Effects of chemical ecological adjustment and control experiment on phytoplankton community in the Aoshan Bay

There is a low nutrient level in the Aoshan Bay. In June 1999, the chemical adjustmentand control experiment was made in the Aoshan Bay. Following tracts investigation was carried out before the experiment and on the 1st, 2nd, 4th, 5th, 6th and 45th day/after the experiment. While the variance of amount of phytoplankton, the replacement of superior species and the species composition of phytoplankton were researched. The results show that the amount of phytoplankton in the Aoshan Bay rises gradually after the experiment. Ceratium macroceros Cleve of pyrophyta was the dominant species before the experiment, its dominant index was 37.7％. Six days after the experiment, its dominant index dropped to 17.6％ . Meanwhile the dominant index of Asterionella japanics Cleve rose from 7.1％ to 39.2％ , it became the first dominant species. Forty-five days after the experiment, the amount of phytoplankton in the Aoshan Bay was 5.15 to 137.32 times more than that in 1997.     

东山湾贝类养殖容量的估算

以初级生产力为基础，应用营养动态模式和沿岸海域能流分析模型，估算东山湾贝类年生产量分别为269331t和295767t，平均282549t。扣除潮间带、潮下带和吊养区浮筏、随着基及延绳上附着的非养殖滤食性附着动物自然现存量35760t，贝类可养殖量为246789t。应用统计分析和逻辑斯谛种群增长模型估计贝类可养面积为11839hm^2，其中缢蛏635hm^2，石蛎1160hm^2,吊蛎1525hm^2，翡翠贻贝633hm^2，菲律宾蛤仔1154hm^2，扇贝698hm^2，江瑶248hm^2，泥蚶601hm^2，巴非蛤4151hm^2，凸壳肌蛤1034hm^2。1998年实际养殖面积和养殖产量分别为10581hm^2和220564t。尚有1258hm^2,26225t的扩大开发潜力。文中还讨论了合理布局和优化养殖结构问题。     

LabVIEW设计中压力传感器的RBF神经网络温度补偿

在石油平台注水压力监测系统设计中 ,采用LabVIEW虚拟仪器平台 ,嵌入逼近能力强和收敛速度快的RBF神经网络 ,以人工环境实验数据为样本进行训练 ,实现了压力传感器的智能网络温度补偿。结果显示 ,此方法能够在压力、温度变化较大的恶劣环境下 ,获得很高的补偿精度。     

东营城区高精度三维地震采集方法研究

根据东营城区内建筑物较多，环境干扰较大，地下构造复杂，断裂非常发育，目的层埋藏深，资料信噪比较低的特点，以地震老资料和钻井资料为基础，建立地震地质模型，利用射线追踪技术选取合适的观测系统参数。充分利用卫星数字地图，没计了灵活多变的观测系统，采用可控震源与炸药震源配合使用方法，及时对城区内地下面元的覆盖次数、方位角和炮检距的分布进行质量监控，利用现场处理系统对资料进行及时分析，提高了地震资料品质。所获得的东营城区高精度三维地震采集资料显示，其浅中层分辨率和中深层信噪比都有了明显改善，取得了良好的地质效果。     

Optimization Mathematical Model of Pile Forces for Offshore Piled Breasting Dolphins

An optimization mathematical model of the pile forces for piled breasting dolphins in the open sea under various loading conditions is presented. The optimum layout with the well distributed pile forces and the least number of piles is achieved by the multiplier penalty function method. Several engineering cases have been calculated and compared with the result of the conventional design method. It is shown that the number of piles can be reduced at least by 10%—20% and the piles‘ bearing state is improved greatly.     

基于网络药理学探究补阳还五汤治疗颈椎病的作用机制

目的：基于网络药理学与分子对接技术分析补阳还五汤治疗颈椎病的作用机制。方法：使用TCMSP、化学专业数据库获取补阳还五汤的活性成分,并对潜在靶点进行预测及规范。分别从PharmGKB、DisGeNET、OMIM、GeneCards数据库中得到颈椎病疾病靶点,利用韦恩图获取补阳还五汤与颈椎病的交集靶点。通过CytoScape软件构建中药-活性成分-疾病靶点和蛋白质-蛋白质相互作用（PPI）网络,获得核心有效成分与关键靶点,利用David数据库对潜在靶点进行富集分析。最后运用AutoDock Vina软件对补阳还五汤核心有效成分与关键靶点进行分子对接验证。结果：共获得补阳还五汤治疗颈椎病的有效活性成分97个,包括槲皮素、山柰酚、黄芩素、木犀草素等;交集靶点64个,关键靶点有白细胞介素-6（IL-6）、肿瘤坏死因子（TNF）、丝氨酸/苏氨酸蛋白激酶1（AKT1）、白细胞介素-1B（IL-1B）等;主要涉及肿瘤坏死因子（TNF）、白细胞介素-17（IL-17）、磷脂酰肌醇3-激酶（PI3K）/蛋白激酶B（Akt）等信号通路,分子对接结果显示核心有效成分与关键靶点之间结合紧密,为补阳还五汤治疗颈椎病提供相应条件。结论：该研究在总体上预测了补阳还五汤治疗颈椎病的活性成分、靶点和信号通路,作用途径广泛,为下一步的临床应用提供参考及思路。     

水下智能潜器的神经网络运动控制

本文介绍一种基于神经网络的水下智能潜器的运动控制方法，该方法通过在线学习，融控制与滤波为一体。计算机仿真与水池实验验证表明，该方法的控制与滤波性能良好，对环境的学习与适应能力强。该方法事实上可用于一般动力系统的控制。     

人工神经网络在地质学判别分析中的应用

将现代人工神经网络方法应用于地质学的判别分析，通过实例计算表明，无论是对于两组判别分析还是多组判别分析，人工神经网络方法都是切实可行的。     

A Linear Programming Model for Seabed Oil-Gas Pipe Network

This paper analyzes the pipe network system of oil-gas collection and transportation foroffshore oilfield development.A"0-1"integer linear programming model is constructed to optimize theinvestment of seabed pipe network.The mathematical model is solved by the spanning tree method ofgraph theory and network analysis.All spanning trees of a network graph compose all the feasible solu-tions of the mathematical model.The optimal solution of the model is the spanning tree with the minimumcost among all spanning trees.This method can be used to optimize the seabed pipe network system andgive a minimum cost plan for the development of offshore marginal oilfield groups.