Relationship between precipitation and the infiltration depth over the middle and lower reaches of the Yellow River and Yangtze-Huaihe River Valley

National Natural Science Foundation of China [40701021, 40625002, 40331013]; National Knowledge Innovation Program of Chinese Academy of Sciences [KZCX2-YW-315-2]

Effects of temperature change on water discharge, and sediment and nutrient loading in the lower Pearl River basin based on SWAT modelling

National Natural Science Foundation of China [U0633002, 30670385]

Quantum dot electrochemiluminescence in aqueous solution at lower potential and its sensing application

The unique strategy for electrochemiluminescence (ECL) sensor based on the quantum dots (QDs) oxidation in aqueous solution to detect amines is proposed for the first time. Actually, there existed two QDs ECL peaks in anhydrous solution, one at high positive potential and another at high negative potential. However, here we introduced the QDs oxidation ECL in aqueous solution to fabricate a novel ECL sensor. Such sensor needed only lower positive potential to produce ECL, which could prevent the interferences resulted from high potential as that of QDs reduction ECL in aqueous solution. Therefore, the present work not only extended the QDs oxidation ECL application field from anhydrous to aqueous solution but also enriched the variety of ECL system in aqueous solution. Furthermore, we investigated the QDs oxidation ECL toward different kinds of amines, and found that both aliphatic alkyl and hydroxy groups could lead to the enhancement of ECL intensity. Among these amines, 2-(dibutylamino)ethanol (DBAE) is the most effective one, and accordingly, the first ECL sensing application of the QDs oxidation ECL toward DBAE is developed; the as-prepared ECL sensor shows wide linear range, high sensitivity, and good stability.

Selection for variables in quantitative structure-activity/property relationship studies - Comparison between methods of orthogonal descriptors and leaps-and-bounds regression analysis

In this paper, the comparison of orthogonal descriptors and Leaps-and-Bounds regression analysis is performed. The results obtained by using orthogonal descriptors are better than that obtained by using Leaps-and-Bounds regression for the data set of nitrobenzenes used in this study. Leaps-and-Bounds regression can be used effectively for selection of variables in quantitative structure-activity/property relationship(QSAR/QSPR) studies. Consequently, orthogonalisation of descriptors is also a good method for variable selection for studies on QSAR/QSPR.

Studies on the method of leaps and bounds regression

In this paper, we introduce the method of leaps and bounds regression which can be used to select variables quickly and obtain the best regression models. These models contain one variable, two variables, three variables and so on. The results obtained by using leaps and bounds regression were compared with those achieved by using stepwise regression to lead to the conclusion that leaps and bounds regression is an effective method.