Fermi and Coulomb correlations in the 21 S state of the helium isoelectronic sequence

The Fermi and Coulomb holes of the 2¹ S state of the helium isoelectronic sequence are investigated. Several interesting differences between the results obtained and those which might be expected on the basis of the corresponding 2³ S state are pointed out and discussed.     

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.     

萜类化合物13C NMR化学位移的定量构谱相关研究

利用原子电性作用矢量(Atomic electro-negativity interaction vector,AEIV)和原子杂化状态指数(Atomic hybridization state index,AHSI)对萜类化合物中的C原子进行结构表征并与其核磁共振碳谱(13C NMR)建立了优良的定量构谱相关(QSSR)模型.其中29个单萜类化合物中的290个C原子建模的计算值经留一法(Leave-one-out,LOO)交互校验(Cross-validation,CV)预测值的复相关系数(R)分别为0.9900和0.9867,进一步使用倍半萜、二萜、三萜化合物分子中65个C原子的13C NMR化学位移值来检测该模型的稳定性,模型预测值和观测值间复相关系数(R)为0.9777,取得了令人满意的结果.     

Electrostatics of phosphatidic acid monolayers: Insights from computer simulations

In this paper, we argue that many of the fascinating electrostatic effects that take place in amphiphilic systems are strongly related to the particular organization of the oxygen atoms within each individual molecule. In particular, we focus on two effects: charge inversion and dielectric overscreening. For that purpose, we present molecular dynamics simulations of phosphatidic acid (DMPA²⁻) in the presence of divalent counterions. Our results show that the many oxygens present in DMPA²⁻ cooperatively create strong binding sites for counterions, which in some cases lead to charge inversion. We also present an analysis of the role of interfacial water and relate our analysis to the phenomenon of dielectric overscreening. Several experimental implications are discussed in the conclusions.     

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.     

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.     

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.     

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.