基于模糊谱聚类的不确定蛋白质相互作用网络功能模块挖掘

针对谱聚类融合模糊C-means（FCM）聚类的蛋白质相互作用（PPI）网络功能模块挖掘方法准确率不高、执行效率较低和易受假阳性影响的问题，提出一种基于模糊谱聚类的不确定PPI网络功能模块挖掘（FSC-FM）方法。首先，构建一个不确定PPI网络模型，使用边聚集系数给每一条蛋白质交互作用赋予一个存在概率测度，克服假阳性对实验结果的影响；第二，利用基于边聚集系数流行距离（FEC）策略改进谱聚类中的相似度计算，解决谱聚类算法对尺度参数敏感的问题，进而利用谱聚类算法对不确定PPI网络数据进行预处理，降低数据的维数，提高聚类的准确率；第三，设计基于密度的概率中心选取策略（DPCS）解决模糊C-means算法对初始聚类中心和聚类数目敏感的问题，并对预处理后的PPI数据进行FCM聚类，提高聚类的执行效率以及灵敏度；最后，采用改进的边期望稠密度（EED）对挖掘出的蛋白质功能模块进行过滤。在酵母菌DIP数据集上运行各个算法可知，FSC-FM与基于不确定图模型的检测蛋白质复合物（DCU）算法相比，F-measure值提高了27.92%，执行效率提高了27.92%；与在动态蛋白质相互作用网络中识别复合物的方法（CDUN）、演化算法（EA）、医学基因或蛋白质预测算法（MGPPA）相比也有更高的F-measure值和执行效率。实验结果表明，在不确定PPI网络中，FSC-FM适合用于功能模块的挖掘。     

DOPO‐Based Phosphorus‐Containing Methacrylic (Co)Polymers: Glass Transition Temperature Investigation

A two‐step synthetic procedure is designed for preparing new flame‐retardant methacrylic monomers containing 9,10‐dihydro‐9‐oxa‐10‐phosphaphenanthrene‐10‐oxide (DOPO) as a substituent side group. DOPO and methacrylate moieties are linked by linear aliphatic hydrocarbon spacers (3 to 11 carbon atoms). Copolymerization with methyl methacrylate is carried out leading to copolymers containing between 2 and 10 wt% phosphorus. All homo‐ and copolymers exhibit a unique glass transition temperature (T_g ). A new group contribution for DOPO‐based substituent is extracted that leads to reasonable estimations of T_g s of other published polymers. The Fox equation provides a good estimation of T_g s for most copolymers and for physical blends of poly(methyl methacrylate) (PMMA) and DOPO. When using monomers having three and four carbon atoms in the hydrocarbon spacer, the T_g of copolymers remains close to that of PMMA over a wide range of composition.     

Piezoelectricity of the Transmembrane Protein ba3 Cytochrome c Oxidase

Controlling the electromechanical response of piezoelectric biological structures including tissues, peptides, and amino acids provides new applications for biocompatible, sustainable materials in electronics and medicine. Here, the piezoelectric effect is revealed in another class of biological materials, with robust longitudinal and shear piezoelectricity measured in single crystals of the transmembrane protein ba₃ cytochrome c oxidase from Thermus thermophilus. The experimental findings from piezoresponse force microscopy are substantiated using a range of control measurements and molecular models. The observed longitudinal and shear piezoelectric responses of ≈ 2 and 8 pm V⁻¹, respectively, are comparable to or exceed the performance of commonly used inorganic piezoelectric materials including quartz, aluminum nitride, and zinc oxide. This suggests that transmembrane proteins may provide, in addition to physiological energy transduction, technologically useful piezoelectric material derived entirely from nature. Membrane proteins could extend the range of rationally designed biopiezoelectric materials far beyond the minimalistic peptide motifs currently used in miniaturized energy harvesters, and the finding of robust piezoelectric response in a transmembrane protein also raises fundamental questions regarding the molecular evolution, activation, and role of regulatory proteins in the cellular nanomachinery, indicating that piezoelectricity might be important for fundamental physiological processes.     

功能性小麦品种的概念、类别和发展前景（网络首发、推荐阅读）

结合全球倡导的营养导向型农业和功能性食品的内容，首次提出“功能性小麦品种”的概念，将其定义为“含有对人体健康有益的活性成分，可调节人体有益代谢，能给人体健康带来某种益处或满足特定人群的特殊需求，同时可以作为日常食物的口感正常、无毒副作用的小麦品种类型”；结合疫情警示和我国进入后工业时代后，人们需求必将由“吃得饱”、“吃得好”向“吃得健康”转变，因而提出继高产品种、优质品种之后培育“功能性小麦品种”的育种目标。根据多年关于小麦淀粉、蛋白、酯类和其他成分的功能研究结果，介绍新育成的“麦黄酮”、“高色素”、“高抗性淀粉”、“富锌”、“低醇溶蛋白”和“低植酸”等功能性小麦新品种（系）的营养特性和农艺产量状况；根据“健康中国2030”规划等国家战略，进行“功能性品种培育是解决我国功能性食品‘卡脖子’的关键基础，一种功能性品种可以形成一类功能性食品，多种功能性品种可以形成我国功能性面制品产业，推动我国整个食品工业的发展”的前景展望；根据功能性品种及其食品的稳定性和可靠性是产品和市场的“生命线”，从对消费者负责的高度，提出关于“功能性农作物品种审定导向和组建功能性成分检测机构；编制有关功能性品种和食品的国家或行业标准，设立功能性食品和功能性农作物品种的商业标志，保证我国功能性农作物品种及其食品健康发展”等方面的具体建议。     

Revamping SiO2 Spheres by Core–Shell Porosity Endowment to Construct a Mazelike Nanoreactor for Enhanced Catalysis in CO2 Hydrogenation to Methanol

Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO₂), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO₂ spheres. The precisely-engineered MVmSiO₂ with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO₂ nanoreactor experimentally demonstrated its expected workability in model gas-phase CO₂ hydrogenation reaction where enhanced CO₂ activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO₂, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO₂ hydrogenation employing both in-situ experimental characterizations and density functional theory calculations.     

基于区间犹豫模糊语言集的水资源多目标决策

以鄂北水资源配置工程为对象,研究大型调水工程背景下的多水源多目标优化配置。将鄂北地区水库分为充蓄水库、补偿水库与在线水库等3类,根据各类水库特点对鄂北水资源配置工程进行系统概化,建立以年缺水量最小和调水成本最低为目标函数的多水源多目标优化配置模型。采用权重系数法进行求解得到非劣解集。最后采用基于区间犹豫模糊语言与TOPSIS的多目标决策方法对各方案的缺水量与调水量作出评价并遴选出最优方案。研究结果表明:对鄂北水资源配置工程而言,缺水量与调水量的权重比为7∶3的方案综合评价最优,重视缺水的同时兼顾调水成本;基于区间犹豫模糊语言集与TOPSIS的水资源多目标决策方法经本文实例验证具有较高的稳定性与可行性。     

Facile synthesis of Ni doped CoWO4 nanoarrays grown on nickel foam substrates for efficient urea oxidation

Urea electrolysis is a promising technology for hydrogen production, which can alleviate environmental pollution of urea-rich wastewater. It's worth noting that electrochemistry activity can be significantly improved by reasonably regulating the electron configuration around the active site for the doped materials. In this work, a series of well-tuned Ni doped CoWO₄ nanoarrays on Ni foam supports have been prepared through a typical hydrothermal approach for the first time. Moreover, the resulting Ni–CoWO₄-2 material significantly promotes urea oxidation performance with an applied potential of 1.35 V at 50 mA cm^?2, which is lower than that of water oxidation reaction (1.60 V). Density functional theory results suggest that the Ni doped CoWO₄ has larger urea adsorption energy compared with CoWO₄ and the CO(NH₂)₂ molecule is strongly adsorbed on surface of Ni doped CoWO₄, which is beneficial to accelerate the kinetics of the reaction and improve the electrocatalytic activity of the urea electrolysis.     

Hydrogen evolution reaction on in-plane platinum and palladium dichalcogenides via single-atom doping

Searching for the catalysts with excellent catalytic activity and high chemical stability is the key to achieve large-scale production of hydrogen (H₂) through hydrogen evolution reaction (HER). Two-dimensional (2D) platinum and palladium dichalcogenides with extraordinary electrical properties have emerged as the potential candidate for HER catalysts. Here, chemical stability, HER electrocatalytic activity, and the origin of improved HER performance of Pt/Pd-based dichalcogenides with single-atom doping (B, C, N, P, Au, Ag, Cu, Co, Fe, Ni, Zn) and vacancies are explored by first-principles calculations. The calculated defect formation energy reveals that most defective structures are thermodynamically stable. Hydrogen evolution performance on basal plane is obviously improved by single-atoms doping and vacancies. Particularly, Zn-doped and Te vacancy PtTe₂ have a ΔG_H value close to zero. Moreover, defect engineering displays a different performance on HER catalytic activity in sulfur group elements, in order of S < Te < Se in Pd-based chalcogenides, and S < Se < Te in Pt-based chalcogenides. The origin of improved hydrogen evolution performance is revealed by electronic structure and charge transfer. Our findings of the highly activating defective systems provide a theoretical basis for HER applications of platinum and palladium dichalcogenides.     

煤油共炼残渣性质分析

采用元素分析、工业分析、热重、X射线衍射、扫描电镜、红外光谱等手段对煤油共炼残渣的组成、微观结构、官能团进行分析表征，并通过红外谱图的分峰拟合对官能团含量进行半定量计算。结果表明：残渣的有机物由具有片层堆积结构碳质颗粒组成，无机物由煤油共炼催化剂和煤中的无机矿物质组成；残渣颗粒粒径呈10 μm和2 μm的两级分布，颗粒呈整体无序、局部有序的分布状态。分别采用工业分析和热重分析得到挥发分、固定碳和灰分的含量，两组数据一致：残渣的氢键中羟基自缔合结构占到了47.95%；脂肪氢中亚甲基结构占64%左右；含氧官能团主要以碳氧键和羰基形式存在，含有微量的硅氧键，没有羧基；芳香结构中烷基侧链取代基较多，五取代氢的芳香结构只占约4.5%。     

Computational personality recognition from Facebook text: psycholinguistic features,words and facets

ABSTRACT

Advances in the Natural Language Processing (NLP) and machine learning fields have led to the development of automated methods for the recognition of personality traits from text available from social media and similar sources. Systems of this kind exploit the close relation between lexical knowledge and personality models – such as the well-known Big Five model – to provide information about the author of an input text in a non-intrusive fashion, and at a low cost. Although now a well-established research topic in the field, the computational recognition of personality traits from text still leaves a number of research questions worth further exploration. In particular, this paper attempts to shed light on three main issues: (i) whether we may develop psycholinguistics-motivated models of personality recognition when such knowledge sources are not available for the target language under consideration; (ii) whether the use of psycholinguistic knowledge may be still superior to contemporary word vector representations; and (iii) whether we may infer certain personality facets from a corpus that does not explicitly convey this information. In this paper these issues are dealt with in a series of individual experiments of personality recognition from Facebook text, whose initial results should aid the future development of more robust systems of this kind.