生物电子等排原理在新药设计中的应用

探索生物电子等排原理在新药研究中应用的规律,推动新药研究的进展;通过查阅文献资料,阐述生物电子等排的定义及各类生物电子等排的特点、使用范围、典型事例;表明生物电子等排既有外层电子总数相等的原子或基因的替换,也有在体积、形状、构象、电子分布、脂水分配系数、pKa、化学反应性(包括代谢相似性)和氢键成键能力等重要参数上存在相似性的原子或基团的替换,是对已知药物的结构改造或结构修饰;所产生新化合物优于、近于或拮抗原来药物的作用,具有成功率高、风险小、投资少的特点,在新药研究中占有重要的地位。应用生物电子等排体进行新药设计,尤其适合我国制药工业现有的实际情况。     

排液采气配套技术在白庙凝析气藏的应用

本文针对白庙凝析气田气井井筒积液、压力下降快、产量递减幅度等特点,论述了排液采气配套技术的原理,总结了白庙气田气举排液方面存在的主要问题,分析了气井积液规律,通过对白50井等20口气实施增压气举排液,多级气举阀配套管柱的优化应用,排液效果明显,提高了白庙气田气井产能,达到了增气、增油的目的。     

浅谈“me-too”药在新药研究中的地位

探索“me-too”药的研究规律,推动新药研究工作的开展;通过文献检索、分析、比较、归纳、综合,阐述“me-too”药的定义、特点、研究方法及典型事例,总结了国内外“me-too”药研究成功的经验。“me-too”药在新药研究中广泛应用。应用生物电子等排体替换、前药设计及手性药物研究等制得了大量“me-too”药物。“me-too”药是以已知药物为先导化合物,经结构修饰、结构改造而得到的新化学实体,比全新结构药物的创制研究难度低、风险小、成功率高,是新药研究的一条重要途径,也是由仿制向创制转轨的捷径。     

北美页岩气开发压裂返排液Ozonix水处理技术

页岩气开发在水力压裂过程中会产生大量的返排液,压裂返排液具有粘度大、稳定性高、悬浮物多、矿化度高和成分复杂等特点。若不进行妥善处理,对页岩气开发的长远发展将造成不可估量的损失。文章详细介绍了北美页岩气开发过程中压裂返排液Ozonix水处理技术,包括该技术的处理原理、设备流程和现场应用效果等内容,同时与其他处理技术进行了对比分析。     

高效节能电子霓虹灯变压器

现有的霓虹灯变压器能耗大,体积也大。根据霓虹灯发光原理,可采用高频高压电子变换装置来替代。新型电子霓虹灯变压器具有寿命长、节能(>50％)、重量轻、体积小等特点。电子霓虹灯变压器的原理如图1所示,结构简单,只要改变其激励信号电平,就可提高其功率。     

浅析各种类自吸泵比较

概述能达到自吸目的离心泵,简析同属于自吸泵类的自吸泵、气液混输同步排吸泵、透平同步排吸泵及无密封自控自吸泵的结构及工作原理,在应用中各自的性能分析,节能效果的比较,举例说明能够达到同样性能的各种自吸泵,在相同性能范围内的运行状态的比较。     

冷轧机油雾分离器排液系统改进

针对冷轧机油雾分离器排液系统存在定期手动排液带来的一系列问题，利用负压差大于零的原理，对排液系统进行了改进，使手动排液变为自动排液。同时对分离器外部的集油坑进行改造，使集油坑也实现了自动排液。系统改进后不仅提高了生产效率和风机设备使用寿命，而且还有益于现场作业环境的改善。     

测酚生物传感器研究进展

介绍了电化学生物传感器、光学生物传感器和压电生物传感器等测酚生物传感器的原理及国内外发展现状,详细论述了测酚酶传感器的酶的选择、酶的固定化方法和酶电极的修饰方法,指出了测酚生物传感器的发展方向及前景。     

输煤电子皮带秤计量精度影响因素研究分析

输煤系统电子皮带秤的计量精度将直接影响电厂的经济效益和成本核算,介绍了火力发电厂输煤系统电子皮带秤的工作原理,分析了为了保证计量精度,设备在选型、安装、调试和日常维护等方面的经验与方法。     

浅谈水力泵联作排液工艺

针对长庆油田压裂后采用抽汲工艺排液时井口防喷盒、排液管线、液体计量罐不密封,排出液体中伴生的CO、H 2S等有毒有害气体在井口和计量罐等作业区域弥漫、富集,存在安全隐患等问题。水力泵联作排液求产是将水力泵排液工艺与压裂施工的有机结合实现一趟管柱压裂施工和水力泵排液求产。缩短了试油排液周期,减轻了劳动强度,具有返排及时、连续、强度大,工作制度可调,可随泵测压等特点,经成44-017井现场应用,效果比较好。     

Optimal time phasing and periodicity for MRP with POQ policy

This paper deals with component supply planning for assembly systems where several types of components are ordered from external suppliers to produce a single type of finished product. Actual component lead times are often different from those contracted because of random delays. An MRP approach with periodic order quantity (POQ) policy is used for the supply planning of components. Our aim is to find the optimal values of the order periodicity and planned lead times at the offsetting step of the MRP procedure. The goal is to minimise the sum of the average component holding, finished product backlogging and setup costs. Several theoretical properties of the objective function are proven and an efficient optimization algorithm is developed. The proofs of the explicit form and properties of the objective function as well as the development of the optimization algorithm occupy a large portion of this paper. The method developed can be used for the optimization of time phasing and periodicity for such an MRP system under lead time uncertainties.     

Comparing procedures for estimating random coefficient logit demand models with a special focus on obtaining global optima

We compare several nested fixed point and optimization procedures for computing the estimator of the widely-used empirical market demand model developed by Berry et al. (1995). It is well-known that the optimization may often lead to multiple local optima, which, if ignored, can lead to erroneous policy conclusions. By combining the frequencies of finding the global minima and the computing times, we propose a new indicator that provides the computing time needed for obtaining the global minima. Using this indicator, we find that the Spectral and Squarem methods (Reynaerts et al., 2012) outperform the benchmark contraction iterations method and the MPEC (Dubé et al., 2012) and ABLP (Lee and Seo, 2015) methods. Moreover, when the share of the outside alternative is relatively large, two derivative-free optimization algorithms, which require less calculations and coding than derivative-based algorithms, outperform the best derivative-based methods. A simple argument suggests that the latter statement is likely to be true for other versions of the model as well.     

创新引领、产业升级与地区基本实现现代化

产业结构是地区现代化的重要构成要素, 通过产业结构优化升级来实现地区现代化是发达国家和地区的通常做法。 目前我国许多地区已经处于工业化的中后期阶段, 科技创新开始成为引领区域产业结构升级的基本动力。 创新引领产业升级, 当前迫切需要实现从招商引资到招才引智, 从被动利用外资企业技术溢出到主动走出去寻求技术, 从利用后发优势到采取先发战略, 从创新与创业脱节到产学研一体化, 从追求 “大而全” 到形成各具特色的区域产业网络的战略变迁。     

考虑营销成本的库存与运输联合优化三阶段决策模型研究

一般来说,个体最优和整体最优是不一致的,二者之间存在着偏差,这一偏差就是分散优化带来的效率损失。库存与运输联合优化（ITIO）将物流系统中的库存控制和运输管理融合到一个大问题中,去寻求这一联合问题而非单个问题的最优解决方案,可以最优化整个配送系统的运营成本。本文在考虑营销成本条件下,建立ITIO三阶段决策模型,并求解分析模型性质。研究表明：ITIO零售价和营销成本与需求的营销成本弹性、零售商订购成本、供应商生产启动成本、供应商生产成本、运输固定成本和运输可变成本正相关;与需求函数的价格弹性和订货批量负相关;当订购数量相同时,零售商单独优化的营销成本大于ITIO联合优化的营销成本。     

Stochastic optimization for transshipment problems with positive replenishment lead times

Transshipments, monitored movements of material at the same echelon of a supply chain, represent an effective pooling mechanism. Earlier papers dealing with transshipments either do not incorporate replenishment lead times into their analysis, or only provide a heuristic algorithm where optimality cannot be guaranteed beyond settings with two locations. This paper uses infinitesimal perturbation analysis by combining with a stochastic approximation method to examine the multi-location transshipment problem with positive replenishment lead times. It demonstrates the computation of optimal base stock quantities through sample path optimization. From a methodological perspective, this paper deploys a duality-based gradient computation method to improve computational efficiency. From an application perspective, it solves transshipment problems with non-negligible replenishment lead times. A numerical study illustrates the performance of the proposed approach.     

Monetäre Anreize zur Steuerung der Ladelast von Elektrofahrzeugen – eine modellgestützte Optimierung

Electric mobility is supposed to contribute to climate policy targets by reducing CO₂-emissions in the transportation sector. Increasing penetration rates of electric vehicles (EV) can lead to new challenges in the electricity sector, especially with regard to local distribution networks. Thus the management of charging loads is discussed as a key issue in energy economics. Due to their long parking times, high electricity and power demand, EV seem to be predestined for load management. Monetary incentives as dynamic pricing can be suitable for that: They reflect the current supply situation, pass the information to the consumers and can thus lead to a corresponding charging behaviour. In this article we analyse this interaction between dynamic pricing and charging loads. For this reason we have developed the optimization model DS-Opt+. It models a total number of 4,000 households in two residential areas of a major city with regard to its electricity demand, its mobility behaviour and its equipment of photovoltaic systems. Four different pricing models are tested for their effects on charging behaviour and thus the total load of the residential area. The results illustrate that only fairly high penetration rates of EV lead to remarkably higher electricity demand and require some load management. The tested dynamic pricing models are suitable for influencing charging loads; load-based tariffs are best in achieving a balanced load curve. In our analysis uncontrolled charging strategies are superior regarding a balanced load curve than controlled strategies by time-varying tariffs. Our results lead to several implications relevant for the energy industry and further research.     

Multi-agent-based transport planning in the newspaper industry

In many cases of today's planning tasks, the synchronization of production and distribution is becoming increasingly important in order to minimize costs and to maximize customer satisfaction. This is especially the case if transport schedules are closely connected to production schedules, as it is in the newspaper industry—where perishable goods are distributed immediately after production. In order to achieve the above mentioned competing objectives, a special kind of vehicle routing problem, the vehicle routing problem with time windows and cluster-dependent tour starts (VRPTWCD), has to be solved. Moreover, the varying print and post-processing schedules due to unknown editorial deadlines lead to the need for a dynamic online control of the newspaper production and distribution process. In this contribution, the outlined dynamic transport problem is solved online under consideration of unforeseen changes in production schedules. The solution concept is based on a multi-agent system consisting of, amongst others, several Edition and Vehicle Agents. This system is exemplarily applied to a real life application case of one of the largest German newspaper companies. It is shown that a static (centralized) optimization of the underlying problem would even lead to worse results in comparison to the current situation and that the appliance of the multi-agent system is suitable in the newspaper industry.     

Controlling for the Impact of Variable Liquidity in Commercial Real Estate Price Indices

Liquidity in private asset markets is notoriously variable over time. Therefore, indices of changes in market value that are based on asset transaction prices will systematically reflect intertemporal differences in the ease of selling a property. We define and develop a concept of "constant-liquidity value" in the context of a model that is characterized by pro-cyclical volume of trading. We then present an econometric model that allows for estimation of both a standard transaction-based price index and a constant-liquidity index. Our application to the NCREIF database reveals that, in the case of institutional commercial real estate investment, constant-liquidity values tend to lead transaction-based and appraisal-based indices in time, and also to display greater volatility and cycle amplitude. The differences can be significant for strategic investment policy viewed from a mean-variance portfolio optimization perspective.     

A production rate control policy for stochastic repair and remanufacturing systems

We consider the control of a manufacturing system responding to planned demand at the end of the expected life of each individual piece of equipment and unplanned demand triggered by a major equipment failure. The difficulty of controlling this type of production system resides in the variable nature of the remanufacturing process. In practice, remanufacturing operations for planned demand can be executed at different rates, referring to different component replacement and repair strategies. We formulate this problem as a multi-level control problem and propose a suboptimal control policy. The proposed control policy is described by inventory thresholds triggering the use of different execution modes. Determination of the control policy parameters is based on parameter optimization of analytical cost expressions. A numerical example based on a real case is presented. Our analysis demonstrates that the use of the proposed control approach can lead to a significant reduction in the total average cost, as compared to current practices.