5种药用植物挥发油对仓库害虫生物活性的研究

研究了香薷、鹤虱等５种药用植物挥发油对仓虫的生物活性作用。结果表明,香薷挥发油的作用最为明显,它（剂量０２μＬ／ｇ）及其粗分离１＃～５＃样品（剂量００５μＬ／ｇ）均有效地抑制了试虫卵、幼虫及成虫的生长发育,从而减少了试虫Ｆ１代种群的发生,其中粗分离１＃样品作用尤为突出。香薷挥发油１＃～５＃样品的主要化学成分为４,５,６,７,８,８ａ－六氢－８ａ－甲基－２［１Ｈ］－奥酮（５２６４％）、百里香酚（３０５％）和一未定成分（２１９２％）。     

复合型导电高分子材料研究进展

简述了复合型导电高分子材料的研究及发展,并对其导电机理、基体树脂、导电填料的研究概况进行了述评,介绍了其在各领域中的应用．     

Chromium-doped forsterite: the influence of crystal characteristics on laser performance

A study of the dependence of the gain-switched laser operation of chromium forsterite on crystal parameters is presented. Results are reported for a wide range of chromium (IV) ion concentration: 0.02-0.12 at. % and 12-41 figure of merit, with emphasis on performance of the recently developed material with a dopant level of >0.10 at. %. Threshold and slope efficiency calculations are compared with measured performance for all crystals, with variation of pump polarization and output coupling. With 3% output coupling, the lowest threshold of 1.8 mJ, and highest slope efficiency of 13% were measured for a short, high-dopant-level crystal. With 33% output coupling a slope efficiency of 44% was measured for this crystal. Results demonstrate the considerable potential of short, high-dopant-level crystals for applications such as amplification, diode pumping, and narrow-bandwidth operation.     

Experimental study on fitness of one-piece casting osseointegrated implant frameworks with relation to fixture abutment positions

An experiment on fitness of one-piece casting osseointegrated implant frameworks was performed among three fixture abument positions where other conditions were controlled. The result revealed that there was statistically significant differences in dimensional change among the three fixture abument positions. In terms of the relation between abument position and fitness, the more backward the abument position was, the worse the osseointegrated framework fitness was. The frameworks showed deformations in "arch form" and "warp" in three dimensions.     

Magento Block设计分析

Magento中的Block是一个很重要的组件.它在Magento中充当非常重要的角色.本文主要讨论Magento中Block的设计.     

CHV190系列变频器在永磁同步电机驱动矿井提升机中的应用

本文分析了矿井提升机的运行特点,详细阐述了英威腾CHV190系列起重提升专用变频器用于永磁同步电动机驱动的节能型矿井提升机的选型配置原则,最后介绍了应用现场的调试步骤及注意事项。     

Globally Exponential Stability for Delayed Neural Networks Under Impulsive Control

In this paper, the dynamic behaviors of a class of neural networks with time-varying delays are investigated. Some less weak sufficient conditions based on p-norm and ∞-norm are obtained to guarantee the existence, uniqueness of the equilibrium point for the addressed neural networks without impulsive control by applying homeomorphism theory. And then, by utilizing inequality technique, Lyapunov functional method and the analysis method, some new and useful criteria of the globally exponential stability with respect to the equilibrium point under impulsive control we assumed are derived based on p-norm and ∞-norm, respectively. Finally, an example with simulation is given to show the effectiveness of the obtained results.     

Modeling contaminant intrusion in water distribution networks: A new similarity-based DST method

Contaminant intrusion in a water distribution network is a complex but a commonly observed phenomenon, which depends on three elements – a pathway, a driving force and a contamination source. However, the data on these elements are generally incomplete, non-specific and uncertain. In an earlier work, Sadiq, Kleiner, and Rajani (2006) have successfully applied traditional Dempster–Shafer theory (DST) to estimate the “risk” of contaminant intrusion in a water distribution network based on limited uncertain information. However, the method used for generating basic probability assignment (BPA) was not very flexible, and did not handle and process uncertain information effectively. In this paper, a more pragmatic method is proposed that utilizes “soft” computing flexibility to generate BPAs from uncertain information. This paper compares these two methods through numerical examples, and demonstrates the efficiency and effectiveness of modified method.     

A hybrid data-fusion system using modal data and probabilistic neural network for damage detection

This paper addresses a novel hybrid data-fusion system for damage detection by integrating the data fusion technique, probabilistic neural network (PNN) models and measured modal data. The hybrid system proposed consists of three models, i.e. a feature-level fusion model, a decision-level fusion model and a single PNN classifier model without data fusion. Underlying this system is the idea that we can choose any of these models for damage detection under different circumstances, i.e. the feature-level model is preferable to other models when enormous data are made available through multi-sensors, whereas the confidence level for each of multi-sensors must be determined (as a prerequisite) before the adoption of the decision-level model, and lastly, the single model is applicable only when data collected is somehow limited as in the cases when few sensors have been installed or are known to be functioning properly. The hybrid system is suitable for damage detection and identification of a complex structure, especially when a huge volume of measured data, often with uncertainties, are involved, such as the data available from a large-scale structural health monitoring system. The numerical simulations conducted by applying the proposed system to detect both single- and multi-damage patterns of a 7-storey steel frame show that the hybrid data-fusion system cannot only reliably identify damage with different noise levels, but also have excellent anti-noise capability and robustness.     

A belief-rule-based inventory control method under nonstationary and uncertain demand

This paper is devoted to investigating inventory control problems under nonstationary and uncertain demand. A belief-rule-based inventory control (BRB-IC) method is developed, which can be applied in situations where demand and demand-forecast-error (DFE) do not follow certain stochastic distribution and forecasting demand is given in single-point or interval styles. The method can assist decision-making through a belief-rule structure that can be constructed, initialized and adjusted using both manager’s knowledge and operational data. An extended optimal base stock (EOBS) policy is proved for initializing the belief-rule-base (BRB), and a BRB-IC inference approach with interval inputs is proposed. A numerical example and a case study are examined to demonstrate potential applications of the BRB-IC method. These studies show that the belief-rule-based expert system is flexible and valid for inventory control. The case study also shows that the BRB-IC method can compensate DFE by training BRB using historical demand data for generating reliable ordering policy.