甘蔗初压汁锤度近红外光谱分析的波段优选

用近红外透射光谱技术和偏最小二乘法建立甘蔗初压汁锤度的定量分析模型。用多元散射校正和Savitzky-Golay平滑化方法对原谱、一阶导数谱和二阶导数谱进行预处理。选取400—1100nm、1100—1400nm、1550—1850nm、2100—2350nm以及全谱（400—2500nm）5个波段,每个波段分别采用原光谱、一阶导数谱、二阶导数谱。同时调整Savitzky-Golay平滑点数和PLS因子数,通过多次PLS数值实验比较,按照预测效果确定每个模型的最优平滑点数、因子数,再从中选优。结果表明,采用二阶导数谱的1550-1850nm波段的定标效果最好,模型的预测相关系数、预测均方根偏差、相对预测均方根偏差分别为0.896,0.406,1.95%。1550—1850nm波段可以代替全谱波段得到好的定标效果,为设计小型专用近红外分析仪器提供依据。     

基于模糊集理论的承包商资格预审模型

招标方在对承包商的资格预审过程中,需要对承包商的财务状况、技术能力、施工经验、社会信誉等方面进行评审,以确定有资格参加投标的承包商,针对有些评审指标难以量化以及评审过程中决策者主观判断影响最终结果的情况,提出了基于模糊集的资格预审模型,并通过算例验证了该模型的可行性。     

Correlations, risk and crisis: From physiology to finance

We study the dynamics of correlation and variance in systems under the load of environmental factors. A universal effect in ensembles of similar systems under the load of similar factors is described: in crisis, typically, even before obvious symptoms of crisis appear, correlation increases, and, at the same time, variance (and volatility) increases too. This effect is supported by many experiments and observations of groups of humans, mice, trees, grassy plants, and on financial time series.A general approach to the explanation of the effect through dynamics of individual adaptation of similar non-interactive individuals to a similar system of external factors is developed. Qualitatively, this approach follows Selye’s idea about adaptation energy.     

A few remarks on divergent sequences: Rates of divergence II

We continue (and, in a sense, close) our investigation begun in the paper Djur?i? et al. (2009) [10] concerning quotient speed of divergence of sequences of positive real numbers and its relations with selection principles and games. By the way, we show a theorem of the generalized Galambos-Bojani?-Seneta type.     

Hereditary topological diagonalizations and the Menger-Hurewicz Conjectures

We consider the question of which of the major classes defined by topological diagonalizations of open or Borel covers is hereditary. Many of the classes in the open case are not hereditary already in ZFC, and none of them are provably hereditary. This is in contrast with the Borel case, where some of the classes are provably hereditary. Two of the examples are counter-examples of sizes and , respectively, to the Menger and Hurewicz Conjectures, and one of them answers a question of Steprans on perfectly meager sets.

     

Enzyme classification using multiclass support vector machine and feature subset selection

Proteins are the macromolecules responsible for almost all biological processes in a cell. With the availability of large number of protein sequences from different sequencing projects, the challenge with the scientist is to characterize their functions. As the wet lab methods are time consuming and expensive, many computational methods such as FASTA, PSI-BLAST, DNA microarray clustering, and Nearest Neighborhood classification on protein–protein interaction network have been proposed. Support vector machine is one such method that has been used successfully for several problems such as protein fold recognition, protein structure prediction etc. Cai et al. in 2003 have used SVM for classifying proteins into different functional classes and to predict their function. They used the physico-chemical properties of proteins to represent the protein sequences. In this paper a model comprising of feature subset selection followed by multiclass Support Vector Machine is proposed to determine the functional class of a newly generated protein sequence. To train and test the model for its performance, 32 physico-chemical properties of enzymes from 6 enzyme classes are considered. To determine the features that contribute significantly for functional classification, Sequential Forward Floating Selection (SFFS), Orthogonal Forward Selection (OFS), and SVM Recursive Feature Elimination (SVM-RFE) algorithms are used and it is observed that out of 32 properties considered initially, only 20 features are sufficient to classify the proteins into its functional classes with an accuracy ranging from 91% to 94%. On comparison it is seen that, OFS followed by SVM performs better than other methods. Our model generalizes the existing model to include multiclass classification and to identify most significant features affecting the protein function.     

Selection and optimization of mirror structure of off-axis two-mirror afocal system北大核心CSCD

According to the structural characteristics of aspheric off-axis two-mirror optical system, the imaging characteristics of the system were analyzed by using primary aberration theory. Based on the characteristics of different aspheric surfaces, the vector expression of system aberrations was derived. Using the Seidel coefficients, the primary wave aberration of systems were expanded and values of system aberration for different aspheric surface shapes were specifically calculated. After the evaluation index of the off-axis structure was determined, the imaging qualities of different surface shape combinations were compared. Then the optimal surface shape selection method was analyzed by quantitative comparison results. The results show that compared with other reflector combination methods, the spherical aberration, coma and astigmatism of the off-axis double paraboloid system are all 0, the wavefront RMS is much better than λ/14 (λ=0.587 6 μm), and the Strehl ratio is greater than 0.8. According to the calculation results, it not only has a stronger ability to suppress multiple primary aberrations, but also can effectively compress the volume of the system. Copyright ©2022 Journal of Applied Optics. All rights reserved.     

SiPLS-CARS与GA-ELM对哈密瓜冠层叶片含水率的反演估测

传统的叶片含水率检测方法效率低、操作繁琐且是有损的检测,不利于大田哈密瓜叶片含水率的快速获取。为实现对大田哈密瓜生长期进行更精细的田间灌水管理,利用光谱技术分别获取了哈密瓜植株在成长期（M₁）、开花期（M₂）、结果期（M₃）、成熟期（M₄）四个时期内的冠层叶片样本,采用烘干法测得叶片样本的含水率。为提高预测模型的精度和稳定性,首先开展并讨论极限学习机（ELM）模型中的核函数与隐含层神经元个数的选择对ELM模型精度的影响。随后分别利用联合子区间偏最小二乘法（SiPLS）及其与竞争性自适应重加权采样法（CARS）、遗传算法（GA）、连续投影算法（SPA）的组合算法对全波段光谱数据中与叶片含水率相关性高的特征波长进行筛选提取。再分别使用GA与粒子群算法（PSO ）对已经确定最佳核函数与隐含层神经元个数的ELM模型中的输入层与隐含层间的连接权值（W）和隐含层神经元阈值（B）进行优化选择,获取最优且稳定的W与B值,进一步提高模型的稳定性和预测精度。最后将四种特征波长提取算法优选出的特征波长分别进行ELM,GA-ELM,PSO-ELM建模分析,以校正集和预测集的相关系数R_c与R_p为模型评价指标,经过对比分析优选出能准确预测哈密瓜冠层叶片含水率的反演估测模型。采用SiPLS及其与CARS,GA和SPA的组合算法提取特征波长,筛选出的变量数分别为273,20,32和6,占全光谱变量的15.6%,1.2%,1.9%和0.03%。进一步将筛选出的特征波长作为自变量,叶片的含水率作为因变量,建立了ELM的预测模型,最佳预测精度R_p值为0.845 0,预测精度不是很理想。故引入GA与PSO对ELM中随机产生的W与B值进行优化选择。最终,经过研究发现,利用GA优化后的ELM模型结合SiPLS-CARS筛选出的特征波长建立的哈密瓜冠层叶片含水率预测精度最优,故反演叶片含水率的最优建模方式为SiPLS-CARS-GA-ELM,R_c值为0.928 9,R_p值为0.903 2,所建模型精度较高,可为大田哈密瓜冠层叶片的含水率进行快速检测,为田间灌溉管理提供科学依据。     

Par-delà la synthèse : l’auto-organisation

The evolution of the universe from the particle to the thinking organism has taken place through self-organization. Chemistry has a major role to play in understanding these processes leading to the generation of complex matter. Chemistry has developed a highly powerful molecular synthetic chemistry, mastering the combination and recombination of atoms into increasingly complex molecules through selective chemical reactions. Supramolecular chemistry is harnessing intermolecular forces for the generation of informed supramolecular systems and processes through supramolecular synthetic chemistry implementing molecular information carried by electromagnetic interactions. Supramolecular chemistry has been actively exploring systems undergoing self-organization, i.e., systems capable of spontaneously generating well-defined functional supramolecular architectures by self-assembly from their components, under the control of interactional molecular recognition events, thus behaving as programmed chemical systems. Molecular chemistry may similarly take advantage of the selectivity of covalent reactions to assemble complex molecular architectures through self-organization processes implementing functional molecular recognition. Supramolecular/non-covalent and molecular/covalent SELF-ORGANIZATION may thus be considered as the ULTIMATE SYNTHETIC CHEMISTRY, whereby chemical objects at both levels are generated on the basis of recognition processes involving either interactional or reactional features. Illustrations from the supramolecular domain will serve as illustrations. Supramolecular entities as well as molecules containing reversible bonds are able to undergo a continuous change in constitution by reorganization and exchange of building blocks. This capability defines a Constitutional Dynamic Chemistry (CDC) on both the molecular and supramolecular levels. CDC introduces a paradigm shift with respect to constitutionally static chemistry. It takes advantage of dynamic constitutional diversity to allow variation and selection and thus leads towards the emergence of adaptive and evolutive chemistry.