中西部地区工业园区建设——中国“第四次工业化”浪潮

进入21世纪以来,我国内陆地区开启了城市化和工业化发展的新时代,各地县乡以"园区经济"为手段改变资本流向,工业化浪潮兴起。目前,我国经济发展特征可概括为"园区经济西渐,遍地开花;内陆工业化提速,奋力追赶"。在空间演进特征方面,欠发达地区工业化起步、京津沪工业化升级、东部沿海地区和东北三省工业化转型"发展三阶段共存"。各地发展呈梯度转移态势,资本下县乡促成工业化与城市化、市场化联动,土地资本化方式决定了我国第四次工业化的模式——政府主导与市场逐利合拍。     

Improved upper bound for the degenerate and star chromatic numbers of graphs

Let \(G=G(V,E)\) be a graph. A proper coloring of G is a function \(f:V\rightarrow N\) such that \(f(x)\ne f(y)\) for every edge \(xy\in E\). A proper coloring of a graph G such that for every \(k\ge 1\), the union of any k color classes induces a \((k-1)\)-degenerate subgraph is called a degenerate coloring; a proper coloring of a graph with no two-colored \(P_{4}\) is called a star coloring. If a coloring is both degenerate and star, then we call it a degenerate star coloring of graph. The corresponding chromatic number is denoted as \(\chi _{sd}(G)\). In this paper, we employ entropy compression method to obtain a new upper bound \(\chi _{sd}(G)\le \lceil \frac{19}{6}\Delta ^{\frac{3}{2}}+5\Delta \rceil \) for general graph G.     

中国交通基础设施促进了区域经济增长吗——兼论交通基础设施的空间溢出效应

在综合考虑多维要素对中国区域经济增长的协同作用的基础上,构建交通基础设施对区域经济增长的空间溢出模型,利用1993—2009年的中国省级面板数据和空间计量经济学的研究方法,实证分析得出以下主要结论。(1)中国交通基础设施对区域经济增长的产出弹性值合计约0.05—0.07,表明其对中国区域经济增长具有重要的作用。(2)中国交通基础设施对区域经济增长的空间溢出效应非常显著,若不考虑空间溢出效应,会高估交通基础设施对区域经济增长的作用。(3)外地交通基础设施对本地经济增长表现为以正的空间溢出效应为主,但是也有空间负溢出的证据。(4)在影响区域经济增长的多维要素中,劳动力和其他公共部门的资本存量对中国区域经济增长的弹性仍然较大,新经济增长因素与新经济地理因素的作用也不容忽视。     

高校学生管理的法律思考

依法治国和高等教育体制改革给高等学校学生管理工作带来了新的挑战,这要求我们必须全面、客观地认识高校和学生之间的法律关系,认真分析当前学生管理工作中存在的法治缺陷及各种新现象和新问题,并不断思考、探索其对策。     

双循环发展的改革开放空间试验场——我国开发区的缘起、演进和趋势

开发区是我国改革开放进程中重要的"制度安排",在制度转型、市场机制培育、产业结构升级和带动地区经济增长等方面发挥着引领示范作用,但同时也存在政策效应边际递减、土地资源浪费、创新不足等诸多问题.梳理我国开发区过去三十多年的发展经验和不足,并展望其未来定位是一项重要的研究课题.在详细讨论我国开发区的缘起、动力机制、发展阶段、功能演变、面临问题的基础上,文章从制度安排、比较优势、产业集聚和商业环境四个方面总结了我国开发区取得的成功经验.未来,开发区的发展应实现从生产到生活、从效率到公平、从地的繁荣到人的繁荣、从外围到中心、从专业化到多样化、从高速增长到高质量发展、从对外开放到国内国际双循环等方面的转变.     

东西方礼仪的伦理基础比较

东西方礼仪的不同,其中一个重要因素是其伦理基础的差异。文章着重对其伦理基础相似、形式特征各异,以及伦理基础各异、形式特征异同的部分进行比较,从而使我们了解那些礼仅从其伦理基础和实践形式,是值得今天借鉴和有利于促进国际交往的,而有些礼仪形式,我们却是不能苟同,并且要明确加以反对的。     

基于视觉传感的路障自收放控制方法实现

高速公路路障摆放与回收是高危作业,为减少公路上交通事故的发生,课题组设计并开发了基于Arduino和Pixy CMUcam5视觉传感器的路障自收放机器人系统,由移动机器人平台搭载手爪自由移动来实现路障的合理摆放与收回。通过移动平台上路障收放装置的合理设计,并通过网络控制接口与机器人平台上的图像采集与识别模块实现通信,将视觉传感器捕捉到的路障的三维空间位置信息传送给微处理器,控制移动机器人移动定位,手爪配合实现路障收放。该路障自收放系统具有很强的实用性,可实现路障摆放和回收无人操作。该设计可提高公路作业的安全性,有一定的推广意义。     

The 3-rainbow index and connected dominating sets

A tree in an edge-colored graph is said to be rainbow if no two edges on the tree share the same color. An edge-coloring of \(G\) is called a 3-rainbow coloring if for any three vertices in \(G\), there exists a rainbow tree connecting them. The 3-rainbow index \(rx_3(G)\) of \(G\) is defined as the minimum number of colors that are needed in a 3-rainbow coloring of \(G\). This concept, introduced by Chartrand et al., can be viewed as a generalization of the rainbow connection. In this paper, we study the 3-rainbow index by using connected 3-way dominating sets and 3-dominating sets. We show that for every connected graph \(G\) on \(n\) vertices with minimum degree at least \(\delta \, (3\le \delta \le 5)\), \(rx_{3}(G)\le \frac{3n}{\delta +1}+4\), and the bound is tight up to an additive constant; whereas for every connected graph \(G\) on \(n\) vertices with minimum degree at least \(\delta \, (\delta \ge 3)\), we get that \(rx_{3}(G)\le \frac{\ln (\delta +1)}{\delta +1}(1+o_{\delta }(1))n+5\). In addition, we obtain some tight upper bounds of the 3-rainbow index for some special graph classes, including threshold graphs, chain graphs and interval graphs.     

Upper bounds for the total rainbow connection of graphs

A two-agent scheduling problem on parallel machines is considered. Our objective is to minimize the makespan for agent A, subject to an upper bound on the makespan for agent B. When the number of machines, denoted by \(m\), is chosen arbitrarily, we provide an \(O(n)\) algorithm with performance ratio \(2-\frac{1}{m}\), i.e., the makespan for agent A given by the algorithm is no more than \(2-\frac{1}{m}\) times the optimal value, while the makespan for agent B is no more than \(2-\frac{1}{m}\) times the threshold value. This ratio is proved to be tight. Moreover, when \(m=2\), we present an \(O(nlogn)\) algorithm with performance ratio \(\frac{1+\sqrt{17}}{4}\approx 1.28\) which is smaller than \(\frac{3}{2}\). The ratio is weakly tight.