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.     

从电子工业“脊梁”到全面开花的镓元素

镓是第一个根据化学元素周期律预言并在自然界中证实的元素，是室温下电导率和热导率均为最大的液态物质，镓在电子工业中得到了广泛应用，被誉为电子工业“脊梁”。近十几年来，镓的更多应用潜力被发掘出来，在电子工业、散热、增材制造、柔性机器、生物医学等领域均有重要的应用前景。     

Tractability frontiers in probabilistic team semantics and existential second-order logic over the reals

Probabilistic team semantics is a framework for logical analysis of probabilistic dependencies. Our focus is on the axiomatizability, complexity, and expressivity of probabilistic inclusion logic and its extensions. We identify a natural fragment of existential second-order logic with additive real arithmetic that captures exactly the expressivity of probabilistic inclusion logic. We furthermore relate these formalisms to linear programming, and doing so obtain PTIME data complexity for the logics. Moreover, on finite structures, we show that the full existential second-order logic with additive real arithmetic can only express NP properties. Lastly, we present a sound and complete axiomatization for probabilistic inclusion logic at the atomic level.     

Single machine group scheduling with ordered criteria

The single machine group scheduling problem is considered. Jobs are classified into several groups on the basis of group technology, i.e. jobs of the same group have to be processed jointly. A machine set-up time independent of the group sequence is needed between each two consecutive groups. A schedule specifies the sequence of groups and the sequence of jobs in each group. The quality of a schedule is measured by the criteriaF ₁, ...,F _m ordered by their relative importance. The objective is to minimize the least important criterionF _m subject to the schedule being optimal with respect to the more important criterionF _m–1 which is minimized on the set of schedules minimizing criterionF _m–2 and so on. The most important criterion isF ₁, which is minimized on the set of all feasible schedules. An approach to solve this multicriterion problem in polynomial time is presented if functionsF ₁, ...,F _m have special properties. The total weighted completion time and the total weighted exponential time are the examples of functionsF ₁, ...,F _m–1 and the maximum cost is an example of functionF _m for which our approach can be applied.The research of the authors was partially supported by a KBN Grant No. 3 P 406 003 05, the Fundamental Research Fund of Belarus, Project N 60-242, and the Deutsche Forschungsgemeinschaft, Project Schema, respectively. The paper was completed while the first author was visiting the University of Melbourne.     

基于支持向量机的羰基化合物红外光谱研究

设计了一个4层分等级分类系统，通过支持向量机技术对羰基化合物的红外光谱成功地进行了信息分类和提取，并与人工神经网络进行比较，结果表明：支持向量机对羰基类化合物红外光谱分类效果优于人工神经网络；另外详细探讨了表征酰胺类化合物的特征光谱峰片段对识圳伯仲叔酰胺的影响，证明了酰胺的N-H伸缩振动峰对识别伯仲叔酰胺贡献最大，为构建红外光谱智能解析系统提供了定量依据。     

The investigation of the (p,ρ,T) and (ps,ρs,Ts) properties of {(1−x)CH3OH + xLiBr} for the application in absorption refrigeration machines and heat pumps

The (p,ρ,T) and (p_s,ρ_s,T_s) properties of {(1−x)CH₃OH + xLiBr} over a wide range of state parameters are reported for the first time. The experiments were carried out in a constant volume piezometer over a temperature range from 298.15 K to 398.15 K, at 0.08421, 0.13617, 0.19692, 0.23133 and 0.26891 mole fractions and from atmospheric pressure up to 60 MPa. The experimental uncertainties are ΔT=±3 mK for temperature, Δp=±5·10⁻² MPa for high pressure and Δp=±5·10⁻⁴ MPa for atmospheric pressure, Δρ=±3·10⁻² kg · m⁻³ for density. An equation of state was derived for correlation of the experimental data of the solutions.     

基于支持向量机的凝血功能诊断模型

使用凝血四项指标诊断凝血功能是临床的常规检查,但根据经验进行诊断正确率不高.剔除临床上最重要的指标FIB后,建立支持向量机模型诊断的正确率和根据凝血四项指标诊断的正确率没有显著差异,100次模拟的平均正确率分别达到了95.4496%和95.5039%.     

基于PLC的三维调整机同步控制系统设计与实现

针对三维调整机难以实现多台同步工作，设计了基于PLC的同步控制方案。在同步控制系统方案中，采用西门子PLC通过工业无线以太网进行同步控制，由各维度油缸的位移传感器来保证同步控制的精确性。经实验，证实了此系统的精度满足设计要求，实现了同步控制的效果。     

Divergent Synthesis of Molecular Winch Prototypes

We report the synthesis of conceptually new prototypes of molecular winches with the ultimate aim to investigate the work performed by a single ruthenium-based molecular motor anchored on a surface by probing its ability to pull a load upon electrically-driven directional rotation. According to a technomimetic design, the motor was embedded in a winch structure, with a long flexible polyethylene glycol chain terminated by an azide hook to connect a variety of molecular loads. The structure of the motor was first derivatized by means of two sequential cross-coupling reactions involving a penta(4-halogenophenyl)cyclopentadienyl hydrotris(indazolyl)borate ruthenium(II) precursor and the resulting benzylamine derivative was next exploited as key intermediate in the divergent synthesis of a family of nanowinch prototypes. A one-pot method involving sequential peptide coupling and Cu-catalyzed azide-alkyne cycloaddition was developed to yield four loaded nanowinches, with load fragments encompassing triptycene, fullerene and porphyrin moieties.