kernel is designed. According to different computing tasks and the load balancing capability of parallel processing system,the system could set different calculating numbers of nodes to meet the system's demand and save the hardware cost.

On the Plaintiff's Subject Qualification for Environmental Public Interest Litigation Instituted by People's Procuratorates

Although it is not the main duty for the People's Procuratorate to institute environmental public interest litigation proceedings, the existence of "reserve" prosecution right of plaintiff not only is beneficial to timely prevention and cure of environmental damage, but also contributes indispensable judicial supervision force to the environmental legality construction. In order to safeguard environmental public interests, many local prosecutorial organizations have practiced environmental public interests litigation. Since Chinese law has not made explicit stipulation on the function of the People's Procuratorate instituting environmental public interest litigation, the plaintiff's subject qualification for environmental public interest litigation instituted by the People's Procuratorate is still in question. In order to propel the People's Procuratorate to completely and fully exercise their power of supervision and prosecution, there shall be corresponding legislation that provides powerful guarantee for the People's Procuratorate instituting environmental public interest litigation.

Cost of treating chronic hepatitis B:Comparison of current treatment guidelines

AIM:To compare program costs of chronic hepatitis B(CHB) screening and treatment using Australian and other published CHB treatment guidelines.METHODS:Economic modeling demonstrated that in Australia a strategy of hepatocellular cancer(HCC) prevention in patients with CHB is more cost-effective than current standard care,or HCC screening.Based upon this model,we developed the B positive program to optimize CHB management of Australians born in countries of high CHB prevalence.We estimated CHB program costs using the B positive program algorithm and compared them to estimated costs of using the CHB treatment guidelines published by the AsianPacific,American and European Associations for the Study of Liver Disease(APASL,AASLD,EASL) and those suggested by an independent United States hepatology panel.We used a Markov model that factored in the costs of CHB screening and treatment,individualized by viral load and alanine aminotransferase levels,and calculated the relative costs of program components.Costs were discounted by 5% and calculated in Australian dollars(AUD).RESULTS:Using the B positive algorithm,total program costs amount to 13 979 224 AUD,or 9634 AUD per patient.The least costly strategy is based upon using the AASLD guidelines,which would cost 34% less than our B positive algorithm.Using the EASL and the United States Expert Group guidelines would increase program costs by 46%.The largest expenditure relates to the cost of drug treatment(66.9% of total program costs).The contribution of CHB surveillance(20.2%) and HCC screening and surveillance(6.6%) is small-and together they represent only approximately a quarter of the total program costs.CONCLUSION:The significant cost variations in CHB screening and treatment using different guidelines are relevant for clinicians and policy makers involved in designing population-based disease control programs.

Multiple Reader Algorithm for Sports Timing Systems and Its Application at Low Frequency Bandwidth

In sports timing systems,P2P communication is used at low frequency bandwidths(under 135 KHz) between tags and readers in the RFID field.However,in such cases,collisions tend to occur when a reader deals with multiple RFID tags simultaneously.To overcome this issue,a sports timing system including a Multi Reader Controller(MRC)loaded with an advanced multiple reader algorithm and application was created and applied at large-scale citizens' marathon events.In these cases,a large number of people pass over the installed urethane type's antenna mat continually during a short period of time.This study verified the superiority of the improved algorithm and application through the on-thespot application of the multi reader algorithm and application program,which allows us to smoothly measure runners' times through multiaccess reading for rapid collision avoidance.

Ship Hull Form Optimization by Evolutionary Algorithm in Order to Diminish the Drag

This study presents a numerical method for optimizing hull form in calm water with respect to total drag which contains a viscous drag and a wave drag. The ITTC 1957 model-ship correlation line was used to predict frictional drag and the corrected linearized thin-ship theory was employed to estimate the wave drag The evolution strategy （ES） which is a member of the evolutionary algorithms （EAs） family obtains an optimum hull form by considering some design constraints. Standard Wigley hull is considered as an initial hull in optimization procedures for two test cases and new hull forms were achieved at Froude numbers 0.24, 0.316 and 0.408. In one case the ES technique was ran for the initial hull form, where the main dimensions were fixed and the only variables were the hull offsets. In the other case in addition to hull offsets, the raain dimensions were considered as variables that are optimized simultaneously. The numerical results of optimization procedure demonstrate that the optimized hull forms yield a reduction in total drag.

Research on extended AHP method with the aid of RST

Analytic Hierarchy Process (AHP) method can be used to solve the tasks of multi-criterion decision system fields, but some complicated questions processed by AHP cannot be easily solved by means of the general method. It is because of being unsatisfied with consistency condition or judgment matrix too intricate to solve, which causes AHP invalidation. So in order to resolve this problem, AHP knowledge systems reduced with the aid of Genetic Algorithms (GA) were proposed, which directly acquired the order of AHP issue through the rule of Rough Sets Theory (RST) method, or solved the tasks reduced by RST with classical AHP method. On this condition, the compare decision system of region informatization level was solved, and the results solved were the same to those by classical AHP, which denoted that this method was more simple and reliable, besides the four rules of changing AHP system into RST Decision System.

An influence function method based subsidence prediction program for longwall mining operations in inclined coal seams

The distribution of the final surface subsidence basin induced by longwall operations in inclined coal seam could be significantly different from that in flat coal seam and demands special prediction methods. Though many empirical prediction methods have been developed, these methods are inflexible for varying geological and mining conditions. An influence function method has been developed to take the advantage of its fundamentally sound nature and flexibility. In developing this method, significant modifications have been made to the original Knothe function to produce an asymmetrical influence function. The empirical equations for final subsidence parameters derived from US subsidence data and Chinese empirical values have been incorpo- rated into the mathematical models to improve the prediction accuracy. A corresponding computer program is developed. A number of subsidence cases for longwall mining operations in coal seams with varying inclination angles have been used to demonstrate the applicability of the developed subsidence prediction model.

Symmetry Groups and Exact Solutions of New(4+1)-Dimensional Fokas Equation

In this paper, we investigate symmetries of the new （4＋1）-dimensional Fokas equation, including point symmetries and the potential symmetries. We firstly employ the algorithmic procedure of computing the point symmetries. And then we transform the Fokas equation into a potential system and gain the potential symmetries of Fokas equation. Finally, we use the obtained point symmetries wave solutions and other solutions of the Fokas equation. and some constructive methods to get some doubly periodic In particular, some solitary wave solutions are also given.

Strategies and Principles of Distributed Machine Learning on Big Data

The rise of big data has led to new demands for machine learning （ML） systems to learn complex mod- els, with millions to billions of parameters, that promise adequate capacity to digest massive datasets and offer powerful predictive analytics （such as high-dimensional latent features, intermediate repre- sentations, and decision functions） thereupon. In order to run ML algorithms at such scales, on a distrib- uted cluster with tens to thousands of machines, it is often the case that significant engineering efforts are required-and one might fairly ask whether such engineering truly falls within the domain of ML research. Taking the view that ＂big＂ ML systems can benefit greatly from ML-rooted statistical and algo- rithmic insights-and that ML researchers should therefore not shy away from such systems design-we discuss a series of principles and strategies distilled from our recent efforts on industrial-scale ML solu- tions. These principles and strategies span a continuum from application, to engineering, and to theo- retical research and development of big ML systems and architectures, with the goal of understanding how to make them efficient, generally applicable, and supported with convergence and scaling guaran- tees. They concern four key questions that traditionally receive little attention in ML research： How can an ML program be distributed over a cluster？ How can ML computation be bridged with inter-machine communication？ How can such communication be performed？ What should be communicated between machines？ By exposing underlying statistical and algorithmic characteristics unique to ML programs but not typically seen in traditional computer programs, and by dissecting successful cases to reveal how we have harnessed these principles to design and develop both high-performance distributed ML software as well as general-purpose ML frameworks, we present opportunities for ML researchers and practitioners to further shape and enlarge the area that lies between ML and systems..

Extended Overlapping Community Detection Algorithm by Label Propagation for Internet Application Identification

The increased capacity and availability of the Intemet has led to a wide variety of applications. Intemet traffic characterization and application identification is important for network management. In this paper, based on detailed flow data collected from the public networks of Intemet Service Providers, we construct a flow graph to model the interactions among users. Considering traffic from different applications, we analyze the community structure of the flow graph in terms of cormmunity size, degree distribution of the community, community overlap, and overlap modularity. The near linear time community detection algorithm in complex networks, the Label Propagation Algorithm （LPA）, is extended to the flow graph for application identification. We propose a new initialization and label propagation and update scheme. Experimental results show that the proposed algorithm has high accuracy and efficiency.

Programmed cell death ligand-1(PD-L1) expression by immunohistochemistry: could it be predictive and/or prognostic in non-small cell lung cancer?

Blockade of immune checkpoints has recently emerged as a novel therapeutic strategy in various tumors. In particular,monoclonal antibodies targeting programmed cell death 1(PD-1) or its ligand(PD-L1) have been most studied in lung cancer,and PD-1 inhibitors are now established agents in the management of non-small cell lung cancer(NSCLC). The reports on highprofile clinical trials have shown the association of PD-L1 expression by immunohistochemistry(IHC) with higher overall response rates to the PD-1/PD-L1 axis blockade suggesting that PD-L1 expression may serve as a predictive marker. Unfortunately,however, each PD-1 or PD-L1 inhibitor is coupled with a specific PD-L1 antibody, IHC protocol and scoring system for the biomarker assessment, making the head-to-head comparison of the studies difficult. Similarly, multiple clinical series that correlated PD-L1 expression with clinicopathologic and/or molecular variables and/or survival have reported conflicting results.The discrepancy could be explained by the differences in ethnicity and/or histologic types included in the studies, but it appears to be attributed in part to the differences in PD-L1 IHC methods. Thus, orchestrated efforts to standardize the PD-L1 IHC are warranted to establish the IHC as a predictive and/or prognostic biomarker in NSCLC.

Signed Directed Graph and Qualitative Trend Analysis Based Fault Diagnosis in Chemical Industry

In the past 30 years,signed directed graph(SDG) ,one of the qualitative simulation technologies,has been widely applied for chemical fault diagnosis.However,SDG based fault diagnosis,as any other qualitative method,has poor diagnostic resolution.In this paper,a new method that combines SDG with qualitative trend analysis(QTA) is presented to improve the resolution.In the method,a bidirectional inference algorithm based on assumption and verification is used to find all the possible fault causes and their corresponding consistent paths in the SDG model.Then an improved QTA algorithm is used to extract and analyze the trends of nodes on the consis-tent paths found in the previous step.New consistency rules based on qualitative trends are used to find the real causes from the candidate causes.The resolution can be improved.This method combines the completeness feature of SDG with the good diagnostic resolution feature of QTA.The implementation of SDG-QTA based fault diagno-sis is done using the integrated SDG modeling,inference and post-processing software platform.Its application is illustrated on an atmospheric distillation tower unit of a simulation platform.The result shows its good applicability and efficiency.

Modified origin-based algorithm for traffic equilibrium assignment problems

Key tactics of origin-based user equilibrium (OUE) algorithm was studied,which involved the algorithm procedure and several implementation issues.To speed up the convergence,update policies of flows,costs and bushes were proposed.The methods of step-size searching and bush construction are proved to be practical.The modified OUE algorithm procedure was also optimized to take the advantage of multi-thread process.Convergence performances were compared with those of other algorithms by different sizes of urban transportation networks.The result shows this modified OUE algorithm is more efficient and consumes less time to achieve the reasonable relative gap in practical applications.