Photoinduced electron transport process in electrochemical cell I. Phenomenological description

The process of electron transport plays an essential role in the fundamental phenomena of life like photosynthesis, respiration and vision as well as in photoelectronic devices. However, the molecular mechanisms of the electron way and factors governing the transport rate in such systems are still unclear. Several groups have reported theoretical approaches for searching the mechanisms by using statistical mechanics, coherent dynamics and quantum mechanics. The current density vector inside the semiconducting layer is determined. In this paper we consider the problem of transport of electron promoted in the electrochemical cell constructed of two electrodes with the dye molecules immersed in. We describe the process of electron promotion by refractive light wave on the vacuum–semiconductor boundary as well as on the semiconducting electrode and the dye molecule layer in terms of extended phenomenological electrodynamics formalism. The results of our theoretical model show that such a theoretical approach will give more information on the mechanism of electron transport and will give insight in the determination of some electric features of materials.     

Equilibrium polymerization in a solvent: Solution on the Bethe lattice

The lattice model for equilibrium polymerization in a solvent proposed by Wheeler and Pfeuty is solved exactly on a Bethe lattice (core of a Caylay tree) with general coordination numberq. Earlier mean-field results are reobtained in the limitq, but the phase diagrams show deviations from them for finiteq. Whenq=2, our results turn into the solution of the one-dimensional problem. Although the model is solved directly, without the use of the correspondence between the equilibrium polymerization model and the diluten0 model, we verified that the latter model may also be solved on the Bethe lattice, its solution being identical to the direct solution in all parameter space. As observed in earlier studies of the puren0 vector model, the free energy is not always convex. We obtain the region of negative susceptibility for our solution and compare this result with mean field and renormalization group (-expansion) calculations.     

FFC-1离子交换纤维物理化学性能的研究

利用扫描电镜、热失重-红外、元素分析、低温氮吸附等技术和化学手段对聚羧酸基FFC-1离子交换纤维的结构与性能特点等进行了系统研究．结果表明：FFC-1离子交换纤维为含适量酰肼类交联键的聚羧酸(钠)型离子交换材料，外比表面积大和传质距离短是其反应动力学性能优异的主要原因，FFC-1纤维具有良好的化学与热稳定性。在5mol/L硫酸、硝酸、盐酸和2mol／L氢氧化钠溶液中浸泡，交换容量未见明显降低。但过氧化氢溶液对其功能基有明显破坏，CO2为FFC-1纤维在高温区间(300℃～350℃)的主要分解产物。     

Investigation of carbon-13 nuclear magnetic resonance spectra-structure correlation based on novel atomic distance-edge (ADE) vector

A set of novel graph-theoretical parameters,called the atomic distance-edge (ADE) vector,was developed.Based on the connecting C-C bond number between central carbon atom and the other ones,various carbon atoms of alkanes were classified as four types,i.e.,type 1,2,3 and 4 for primary,secondary,ternary and quaternary carbon,respectively; and then four regression equations were obtained to link carbon-13 chemical shift (CS) of each type of atoms.Furthermore,these regression models were used to predict the carbon-13 nuclear magnetic resonance spectra of alkanes and it was found that the estimated CS were in agreement with the experimental results.     

Ga^3＋的新萃取体系的界面特性和胶团化作用研究

研究了Ｇａ~（３＋）协萃体系（Ｇａ~（３＋）－Ｄ_２ＥＨＰＡ－Ｈ_２ＭＰＡ－正十二烷－Ｈ_２ＳＯ_４）的界面吸附和胶团形成热力学，发现该萃取体系中［Ｈ_２ＭＰＡ］影响Ｄ_２ＥＨＰＡ和Ｈ_２ＭＰＡ的界面吸附性质。在中、高［Ｈ_２ＭＰＡ］范围内Ｄ_２ＥＨＰＡ与Ｈ_２ＭＰＡ的界面吸附行为相反，Ｄ_２ＥＨＰＡ的存在也影响Ｈ_２ＭＰＡ的界面吸附行为。研究了界面张力与各因素关系的数学模型，并获得某些胶团形成和界面吸附特性的物化参数。     

predForm-Site: Formylation site prediction by incorporating multiple features and resolving data imbalance

Formylation is one of the newly discovered post-translational modifications in lysine residue which is responsible for different kinds of diseases. In this work, a novel predictor, named predForm-Site, has been developed to predict formylation sites with higher accuracy. We have integrated multiple sequence features for developing a more informative representation of formylation sites. Moreover, decision function of the underlying classifier have been optimized on skewed formylation dataset during prediction model training for prediction quality improvement. On the dataset used by LFPred and Formator predictor, predForm-Site achieved 99.5% sensitivity, 99.8% specificity and 99.8% overall accuracy with AUC of 0.999 in the jackknife test. In the independent test, it has also achieved more than 97% sensitivity and 99% specificity. Similarly, in benchmarking with recent method CKSAAP_FormSite, the proposed predictor significantly outperformed in all the measures, particularly sensitivity by around 20%, specificity by nearly 30% and overall accuracy by more than 22%. These experimental results show that the proposed predForm-Site can be used as a complementary tool for the fast exploration of formylation sites. For convenience of the scientific community, predForm-Site has been deployed as an online tool, accessible at http://103.99.176.239:8080/predForm-Site.     

Influence of SMA content on the electro-optical properties of polymer-dispersed liquid crystal prepared by monodisperse poly(MMA-co-SMA)/LC microcapsules

Monodisperse poly(methyl methacrylate) (PMMA) particles containing various concentrations of stearyl methacrylate (SMA) were prepared, and a liquid crystal (LC) was swollen into the particles using a solute co-diffusion method (SCM). Phase separation behaviors between the polymer and LC were monitored by utilizing an optical and a polarized microscope (OM/POM). The monodisperse LC microcapsules were then applied to a polymer-dispersed liquid crystal (PDLC), and the electro-optical properties were investigated. As a result, the threshold and driving voltages were improved when the SMA content increased. The long alkyl chains of SMA in the capsules should exist at the interface of the LC and polymer resulting in an enhancement of phase separation between the polymer and LC, which largely influences the electro-optical properties of PDLC.     

A combination of modified particle swarm optimization algorithm and support vector machine for gene selection and tumor classification

In the analysis of gene expression profiles, the number of tissue samples with genes expression levels available is usually small compared with the number of genes. This can lead either to possible overfitting or even to a complete failure in analysis of microarray data. The selection of genes that are really indicative of the tissue classification concerned is becoming one of the key steps in microarray studies. In the present paper, we have combined the modified discrete particle swarm optimization (PSO) and support vector machines (SVM) for tumor classification. The modified discrete PSO is applied to select genes, while SVM is used as the classifier or the evaluator. The proposed approach is used to the microarray data of 22 normal and 40 colon tumor tissues and showed good prediction performance. It has been demonstrated that the modified PSO is a useful tool for gene selection and mining high dimension data.