Potential polymorphs of aspirin

Aspirin is only found experimentally in one crystal structure. In this article, the method of Karfunkel and Gdanitz is used to predict potential polymorphs of aspirin. The known structure, containing a nonplanar conformer is found, along with a number of other low energy structures, many of which are based on a planar conformer. Semiempirical and ab initio calculations show that the planar conformer is less stable than the experimentally known one. Force field calculations suggest that the planar conformer is more stable. The lattice energy of the experimentally known crystal structure is 1.4 kcal/mol lower than any of the potential crystal structures, even though there are a number of structures with lower total (lattice+intramolecular) energies. Conformational maps indicate that another stable conformation occurs within a few kilocalories per mole of the known structure. Polymorphs are predicted for this conformer, but it is found to pack poorly. It is proposed that routes to producing polymorphs of aspirin might be found if consideration is given to promoting the stability of the planar conformer with appropriate solvents or additives. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 262–273, 1999     

Interactive System for Similarity-Based Inspection and Assessment of the Well-Being of mHealth Users

Recent digitization technologies empower mHealth users to conveniently record their Ecological Momentary Assessments (EMA) through web applications, smartphones, and wearable devices. These recordings can help clinicians understand how the users’ condition changes, but appropriate learning and visualization mechanisms are required for this purpose. We propose a web-based visual analytics tool, which processes clinical data as well as EMAs that were recorded through a mHealth application. The goals we pursue are (1) to predict the condition of the user in the near and the far future, while also identifying the clinical data that mostly contribute to EMA predictions, (2) to identify users with outlier EMA, and (3) to show to what extent the EMAs of a user are in line with or diverge from those users similar to him/her. We report our findings based on a pilot study on patient empowerment, involving tinnitus patients who recorded EMAs with the mHealth app TinnitusTips. To validate our method, we also derived synthetic data from the same pilot study. Based on this setting, results for different use cases are reported.     

Reservoir Computing with Delayed Input for Fast and Easy Optimisation

Reservoir computing is a machine learning method that solves tasks using the response of a dynamical system to a certain input. As the training scheme only involves optimising the weights of the responses of the dynamical system, this method is particularly suited for hardware implementation. Furthermore, the inherent memory of dynamical systems which are suitable for use as reservoirs mean that this method has the potential to perform well on time series prediction tasks, as well as other tasks with time dependence. However, reservoir computing still requires extensive task-dependent parameter optimisation in order to achieve good performance. We demonstrate that by including a time-delayed version of the input for various time series prediction tasks, good performance can be achieved with an unoptimised reservoir. Furthermore, we show that by including the appropriate time-delayed input, one unaltered reservoir can perform well on six different time series prediction tasks at a very low computational expense. Our approach is of particular relevance to hardware implemented reservoirs, as one does not necessarily have access to pertinent optimisation parameters in physical systems but the inclusion of an additional input is generally possible.     

A novel approach toward the prediction of the glass transition temperature: Application of the EVM model,a designer QSPR equation for the prediction of acrylate and methacrylate polymers

We describe an original QSPR model called the EVM model (Energy, Volume, Mass) to calculate the glass transition temperature (T_g) of aliphatic acrylate and methacrylate homopolymers using classical molecular mechanics and dynamics. The latter was used to calculate an energy density function related to the cylindrical volume of a 20 monomer unit polymer segment (TSSV, Total Space around a Standard deviation Volume). We then calculated the T_g as a function of this density function and the repeat unit molecular weight, although no interchain interactions were taken into account. For linear and branched aliphatic acrylate and methacrylate polymers, the standard deviation from linear regression was 12 K, and the r² was 0.96. The model allows calculation of the T_g with an average absolute error of error of 10% for linear and branched derivatives not included in the original linear regression analysis. The results obtained with the EVM model are compared with those obtained with Bicerano's model. © 1997 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 35: 2579–2590, 1997     

Prediction of Migration Times of Organic Ions in Capillary Zone Electrophoresis

The electrophoretic mobility ratio (R value) of any two ions is constant and independent of the capillary type and electrophoretic conditions if their electrical charges and hydration radii are constant. The use of strong acid salts and quaternary ammonium salts is therefore proposed for the determination of R values. Such analytes are called markers. The following determinations can be carried out: (i) the determination of the migration time corresponding to the electroosmotic flow (EOF) in any capillary under any electrophoretic condition by measuring the migration times of two markers in the condition studied (useful when the EOF is weak); (ii) the determination of the migration time of an analyte in any capillary by knowing the migration time of the markers in the capillary studied. If the pH is changed and the ionization of the analyte is pH dependent, the resulting migration time for the analyte can be calculated. The constancy of the mobility ratios of seven markers was checked experimentally at eight different pH values (between pH 3 and 10), at three temperatures, and for two buffer concentrations. The predicted and experimental migration times were also compared in two different types of capillaries.     

Crystal structure predictions for acetic acid

Possible crystal structures of acetic acid were generated, considering eight space groups and assuming one molecule in the asymmetric unit. Our grid-search method was compared with a Monte Carlo approach as implemented in the Biosym/MSI Polymorph Predictor. This revealed no sampling deficiencies. A large number of possible crystal structures were found (∼100 within only 5 kJ/mol), including the experimental structure. Energy minimizations were done with a united-atoms force field (GROMOS), an all-atoms force field (AMBER), and a potential that describes the electrostatic interactions with distributed multipoles (DMA). In all cases, the experimental structure had a low lattice energy. The number of hypothetical crystal structures was reduced considerably by removing space-group symmetry constraints, or by a primitive molecular dynamics shake-up. Nevertheless, sufficient structures of equal or lower energy compared with the experimental structure remained to suggest that other factors need to be considered for genuine structure prediction. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 459–474, 1998     

磁头/盘界面超薄气膜挤压效应和动压效应研究

针对求解磁头/磁盘界面动态气膜力时出现的不易收敛和编程复杂的问题,本文提出了基于PDE工具求解气体润滑的瞬态和稳态雷诺方程的方法,计算了具有不同最小气膜厚度的Tri-pad正压型和Tri-pad负压型浮动块空气轴承在加载和卸载过程中的瞬态和稳态气膜压力分布,求解了作用面上的轴承力,并将2种状态下超薄气膜挤压效应和动压效应对轴承力的影响进行了对比.仿真结果表明:该方法具有足够的求解精度,且收敛速度快,为研究具有复杂磁头形貌特征的超薄气体润滑的动态特性提供了方便、准确的方法.     

Synthesis,Biological Evaluation and Molecular Docking Studies of 5-Indolylmethylen-4-oxo-2-thioxothiazolidine Derivatives

Background: Infectious diseases represent a significant global strain on public health security and impact on socio-economic stability all over the world. The increasing resistance to the current antimicrobial treatment has resulted in the crucial need for the discovery and development of novel entities for the infectious treatment with different modes of action that could target both sensitive and resistant strains. Methods: Compounds were synthesized using the classical organic chemistry methods. Prediction of biological activity spectra was carried out using PASS and PASS-based web applications. Pharmacophore modeling in LigandScout software was used for quantitative modeling of the antibacterial activity. Antimicrobial activity was evaluated using the microdilution method. AutoDock 4.2^® software was used to elucidate probable bacterial and fungal molecular targets of the studied compounds. Results: All compounds exhibited better antibacterial potency than ampicillin against all bacteria tested. Three compounds were tested against resistant strains MRSA, P. aeruginosa and E. coli and were found to be more potent than MRSA than reference drugs. All compounds demonstrated a higher degree of antifungal activity than the reference drugs bifonazole (6–17-fold) and ketoconazole (13–52-fold). Three of the most active compounds could be considered for further development of the new, more potent antimicrobial agents. Conclusion: Compounds 5b (Z)-3-(3-hydroxyphenyl)-5-((1-methyl-1H-indol-3-yl)methylene)-2-thioxothiazolidin-4-one and 5g (Z)-3-[5-(1H-Indol-3-ylmethylene)-4-oxo-2-thioxo-thiazolidin-3-yl]-benzoic acid as well as 5h (Z)-3-(5-((5-methoxy-1H-indol-3-yl)methylene)-4-oxo-2-thioxothiazolidin-3-yl)benzoic acid can be considered as lead compounds for further development of more potent and safe antibacterial and antifungal agents.     

未添加晶种结晶过程的中后期动力学模拟

以KNO₃-H₂O为模型体系, 考察了未添加晶种的间歇结晶过程动力学, 将历经爆发成核后的结晶体系近似为添加晶种的结晶体系. 并结合光学关联方法, 推导了可描述历经爆发成核后的晶体形成和生长速率模型. 模型中含有可反映结晶固相信息的透光率变量, 从而避免了以往模型仅靠液相浓度数据求解模型参数的不便. 运用该模型拟合未添加晶种结晶过程的中后期实验数据, 得到了KNO₃晶体的二次成核和生长动力学参数, 参数结果与文献中报道的添加晶种结晶过程的参数值相近. 在此基础上, 针对添加晶种的结晶过程, 提出了晶种添加量的定量设计方法, 并得到了实验的初步验证.     

一种基于百度指数的城市日游客规模预测方法

百度指数数据为预测游客规模提供了新思路。以杭州市为例,首先研究新浪微博签到数据与统计年鉴中实际游客量的关系,用新浪微博签到人数模拟实际旅游人数,建立杭州市日游客规模自回归移动平均（auto regressive moving average,ARMA）模型,并进行预测;然后结合计量经济学中的协整检验和格兰杰因果关系检验,分析百度指数与微博签到人数之间的关系,利用百度指数空间分布特征及主成分分析后提取的3个解释变量构建向量自回归（vector auto regression,VAR）模型;最后比较了2个模型的预测精度。结果显示,百度指数存在地理空间属性,且与新浪微博签到人数互为格兰杰因果关系,存在1~23 d的滞后期。此外,相比ARMA模型,考虑了百度指数地理属性的VAR模型在样本期内的预测精度提高了13.1%,在样本期外的预测精度提高了27.9%。研究表明,百度指数的时间和空间属性对游客规模预测有重要意义和价值。