Comparison study of exchange-correlation functionals on prediction of ground states and structural properties

Despite significant advances in first-principles calculation methods, there is no single exchange-correlation functional which predicts the ground state of materials without an error yet. We investigated how accurately ground states of binary semiconductors are described using 16 exchange-correlation functionals (with or without van der Waals corrections). LDA, PBEsol, SCAN (with or without rVV10 correction), and PBE with D3 van der Waals correction (zero or Becke-Johnson damping) show good predicting power. The lattice constants of stable phases were slightly better described by SCAN, PBEsol, PBE+D3 (Becke-Johnson damping), and MS2. We also propose a set of functionals to double-check the stability of new materials based on the majority vote.     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.     

Identifying aspirin polymorphs from combined DFT-based crystal structure prediction and solid-state NMR

A combined experimental and computational approach was used to distinguish between different polymorphs of the pharmaceutical drug aspirin. This method involves the use of ab initio random structure searching (AIRSS), a density functional theory (DFT)-based crystal structure prediction method for the high-accuracy prediction of polymorphic structures, with DFT calculations of nuclear magnetic resonance (NMR) parameters and solid-state NMR experiments at natural abundance. AIRSS was used to predict the crystal structures of form-I and form-II of aspirin. The root-mean-square deviation between experimental and calculated ¹H chemical shifts was used to identify form-I as the polymorph present in the experimental sample, the selection being successful despite the large similarities between the molecular environments in the crystals of the two polymorphs.     

A new rule of vibration sampling for predicting acoustical radiation from rectangular plates

Structural surface velocity distribution is often used to predict structural borne sound radiation. However the sampling interval of velocity should be chosen carefully to increase the prediction accuracy and to reduce the system cost. In this paper, several factors affecting the sampling interval are theoretically analyzed and discussed for a vibrating baffled rectangular plate. A new rule for the determination of the sampling interval is formulated. Using this rule, the results from both numerical simulations and experiments may be explained well.     

Predictability and model selection in the context of ARCH models

Most of the methods used in the ARCH literature for selecting the appropriate model are based on evaluating the ability of the models to describe the data. An alternative model selection approach is examined based on the evaluation of the predictability of the models in terms of standardized prediction errors. Copyright © 2005 John Wiley & Sons, Ltd.     

Some Aspects of the Implementation of Scaling Quantum Mechanical Molecular Force Fields

Some features of software implementation of the Pulay scaling procedure are considered. The advantages of the single value decomposition method for maintaining well-conditionality of the scale factor determination problem are demonstrated. The necessity of using a rational number of scale factors is shown. The possibility of obtaining transferable scale factors with the Pulay method and thus predict the vibrational spectra of related compounds is emphasized.     

现代优化计算方法在蛋白质结构预测中的应用

现代优化计算方法在蛋白质结构预测中占有重要地位.简要地介绍了模拟退火算法,遗传算法,人工神经网络和图论算法在蛋白质结构预测中的应用.对国内外近年来应用这些算法,特别是在蛋白质构象搜索问题中,解决蛋白质结构预测的研究作了回顾,并分析、比较了这几种算法的效果和特点.     

Non-Parametric Regression Methods

The nature of the financial time series is complex, continuous interchange of stochastic and deterministic regimes. Therefore, it is difficult to forecast with parametric techniques. Instead of parametric models, we propose three techniques and compare with each other. Neural networks and support vector regression (SVR) are two universally approximators. They are data-driven non parametric models. ARCH/GARCH models are also investigated. Our assumption is that the future value of Istanbul Stock Exchange 100 index daily return depends on the financial indicators although there is no known parametric model to explain this relationship. This relationship comes from the technical analysis. Comparison shows that the multi layer perceptron networks overperform the SVR and time series model (GARCH).     

基于改进的语音参数提取的线性预测

根据语音发生基本原理和线性预测编码原理，针对自相关法需要加窗从而降低了解的精度，而协方差法不能保证保证解所重构出系统的稳定性的特点，提出了一种改进的Cholesky分解的方法求解协方差方程组以产生声道模型参数的方法，实践证明，这种方法既保证了系统的稳定性，又提高了解的精度。     

Theoretical analysis of the onset of liquid entrainment for slots of finite width

The onset of liquid entrainment during discharge from large reservoirs containing a stratified mixture of two immiscible fluids through a side slot of a finite width is considered theoretically. A previously reported analysis in which the slot was approximated as a two-dimensional line sink has been extended to account for the finite width of the slot. The model resulting from the present analysis is expressed in terms of two simple algebraic equations suitable for hand calculations. According to the present results, the ratio of the critical height to the slot width is dependent only on the Froude number. Numerical results show that the present model approaches the correct physical limits at low Froude numbers and it converges to the predictions of the previously reported simple model at high Froude numbers.