Nano palladium supported on high‐surface‐area metal–organic framework MIL‐101: an efficient catalyst for Sonogashira coupling of aryl and heteroaryl bromides with alkynes

Palladium nanoparticle‐incorporated metal–organic framework MIL‐101 (Pd/MIL‐101) was successfully synthesized and characterized using X‐ray diffraction, nitrogen physisorption, X‐ray photoelectron, UV–visible and infrared spectroscopies, and transmission electron microscopy. The characterization techniques confirmed high porosity and high surface area of MIL‐101 and high stability of nano‐size palladium particles. Pd/MIL‐101 nanocomposite was investigated for the Sonogashira cross‐coupling reaction of aryl and heteroaryl bromides with various alkynes under copper‐free conditions. The reusability of the catalyst was tested for up to four cycles without any significant loss in catalytic activity. Copyright © 2015 John Wiley & Sons, Ltd.     

A self-penetrating and chemically stable zinc (ii)-organic framework as multi-responsive chemo-sensor to detect pesticide and antibiotics in water

Guided by the self-penetrating features can improve the stability of metal organic frameworks (MOFs), an unprecedented 3D self-penetrated framework, {[Zn (tptc)_0.5(bimb)]·H₂O}_n ( NUC-6 , here NUC corresponding to North University of China), with 3D (4,4)-c {8⁶} net, was designed. Benefit from the high chemical stability and excellent luminescent property, NUC-6 can be act as an efficient multi-response chemo-sensor in detecting dichloronitroaniline pesticide and nitrofuran antibiotics in water with the detection limits are 116 ppb for DCN pesticide, 16 ppb for NFT antibiotic, and 12 ppb for NTZ antibiotic. Besides, the mechanisms of luminescence quenching were revealed from the viewpoint of internal filter effect (IFE) and photo-induced electron transfer (PET), implied by the optical spectroscopy and quantum chemical calculation. This work provides a promising strategy to design stable MOFs by improving the self-penetrating features and to expand their practical applications in the detection of organic pollutants in aqueous medium.     

卷积神经网络用于近红外光谱古筝面板木材分级

目前,我国乐器制作行业在古筝面板用木材等级的筛选上主要依赖于技师主观评判,但此法缺少科学理论的依据,效率低,客观性及出材率的提高等方面受到限制,无法满足乐器市场的大量需求。实现古筝面板用木材快速、智能化的分级工作是一个急需解决的课题。近红外光谱非常适用于测量含氢的有机物质。古筝面板木材主要化学成分的化学键均由含氢基团组成,不同等级板材的化学成分存在差异,这些差异反映在近红外光谱中,为判断木材等级提供了可能。同时卷积神经网络对非线性数据具有较强的特征提取能力,所以提出一种应用卷积神经网络模型对光谱数据进行分析的方法,进而判别木材的等级。应用了Savitzky Golay一阶、二阶微分两种预处理方法和核主成分分析、连续投影算法两种数据压缩方法,通过所设计的卷积神经网络模型以样本识别准确率和模型构建过程中的损失值作为判定指标选出最佳预处理和数据压缩方法。为了提高模型提取分析光谱数据的能力和避免过拟合现象,应用了多通道卷积核、批量归一化和early stopping策略,将通过两层卷积层提取的特征信息送入全连接层,从而充分提取剩余信息,通过Softmax函数获得板材的最终预测等级,从而确定了最终模型。最终Savitzky Golay一阶微分和核主成分分析为最佳数据处理方法,同时得出用于区分不同等级的古筝面板用木材的主要关键谱带,分别为1 163~1 243, 1 346~1 375和1 525~1 584 nm。将该模型应用于测试集样本,古筝面板用木材的等级识别准确率为95.5%。实验结果表明所提出的方法可以高效地处理光谱数据,有效识别区分不同等级的古筝面板用木材的关键特征,从而为广阔的乐器市场提供一定的技术支持。     

VRPTW的扰动恢复及其TABU SEARCH算法

本文对带时间窗的车辆路线安排扰动恢复问题进行了讨论,分析了各种可能的扰动:增加减少客户,时间窗、客户需求及路线可行性的扰动,构造了扰动模型.利用禁忌搜索算法对问题进行求解,同时通过对模型参数重新设置,得到了多个满足要求的不同的解,这样使解更具有实际可行性和有效性.     

Hydrothermal Synthesis and Characterization of a Novel Two-dimensional Framework Materials Constructed from Polyoxometalate and Coordination Groups: [H_2Mo_(5.5)V_(10.5)O_(40)(PO_4)][Cu(en)_2]_4·7H_2O

IntroductionPolyoxometalatesarewidelystudiedfortheirin terestingapplicationsincatalysis ,electronicconduc tivity ,magnetism ,nonlinearopticsandmedicine[1— 4 ] .Whilethemechanismofthesynthesisofpolyoxometalatesremainselusiveandisoftende scribedasself assembly ,thereseemstobeanincreas inguseofthecombinationofthehydrothermalmethodandthestructure directingtemplate .There searchwiththismethodhasdemonstratedthatanum beroftransitionmetaloxides ,typicallyreducedmolybdenumoxides ,mixedvalancevanadiumo…     

上海基础房价相关指标及走势的分析与研究

基础房价的相关指标及其走势一直是大众关心的热门话题．本文通过对上海基础房价相关指标的分析，建立了市场房价走势的两个数学模型．模型一：在相关性分析的基础上利用主成分分析消除指标间的共线性，再用回归拟合房价模型并进行预测；模型二：在相关性分析的基础上利用核估计方法预测出房价．继呵对2005年下半年的房价走势进行了预测，得出的结果与实际情况相吻合．     

Reducing structural changes in van Emde Boas' data structure to the lower bound for the dynamic predecessor problem

We consider the problem of maintaining a dynamic ordered set of n integers in a universe U under the operations of insertion, deletion and predecessor queries. The computation model used is a unit-cost RAM, with a word length of w bits, and the universe size is |U|=2^w. We present a data structure that uses O(|U|/log|U|+n) space, performs all the operations in O(loglog|U|) time and needs O(loglog|U|/logloglog|U|) structural changes per update operation. The data structure is a simplified version of the van Emde Boas' tree introducing, in its construction and functioning, new concepts, which help to keep the important information for searching along the path of the tree, in a more compact and organized way.     

一种带时间窗和车辆数目限制的车辆路线问题及其算法

本文提出了带时间窗和车辆数目限制的车辆路线问题的数学模型,针对该问题的特征构造了一种路线生成算法和禁忌搜索算法,并对Solomon提出的C1、R1、RC1类数据集给出了数值运算的结果,实验结果表明算法是有效的.     

A Variable Neighborhood Search for the Multi Depot Vehicle Routing Problem with Time Windows

The aim of this paper is to propose an algorithm based on the philosophy of the Variable Neighborhood Search (VNS) to solve Multi Depot Vehicle Routing Problems with Time Windows. The paper has two main contributions. First, from a technical point of view, it presents the first application of a VNS for this problem and several design issues of VNS algorithms are discussed. Second, from a problem oriented point of view the computational results show that the approach is competitive with an existing Tabu Search algorithm with respect to both solution quality and computation times.     

Randomly censored partially linear single-index models

This paper proposes a method for estimation of a class of partially linear single-index models with randomly censored samples. The method provides a flexible way for modelling the association between a response and a set of predictor variables when the response variable is randomly censored. It presents a technique for “dimension reduction” in semiparametric censored regression models and generalizes the existing accelerated failure-time models for survival analysis. The estimation procedure involves three stages: first, transform the censored data into synthetic data or pseudo-responses unbiasedly; second, obtain quasi-likelihood estimates of the regression coefficients in both linear and single-index components by an iteratively algorithm; finally, estimate the unknown nonparametric regression function using techniques for univariate censored nonparametric regression. The estimators for the regression coefficients are shown to be jointly root-n consistent and asymptotically normal. In addition, the estimator for the unknown regression function is a local linear kernel regression estimator and can be estimated with the same efficiency as all the parameters are known. Monte Carlo simulations are conducted to illustrate the proposed methodology.