Ghrelin对大鼠小肠转运的作用及对中枢和胃肠道c-Fos表达的影响

目的观察静脉注射ghrelin对大鼠小肠转运的作用及对中枢和胃肠道c-Fos表达的影响。方法大鼠禁食24h,静脉注射ghrelin(2、5、10、20μg/kg),经预先埋置在十二指肠内的导管注入伊文氏蓝溶液,观察不同剂量ghrelin对大鼠小肠转运的影响及ghrelin受体拮抗剂(D-Lys3)GHRP-6对其作用的影响。采用免疫组织化学和图像分析方法观察静脉给予ghrelin对大鼠中枢和胃肠道的c-Fos蛋白的激活情况;观察(D-Lys3)GHRP-6对ghrelin作用的影响。结果 1静脉给予ghrelin 2μg/kg对大鼠小肠转运无显著影响,给予ghrelin 5、10、20μg/kg可剂量依赖性促进小肠转运,此作用可被(D-Lys3)GHRP-6阻断。2静脉注射ghrelin可激活中枢多个部位的c-Fos表达,包括下丘脑室旁核、弓状核、杏仁内侧核、迷走神经背核、孤束核、延髓最后区和胸腰段脊髓背角c-Fos均有表达;胃、十二指肠、空肠和近端结肠肠神经丛的c-Fos有不同程度的表达,其中以胃和近端结肠的c-Fos表达最为显著。应用ghrelin受体拮抗剂(D-Lys3)GHRP-6可抑制ghrelin激活的c-Fos表达。结论 Ghrelin可促进小肠转运,其促动力作用由其受体GHS-R所介导;静脉给予ghrelin可通过肠神经系统和中枢神经系统调节小肠运动。     

A hybrid optimization-simulation approach for robust weekly aircraft routing and retiming

We address the robust weekly aircraft routing and retiming problem, which requires determining weekly schedules for a heterogeneous fleet that maximizes the aircraft on-time performance, minimizes the total delay, and minimizes the number of delayed passengers. The fleet is required to serve a set of flights having known departure time windows while satisfying maintenance constraints. All flights are subject to random delays that may propagate through the network. We propose to solve this problem using a hybrid optimization-simulation approach based on a novel mixed-integer nonlinear programming model for the robust weekly aircraft maintenance routing problem. For this model, we provide an equivalent mixed-integer linear programming formulation that can be solved using a commercial solver. Furthermore, we describe a Monte-Carlo-based procedure for sequentially adjusting the flight departure times. We perform an extensive computational study using instances obtained from a major international airline, having up to 3387 flights and 164 aircraft, which demonstrates the efficacy of the proposed approach. Using the simulation software SimAir to assess the robustness of the solutions produced by our approach in comparison with that for the original solutions implemented by the airline, we found that on-time performance was improved by 9.8–16.0%, cumulative delay was reduced by 25.4–33.1%, and the number of delayed passengers was reduced by 8.2–51.6%.     

Boundedly rational user equilibria (BRUE): Mathematical formulation and solution sets

Boundedly rational user equilibria (BRUE) represent traffic flow distribution patterns where travellers can take any route whose travel cost is within an ‘indifference band’ of the shortest path cost. Those traffic flow patterns satisfying the above condition constitute a set, named the BRUE solution set. It is important to obtain all the BRUE flow patterns, because it can help predict the variation of the link flow pattern in a traffic network under the boundedly rational behavior assumption. However, the methodology of constructing the BRUE set has been lacking in the established literature. This paper fills the gap by constructing the BRUE solution set on traffic networks with fixed demands. After defining ε-BRUE, where ε is the indifference band for the perceived travel cost, we formulate the ε-BRUE problem as a nonlinear complementarity problem (NCP), so that a BRUE solution can be obtained by solving a BRUE–NCP formulation. To obtain the BRUE solution set encompassing all BRUE flow patterns, we propose a methodology of generating acceptable path set which may be utilized under the boundedly rational behavior assumption. We show that with the increase of the indifference band, the acceptable path set that contains boundedly rational equilibrium flows will be augmented, and the critical values of indifference band to augment these path sets can be identified by solving a family of mathematical programs with equilibrium constraints (MPEC) sequentially. The BRUE solution set can then be obtained by assigning all traffic demands to the acceptable path set. Various numerical examples are given to illustrate our findings.     

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership estimates that account for day-to-day demand variations in the near future (e.g., next week, next month). It is one of the most critical tasks in high-speed passenger rail planning, operational decision-making and dynamic operation adjustment. An accurate short-term HSR demand prediction provides a basis for effective rail revenue management. In this paper, a hybrid short-term demand forecasting approach is developed by combining the ensemble empirical mode decomposition (EEMD) and grey support vector machine (GSVM) models. There are three steps in this hybrid forecasting approach: (i) decompose short-term passenger flow data with noises into a number of intrinsic mode functions (IMFs) and a trend term; (ii) predict each IMF using GSVM calibrated by the particle swarm optimization (PSO); (iii) reconstruct the refined IMF components to produce the final predicted daily HSR passenger flow, where the PSO is also applied to achieve the optimal refactoring combination. This innovative hybrid approach is demonstrated with three typical origin–destination pairs along the Wuhan-Guangzhou HSR in China. Mean absolute percentage errors of the EEMD-GSVM predictions using testing sets are 6.7%, 5.1% and 6.5%, respectively, which are much lower than those of two existing forecasting approaches (support vector machine and autoregressive integrated moving average). Application results indicate that the proposed hybrid forecasting approach performs well in terms of prediction accuracy and is especially suitable for short-term HSR passenger flow forecasting.     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.     

Development and evaluation of a statistically reliable traffic counting program

This paper reviews the existing procedures to compute the seasonal factors, growth factors, and the number of automatic traffic recorder stations (ATRs) for developing a statistically reliable traffic counting program. The review is based on, (i) theoretical evaluation of the procedures, (ii) analysis of the results obtained from applying these procedures to extensive real life data, and (iii) experience of past researchers with these methods. The paper primarily deals with existing statistical procedures for determining seasonal factors, since it is believed that these factors play the most important role in estimating Annual Average Daily Traffic (AADTs) from short counts. The procedure of cluster analysis (which is most commonly used to determine seasonal factors) is critically reviewed. The shortcomings of this method motivated the development of a different statistical procedure, based on regression analysis, to determine seasonal factors. It is shown that this newly developed method gives better results than the cluster analysis techniques. Furthermore, separate sections are dedicated to a thorough analysis of determination of number of ATR stations and computation of growth factors.     

碗扣满堂支架法在盖梁施工中的应用

跨铁路公路立交桥高墩盖梁模板支撑体系的稳固与否直接关系到铁路运营安全,碗扣式脚手架作为高墩盖梁模板支撑体系以其拆卸迅速简便、承载能力大、安全可靠等特点得到了广泛的认可,而脚手架立杆的稳定性是脚手架支撑体系稳定的关键。以某跨铁路的公路桥高墩盖梁模板支撑体系为例,对碗扣式支撑体系的稳定性进行了分析验算,确定了盖梁模板支护方案并应用于漾泉大道跨白荫支线改线立交桥工程,应用效果良好。     

高桥墩桩基础的优化设计及因素分析

在高桥墩桩基屈曲能量法分析的基础上,提出兼顾结构稳定、强度和经济性的优化模型,并应用优化算法中非线性序列二次规划法,进行优化设计探讨,同时给出优化设计算法流程图,编制了相应的优化计算程序;为了解桥墩高度、轴向荷载、地基比例系数和混凝土弹性模量对于高桥墩桩基屈曲的影响,结合优化设计模型进行了因素分析,探讨了参数变量对目标函数最优值的影响规律和程度,比较结果说明,在进行高桥墩桩基的屈曲受力分析时,高桥墩的大变形影响不容忽视;而一般在工程设计中,可考虑将桩周土体和混凝土弹性模量的增强作用作为设计的安全储备。     

高强度混凝土配合比设计方法

简要介绍高强度混凝土配合比设计方法以及对材料的要求。     

GTM法在公路沥青路面施工中的应用研究

结合GTM法技术在河北省张石高速公路中的实践应用,介绍GTM法的设计原理、施工工艺和质量控制体系,尤其是对施工过程质量控制点和沥青路面最大密实度标准的研究分析,有效地降低了工程施工费用,提高了路面的服务寿命。