Protein secondary structure and stability determined by combining exoproteolysis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

In the post-genomic era, several projects focused on the massive experimental resolution of the three-dimensional structures of all the proteins of different organisms have been initiated. Simultaneously, significant progress has been made in the ab initio prediction of protein three-dimensional structure. One of the keys to the success of such a prediction is the use of local information (i.e. secondary structure). Here we describe a new limited proteolysis methodology, based on the use of unspecific exoproteases coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), to map quickly secondary structure elements of a protein from both ends, the N- and C-termini. We show that the proteolytic patterns (mass spectra series) obtained can be interpreted in the light of the conformation and local stability of the analyzed proteins, a direct correlation being observed between the predicted and the experimentally derived protein secondary structure. Further, this methodology can be easily applied to check rapidly the folding state of a protein and characterize mutational effects on protein conformation and stability. Moreover, given global stability information, this methodology allows one to locate the protein regions of increased or decreased conformational stability. All of this can be done with a small fraction of the amount of protein required by most of the other methods for conformational analysis. Thus limited exoproteolysis, together with MALDI-TOF MS, can be a useful tool to achieve quickly the elucidation of protein structure and stability.     

Benzodiazepine analogues. Part 21. 13C NMR analysis of benzoxathiepine derivatives

The influence of substituents and structure on the 13C NMR spectra of four series of benzoxathiepine derivatives has been investigated. Signal assignments in the 13C NMR spectra have been facilitated by the use of several predictive methods, permitting comparison of their relative efficacy.     

基于储量结构变化的油田开发指标预测与优化数学模型研究

大型油田开发过程中,随着不同类型新储量的不断投入,地质储量结构发生变化,表征油田整体开发技术与经济效果的关键性指标,如产量、可采储量、采收率、储采比、开发成本与操作成本等等也随之改变,其变化规律可用一套数学模型来描述。在开发指标预测基础上,运用多属性决策方法如TOPSIS,可以实现新投产区块组合方案的优选。应用实例表明,本文方法实用、操作性强,可以为油区开发决策提供重要方法与手段。     

一般工商业零售电价套餐适应性评估与优化方法

在电力体制改革的大背景下,合理评估零售电价套餐适应性,对控制电网经营风险和推进售电侧改革有重要意义。针对我国电力市场以及一般工商业的特点,首先从竞争、用户以及市场环境角度出发建立了一般工商业零售电价套餐评估指标体系;其次将层次分析法和改进的灰色白化权函数相结合,对电价套餐进行适应性评估;最后针对该评估方法建立了基于蚁群算法的优化模型,以最小成本得到提高电价套餐适应性等级的优化方案,并验证了该方法具有良好的鲁棒性,具有一定的参考意义。     

价格与质量双重竞争下电商平台渠道模式决策研究

近年来传统电商正加速从经销商转变为连接消费者与供应商的在线市场中间商, 电商平台与供应商形成三种渠道结构:经销商模式、混合模式和在线市场模式。本文通过构建Stackelberg博弈模型讨论产品质量与价格双重竞争情境下电商平台与供应商销售合作模式最新选择问题。研究表明,当价格竞争强度适中而佣金比例较大时,混合模式是电商平台最优选择,此时产品质量差异最大;当价格竞争强度较小而佣金比例较大时,在线市场模式则是最优选择;在其他条件下,经销商模式是其最优选择。本文结论对电商平台与供应商合作模式选择、产品质量与定价决策具有参考价值。     

灰色GM(1,1,k,k2)模型背景值及时间响应函数优化

本文提出了一种新的带有时间幂次项的灰色GM(1,1,k,k²)模型,给出了其灰微分方程和白化微分方程基本形式。基于最小二乘法获得了该模型参数估计值,并推导了该模型时间响应函数。鉴于GM(1,1,k,k²)模型灰微分方程与白化微分方程之间存在跳跃关系,首先对灰微分方程的背景值进行了优化,并推导了优化后的背景值计算公式。为了克服初始值的影响,根据误差平方和最小,进一步优化了GM(1,1,k,k²)模型时间响应函数。最后,该优化后的GM(1,1,k,k²)模型被应用于软土地基沉降预测,获得了较好的模拟预测效果,说明模型是可行的。     

Fastiterative methods for least squares estimations

Least squares estimations have been used extensively in many applications, e.g. system identification and signal prediction. When the stochastic process is stationary, the least squares estimators can be found by solving a Toeplitz or near-Toeplitz matrix system depending on the knowledge of the data statistics. In this paper, we employ the preconditioned conjugate gradient method with circulant preconditioners to solve such systems. Our proposed circulant preconditioners are derived from the spectral property of the given stationary process. In the case where the spectral density functions() of the process is known, we prove that ifs() is a positive continuous function, then the spectrum of the preconditioned system will be clustered around 1 and the method converges superlinearly. However, if the statistics of the process is unknown, then we prove that with probability 1, the spectrum of the preconditioned system is still clustered around 1 provided that large data samples are taken. For finite impulse response (FIR) system identification problems, our numerical results show that annth order least squares estimator can usually be obtained inO(n logn) operations whenO(n) data samples are used. Finally, we remark that our algorithm can be modified to suit the applications of recursive least squares computations with the proper use of sliding window method arising in signal processing applications.Research supported in part by HKRGC grant no. 221600070, ONR contract no. N00014-90-J-1695 and DOE grant no. DE-FG03-87ER25037.     

A generalized Dantzig—Wolfe decomposition principle for a class of nonconvex programming problems

Since Dantzig—Wolfe's pioneering contribution, the decomposition approach using a pricing mechanism has been developed for a wide class of mathematical programs. For convex programs a linear space of Lagrangean multipliers is enough to define price functions. For general mathematical programs the price functions could be defined by using a subclass of nondecreasing functions. However the space of nondecreasing functions is no longer finite dimensional. In this paper we consider a specific nonconvex optimization problem min {f(x):h _j (x)g(x),j=1, ,m, xX}, wheref(·),h _j (·) andg(·) are finite convex functions andX is a closed convex set. We generalize optimal price functions for this problem in such a way that the parameters of generalized price functions are defined in a finite dimensional space. Combining convex duality and a nonconvex duality we can develop a decomposition method to find a globally optimal solution.This paper is dedicated to Phil Wolfe on the occasion of his 65th birthday.     

Prediction of aqueous solubility of drugs and pesticides with COSMO-RS

The COSMO-RS method, originally developed for the prediction of liquid-liquid and liquid-vapor equilibrium constants based on quantum chemical calculations, has been extended to solid compounds by addition of a heuristic expression for the Gibbs free energy of fusion. By this addition, COSMO-RS is now capable of a priori prediction of aqueous solubilities of a wide range of typical neutral drug and pesticide compounds. Only three parameters in the heuristic expression have been fitted on a data set of 150 drug-like compounds. On these data an rms deviation of 0.66 log-units was achieved. Later, the model was tested on a set of 107 pesticides, which have been critically selected based on two experimental data sources and by a crosscheck with an independent HQSAR model. On this data set an rms of 0.61 log-units was achieved, without any adjustments to the structurally extremely diverse pesticides. This result verifies the ability of this extended COSMO-RS to predict aqueous solubilities of drugs and pesticides of almost arbitrary structural classes. The new method is COSMO-RSol.     

Computer interactive identification system for polycyclic aromatic hydrocarbons in reversed-phase microcolumn liquid chromatography

Summary A computer interactive identification system is proposed which is based on the relationship between retention and molecular properties such as the size and shape of polycyclic aromatic hydrocarbons (PAHs). This system offers an automatic analytical process for liquid chromatography, providing a reliable identification of the separated components. The identification can be further enhanced by the use of multiple detectors such as a multichannel UV detector. The system can be used for optimization procedures, resulting in a highly automatic complex analytical system.