金纳多对抗大鼠脑出血后脑水肿的作用机制

目的探讨金纳多对抗脑出血后脑水肿形成的作用机制。方法选健康Wistar大鼠80只,雌雄不拘,随机分为4组,每组20只。采用立体定向注射方法,用微量注射器在右侧尾状核部位,注入50μL生理盐水(A、B组)或等量自体血红蛋白(C、D组)。术后A、C组给予50 g/L羧甲基纤维素钠溶液3 mL灌胃,B、D组给予等量羧甲基纤维素钠溶解均匀的金纳多(200 mg/kg)溶液灌胃,每日1次,持续3周。断头取脑,测定超氧化物歧化酶(SOD)、丙二醛(MDA)值及血红素氧合酶-1(HO-1)阳性细胞数。结果除A、B组比较无明显差异外,其余各组间SOD、MDA含量及HO-1阳性细胞数比较差异均有统计学意义(P<0.05)。结论金纳多可以抑制血红蛋白所引起的脑水肿。     

智能化航标系统的设计

由于海运业的不断繁荣发展，安全通航尤为重要，这使得航标设备的自动化改造迫在眉睫，计算机的普及、无线通讯风的全球覆盖、蓝牙技术的出现为航标设备的自动化改造创造了条件，使之成为可能。航标设备遥测遥控功能的实现将大大提高航标设备的可利用率，降低维护成本，提高管理效率，具有现实意义。     

基于J2ME的手机移动电子邮件系统的研究

随着移动通信数据业务的发展，移动手机和智能化移动终端的实现和普及，移动邮件系统随之产生。目前常用的移动邮件业务需通过WAP网关访问Internet，进行在线交流时会增加服务器负荷，这导致无线Internet的应用受到很大限制。利用J2ME设计了一个新的移动邮件系统以解决上述问题，该系统利用设计的中间层服务器连接Web Mail的SMTP／IMAP／POP3服务器，执行中间业务逻辑的处理，最终实现移动邮件的所有操作。     

校园网中P2P流量的识别及其控制

结合P2P网络应用中出现的问题,分析了P2P对校园网网络流量的影响,提出了如何在校园网中识别和控制P2P,为校园网解决P2P问题提供了相应的方法。     

饮用水消毒剂的特点及杀菌技术的研究

阐述了几种消毒方式的特性及其应用前景,通过对比臭氧,ClO2,微波,KMnO4及紫外线的消毒效果,确定了取代液氯消毒饮水的最佳方案.影响消毒剂效果的主要因素有温度、pH值及作用时间.消毒剂浓度与作用时间的关系可用ct(mg*min/L)值来表示,代表消毒剂的杀菌能力,对大肠杆菌,当pH为6～7时,臭氧、ClO2、氯的ct值分别为0.02,0.40～0.75,0.034～0.050.升高温度会加强消毒剂的灭菌效果,要保持原来的消毒效果就需要延长作用时间或增大消毒剂的剂量.     

β淀粉样肽1～42单克隆抗体的制备

目的　制备稳定分泌β -淀粉样肽 1～ 4 2 (Aβ1-42 )单克隆抗体的杂交瘤细胞 ,产生高效价抗体。方法　通过基因工程技术 ,将Aβ1-42 基因融合于乙肝核心抗原 (HBcAg)的主要免疫优势区 (MIR) ,制备Aβ和HBcAg的融合蛋白 ,免疫BALB/c小鼠 ,取脾细胞与SP2 / 0细胞融合 ,筛选能稳定分泌Aβ1-42 单克隆抗体的杂交瘤细胞。结果　得到两株能稳定分泌Aβ1-42 单克隆抗体的杂交瘤细胞 ,Aβ1-42 单克隆抗体的Ig亚类为IgG3 。结论　制备得到的Aβ1-42 单克隆抗体特异性强 ,效价高     

EXPRESSION OF MATRIX METALLOPROTEINASE-2 AND VASCULAR ENDOTHELIAL GROWTH FACTOR IN HUMAN GLIOMA AND THEIR RELATION TO THE INVASION OF THE TUMOR

Neovascularizationcanbeobservedinthe courseoftumorformationandmalignantinvasion,whichwillpromotethemalignantinvasionofthe tumor[1].Vascularendothelialgrowthfactor(VEGF)andmatrixmetalloproteinases(MMPs)are theimportantadjustiveproteinsintheinvasionand neov…     

葛根素对血管性痴呆大鼠海马中低氧诱导因子-1α和红细胞生成素表达的影响

目的观察葛根素对血管性痴呆(VD)大鼠海马中低氧诱导因子-1α和红细胞生成素表达的影响并探讨其可能机制。方法采用大鼠双侧颈总动脉永久性阻断法(2-VO)建立VD的动物模型,SD大鼠随机分为假手术组、2-VO组和葛根素组,每组又分为1周、3周、6周、2月(n=6)四个时间点;应用Y型水迷宫实验测定动物的学习记忆能力,采用免疫组化法检测大鼠海马CA1区HIF-1α和EPO蛋白的表达。结果①2-VO组和葛根素组大鼠游全程时间和误入盲端次数均显著增加,但各时间点葛根素组大鼠的学习记忆成绩均显著优于2-VO组。②各时间点,2-VO组和葛根素组大鼠海马CA1区HIF-1α和EPO的表达均较假手术组明显增高,但葛根素组两种蛋白的表达均较2-VO组明显降低。结论葛根素可提高缺血脑组织细胞内氧浓度,改善学习记忆功能,对VD具有确切的保护作用。     

Short/medium-term prediction for the aviation emissions in the en route airspace considering the fluctuation in air traffic demand

This paper proposes a novel short/medium-term prediction method for aviation emissions distribution in en route airspace. An en route traffic demand model characterizing both the dynamics and the fluctuation of the actual traffic demand is developed, based on which the variation and the uncertainty of the short/medium-term traffic growth are predicted. Building on the demand forecast the Boeing Fuel Flow Method 2 is applied to estimate the fuel consumption and the resulting aviation emissions in the en route airspace. Based on the traffic demand prediction and the en route emissions estimation, an aviation emissions prediction model is built, which can be used to forecast the generation of en route emissions with uncertainty limits. The developed method is applied to a real data set from Hefei Area Control Center for the en route emission prediction in the next 5 years, with time granularities of both months and years. To validate the uncertainty limits associated with the emission prediction, this paper also presents the prediction results based on future traffic demand derived from the regression model widely adopted by FAA and Eurocontrol. The analysis of the case study shows that the proposed method can characterize well the dynamics and the fluctuation of the en route emissions, thereby providing satisfactory prediction results with appropriate uncertainty limits. The prediction results show a gradual growth at an average annual rate of 7.74%, and the monthly prediction results reveal distinct fluctuation patterns in the growth.     

Assessing the Potential Impacts of Connected Vehicles: Mobility,Environmental, and Safety Perspectives

The connected vehicle is a rapidly emerging paradigm aimed at deploying and developing a fully connected transportation system that enables data exchange among vehicles, infrastructure, and mobile devices to improve mobility, enhance safety, and reduce the adverse environmental impacts of the transportation systems. This study focuses on micromodeling and quantitatively assessing the potential impacts of the connected vehicle (CV) on mobility, safety, and the environment. To assess the benefits of CVs, a modeling framework is developed based on traffic microsimulation for a real network located in the city of Toronto, Canada, to mimic communication between enabled vehicles. In this study, we examine the effects of providing real-time routing guidance and advisory warning messages to CVs. In addition, to take into account the rerouting in nonconnected vehicles (non-CVs) in response to varying sources of information such as apps, global positioning systems (GPS), variable message signs (VMS), or simply seeing the traffic back up, the impact of fraction of non-CV vehicles was also considered and evaluated. Therefore, vehicles in this model are divided into; uninformed/unfamiliar not connected (non-CV), informed/familiar but not connected (non-CV) that get updates infrequently every 5 minutes or so (non-CV), and connected vehicles that receive information more frequently (CV). The results demonstrate the potential of connected vehicles to improve mobility, enhance safety, and reduce greenhouse gas emissions (GHGs) at the network-wide level. The results also show quantitatively how the market penetration of connected vehicles proportionally affects the performance of the traffic network. While the presented results are pertinent to the specifics of the road network modeled and cannot be generalized, the quantitative figures provide researchers and practitioners with ideas of what to expect from vehicle connectivity concerning mobility, safety, and environmental improvements.