多agent系统中逻辑依赖关系的表达与求解

多agent系统中事件间的逻辑约束形成事件间的逻辑依赖关系.在分析逻辑依赖关系与一阶谓词表示法基础上,分别给出了单agent单目标、多agent单目标、多agent联合目标的逻辑依赖关系的与/或图表达方法,并应用与/或图的AO＊搜索算法,以多agent单目标情形为例,演示多agent系统中逻辑依赖关系的计算过程.     

NT4-ADNF-9融合基因原核表达载体的构建

目的　构建神经营养素 (NT4 )与活性依赖性神经营养因子 9(ADNF 9)融合基因的原核表达载体pBV2 2 0 /NT4 ADNF 9,为进一步对神经系统退行性疾病基因治疗的研究奠定基础。方法　采用非对称互补引物 /模板法 ,制备两端含有酶切位点的ADNF 9的cDNA ,将其连接到NT的信号肽和前导序列的 3′端 ,组成融合基因NT4 ADNF 9,再将该融合基因亚克隆于原核表达载体pBV2 2 0 ,构建为pBV2 2 0 /NT4 ADNF 9。结果　经DNA测序 ,限制性内切酶酶切等方法证实已成功地将ADNF 9重组到NT4信号肽和前导序列的 3′端 ,并将融合基因亚克隆于pBV2 2 0内。结论　成功构建了NT4与ADNF 9融合基因的原核表达载体pBV2 2 0 /NT4 ADNF 9。     

CLINICAL ANALYSIS OF 52 CASES OF JUVENILE DIABETES MELLITUS

ＣＬＩＮＩＣＡＬＡＮＡＬＹＳＩＳＯＦ５２ＣＡＳＥＳＯＦＪＵＶＥＮＩＬＥＤＩＡＢＥＴＥＳＭＥＬＬＩＴＵＳＳｋｉＢｉｎｇｙｉｎ；ＸｉｅＺｈｉｙｕ；（ＤｅｐａｒｔｍｅｎｔｏｆＥｎｄｏｃｒｉｎｏｌｏｇｙ，ＦｉｒｓｔＡｆｆｉｌｉａｔｅｄＨｏｓｐｉｔａｌ，Ｘｉ＇...     

基于时间依赖网络的城市交通紧急疏散线路研究

研究时间依赖网络的城市紧急疏散交通线路问题.在对考虑疏散过程中交叉口延误和通行能力、紧急疏散网络防堵塞改造已有研究的基础上,对紧急疏散时城市交通网络的时变特性进行分析,提出了动态路阻交通紧急疏散线路的思想.考虑到紧急疏散时不一定满足FIFO要求的特性,将研究对象转化为时间依赖非FIFO网络交通紧急疏散线路的确定问题,建...     

STUDY ON THE IMMUNE FUNCTION OF ERYTHROCYTE IN PATIENT WITH NIDDM

ＳＴＵＤＹＯＮＴＨＥＩＭＭＵＮＥＦＵＮＣＴＩＯＮＯＦＥＲＹＴＨＲＯＣＹＴＥＩＮＰＡＴＩＥＮＴＷＩＴＨＮＩＤＤＭＸｕＪｉｎｇ（徐静）（ＤｅｐａｒｔｍｅｎｔｏｆＥｎｄｏｃｒｉｎｅ，ＳｅｃｏｎｄＡｆｆｉｌｉａｔｅｄＨｏｓｐｉｔａｌ，Ｘｉ＇ａｎＭｅｄｉｃａｌ...     

预弯组合梁长期性能分析

本文根据预弯组合梁的受力特点,建立了以应变理论为基础的综合考虑混凝土收缩、徐变以及钢梁的松弛等时效因素的全过程时效分析方法。采用该方法,对哈尔滨中山立交桥和上海莘奉金高速公路跨线桥所采用的预弯组合梁进行全过程时效分析,以对该种结构的长期性能进行定量的评价。     

时间相关Aharonov—Bohm磁通驱动下介观环中的超电流

利用时间相关Ａｈａｒｏｎｏｖ－Ｂｏｈｍ（ＡＢ）型磁通驱动下介观弹道环中单电子波函数的单值性，讨论了含时驱动下环中超电流的周期变化特性。结果表明，时间相关的ＡＢ型磁通φ（ｔ）可以在环上感应出电场Ｅ（ｔ）≠０，但不影响超电流的幅度大小而令影响其频率。     

Time-dependent green vehicle routing problem with stochastic vehicle speeds: An approximate dynamic programming algorithm

This paper addresses a Time Dependent Capacitated Vehicle Routing Problem with stochastic vehicle speeds and environmental concerns. The problem has been formulated as a Markovian Decision Process. As distinct from the traditional attempts on the problem, while estimating the amount of fuel consumption and emissions, the model takes time-dependency and stochasticity of the vehicle speeds into account. The Time Dependent Capacitated Vehicle Routing Problem is known to be NP-Hard for even deterministic settings. Incorporating uncertainty to the problem increases complexity, which renders classical optimization methods infeasible. Therefore, we propose an Approximate Dynamic Programming based heuristic as a decision aid tool for the problem. The proposed Markovian Decision Model and Approximate Dynamic Programming based heuristic are flexible in terms that more environmentally friendly solutions can be obtained by changing the objective function from cost minimization to emissions minimization. The added values of the proposed decision support tools have been shown through computational analyses on several instances. The computational analyses show that incorporating vehicle speed stochasticity into decision support models has potential to improve the performance of resulting routes in terms of travel duration, emissions and travel cost. In addition, the proposed heuristic provides promising results within relatively short computation times.     

A comprehensive dwelling unit choice model accommodating psychological constructs within a search strategy for consideration set formation

This study adopts a dwelling unit level of analysis and considers a probabilistic choice set generation approach for residential choice modeling. In doing so, we accommodate the fact that housing choices involve both characteristics of the dwelling unit and its location, while also mimicking the search process that underlies housing decisions. In particular, we model a complete range of dwelling unit choices that include tenure type (rent or own), housing type (single family detached, single family attached, or apartment complex), number of bedrooms, number of bathrooms, number of storeys (one or multiple), square footage of the house, lot size, housing costs, density of residential neighborhood, and commute distance. Bhat’s (2015) generalized heterogeneous data model (GHDM) system is used to accommodate the different types of dependent outcomes associated with housing choices, while capturing jointness caused by unobserved factors. The proposed analytic framework is applied to study housing choices using data derived from the 2009 American Housing Survey (AHS), sponsored by the Department of Housing and Urban Development (HUD) and conducted by the U.S. Census Bureau. The results confirm the jointness in housing choices, and indicate the superiority of a choice set formation model relative to a model that assumes the availability of all dwelling unit alternatives in the choice set.