马克思“支配自然”的思想与生态环境问题关系之辨

大多数环境主义者以“支配自然”为口实,指责马克思过分强调人对自然有意识的改造,忽视了自然的极限和自然资源的稀缺性,从而把马克思视为生态环境保护的对立面。这是对马克思“支配自然”的思想不加分析的结果。由于“支配自然”的目的和方式的异质性,马克思关于“支配自然”的看法也有着鲜明的不同。对于以“支配自然”为前提资本主义生产,马克思坚决批判其逐利逻辑以及由此导致的生态环境问题;对于未来社会仍然存在的“支配自然”的事实,马克思在予以积极肯定的同时,还从其支配方式和支配目的中思考人与自然矛盾的解决。质言之,在马克思那里,的确存在“支配自然”的思想,但这种思想却不必然导致生态环境问题。

韦伯论政治合法性与合法律性及其现实意义

政治的合法性一直以来都是人类社会的首要问题之一,越是在变动社会中,越是如此。尽管作为西方文明成果的形式理性化法律自现当代以来不断受到质疑,但从目前所能够获得的历史经验来看,只有该种类型的法律方能为政治的合法性提供一个稳固的意识形态基础。韦伯对此进行了系统化的理论总结,重新考察该理论对于中国政治合法性建构将具有一定的理论意义。

(α,β)-constraints connected dominating set algorithm in wireless sensor network

To cope with the constraint problem of power consumption and transmission delay in the virtual backbone of wireless sensor network, a distributed connected dominating set （CDS） algorithm with （α,β）-constraints is proposed. Based on the （α, β）-tree concept, a new connected dominating tree with bounded transmission delay problem（CDTT） is defined and a corresponding algorithm is designed to construct a CDT-tree which can trade off limited total power and bounded transmission delay from source to destination nodes. The CDT algorithm consists of two phases： The first phase constructs a maximum independent set（MIS）in a unit disk graph model. The second phase estimates the distance and calculates the transmission power to construct a spanning tree in an undirected graph with different weights for MST and SPF, respectively. The theoretical analysis and simulation results show that the CDT algorithm gives a correct solution to the CDTF problem and forms a virtual backbone with（ α,β）-constraints balancing the requirements of power consumption and transmission delay.

Surgical anatomy of innervation of the gallbladder in humans and Suncus murinus with special reference to morphological understanding of gallstone formation after gastrectomy

AIM： To clarify the innervation of human gallbladder,with special reference to morphological understanding of gallstone formation after gastrectomy.METHODS： The liver, gallbladder and surrounding structures were immersed in a 10 mg/L solution of alizarin red S in ethanol to stain the peripheral nerves in cadavers （n = 10）. Innervation in the areas was completely dissected under a binocular microscope. Similarly,innervation in the same areas of 10 Suncus murinus （S. murinus） was examined employing whole mount immunohistochemistry.RESULTS： Innervation of the gallbladder occurred predominantly through two routes. One was from the anterior hepatic plexus, the innervation occurred along the cystic arteries and duct. Invariably this route passed through the hepatoduodenal ligament. The other route was from the posterior hepatic plexus, the innervation occurred along the cystic duct ventrally. This route also passed through the hepatoduodenal ligament dorsally.Similar results were obtained in S. murinus.CONCLUSION： The route from the anterior hepatic plexus via the cystic artery and/or duct is crucial for preserving gallbladder innervation. Lymph node dissection specifically in the hepatoduodenal ligament may affect the incidence of gallstones after gastrectomy.Furthermore, the route from the posterior hepatic plexus via the common bile duct and the cystic duct to the gallbladder should not be disregarded. Preservation of the plexus may attenuate the incidence of gallstone formation after gastrectomy.

Optimization of maintenance strategy for high-speed railwaycatenary system based on multistate model

A multi-objective optimization model considering both reliability and maintenance cost is proposed to solve the contradiction between reliability and maintenance cost in high-speed railway catenary system maintenance activities.The non-dominated sorting genetic algorithm 2(NSGA2)is applied to multi-objective optimization,and the optimization result is a set of Pareto solutions.Firstly,multistate failure mode analysis is conducted for the main devices leading to the failure of catenary,and then the reliability and failure mode of the whole catenary system is analyzed.The mathematical relationship between system reliability and maintenance cost is derived considering the existing catenary preventive maintenance mode to improve the reliability of the system.Secondly,an improved NSGA2(INSGA2)is proposed,which strengths population diversity by improving selection operator,and introduces local search strategy to ensure that population distribution is more uniform.The comparison results of the two algorithms before and after improvement on the zero-ductility transition(ZDT)series functions show that the population diversity is better and the solution is more uniform using INSGA2.Finally,the INSGA2 is applied to multi-objective optimization of system reliability and maintenance cost in different maintenance periods.The decision-makers can choose the reasonable solutions as the maintenance plans in the optimization results by weighing the relationship between the system reliability and the maintenance cost.The selected maintenance plans can ensure the lowest maintenance cost while the system reliability is as high as possible.

Integration optimization of novel electric power steering system based on quality engineering theory

The dynamic model of a novel electric power steering （EPS） system integrated with active front steering function （the novel EPS system） is built. The concepts and quantitative expressions of the steering road feel, steering sensibility, and steering operation stability are introduced. Based on quality engineering theory, the optimization algorithm is proposed by integrating the Monte Carlo descriptive sampling, elitist non-dominated sorting genetic algorithm （NSGA-II） and 6-sigma design method. With the steering road feel and the steering portability as optimization targets, the system parameters are optimized by the proposed optimization algorithm. The simulation results show that the system optimized based on quality engineering theory can improve the steering road feel, guarantee steering stability and steering portability and thus provide a theoretical basis for the design and optimization of the novel electric power steering system.

Method for optimizing manipulator's geometrical parameters and selecting reducers

A geometrical parameters optimization and reducers selection method was proposed for robotic manipulators design. The Lagrangian approach was employed in deriving the dynamic model of a two-DOF manipulator. The flexibility of links and joints was taken into account in the mechanical structure dimensions optimization and reducers selection, in which Timoshenko model was used to discretize the hollow links. Two criteria, i.e. maximization of fundamental frequency and minimization of self-mass/load ratio, were utilized to optimize the manipulators. The NSGA-II (fast elitist nondominated sorting genetic algorithms) was employed to solve the multi-objective optimization problem. How the joints flexibility affects the manipulators design was analyzed and shown in the numerical analysis example. The results indicate that simultaneous consideration of the joints and the links flexibility is very necessary for manipulators optimal design. Finally, several optimal combinations were provided. The effectiveness of the optimization method was proved by comparing with ADAMS simulation results. The self-mass/load ratio error of the two methods is within 10%. The maximum error of the natural frequency by the two methods is 23.74%. The method proposed in this work provides a fast and effective pathway for manipulator design and reducers selection.

Surgical anatomy of the innervation of pylorus in human and Suncus murinus, in relation to surgical technique for pylorus-preserving pancreaticoduodenectomy

AIM： To clarify the innervation of the antro-pyloric region in humans from a clinico-anatomical perspective. METHODS： The stomach, duodenum and surrounding structures were dissected in 10 cadavers, and immersed in a 10mg/L solution of alizarin red S in ethanol to stain the peripheral nerves. The distribution details were studied to confirm innervations in the above areas using a binocular microscope. Similarly, innervations in 10 Suncus murinus were examined using the method of whole-mount imm unohistochemistry. RESULTS： The innervation of the pyloric region in humans involved three routes： One arose from the anterior hepatic plexus via the route of the suprapyloric/supraduodenal branch of the right gastric artery; the second arose from the anterior and posterior gastric divisions, and the third originated from the posterior-lower region of the pyloric region, which passed via the infrapyloric artery or retroduodenal branches and was related to the gastroduodenal artery and right gastroepiploic artery. For Suncus murinus, results similar to those in humans were observed. CONCLUSION： There are three routes of innervation of the pyloric region in humans, wherein the route of the right gastric artery is most important for preserving pyloric region innervation. Function will be preserved by more than 80% by preserving the artery in pylorus-preserving pancreaticoduodenectomy （PPPD）. However, the route of the infrapyloric artery should not be disregarded. This route is related to several arteries （the right gastroepiploic and gastroduodenal arteries）, and the preserving of these arteries is advantageous for preserving pyloric innervation in PPPD. Concurrently, the nerves of Latarjet also play an important role in maintaining innervation of the antro-pyloric region in PPPD. This is why pyloric function is not damaged in some patients when the right gastric artery is dissected or damaged in PPPD.

Multi-objective modeling and optimization for scheduling of cracking furnace systems

Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non- linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables （MDNSGA-II） is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta- tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.

Theoretical and experimental investigation on optimization of a non-contact air conveyor

Air film conveyors equipped with porous pads have been developed to bring the liquid crystal display(LCD) into a non-contact state during transportation process. In this work, a theoretical model including flow property of porous media and Reynolds equation is established within a representative region in order to optimize the design parameters of a partial porous air conveyor. With the theoretical model, an optimization method using nondominated sorting genetic algorithm – II(NSGA-II) is applied for a two-objective optimization to achieve a minimum air consumption and maximum load capacity. Three Pareto-optimal solutions are selected to analyze the influence of each parameter on the characteristics of the air conveyor, and the results indicate that the position of the porous pads has the most significant impact on the performance and of course must be determined with care. Furthermore, experimental results in terms of the supporting force versus gap clearance show that the optimized air conveyor can greatly improve the load capacity over the normal one, indicating that the optimization method is applicable for practical use.

Optimal transmission lines assignment with maximal reliabilities in multi-source multi-sink multi-state computer network

The optimal transmission lines assignment with maximal reliabilities (OTLAMR) in the multi-source multi-sink multi-state computer network (MMMCN) was investigated. The OTLAMR problem contains two sub-problems: the MMMCN reliabilities evaluation and multi-objective transmission lines assignment optimization. First, a reliability evaluation with a transmission line assignment (RETLA) algorithm is proposed to calculate the MMMCN reliabilities under the cost constraint for a certain transmission lines configuration. Second, the non-dominated sorting genetic algorithm II (NSGA-II) is adopted to find the non-dominated set of the transmission lines assignments based on the reliabilities obtained from the RETLA algorithm. By combining the RETLA and the NSGA-II algorithms together, the RETLA-NSGA II algorithm is proposed to solve the OTLAMR problem. The experiments result show that the RETLA-NSGA II algorithm can provide efficient solutions in a reasonable time, from which the decision makers can choose the best solution based on their preferences and experiences.

Sustainability of Touristic Potential of the Old Van City and Castle of Van in Terms of Cultural, Historical and Natural Values

Tourism has become the world＇s fastest growing sector due to acceleration of technology and information flow in the globalized world of today, development of the modem mass transport system and increase in people＇s disposable income. Upon tourism＇s being considered as a serious development strategy in the developments of the countries, all the countries of the world have begun to accelerate their investments in this area through utilizing the natural and cultural assets of their countries （heritage） with a view to provide revenue to their economy as well as creation of jobs. This situation, which has emerged as a result of the globalization of supply and demand in tourism, has created certain problems in terms of environmental balance and the living conditions of local people as a result of poor management of the utilization of natural and cultural resources. The objective of this paper is to examine the concepts and principles germane to sustainable tourism which has significant contribution to the development of the countries, made at the macro level both in the world and in Turkey. The aim of this paper, at the micro level, is to create awareness incident to the tourism resources of the Van Region and the Old Van province and ensure the utilization of these resources through protection thereof. At the end of the study, the importance of the protection of heritage resources as well as fair use thereof in terms of increasing the competitiveness of Turkey on a global scale in tourism is addressed in the light of the overall evaluations.

Investigation on Optimization Design of an Equivalent Water Depth Truncated Mooring System Based on INSGA-Ⅱ

At present,equivalent water depth truncated mooring system optimization design is regarded as the priority of hybrid model testing for deep sea platforms,and will replace the full depth system test in the future.Compared with the full depth system,the working depth and span are smaller in the truncated one,and the other characteristics maintain more consistency as well.In this paper,an inner turret moored floating production storage ＆ offloading system（FPSO） which works at a water depth of 320m,was selected to be a research example while the truncated water depth was 80m.Furthermore,an improved non-dominated sorting genetic algorithm（INSGA-II） was selected to optimally calculate the equivalent water depth truncated system,considering the stress condition of the total mooring system in both the horizontal and vertical directions,as well as the static characteristic similarity of the representative single mooring line.The results of numerical calculations indicate that the mathematical model is feasible,and the optimization method is fast and effective.

NSGA Ⅱ based multi-objective homing trajectory planning of parafoil system

Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a kind of multi-objective optimization problem.Being different from traditional ways of transforming the multi-objective optimization into a single objective optimization by weighting factors,this work applies an improved non-dominated sorting genetic algorithm Ⅱ(NSGA Ⅱ) to solve it directly by means of optimizing multi-objective functions simultaneously.In the improved NSGA Ⅱ,the chaos initialization and a crowding distance based population trimming method were introduced to overcome the prematurity of population,the penalty function was used in handling constraints,and the optimal solution was selected according to the method of fuzzy set theory.Simulation results of three different schemes designed according to various practical engineering requirements show that the improved NSGA Ⅱ can effectively obtain the Pareto optimal solution set under different weighting with outstanding convergence and stability,and provide a new train of thoughts to design homing trajectory of parafoil system.

OPTIMIZATION ON ANTENNA PATTERN OF SPACEBORNE SAR WITH IMPROVED NSGA-Ⅱ

Optimization of antenna array pattern used in a spaceborne Synthetic Aperture Radar (SAR) system is considered in this study. A robust evolutionary algorithm, Non-dominated Sorting Genetic Algorithms (the improved NSGA-Ⅱ), is applied on a spaceborne SAR antenna pattern design. The system consists of two objective functions with two constraints. Pareto fronts are generated as a result of multi-objective optimization. After being validated by a test problem ZDT4, the algorithms are used to synthesize spaceborne SAR antenna radiation pattern. The good results with low Ambi- guity-to-Signal Ratio (ASR) and high directivity are obtained in the paper.

Optimal design of functionally graded Pm PV/CNT nanocomposite cylindrical tube for purpose of torque transmission

Carbon nanotube(CNT)/polymer nanocomposites have vast application in industry because of their light mass and high strength. In this work, a cylindrical tube which is made up of functionally graded(FG) PmP V/CNT nanocomposite, is optimally designed for the purpose of torque transmission. The main confining parameters of a rotating shaft in torque transmission process are mass of the shaft, critical speed of rotation and critical buckling torque. It is required to solve a multi-objective optimization problem(MOP) to consider these three targets simultaneously in the process of design. The three-objective optimization problem for this case is defined and solved using a hybrid method of FEM and modified non-dominated sorting genetic algorithm(NSGA-II), by coupling two softwares, MATLAB and ABAQUS. Optimization process provides a set of non-dominated optimal design vectors. Then, two methods, nearest to ideal point(NIP) and technique for ordering preferences by similarity to ideal solution(TOPSIS), are employed to choose trade-off optimum design vectors. Optimum parameters that are obtained from this work are compared with the results of previous studies for similar cylindrical tubes made from composite or a hybrid of aluminum and composite that more than 20% improvement is observed in all of the objective functions.

Tri-level programming model for combined urban traffic signal control and traffic flow guidance

In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.

Area-Based Connected Dominating Set Construction and Maintenance Algorithm in Ubiquitous Stub Environment

In order to construct and maintain stability Connected Dominating Set over MANET in Ubiquitous Stub Network, this paper proposes a novel area-based CDS construction and maintenance algorithm. The algorithm is divided into three phases: 1) Area Partition; 2) Area Expansion; 3) Area Connection. In additional, maintenance strategy is proposed in each phase respectively to handle node mobility with timer. At last, the simulation is implemented with OPNET and MATLAB and the results are analyzed in detailed with Size of CDS, Message Overhead and other indexes.

Best compromising crashworthiness design of automotive S-rail using TOPSIS and modified NSGAⅡ

In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Modified non-dominated sorting genetic algorithm II(NSGA II) was used for multi-objective optimization of automotive S-rail considering absorbed energy(E), peak crushing force(Fmax) and mass of the structure(W) as three conflicting objective functions. In the multi-objective optimization problem(MOP), E and Fmax are defined by polynomial models extracted using the software GEvo M based on train and test data obtained from numerical simulation of quasi-static crushing of the S-rail using ABAQUS. Finally, the nearest to ideal point(NIP)method and technique for ordering preferences by similarity to ideal solution(TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. Results represent that the optimum design point obtained from TOPSIS method exhibits better trade-off in comparison with that of optimum design point obtained from NIP method.

Multi-objective Optimization Based on Unsteady Analysis Considering the Efficiency and Radial Force of a Single-Channel Pump for Wastewater Treatment

A multidisciplinary optimization was conducted to simultaneously improve the efficiency and reduce the radial force of a single-channel pump for wastewater treatment. A hybrid multi-objective evolutionary algorithm was coupled with a surrogate model to optimize the geometry of the single-channel pump volute. Steady and unsteady Reynolds-averaged Navier-Stokes equations with a shear stress transport turbulence model were discretized using finite volume approximations and were then solved on tetrahedral grids to analyze the flow in the single-channel pump. The three objective functions represented the total efficiency, the sweep area of the radial force during one revolution, and the distance of the mass center of sweep area from the origin while the two design variables were related to the cross-sectional area of the internal flow of the volute. Latin hypercube sampling was employed to generate twelve design points within the design space, and response surface approximation models were constructed as surrogate models for the objectives based on the values of the objective function at the given design points. A fast non-dominated sorting genetic algorithm for local search was coupled with the surrogate models to determine the global Pareto-optimal solutions. The trade-off between the objectives was determined and was described in terms of the Pareto-optimal solutions. The results of the multi-objective optimization showed that the optimum design simultaneously improved the efficiency and reduced the radial force relative to those of the reference design.