目的 观察脑缺血后LINGO-1的动态表达,研究维甲酸对LINGO-1表达的影响,探讨LINGO-1在缺血性脑损伤中的可能作用.方法 用改良线栓法建立SD大鼠大脑中动脉永久性闭塞动物模型,用Western blot 技术检测LINGO-1表达.实验分为3组:假手术组(Sham组)、缺血组(CI组)和维甲酸治疗组(RA组).结果 脑缺血后6h、1d、3d、7d、14 d、21dLINGO-1的表达,CI组及RA组均显著高于Sham组(P＜0.01).LINGO-1的表达于6h开始升高,在14d时达高峰.LINGO-1拮抗剂(维甲酸)能够抑制脑缺血后LINGO-1蛋白的表达(P＜0.01).结论 LINGO-1在脑缺血早期即上调并呈一定规律性改变,RA可以抑制LINGO-1的表达,提示LINGO-1与脑缺血有关,研究的结果可能为选择合适的时间窗将LINGO-1拮抗剂应用于脑缺血的治疗提供实验依据.

Objective To study the dynamic expression of L1NGO-1 after cerebral ischemia,and the role of LINGO-1 in ischemia brain injury.Methods With modified suture method,models of permanent focal cerebral ischemia were established by middle cerebral artery occlusion (MCAO) of SD rats.Western blot was used to detect the expression of LINGO-1.Results The expression of LINGO-1 at 6 h、l d、3 d、7 d、14 d、21 d after cerebral ischemia in cerebral ischemia group (CI group) and retinoic acid treatment group (RA group) were significantly higher than that of sham operation group (sham group) (P ＜ 0.01).LINGO-1 expression started to increase at 6 h,and gradually increased to peak at 14 d.The antagonistof LINGO-1,retinoic acid,inhibited the expression of LINGO-1 at 14 d after MCAO.Conclusion LINGO-1 expression is up-regulated at the early stage of the cerebral ischemia.RA can inhibit the expression of LINGO-1.It suggests that LINGO-1 is associated with cerebral ischemia.

针对单产品多层次生产外包环境下企业面对顾客需求随机导致运输成本过高的问题，采取允许代工厂和仓库可开关以及物流再分配方法，建立考虑代工厂的能力和最小加工批量、仓库转运能力以及货车运输能力的决策模型，设计加入STP（Shortest Travel Path）快速搜索策略的MGA（Modified Genetic Algorithm）进行求解。在变化工厂总数、仓库总数、顾客总数的不同维度下，将MGA与GA和LINGO分别进行对比。分析表明，MGA与LINGO求得的最优解之间差距均在10%以内，但求解时间明显优于LINGO求解时间，MGA在求解结果和时间方面均优于GA。

To solve single product and multi-level problem of high transportation cost caused by stochastic demand under original equipment manufacturer, allowing opening or closing plants and warehouses, a new model is developed with the capacity and minimum order quantity constraints of plants, the capacity of warehouses and trucks. To minimize the whole supply chain cost, a Modified Genetic Algorithm(MGA)is constructed to solve the problem, while lingo is used to find the optimal solution. The two algorithms are compared by changing the number of plants, warehouses and customers. MGA is also compared with Genetic Algorithm(GA). Numerical experiment results show that the gaps between MGA and lingo are below 10%, but the time is apparently less than lingo. MGA is better than GA both in cost and time.

以某高校大二年级的选课为例,研究了由0-1规划描述的选课模型,利用计算机软件MATLAB和LINGO进行编程求解,给出了选课问题的最优方案,从而为学生顺利选课提供了参考策略.

Taking sophomore course of a college as an example,gave a course selection model based on 0-1 planning used computer software MATLAB and LINGO to program,obtained the optimal solution. The optimal plan of the problem provided reference for students in selecting course.

结合数学与应用数学专业人才的培养方案，探讨了离散优化类课程教学中存在的问题，提出了改革教学方法的新思路。结合教学案例，将Lingo软件用于课堂教学，发挥计算机辅助教学优势，使抽象推理形象化，提高了教学质量。

Combined with the professional personnel training program of mathematics and applied mathematics ,this paper discussed the problems exist in current discrete optimization courses ,and put forward new ideas of teaching re‐form .Combined with cases ,the software Lingo was put into the classroom teaching ,and the advantages of computer‐aided instruction were brought into play .The abstract inference was visualized and the teaching quality was improved .

资源分配问题是将一种或几种资源,恰当地分配给若干个用户,而使目标函数为最优.介绍了应用动态规划的方法解决资源分配问题时的一般策略,并通过实例应用Lingo编程方便地求解此类问题.

The resource allocation problem is one or more of the following resources, properly assigned to a number of users, and makes the objective function for the optimal. This paper introduces the application of dynamic programming method to solve the problem of resource allocation in the general strategy. And through the Lingo programming convenient, an application example to solve these problems, to guide enterprises to better allocation of resources has a certain reference value.