重组人单链白细胞介素12融合基因(rhscIL-12)的构建和真核表达

克隆人 IL - 1 2 ( h IL - 1 2 ) p40和 p35亚单位 c DNA,构建人单链 IL- 1 2 ( rhsc IL- 1 2 )融合基因 ,并在哺乳动物细胞中进行表达。方法　从经 PDBu刺激的 EBV转化的人 B淋巴母细胞株 NC37中提取 m RNA,经 RT- PCR分别获得 h IL- 1 2 p40和 p35亚单位编码序列的 c DNA,运用重组 PCR技术将两段基因通过一疏水性多肽接头 ( Gly4 Ser) 3 DNA序列进行体外基因重组 ,构建 rhsc IL- 1 2融合基因 ,将其插入 pc DNA3.1 ( + )真核表达载体 ,经脂质体转染 COS7细胞进行表达 ,Western blot进行分析。结果　所克隆的 h IL- 1 2 p40、p35c DNA序列和构建的 rhsc IL - 1 2融合基因 DNA序列均经测序得以证实 ,融合基因可在 COS7中表达其产物 rhsc IL- 1 2融合蛋白 ,其分子量为 70 KD,可与鼠抗人 IL - 1 2 p40 /p70单克隆抗体特异性结合。结论　本研究结果为进一步探讨 rhsc IL- 1 2融合蛋白的生物学活性和特性奠定了基础 ,也为 rhsc IL- 1 2融合基因在原核细胞中的表达提供了可能性     

椭圆曲线密码算法的边信道攻击研究

边信道攻击是一种对密码算法实现的有效的攻击.针对椭圆曲线密码的实现,简单边信道攻击可以逐步确定私钥.文中讨论了通过模糊私钥的标量表示和椭圆曲线计算序列的关系来抵抗简单边信道攻击.为了分析这些算法,文中提出了一种新的方法,即把椭圆曲线标量乘运算看作马尔可夫链.理论证明,这种方法比标准的简单边信道攻击更有效.     

基于马尔可夫链的极值波高预测

本文研究了由日最大波高系列估算设计极值波高时，相邻日最大波高间的相关性对极值预测的影响，从日最大波高系列遵从马尔可夫链的假定出发，考虑到国内外经常采用对数一正态分布的韦布尔分布拟合波高长期分布的现实，本文用解析法求解了对数一正态分布情况下的极值预测。同时，对解析法难以求解的非正态随机变量情况（如韦布尔分布），用计算机随机模拟方法求解其极值预测，用上述两种方法对北大西洋和北海有关日最大波高系列的预测     

供应链物流能力的管理过程分析

供应链物流能力是保障供应链正常运作的关键能力之一.笔者首先分析了供应链物流能力的基本概念和研究现状,分析了供应链物流能力的构成及影响因素,提出了常见的几种供应链物流能力.从“计划——执行——监督控制”三个主要的管理过程出发,对供应链物流能力管理过程进行了系统的分析,论述了在不同的阶段中,供应链物流能力管理的主要任务.论文提出了执行过程中供应链物流能力的五大影响因素和调节供应链物流能力的四种主要策略,提出了供应链上不同企业主体对物流能力管理过程的作用,最后对全文总结.     

发电机组维修时间进程影响的因素及对策

探讨了影响装备维修进度计划制定的因素。分析了基于关键链的维修管理方法,并总结了关键链方法的实施原则。此方法可以解决传统维修进度管理中的资源冲突问题,缩短维修周期,保障装备的正常运行,提高了装备保障性能。结合发电机组维修实例,分析了关键链方法在发电机组维修方面的应用,通过该方法的运用,优化了维修进度管理。     

供应链企业在各种关系下的价格折扣方案设计

供应链企业间的关系管理是供应链管理的重点,而价格折扣是供应链企业间最常用的关系协调机制。文中用一个有一个供应商与多个经销商的供应链,假定了四种特殊关系,即：（1）横向（经销商之间）、纵向（与供应商）不合作;（2）横向不合作,纵向合作;（3）横向合作,纵向不合作;（4）横向合作,纵向合作。针对供应链企业之间的各种关系设计不同的价格折扣方案以满足供应链企业的利益最大化;对各种关系下的价格折扣方案进行比较,得到了不同关系下价格折扣率的取值范围。     

A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study

The management of products’ end-of-life and the recovery of used products has gained significant importance in recent years. In this paper, we address the carbon footprint-based problem that arises in a closed-loop supply chain where returned products are collected from customers. These returned products can either be disposed of or be remanufactured to be resold as new ones. Given this environment, an optimization model for a closed-loop supply chain (CLSC) in which carbon emission is expressed in terms of environmental constraints, i.e., carbon emission constraints, is developed. These constraints aim to limit the carbon emission per unit of product supplied with different transportation modes. Here, we design a closed-loop network where capacity limits, single-item management and uncertainty on product demands and returns are considered. First, fuzzy mathematical programming is introduced for uncertain modeling. Then, the statistical approach to the possibility to synthesize fuzzy information is utilized. Therefore, using a defined possibilistic mean and variance, we transform the proposed fuzzy mathematical model into a crisp form to facilitate efficient computation and analysis. Finally, the risk caused by violating the estimated resource constraints is analyzed so that decision makers (DMs) can trade off between the expected cost savings and the expected risk. We utilize data from a company located in Iran.     

Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data

Assessing sustainability of supply chains is a critical and increasingly complex problem. In recent years sustainability has received more attention in supply chain management (SCM) literature with triple bottom lines including social, environmental, and economic factors. Conventional data envelopment analysis (DEA) models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration internal interactions of DMUs. Two-stage DEA models deal with such DMUs. However, existing two-stage DEA models are applicable only in technologies characterized by positive inputs/outputs. This paper aims to build and present a new two-stage DEA model considering negative input-intermediate-output data. Some numerical examples along with some theorems and properties are given to show capability of proposed method. The proposed ideas are used in a case study where 29 Iranian supply chains producing equipment of expendable medical devices are evaluated in terms of sustainability.     

A competing Markov model for cracking prediction on civil structures

Cracks on the surface of civil structures (e.g. pavement sections, concrete structures) progress in several formations and under different deterioration mechanisms. In monitoring practice, it is often that cracking type with its worst damage level is selected as a representative condition state, while other cracking types and their damage levels are neglected in records, remaining as hidden information. Therefore, the practice in monitoring has a potential to conceal with a bias selection process, which possibly result in not optimal intervention strategies. In overcoming these problems, our paper presents a non-homogeneous Markov hazard model, with competing hazard rates. Cracking condition states are classified in three types (longitudinal crack, horizontal crack, and alligator crack), with three respective damage levels. The dynamic selection of cracking condition states are undergone a competing process of cracking types and damage levels. We apply a numerical solution using Bayesian estimation and Markov Chain Monte Carlo method to solve the problem of high-order integration of complete likelihood function. An empirical study on a data-set of Japanese pavement system is presented to demonstrate the applicability and contribution of the model.     

滑坡、崩塌、泥石流三者之间的关系研究

以四川省九环线平武段地质灾害为对象,通过大量野外调查研究,得出滑坡、崩塌和泥石流三者之间是相互联系、相互促进、相互转化的结论。不同地质条件形成不同类型的地质灾害链,它们是循环发生的,在地质灾害治理中应予以重视,尽量做到一次性彻底治理。