Anion recognition by 1,3-disiloxane-1,1,3,3-tetraols in organic solvents

Anion recognition by 1,3-disiloxane-1,1,3,3-tetraols has been elucidated by ¹H NMR titrations and ESI-MS in organic solvents. The association constants of the receptors for halide anions are larger than those of silanediol and 1,3-disiloxane-1,3-diol due to the cooperative hydrogen bonds by four silanol hydroxy groups of 1,3-disiloxane-1,1,3,3-tetraols.     

Modeling of retention of adrenoreceptor agonists and antagonists on polar stationary phases in hydrophilic interaction chromatography: a review

Retention prediction models for reversed-phase liquid chromatography (RPLC) have been extensively studied owing to the fact that RPLC remains the most widely used chromatographic technique especially in the field of pharmaceutical and biomedical analyses. However, RPLC is not always the method of choice for the analysis of some compounds that have high polarity. Hydrophilic interaction chromatography (HILIC) has been gaining interest in the last few years as an alternative option to RPLC for the analysis of polar and hydrophilic analytes. HILIC is a variant of normal-phase liquid chromatography, but utilizes water in a water-miscible organic solvent as the eluent in conjunction with a hydrophilic stationary phase. The present review aims to summarize recent contributions on the development of retention prediction models for a group of basic analytes, namely, the adrenoreceptor agonists and antagonists, on different polar stationary phases. The use of multiple linear regression and artificial neural networks in model building is highlighted.     

扑热息痛片剂药品的近红外光谱法非破坏定量分析

现代近红外光谱分析技术将近红外光谱 (NIR)法同计算机科学和化学计量学结合 ,实现了对样品进行无损非破坏性定量分析 .该法具有速度快、操作简单及所需样品少等特点 ,能够实现样品分析的时间同步、地点同步及无损非破坏分析 .为实现生产过程中即时、在线的质量控制提供了新的手段[1 ] .本文应用人工神经网络 [2 ]与近红外漫反射光谱相结合对扑热息痛片剂药品进行了非破坏快速定量分析 .用扑热息痛片剂药品的近红外漫反射光谱数据、一阶导数光谱数据及二阶导数光谱数据分别建立了 ANN模型 ,预测未知样品 ,讨论了影响网络的因素 ,使用了新…     

Mass deacidification and reinforcement of papers and books VI - Study of aminopropylmethyldiethoxysilane treated papers

In libraries and archives some of the items which, upon ageing, have acidified considerably since their production are so brittle that they cannot be handled without risking loss of material. In contrast to current deacidification processes, aminoalkylakoxysilanes (AAAS) improve the mechanical properties of paper. A simple AAAS, aminopropylmethyldiethoxysilane (AMDES) was used as a model to better understand previous observations made on these systems (hydrolysis, condensation and possible reactions with the organic substrate). The evaluation of the mechanical properties of papers that were treated with AMDES showed that there was no formation of a polymer network on the fibres’ surface. However, treated papers not only exhibited a high alkaline reserve, but also a significant increase in both their tensile breaking length and their folding endurance. Treatment of hygrothermally aged papers with AMDES provided improved folding endurance as well as a good resistance to ageing. Various oxidation treatments of the model papers using sodium hypochlorite led to the conclusion that the nature of the oxidised groups formed on cellulose did not seem to play a significant role in the strengthening mechanism but rather that this effect of AMDES mainly arose from hydrogen bonding between the two molecules.     

Madaline网络用于分光光度法同时测定铜钴镍的研究

采用4－（2－吡啶偶氮）－间苯二酚（PAR）－Cu,Co,Ni显色体系，应用Madline神经网络原理，对于吸收光谱严重重叠的三组分金属配合物体系同时进行含量测定，Cu^2 ,Co^2 ,Ni^2 的平均回收率分别为94％，101％，102％，实验表明，该法具有训练速度快，预测结果准确度良好等特点，有望成为多组分分析的有效方法之一。     

人工神经网络应用于NO-3和NO-2两组分同时测定

应用人工神经网络原理,结合分光光度法,对吸收光谱严重重叠的硝酸根和亚硝酸根两组分进行同时测定,其结果令人满意。     

Enhanced Characterization of Naproxen Formulation by Near Infrared Spectroscopy

Near infrared spectroscopy in combination with appropriate chemometric methods is an effective technique for quantitative analysis of parameters of interest for the pharmaceutical industry. In this study, the artificial neural network (ANN) was applied to monitor critical parameters (compression force, tablet hardness, mean particle size, and active pharmaceutical ingredient concentration of tablets) in the process of naproxen pharmaceutical preparation. The performance of ANN was compared to linear methods (partial least squares regression (PLS) and synergy interval partial squares (siPLS)). The ANN models for compression force, tablet hardness, mean particle size, and active pharmaceutical ingredient concentration of tablets yielded the low root mean square error of prediction (RMSEP) values of 0.936 KN, 0.302 kg, 4.49 mg, and 2.14 µm, respectively. The predictive ability of the PLS model was improved by siPLS with selection of spectral regions and the best performance among all calibration methods was showed by the nonlinear method (ANN). Effective models were built by using these approaches using near infrared spectroscopy.     

人工神经网络法用于高效毛细管电泳分离条件优化的研究

把人工神经网络（ＡＮＮ）法应用于高效毛细管电泳（ＨＰＣＥ）分离条件的优化，给出了反向传播（ＢＰ）的ＡＮＮ模型的具体算法。用正交试验法同时考察了缓冲溶液组成、浓度、ｐＨ值和有机添加剂浓度等实验因素对ＨＰＣＥ分离合成色素和防腐剂的影响，采用误差反向传播方法建立了有效的ＡＮＮ预测模型，预测最佳分离条件，获得了满意的分离结果。