独立学院在分类管理下的路径和法规问题研究

独立学院从产生起就存在法律制度困境,属性界定与法规偏离,法人属性不明晰,法律规定的社会公益性与办学回报相冲突,如此种种导致独立学院在选择营利和非营利道路上艰难坎坷,步履维艰。为了规避此种困境,独立学院必须先转设而后选择营利与非营利道路。在此前提下,独立学院发展道路选择过程中必须秉持四个坚持:坚持社会主义办学方向,坚持特色为导向,坚持精简效能原则及坚持品牌定位。

中国转基因种子市场发展现状及法规问题

中国转基因种子市场的发展现状及法规问题一直备受关注。本研究通过对相关文献进行综述,概述了中国转基因种子市场的发展现状和法规问题,并提出了相应的解决途径。中国转基因种子市场规模巨大,呈现出快速增长的趋势,主要种类包括转基因大豆、转基因玉米和转基因棉花等。然而,该市场面临着审批和监管制度不完善、标识和追溯体系建设不健全以及公众参与和风险沟通不足等问题。为了解决这些问题,提出了加强法规制定和修订、完善监管体系和技术手段、促进公众参与和风险沟通等策略和建议。进一步研究应关注转基因种子市场的食品安全、农民权益、公众参与和国际经验等方面。本研究为中国转基因种子市场的可持续发展和法规完善提供了参考。

中国转基因植物专利保护的法规问题及挑战性分析

本研究旨在对中国转基因植物专利保护的法规问题及挑战性进行分析。通过对相关法律法规、专利申请和审批过程的探讨,以及对转基因植物专利保护对创新和市场竞争的影响的研究,揭示了中国转基因植物专利保护所面临的法规问题和挑战性。针对这些问题,本研究提出了加强技术评估、平衡利益相关者权益、优化专利有效期等方面的改进建议。同时,我们从可持续发展的角度思考转基因植物专利保护问题,探讨了环境风险评估和监管、技术转移和知识共享、科学研究和公众教育等方面的策略。通过本研究的分析和讨论,旨在为中国转基因植物专利保护的法规制定和可持续发展提供参考和借鉴。

中国转基因作物产业化现状及法规问题

全球范围内转基因作物产业化种植的国家数量逐年增长,转基因作物产业化种植的产量也呈现不断增长态势。中国在转基因作物产业化种植的面积越来越大,但对于开放转基因作物产业化种植的质疑依然存在。本研究系统分析中国转基因作物产业化现状以及中国转基因作物产业化中存在的法规问题,提出了通过构建和完善转基因作物产业化生产和应用等各个环境中的相关法律制度和风险防控措施,促进中国转基因作物产业化的法律体系建设,进而保障中国转基因作物产业化的可持续发展。

关于会计人员执行会计法规中存在的问题与对策

本文对会计人员执行会计法规中存在的问题,提出了如何解决的对策,旨在加强会计工作管理,提高会计人员执法水平,杜绝违规违法事件的发生,保护国家财产的安全与完整。

高考替考、舞弊行为的刑法规制问题研究

高考替考、舞弊行为严重侵犯了广大考生的利益,造成了社会诚信的缺失,给社会及国家考试的秩序带来了不良影响,成为目前我国打击的重点。随着《刑法修正案(九)》的提出,增加了考试作弊罪、非法出售、提供试题、答案罪,代替考试罪,从而为高考舞弊行为的定罪与判刑提供了刑事法依据。

完善我国转基因食品标识的法律问题研究

转基因食品标识制度在转基因食品监管中具有至关重要的作用。文章首先从法律规定、监管制度的角度分别阐述了我国转基因食品标识法律制度的现状;而后分析了我国转基因食品标识法律存在的主要问题,认为我国转基因法律存在规范尚不完善、监管制度仍不健全、惩罚救济法律制度还不完备等问题;最后提出具有针对性的建议对策,认为应进一步完善我国转基因食品标识的法律体系规范,建立高效的转基因食品标识的监管制度,加强转基因食品标识的处罚和救济制度建设。

高校图书馆图书采购招标过程中存在的问题解析

本文通过解读政府采购招投标相关法律法规文件,结合高校图书馆图书采购招标工作的调研,列举了招标响应过程中常见的一些问题并分析了其产生的原因,提出了应对措施和解决方案。

关于我国食品安全管理中存在的问题及解决措施

随着我国经济的快速发展，人们物质文化生活水平的不断提高，健康问题越来越成为人们关注的重点。人们在关注健康的同时，发现我国食品安全管理上存在的隐患越来越多，直接影响到了人们身体的健康及社会的和谐发展。特别是在最近几年，媒体、报端一些关到食品安全事故的报道屡见不鲜。本文分析了目前我国食品安全管理存在的问题，并进一步对加强我国食品安全管理的具体措施进行了阐述。

转基因育种产业发展及法律问题探析

转基因育种是指通过基因工程技术对植物或动物进行基因改造,以获得更优良的品种或性状。转基因育种产业在提高农业生产效率和食品安全方面具有显著优势,但同时也存在着生态风险和伦理问题,需要加强监管和安全评估。本研究旨在探讨转基因育种产业发展的法规问题,分析现有监管制度的不足之处,提出加强监管和安全评估的建议。通过对国内外相关法规和标准的研究,结合实际案例分析,初步得出了一些结论和展望。本研究的意义在于促进转基因育种产业的可持续发展,保障食品安全和生态环境的健康。

A NEW MODEL AND SOLUTION FOR TRANSPORTATION PROBLEM

Transportation problem has many real world applications, it can be solved by linear programming model, but in most time the model exists more for less paradox, this paper considers the reasons for the paradox and search the way to eliminate the phenomenon. First this paper formulates a loose constrained linear programming model for the transportation problem, and gives the definition of the paradox which exists in it, some preliminary notions and one example is also given. Then it gives a table based algorithm for the loose constrained model, the steps of the algorithm and example will follow. The examples show that: (1) It is not a contradictory that transportation problem exists more for less paradox. (2) The loose constrained model is better used in practice for its less total cost. (3) The algorithm is easy to calculate, to study and highly speed to convergence. Finally, comparied with other ways it shows that the loose constrained model can thoroughly eliminate the paradox.

亚洲苯的市场走向

一些预测认为在今后2～3年苯的供应会严重短缺，但也肓预测会大量过剩。作者对此问题的不确定因素进行了调查研究。

蚂蚁IPO悬疑:注册是否依然有效?

假若蚂蚁集团不管证监会是否撤回注册决定,在经过对相关会后事项核查和评估,过段时间重新启动发行,是否允许呢?其中或许存在法律法规空白。在证监会尚未明确是否撤回注册决定之前,发行人不应允许重启发行11月17日证监会副主席方星海在创新经济论坛上表示,蚂蚁集团上市是不是有时间表,取决于政府如何重组监管框架。笔者认为,此前蚂蚁集团获得证监会同意注册,是否依然有效,这是问题的一个关键,为此笔者梳理注册制程序涉及的法律法规问题。

New Approach to Linear Stackelberg Problems with Multiple Leaders-followers

In this paper, we study linear static Stac kelberg problems with multiple leaders-followers in which each decision maker wi thin his group may or may not cooperate. An exact penalty function method is dev eloped. The duality gaps of the followers’ problems are appended to the leaders’ objective function with a penalty. The structure leads to the decomposition of the composite problem into a series of linear programmings leading to an efficie nt algorithm. We prove that local optimality is reached for an exact penalty fun ction and illustrate the method with three examples. The model in this paper ext ends the stackelberg leader-follower model.

Hybrid particle swarm optimization with chaotic search for solving integer and mixed integer programming problems

A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.

Least squares weighted twin support vector machines with local information

A least squares version of the recently proposed weighted twin support vector machine with local information(WLTSVM) for binary classification is formulated. This formulation leads to an extremely simple and fast algorithm, called least squares weighted twin support vector machine with local information(LSWLTSVM), for generating binary classifiers based on two non-parallel hyperplanes. Two modified primal problems of WLTSVM are attempted to solve, instead of two dual problems usually solved. The solution of the two modified problems reduces to solving just two systems of linear equations as opposed to solving two quadratic programming problems along with two systems of linear equations in WLTSVM. Moreover, two extra modifications were proposed in LSWLTSVM to improve the generalization capability. One is that a hot kernel function, not the simple-minded definition in WLTSVM, is used to define the weight matrix of adjacency graph, which ensures that the underlying similarity information between any pair of data points in the same class can be fully reflected. The other is that the weight for each point in the contrary class is considered in constructing equality constraints, which makes LSWLTSVM less sensitive to noise points than WLTSVM. Experimental results indicate that LSWLTSVM has comparable classification accuracy to that of WLTSVM but with remarkably less computational time.

Genetic Algorithm Based on Duality Principle for Bilevel Programming Problem in Steel-making Production

Steel-making and continuous/ingot casting are the key processes of modern iron and steel enterprises. Bilevel programming problems(BLPPs) are the optimization problems with hierarchical structure. In steel-making production, the plan is not only decided by the steel-making scheduling, but also by the transportation equipment.This paper proposes a genetic algorithm to solve continuous and ingot casting scheduling problems. Based on the characteristics of the problems involved, a genetic algorithm is proposed for solving the bilevel programming problem in steel-making production. Furthermore, based on the simplex method, a new crossover operator is designed to improve the efficiency of the genetic algorithm. Finally, the convergence is analyzed. Using actual data the validity of the proposed algorithm is proved and the application results in the steel plant are analyzed.

A Distributed User Association and Resource Allocation Method in Cache-Enabled Small Cell Networks

Cache-enabled small cell networks have been regarded as a promising approach for network operators to cope with the explosive data traffic growth in future 5 G networks. However, the user association and resource allocation mechanism has not been thoroughly studied under given content placement situation. In this paper, we formulate the joint optimization problem of user association and resource allocation as a mixed integer nonlinear programming(MINLP) problem aiming at deriving a balance between the total utility of data rates and the total data rates retrieved from caches. To solve this problem, we propose a distributed relaxing-rounding method. Simulation results demonstrate that the distributed relaxing-rounding method outperforms traditional max-SINR method and range-expansion method in terms of both total utility of data rates and total data rates retrieved from caches in practical scenarios. In addition, effects of storage and backhaul capacities on the performance are also studied.