含一般模糊弹性约束的广义模糊变量线性规划

建立并讨论了一类含有一般模糊弹性约束的广义模糊变量线性规划问题.首先,简单介绍了结构元方法并对结构元加权排序中权函数表征决策者风险态度进行了深入分析.然后选取风险中性的决策者来定义序关系,应用Verdegay模糊线性规划方法将含一般模糊弹性约束的广义模糊变量线性规划转化经典的线性规划问题,简化了原问题的求解.最后通过数值算例进一步说明了该方法的有效性.     

Hierarchical fractal‐structured allophanate‐derived network formation in bulk polyurethane synthesis

Polyurethanes are among the most applied and researched polymers worldwide. Nevertheless, polyurethane synthesis is accompanied by a side‐reaction occurring between isocyanate groups and the secondary nitrogen of already formed urethane groups, leading to the formation of crosslinking allophanates. This inevitably requires the development of highly diagnostic direct analytical methods that can be performed in the solid state of the polymer. The present research focused on the direct investigation and diagnostic determination of the chemical structure formation in bulk polyurethane synthesis, using a combination of Fourier transform infrared and solid‐state ¹³C nuclear magnetic resonance analysis. Polyurethane syntheses were performed in bulk and designed as to obtain significantly strong diagnostic analytical measurements signals for the accurate identification of each of the investigated chemical structures. The present research results led to the conclusive analytical identification of allophanate formation during polyurethane synthesis. In addition, the occurrence of a new reaction mechanism was discovered in the present research. It was demonstrated in the present research that this newly described reaction occurs via the further reaction of the allophanate secondary nitrogen with an isocyanate group, the reaction creating a tertiary nitrogen and an additional reactive secondary nitrogen, and so on, in a consecutive step progression, leading to the formation of a 3‐dimensional hierarchical fractal‐like crosslinked polymeric structure. Solid‐state ¹³C nuclear magnetic resonance analysis results were highly consistent with the Fourier transform infrared results. The discovery of this newly described reaction can facilitate the optimization of industrial processes and potentially opens a new door to the development of a vast variety of biomedical and nanotechnology applications.     

A fitting algorithm for real coefficient polynomial rooting

A new algorithm for computing all roots of polynomials with real coefficients is introduced. The principle behind the new algorithm is a fitting of the convolution of two subsequences onto a given polynomial coefficient sequence. This concept is used in the initial stage of the algorithm for a recursive slicing of a given polynomial into degree-2 subpolynomials from which initial root estimates are computed in closed form. This concept is further used in a post-fitting stage where the initial root estimates are refined to high numerical accuracy. A reduction of absolute root errors by a factor of 100 compared to the famous Companion matrix eigenvalue method based on the unsymmetric QR algorithm is not uncommon. Detailed computer experiments validate our claims.     

Mathematical attitudes and semantic differentials

The semantic differential—one approach to attitude measurement— basically records a combination of a person's associations with a particular concept with a scaling procedure. This paper considers the implications of such a device for teachers of mathematics.     

Logging damage and injured tree mortality in tropical forest management

Using insights from the forest ecology literature, we analyze the effect of injured trees on stand composition and carbon stored in above‐ground biomass and the implications for forest management decisions. Results from a Faustmann model with data for a tropical forest on Kalimantan show that up to 50% of the basal area of the stand before harvest can consist of injured trees. Considering injured trees leads to an increase in the amount of carbon in above‐ground biomass of up to 165%. These effects are larger under reduced impact logging than under conventional logging. The effects on land expectation value and cutting cycle are relatively small. The results suggest that considering injured trees in models for tropical forest management is important for the correct assessment of the potential of financial programs to store carbon and conserve forest ecosystem services in managed tropical forests, such as reducing emissions from deforestation and forest degradation and payment for ecosystem services. Recommendations for Resource Managers

• Considering the role of injured trees is important for managing tropical forests
• These trees can cover up to 50% of basal area and contain more than 50% of the carbon stored in above‐ground biomass
• Reduced impact logging leads to a larger basal area of injured trees and more carbon stored in injured trees than conventional logging
• Injured trees play an important role when assessing the potential for carbon storage in the context of payment for forest ecosystem services.

     

Blind separation of fluorescence spectra using sparse non‐negative matrix factorization on right hand factor

Sparse non‐negative matrix factorization on right side factor (SNMF/R) has better performance in feature extraction than non‐negative matrix factorization. In this work, SNMF/R was first used to separate the overlapped three‐dimensional fluorescence spectra of polycyclic aromatic hydrocarbons mixtures in pure water, lake water, and river water, respectively. It is found that the similarity coefficients between the acquired three‐dimensional spectra and the corresponding reference spectra with random initials are all above 0.80; the recognition rate of SNMF/R is higher than that of PARAFAC and non‐negative matrix factorization algorithms, especially in the case of lake water and river water samples. In addition, SNMF/R does not need any initialization scheme designing during spectra separation. These results demonstrate that SNMF/R is an appropriate algorithm to separate the overlapped fluorescence spectra of polycyclic aromatic hydrocarbons in aquatic environment accurately and effectively. Copyright © 2015 John Wiley & Sons, Ltd.     

Explicit–implicit mapping approach to nonlinear blind separation of sparse nonnegative dependent sources from a single mixture: pure component extraction from nonlinear mixture mass spectra

The nonlinear, nonnegative single‐mixture blind source separation problem consists of decomposing observed nonlinearly mixed multicomponent signal into nonnegative dependent component (source) signals. The problem is difficult and is a special case of the underdetermined blind source separation problem. However, it is practically relevant for the contemporary metabolic profiling of biological samples when only one sample is available for acquiring mass spectra; afterwards, the pure components are extracted. Herein, we present a method for the blind separation of nonnegative dependent sources from a single, nonlinear mixture. First, an explicit feature map is used to map a single mixture into a pseudo multi‐mixture. Second, an empirical kernel map is used for implicit mapping of a pseudo multi‐mixture into a high‐dimensional reproducible kernel Hilbert space. Under sparse probabilistic conditions that were previously imposed on sources, the single‐mixture nonlinear problem is converted into an equivalent linear, multiple‐mixture problem that consists of the original sources and their higher‐order monomials. These monomials are suppressed by robust principal component analysis and hard, soft, and trimmed thresholding. Sparseness‐constrained nonnegative matrix factorizations in reproducible kernel Hilbert space yield sets of separated components. Afterwards, separated components are annotated with the pure components from the library using the maximal correlation criterion. The proposed method is depicted with a numerical example that is related to the extraction of eight dependent components from one nonlinear mixture. The method is further demonstrated on three nonlinear chemical reactions of peptide synthesis in which 25, 19, and 28 dependent analytes are extracted from one nonlinear mixture mass spectra. The goal application of the proposed method is, in combination with other separation techniques, mass spectrometry‐based non‐targeted metabolic profiling, such as biomarker identification studies. Copyright © 2015 John Wiley & Sons, Ltd.     

Pt 含量对Co@Pt/C核壳结构催化剂性能的影响

采用两步还原法制得Co@Pt/C核壳结构催化剂, 其中Co与Pt 的总质量分数为20%. 通过改变金属前驱体的用量, 制备了不同Co:Pt 原子比的Co@Pt/C 催化剂, 以20% (w) Co@Pt(1:1)/C 与20% (w) Co@Pt(1:3)/C 表示. 采用透射电镜(TEM)、光电子射线能谱分析(XPS)、循环伏安(CV)、线性扫描伏安(LSV)等方法考察了其结构与性能, 并与实验室早先制备的40% (w) Co@Pt/C 催化剂进行了比较. 自制20% Co@Pt(1:1)/C 与20% Co@Pt(1:3)/C 催化剂的金属颗粒直径约为2.2-2.3 nm, 在碳载体上分散均匀, 粒径分布范围较窄, 电化学活性比表面积(ECSA)分别为56 和60 m²·g^-1, 均超过商用催化剂20% Pt/C(E-tek) (ECSA=54 m²·g^-1). 20%Co@Pt(1:1)/C 与20% Co@Pt(1:3)/C 的半波电位相较于40% Co@Pt(1:1)/C 和40% Co@Pt(1:3)/C 均向正向移动, 表现出更好的氧还原(ORR)催化活性, 并有望降低催化剂的成本, 在质子交换膜燃料电池领域表现出良好的应用前景.     

Topography and field effects in the inner side of microvia hole using ToF‐SIMS

We have developed a simple and powerful method, which is called ‘angled sample holder method’, to characterize a topographic structured sample such as microsized via hole of ball grid array using time‐of‐flight SIMS. The diameter of via holes was 100 µm and the depth was 70 µm. To remove the shaded area by incidence primary ion beam and to extract secondary ions from the bottom of a via hole, several types of angled sample holders with compensation steering plate were applied on the basis of simulation results using SIMION code. And the analyses using angled sample holder method enabled us to characterize the bottom and side wall of a via hole in clear. Copyright © 2014 John Wiley & Sons, Ltd.