大米镉结合蛋白的凝胶层析纯化及生化性质

目的研究大米镉结合蛋白(rice cadmum-binding protein,RCBP)的纯化及生化性质,探讨RCBP的形成机制。方法采用Sephedex G-75凝胶层析从乙醇沉淀的大米蛋白(Ethanol precipitation protein,EP)中纯化RCBP,SDS-PAGE鉴定RCBP的纯度及测定分子质量,氨基酸自动分析仪、FTIR分析RCBP的氨基酸组成及二级结构。结果凝胶层析纯化得到组分b(目标RCBP),组分b为纯度均一的RCBP,分子质量约为32 kDa。组分b中疏水性氨基酸占56.76%、芳香族氨基酸占19.41%,是一类富含疏水性氨基酸和芳香族氨基酸的镉结合蛋白。组分b中N-H相对于C=O以反式构型存在,二级结构只含有β-折叠和β-转角。结论镉通过疏水氨基酸或芳香族氨基酸的特征基团与大米蛋白结合形成RCBP。     

注水井酸化解堵用的水溶酸不溶暂堵剂CY-4

大庆油田二、三次加密井层间渗透率差异较大 ,在这类注水井进行酸化解堵时需暂时堵住高渗透层 ,将酸液导向低渗透层。研制了一种水溶而酸不溶的暂堵剂CY 4 ,其组成为 :主剂聚合物 ,有效成分 95 % ,细度 2 0 0目 ;增强剂QZ ,加量 2 4 % ;溶解速率调节剂LHN ,加量 2 %～ 3%。暂堵剂CY 4为浅黄色颗粒 ,粒径 2～ 4mm ,密度 0 .9～ 1.1g/cm3 ,抗压强度 2 0MPa ,2 4小时水溶率 >98% ,酸溶率 <1%。暂堵剂CY 4由酸液携带进入井筒 ,自然选择进入高渗透层炮眼 ,形成暂时堵塞 ,酸化后恢复注水时堵塞物可被溶去。在大庆杏树岗油田 11口加密注水井酸化时应用暂堵剂CY 4 ,使注水压力下降 ,注水量增大 ,吸水层数、厚度增加 ,低渗透目的层吸水比例由 18%上升到6 4 %。图 2表 3参 1。     

The Gel-Crystallization of 1-Phenylalanine and Aspartame from Aqueous Solutions

It was observed that 1-phenylalanine and aspartame form thermoreversible gels in aqueous solutions (which include crystals) through nonagitated crystallization. FT-IR spectra of aspartame gel-crystals indicated that the possible interactions involved in gel formation are hydrogen bonding between the carbonyl and the amine groups and electrostatic interactions between NH 3 + and COO - . For gel-crystals of 1-phenylalanine, the main interaction involved was electrostatic interaction between NH 3 + and COO - . According to the thermal analysis of aspartame and 1-phenylalanine solutions, the gel-melting temperature increased with increasing heating rate and the gel-crystallization temperature decreased with increasing cooling rate.     

一种利用无条件认证实现的强保密增强协议

要解决保密增强中的防主动攻击的问题,就必须对公共信道上的通信内容进行认证。文中提出并分析了一种新的用纠错码构造认证码的方法,这种认证码构造简单对域ＧＦ（ｑ）上的任意一个码都找到一个相应的认证码。如果通信双方共享一个ｎｂｉｔ的部分保密串Ｓ,则可以构造一种基于（２＾ｍ,ｋ,２＾ｍ－ｋ＋１）扩展ＲＳ码的认证码,其中ｍ＝〖ｎ／ｋ〗且２＾ｍ〉ｋ,只要双方间共享一个至少３ｍｂｉｔ的认证密钥,就有可能在一个不安     

基于流形距离的人工免疫无监督分类与识别算法

将一种新的流形距离作为相似性度量测度, 提出了一种用于无监督分类与识别的人工免疫系统方法. 通过基于流形距离的相似性度量, 有效利用样本集固有的全局一致性信息, 充分挖掘无类属样本的空间分布信息, 对样本进行类别划分. 新方法将免疫响应过程建模为一个四元组 AIR=(G,I,R,A) , 其中 G 为引发免疫响应的外界刺激, 即抗原; I 为所有可能抗体的集合; R 为抗体间相互作用的规则集合; A 为支配抗体反应、指导抗体进化的动态算法. 针对无监督分类问题, 将抗体编码为代表各类别的典型样本序号的排列, 利用动态算法 A 搜索能代表各类别的典型样本的最佳组合. 将新方法与标准的 K-均值算法、基于流形距离的进化聚类算法以及 Maulik 等人提出的基于遗传算法的聚类算法进行了性能比较. 对 6 个人工数据集及手写体数字识别问题的仿真实验结果显示, 新方法对样本空间分布复杂的无监督分类问题和实际的模式识别问题具有较高的准确率和较好的鲁棒性.     

Modelling Intelligent Water Resources Allocation for Multi-users

This study proposes intelligent water resources allocation strategies for multiple users through hybrid artificial intelligence techniques implemented for reservoir operation optimization and water shortage rate estimation. A two-fold scheme is developed for (1) knowledge acquisition through searching input–output patterns of optimal reservoir operation by optimization methods and (2) the inference system through mapping the current input pattern to estimate the water shortage rate by artificial neural networks (ANNs). The Shihmen Reservoir in northern Taiwan is the study case. We first design nine possible water demand conditions by investigating the changes in historical water supply. With the nine designed conditions and 44-year historical 10-day reservoir inflow data collected during the growth season (3 months) of the first paddy crop, we first conduct the optimization search of reservoir operation by using the non-dominated sorting genetic algorithm-II (NSGA-II) in consideration of agricultural and public water demands simultaneously. The simulation method is used as a comparative model to the NSGA-II. Results demonstrate that the NSGA-II can suitably search the optimal water allocation series and obtain much lower seasonal water shortage rates than those of the simulation method. Then seasonal water shortage rates in response to future water demands for both sectors are estimated by using the adaptive network fuzzy inference system (ANFIS). The back-propagation neural network (BPNN) is adopted as a comparative model to the ANFIS. During model construction, future water demands, predicted monthly inflows (or seasonal inflow) of the reservoir in the next coming quarter and historical initial reservoir storages configure the input patterns while the optimal seasonal water shortage rates obtained from the NSGA-II serve as output targets (training targets) for both neural networks. Results indicate that the ANFIS and the BPNN models produce almost equally good performance in estimating water shortage rates, yet the ANFIS model produces even better stability. The reliability of the proposed scheme is further examined by scenario analysis. The scenario analysis indicates that an increase in public water demand or a decrease in agricultural water demand would bring more impacts of water supply on agricultural sectors than public sectors. Similarly, a bigger decrease in inflow amount would obviously bring more influence on agricultural sectors than public one. Consequently, given predicted inflow, decision makers can pre-experience the possible outcomes in response to competing water demands through the estimation models in order to determine adequate water supply as well as preparedness measures, if needed, for drought mitigation.     

Exploring the Mechanism of Surface and Ground Water through Data-Driven Techniques with Sensitivity Analysis for Water Resources Management

The over extraction of groundwater in central-western and southwestern Taiwan has resulted in serious land subsidence for decades. For making countermeasures in response to land subsidence, this study collects long-term hydrological data to explore the relationships between surface water and groundwater in various monitoring stations, and then constructs one-month-ahead forecast models by using data-driven techniques for the water resources management of the Zhuoshui River basin in Taiwan. The results demonstrate that the constructed models can accurately forecast monthly groundwater levels. The sensitivity analysis is next conducted on the input variables of the constructed models by using the partial derivative method. The analysis results reveal that streamflow is a predominant factor for groundwater level variation, and therefore streamflow management made by the upstream weir of the river would influence groundwater level variations. This study further implements several scenario analyses based on the interactive mechanism between groundwater and surface water in response to future climatic conditions and weir discharge management, respectively. The results of scenario analyses indicate that the groundwater recharge zone spreads along the Zhuoshui River while lateral and vertical recharge sources would cause different quantities and distribution patterns of groundwater recharge. Besides, an increase in weir discharge would improve groundwater recharge quantities with groundwater level variations at 0.12 m and 0.06 m in wet and dry seasons, respectively. As a consequence, the operation of weir discharge would play an import role in sustainable development of water resources management in the study area.