Predictive modelling of the 3-D structure of interleukin-13

Several atomic structures are now available for the family ofhelical cytokines, which includes growth hormone as well asmany of the interleukins. Using structural information fromfive members of this family, two alternative models of interleukin(IL)-13 are proposed. IL-13 has biological properties similarto those of IL-4 and, like the other interleukins, is a potentiallyimportant pharmaceutical target. The model of IL-13 is discussedand compared with the known interleukin structures.     

正庚烷-甲苯-三甘醇三元体系液-液相平衡数据的测定与关联

利用气相色谱法测定了常压下２５℃、４０℃和５０℃时正庚烷－甲苯－三甘醇体系的液－液相平衡数据，采用峰面积归一化法定量，所得数据准确、可靠。用ＮＲＴＬ模型对所测数据进行了热力学关联，求出了相应的模型参数。用该模型对本三元体系进行了预测，结果令人满意。     

大庆油田深层岩石力学特性参数的试验研究

通过对岩石可钻性、硬度、抗压强度等参数的测量 ,对大庆油田深井不同深度、不同层位、不同岩性的具有广泛代表性的岩心进行试验。并通过线性回归分析 ,建立了适用性较广的钻井岩石力学特性参数预测模型 ,为深井钻头选型提供了依据。     

现场地质预测与决策技术

油气的生成、运移、分布、成藏、保存具有规律性，技术人员可以依据其规律性对地下地质情况进行推理、预测和决策。钻井过程的现场地质预测技术方法主要是外推法、因果法和直观法三大类。外推法是常用的预测方法，包含了岩性、沉积旋回、标志层、标准层、重矿物等岩石地层学对比方法和生物地层学方法及地球物理方法。现场地质预测与决策是通过确定预测目标、收集相关资料、进行对比分析、形成地质预测结果、拟定地质决策方案、方案优选、方案实施等环节来完成。该技术是现场地质监督的核心技术，在实践中取得显著成效。     

升平气田产能预测方法

依据升平气田的试井资料，建立了气井产能与压差之间的二次项产能方程。运用此方程可以预测升平气田的单井产能，并且建立了压差平方与kh值相关的气田综合产能方程。当求得气田的平均kh值后，利用该方法可以求得气田的平均产能或生产压差。     

金属矿山深热矿井空气温度的灰色预测

金属矿山深热矿井气温的预测计算是一个难题，本文探讨了应用灰色系统预测理论来解决这一难题的新途径，并通过实例验证了该方法的可行性和有效性。     

Predicting postdischarge opiate abstinence from admission measures of motivation and confidence.

Admission scores from a model comprising 3 motivation factors concerning the cessation of heroin use and a confidence scale concerning postdischarge abstinence were tested for their ability to predict postdischarge outcomes in patients beginning inpatient opiate detoxification. Statistically significant prediction of abstinence from heroin 30 days after discharge and the number of heroin-free days in the 3 months following admission was based on the confidence scale and a factor concerned with externally imposed constraints on continued heroin use. The single-scale confidence measure made the largest contribution to each prediction, indicating that such scales may be potentially useful outcome predictors for postdischarge abstinence. External constraints on heroin use may not provide a basis for success in this treatment modality. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

High temperature low cycle fatigue

Fatigue at high temperature is a complex phenomenon as it is influenced by a number of time-dependent processes which become important at elevated temperatures. These processes include creep, oxidation, phase instabilities and dynamic strain ageing (DSA), acting either independently or synergistically influence fatigue behaviour, often lowering the fatigue life. Current design approaches employ linear summation of fatigue and creep damage with suitable factors on permissible damage to take care of uncertainties in interaction between cyclic and time-dependent processes. It is, therefore, important to develop a deeper understanding of the processes that occur during high temperature fatigue so that realistic life predictions could be made. Results on the high temperature fatigue behaviour of austenitic stainless steels, ferritic steels and nickel base alloys are presented here. The important mechanisms of interaction of high temperature time-dependent processes with fatigue under various conditions are discussed in detail. Emphasis is placed on cyclic stress response, fatigue life, deformation substructure and fracture behaviour. This is followed by a review of important life prediction techniques under combined creep-fatigue loading conditions. Life prediction techniques considered here include linear damage summation, strain range partitioning, ductility exhaustion approach, frequency modified and frequency separation methods, techniques based on hysteresis energy and damage rate models, and methods based on crack-cavitation interation models.     

衰减曲线分析的诺模图

基于Arps递减方程,建立了衰减曲线分析的诺模图。应用该诺模图,可以方便地确定油气田的可采储量。     

基于改进的Elman神经网络的网络流量预测

在Elman神经网络的基础上提出了改进的网络,根据实际网络中测量的网络流量数据,建立了基于Elman神经网络的流量模型,分别用Elman神经网络和改进的Elman神经网络对实际网络流量进行预测,仿真实验结果表明,改进的Elman神经网络具有良好的预测效果,改进的Elman神经网络具有更高的预测精度和更好的动态性能.