Theoretical advances of the structures and catalytic activities of small-sized gold nanoclusters

Gold nanoclusters exhibit extraordinary catalytic activities,but the dominating factor is still unclear due to the complexity of the structures.In this review,we briefly summarized the recent theoretical progress on their structures and catalytic activities.Combining the experimental and theoretical efforts,the structures of small-sized gold clusters have been explored systematically.Based on the determined structures,factors that influence the catalytic capabilities of small-sized gold clusters(Au_(16)-Au_(35))are studied using CO oxidation asa probe.The preadsorption energies of CO and O_2are found strongly correlated with catalytic activities,which could be affected by the clusters'geometries,sizes,and charge distributions.In addition,the presence of water could significantly lower the activation energy barrier of O_2 dissociation to enhance the clusters'catalytic activities.     

不允许卖空限制下跳扩散模型的动态均值-方差资产负债问题

研究了在不允许卖空情况下跳扩散模型的动态均值一方差资产负债问题。本文利用两个黎卡提方程构造出HJB方程的一个连续解V（t，x），然后验证这个解是方程的粘性解，并利用粘性解和识别定理得到了最优投资策略和有效边界。     

未免有浮夸之嫌——且说“弄《水浒》惹大祸”

白驹施彦端一些真实可靠的史料文物中,并无"中进士"、"字耐庵"、"著水浒"之类记载,而一些学者却以"著《水浒》惹大祸"来辩解其无;相距施彦端四五百年之后,居然出现上述内容,而一些学者却以朝廷无力"禁《水浒》"来辩解其有。这些,都未免有浮夸之嫌,实难以此论证"白驹施彦端进士,字耐庵,为〈水浒传〉作者"。     

Description of rotational properties of the superheavy nucleus ^256,258,260Rf by projected shell model

Band structure of the Z = 104 nucleus 256Rf has been a recent research focus in nuclear physics. We performed projected shell model calculations for this and some other neighboring Rf isotopes. Specifically, we studied rotational properties of these nuclei and showed that variations in dynamic moment of inertia were sensitive to single-particle structures, which may be useful information for locating the anticipated island of stability. Electromagnetic transition properties were also calculated, and measurable quantities were predicted for further experimental test.     

LEARNING CAUSAL GRAPHS OF NONLINEAR STRUCTURAL VECTOR AUTOREGRESSIVE MODEL USING INFORMATION THEORY CRITERIA

Detection and clarification of cause-effect relationships among variables is an important problem in time series analysis. Traditional causality inference methods have a salient limitation that the model must be linear and with Gaussian noise. Although additive model regression can effectively infer the nonlinear causal relationships of additive nonlinear time series, it suffers from the limitation that contemporaneous causal relationships of variables must be linear and not always valid to test conditional independence relations. This paper provides a nonparametric method that employs both mutual information and conditional mutual information to identify causal structure of a class of nonlinear time series models, which extends the additive nonlinear times series to nonlinear structural vector autoregressive models. An algorithm is developed to learn the contemporaneous and the lagged causal relationships of variables. Simulations demonstrate the effectiveness of the nroosed method.     

基于社会需求的高职类物流管理专业人才培养探讨

伴随着物流产业的迅猛发展,社会对物流人才的需求持续猛增。作为培养技能型人才为主的高职类院校,其责任重大。本文根据当前社会需求,分析我国高职院校物流管理专业教学现状,从而更深刻地认识其人才培养的有效途径。     

共培养技术及化学絮凝法对小球藻C.vulgaris XJB絮凝的影响

微藻是生物柴油理想的原料,但微藻尺寸较小,细胞密度较低,导致微藻采收困难。为提高微藻的采收率,节约成本,实验采用自絮凝斜生栅藻Scenedesmus sp.-BH与富油小球藻C.vulgaris XJB共培养技术来提高小球藻C.vulgaris XJB的絮凝率,同时与调节p H、添加Fe Cl3和添加壳聚糖3种化学絮凝法对比。结果表明:3种化学絮凝法60 min时的最佳絮凝率分别为84.2%、96.5%和72.9%;共培养最佳条件下小球藻C.vulgaris XJB 60 min时的絮凝率为33.3%,8 h后的絮凝率可达73.2%。共培养条件下小球藻C.vulgaris XJB的絮凝率比化学絮凝法的稍低,但该方法不会引入有害化学物质,后期分离成本低,是一种经济、环保的絮凝方法。     

Higher-order principal component pursuit via tensor approximation and convex optimization

Recovering the low-rank structure of data matrix from sparse errors arises in the principal component pursuit （PCP）. This paper exploits the higher-order generalization of matrix recovery, named higher-order principal component pursuit （HOPCP）, since it is critical in multi-way data analysis. Unlike the convexification （nuclear norm） for matrix rank function, the tensorial nuclear norm is stil an open problem. While existing preliminary works on the tensor completion field provide a viable way to indicate the low complexity estimate of tensor, therefore, the paper focuses on the low multi-linear rank tensor and adopt its convex relaxation to formulate the convex optimization model of HOPCP. The paper further propose two algorithms for HOPCP based on alternative minimization scheme： the augmented Lagrangian alternating direction method （ALADM） and its truncated higher-order singular value decomposition （ALADM-THOSVD） version. The former can obtain a high accuracy solution while the latter is more efficient to handle the computationally intractable problems. Experimental results on both synthetic data and real magnetic resonance imaging data show the applicability of our algorithms in high-dimensional tensor data processing.     

Underdetermined DOA estimation and blind separation of non-disjoint sources in time-frequency domain based on sparse representation method

This paper deals with the blind separation of nonstation-ary sources and direction-of-arrival （DOA） estimation in the under-determined case, when there are more sources than sensors. We assume the sources to be time-frequency （TF） disjoint to a certain extent. In particular, the number of sources presented at any TF neighborhood is strictly less than that of sensors. We can identify the real number of active sources and achieve separation in any TF neighborhood by the sparse representation method. Compared with the subspace-based algorithm under the same sparseness assumption, which suffers from the extra noise effect since it can-not estimate the true number of active sources, the proposed algorithm can estimate the number of active sources and their cor-responding TF values in any TF neighborhood simultaneously. An-other contribution of this paper is a new estimation procedure for the DOA of sources in the underdetermined case, which combines the TF sparseness of sources and the clustering technique. Sim-ulation results demonstrate the validity and high performance of the proposed algorithm in both blind source separation （BSS） and DOA estimation.