Signature invariants of covering links

We apply the theory of signature invariants of links in rational homology spheres to covering links of homology boundary links. From patterns and Seifert matrices of homology boundary links, we derive an explicit formula to compute signature invariants of their covering links. Using the formula, we produce fused boundary links that are positive mutants of ribbon links but are not concordant to boundary links. We also show that for any finite collection of patterns, there are homology boundary links that are not concordant to any homology boundary links admitting a pattern in the collection.

     

Power and reversal power links for binary regressions: An application for motor insurance policyholders

In binary regression, symmetric links such as logit and probit are usually considered as standard. However, in the presence of unbalancing of ones and zeros, these links can be inappropriate and inflexible to fit the skewness in the response curve and likely to lead to misspecification. This is the case of covering some type of insurance, where it can be observed that the probability of a given binary response variable approaches zero at different rates than it approaches one. Furthermore, when usual links are considered, there is not a skewness parameter associated with the distribution chosen that, regardless of the linear predictor, is easily interpreted. In order to overcome such problems, a proposal for the construction of a set of new skew links is developed in this paper, where some of their properties are discussed. In this context, power links and their reversal versions are presented. A Bayesian inference approach using MCMC is developed for the presented models. The methodology is illustrated considering a sample of motor insurance policyholders selected randomly by gender. Results suggest that the proposed link functions are more appropriate than other alternative link functions commonly used in the literature. Copyright © 2016 John Wiley & Sons, Ltd.     

Automated flow-based anion-exchange method for high-throughput isolation and real-time monitoring of RuBisCO in plant extracts

In this work, a miniaturized, completely enclosed multisyringe-flow system is proposed for high-throughput purification of RuBisCO from Triticum aestivum extracts. The automated method capitalizes on the uptake of the target protein at 4 °C onto Q-Sepharose Fast Flow strong anion-exchanger packed in a cylindrical microcolumn (105 × 4 mm) followed by a stepwise ionic-strength gradient elution (0-0.8 mol/L NaCl) to eliminate concomitant extract components and retrieve highly purified RuBisCO. The manifold is furnished downstream with a flow-through diode-array UV/vis spectrophotometer for real-time monitoring of the column effluent at the protein-specific wavelength of 280 nm to detect the elution of RuBisCO. Quantitation of RuBisCO and total soluble proteins in the eluate fractions were undertaken using polyacrylamide gel electrophoresis (PAGE) and the spectrophotometric Bradford assay, respectively. A comprehensive investigation of the effect of distinct concentration gradients on the isolation of RuBisCO and experimental conditions (namely, type of resin, column dimensions and mobile-phase flow rate) upon column capacity and analyte breakthrough was effected. The assembled set-up was aimed to critically ascertain the efficiency of preliminary batchwise pre-treatments of crude plant extracts (viz., polyethylenglycol (PEG) precipitation, ammonium sulphate precipitation and sucrose gradient centrifugation) in terms of RuBisCO purification and absolute recovery prior to automated anion-exchange column separation. Under the optimum physical and chemical conditions, the flow-through column system is able to admit crude plant extracts and gives rise to RuBisCO purification yields better than 75%, which might be increased up to 96 ± 9% with a prior PEG fractionation followed by sucrose gradient step.     

Co-authorship model with link strength

We generalize a network formation model for co-authorship introducing the possibility of the connections having different link strengths. Different link strengths represent the fact that authors may put different efforts into different collaborations. To evaluate the model, we consider the notions of efficiency and pairwise stability, which are based on a utility function that measures the benefits for an author to belonging to a certain network structure. We divide the analysis in two cases, considering that link strengths are unbounded or bounded. In the first case, we show that if there are more than two authors in the network, then there is no pairwise stable network. In the second case, we show that the pairwise stable networks consist of completely connected disjoint components where essentially all link strengths are maximal. Regarding efficiency, in both cases, if the number of authors is even, then the unique efficient network structure consists of pairs of connected authors.     

Two-dimensional β-ketoenamine linked azo covalent organic frameworks as heterogeneous catalysts for photo-induced RCMP

Photo-induced reversible complexation-mediated polymerization (RCMP) is a green and economical method to prepare polymers with precise molecular weights, narrow molecular weight distributions and functionally active chain ends. Covalent organic frameworks (COFs) are a promising heterogeneous photocatalyst for mediating RCMP due to their adjustable structure, band gap, and porosity. In this work, 1,3,5-triformylphloroglucinol (Tp) and p-azoaniline (Azo) were selected to construct 2D β-ketoenamine linked Tp-Azo-COF as a heterogeneous photocatalyst to trigger RCMP under white light irradiation. A series of polymers with controllable molecular weight and narrow molecular weight distribution were successfully prepared by using Tp-Azo-COF as photocatalysis. On/off light experiments confirmed the good spatiotemporal control feature, and chain expansion experiments demonstrated the high “activity” of polymer chain ends. Furthermore, the mechanistic research elucidated that electron transfer between Tp-Azo-COF and initiator occurred, allowing the formation of reactive radicals to mediate RCMP. Density functional theory calculations revealed that the coordination of iodine on the initiator to catalyst obviously reduced the bond dissociation energy, leading to enhance in the polymerization rate. This work provides a platform for constructing heterogeneous photocatalysts with more efficient and stable to mediate RCMP.     

以提升创新能力为目标的基础力学实践教学初探

创新型基础力学人才的培养既要注重专业知识的学习,又要重视学生思辨、质疑与应用能力的提升。受限于不断削减的学时,传统基础力学课程仍以讲授为主,难以开展有效的实践教学环节。这种重理论轻实践的模式易导致学生学习兴趣下降、综合能力不足。为弥补实践短板,国内高校正逐步开展各类型大学生实践项目。本文以大学生创新训练项目为例,系统介绍项目实施期间教师有效的引导方式,以期为新时期力学人才培养贡献力量。

     

Relative Entropy of Distance Distribution Based Similarity Measure of Nodes in Weighted Graph Data

Many similarity measure algorithms of nodes in weighted graph data have been proposed by employing the degree of nodes in recent years. Despite these algorithms obtaining great results, there may be still some limitations. For instance, the strength of nodes is ignored. Aiming at this issue, the relative entropy of the distance distribution based similarity measure of nodes is proposed in this paper. At first, the structural weights of nodes are given by integrating their degree and strength. Next, the distance between any two nodes is calculated with the help of their structural weights and the Euclidean distance formula to further obtain the distance distribution of each node. After that, the probability distribution of nodes is constructed by normalizing their distance distributions. Thus, the relative entropy can be applied to measure the difference between the probability distributions of the top d important nodes and all nodes in graph data. Finally, the similarity of two nodes can be measured in terms of this above-mentioned difference calculated by relative entropy. Experimental results demonstrate that the algorithm proposed by considering the strength of node in the relative entropy has great advantages in the most similar node mining and link prediction.     

Control of multi-node mobile communications networks with time-varying channels via stability methods

Consider a communications network consisting of mobiles and random external data processes, each destined to a particular destination. Each mobile can serve as a node in the multi-hop path from source to destination. At each mobile the data is queued according to the source destination pair. The quality of the connecting channels are randomly varying. Time is divided into small scheduling intervals. At the beginning of each interval, the channels are estimated and this information is used for the decisions concerning allocation of transmission power and/or time, bandwidth, and perhaps antennas, in a queue and channel-state dependent way. Under a natural (and “almost” necessary) “average flow” condition, stochastic stability methods are used to develop scheduling policies that assure stability. The policies are readily implementable and allow a range of tradeoffs between current rates and queue lengths, under very weak conditions. Because of the non-Markovian nature of the problem, we use the perturbed Stochastic Liapunov function method. The choice of Liapunov function allows a choice of the effective performance criteria. All essential factors are incorporated into a “mean rate” function, so that the results cover many different systems. Extensions concerning acknowledgments, multicasting, non-unique routes, and others are given to illustrate the versatility of the method, and a useful method for getting the a priori routes is discussed.     

The connectivity of a graph on uniform points on [0,1]

A random graph G_n(x) is constructed on independent random points U₁,…,U_n distributed uniformly on [0,1]^d, d1, in which two distinct such points are joined by an edge if the l_∞-distance between them is at most some prescribed value 0<x<1. The connectivity distance c_n, the smallest x for which G_n(x) is connected, is shown to satisfy

(1)

For d2, the random graph G_n(x) behaves like a d-dimensional version of the random graphs of Erdös and Rényi, despite the fact that its edges are not independent: c_n/d_n→1, a.s., as n→∞, where d_n is the largest nearest-neighbor link, the smallest x for which G_n(x) has no isolated vertices.     

洞庭湖区洪涝灾害的形成机制分析

为搞好洞庭湖区洪涝灾害的预测和防灾减灾,促进湖区经济建设,本文对洞庭湖区洪涝灾害的形成机制进行了分析研究.结果表明:80 %特大洪涝灾害的发生在厄尔尼诺年的次年,其内在机制是厄尔尼诺事件所导致的全球气候异常.大气环流的异常是洪涝发生的根本原因,主要表现在有特大洪涝年汛期,位于110°~120°E的西太平洋副高脊线位置都稳定处于19°~24°N之间,且越过24°N的时间大致与城陵矶年最高水位出现时间相吻合;西风带形势稳定;印度低压偏强并持续稳定.洞庭湖区洪涝与湖区、四水流域、长江上游东部区和西部区等广泛地域的降水密切相关,汛期在这4个区域第一次大范围的强降水过程以后20 天各代表站降水量总和的平均值对洞庭湖的洪涝预测具有决定性意义.