High resolution capillary electrophoresis of carbon nanotubes

Purification of single-walled carbon nanotubes by capillary electrophoresis (CE) is demonstrated. Real-time Raman spectroscopy of the separation process and single-wavelength UV/vis detection show the ability of CE to provide high-resolution separations of nanotube fractions with baseline separation. AFM images of collected fractions demonstrate that separations are based on tube length. The separation method is suggested to be based on alignment of the nanotubes along the separation field.     

The amperometric determination of indole-3-acetic acid based on CeCl<Subscript>3</Subscript>-DHP film modified gold electrode

An amperometric sensor for the determination of indole-3-acetic acid (IAA) based on the CeCl₃-DHP film modified gold electrode was developed. CeCl₃ was dissolved into water in the presence of dihexadecyl hydrogen phosphate (DHP). The IAA sensor was prepared via evaporating solvent of the CeCl₃-DHP dispersion on the gold electrode surface. The amperometric response of IAA on the CeCl₃-DHP film modified gold electrode was investigated. The experimental results indicate that the passivation of the electrode due to the adsorption of the oxidation product of IAA decreases significantly at the CeCl₃-DHP film modified gold electrode, in contrast to that at the bare and the DHP modified gold electrode. The experimental parameters were optimized and an electrochemical method for the determination of IAA was established. The oxidation peak current is linearly with the concentration of IAA from 1 × 10⁻⁷ to 2 × 10⁻⁵ mol l⁻¹ and the detection limit is 3 × 10⁻⁸ mol l⁻¹. The relative standard deviation of eight measurements is 3.2% for 5 × 10⁻⁷ mol l⁻¹ IAA. The IAA in plant leaves were extracted and determined by the IAA sensor.     

Comparison and characterization of polysaccharides from natural and cultured <Emphasis Type="Italic">Cordyceps</Emphasis> using saccharide mapping

Comparison and characterization of polysaccharides from natural and cultured Cordyceps on the basis of their chemical characteristics such as glycosidic linkages were performed for the first time using saccharide mapping. The results showed that polysaccharides from most of the natural and cultured Cordyceps had similar responses to enzymatic digestion. These polysaccharides mainly contained (1→4)-β-D-glucosidic linkages, and (1→4)-α-glucosidic, (1→6)-α-glucosidic, 1,4-β-D-mannosidic, as well as (1→4)-α-D-galactosiduronic linkages also existed in some polysaccharides. Especially, natural and cultured Cordyceps polysaccharides could be discriminated on the basis of high performance liquid chromatography profiles of pectinase hydrolysates, which is helpful to control the quality of polysaccharides from Cordyceps.     

A relaxation times coupling method to construct acoustic relaxation calibration for two-frequency measuring gas compositions

In our previous work (Hu et al., 2014), a method has been proposed to detect gas compositions by locating the acoustic spectral peaks, which can be detected only by two-frequency acoustic measurements in practice. However, as a ‘Detection Calibration’, the effective relaxation area (ERA) constructed by existing theoretical model cannot match the two-frequency measurements when there are more than one strong relaxational components in gas mixtures. This paper proposes a method to construct the ERA by coupling the decoupled single relaxation times together to a whole relaxation time. For gas mixtures with only one single relaxation process, the predicted ERA results match with the experimental data better than those predicted by the existing model. Moreover, for gas mixtures in which more than one relaxation process are significant, the ERA results predicted by the proposed method also match with the detection results of two-frequency measurements better than the existing model. This relaxation time coupling based ERA constructing method is validated by the application in low-quality natural gas detection.     

Recommendation in evolving online networks

Recommender system is an effective tool to find the most relevant information for onlineusers. By analyzing the historical selection records of users, recommender system predictsthe most likely future links in the user-item network and accordingly constructs apersonalized recommendation list for each user. So far, the recommendation process ismostly investigated in static user-item networks. In this paper, we propose a model whichallows us to examine the performance of the state-of-the-art recommendation algorithms inevolving networks. We find that the recommendation accuracy in general decreases with timeif the evolution of the online network fully depends on the recommendation. Interestingly,some randomness in users’ choice can significantly improve the long-term accuracy of therecommendation algorithm. When a hybrid recommendation algorithm is applied, we find thatthe optimal parameter gradually shifts towards the diversity-favoring recommendationalgorithm, indicating that recommendation diversity is essential to keep a high long-termrecommendation accuracy. Finally, we confirm our conclusions by studying therecommendation on networks with the real evolution data.