Use of chemometrics and mid infrared spectroscopy for the selection of extraction alternatives to reference analytical methods for total fat isolation

Chemometric techniques have been used to compare two methods for fat extraction, namely focused microwave-assisted Soxhlet extraction (FMASE) and dynamic ultrasound-assisted extraction (DUAE), with the conventional Folch method, frequently used as reference. The data generated by a mid infrared spectrometer, after appropriate treatment, provide a simple and effective way for the detection of potential alterations of the fat obtained with the assistance of auxiliary energies, in this case, microwaves and ultrasounds. The results thus obtained are as compared with those from the Folch method, a mild extraction method with a view to finding faster alternatives for routine analysis. Moreover, classification of the samples between cookies and snacks based on extraction kinetics studies was possible, thus demonstrating the importance of these studies for the development of analytical methods. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were used for both purposes, namely detection of alterations and classification of the samples as a function of their extraction kinetics, while K Nearest Neighbours (KNN) and Soft Independent Modelling of Class Analogy (SIMCA), based on PCA, models were generated in order both to predict the extraction kinetics of unknown samples, thus adjusting the extraction time as a function of the matrix, and find out explanation to the different extraction kinetics.     

Fuzzy structure-activity relationships

While quantitative structure-activity relationships attempt to predict the numerical value of the activities, it is found that statistically good predictors do not always do a good job of qualitatively determining the activity. This study shows how Fuzzy classifiers can be used to generate Fuzzy structure-activity relationships which can more accurately determine whether or not a compound will be highly inactive, moderately inactive or active, or highly active. Four examples of these classifiers are presented and applied to a well-studied activity dataset.     

A Structure-activity Relationship （SAR） Study of Fluoroquinolones with Biological Activity against Anti-S.pneumoniae

1INTRODUCTION Streptococcus pneumoniae is a key pathogen in many respiratory tract infections.In a Canada-wide surveillance study published in1999,it was reported that21.2%of pneumococcal tested were interme-diately susceptible or resistant to penicillin.As the newer respiratory fluoroquinolones are active aga-inst both penicillin-susceptible and penicillin-resis-tant isolates of S.pneumoniae,they will be increa-singly important in the future treatment of infections caused by this pathoge…     

Wavelength selection framework for classifying food and pharmaceutical samples into multiple classes

Near infrared (NIR) spectroscopy is an efficient, low‐cost analytical technique widely applied to identify the origin of food and pharmaceutical products. NIR spectra‐based classification strategies typically use thousands of equally spaced wavelengths as input information, some of which may not carry relevant information for product classification. When that is the case, the performance of predictive and exploratory multivariate techniques may be undermined by such noisy information. In this paper, we propose an iterative framework for selecting subsets of NIR wavelengths aimed at classifying samples into categories. For that matter, we integrate Principal Components Analysis (PCA) and three classification techniques: k‐Nearest Neighbor (KNN), Probabilistic Neural Network (PNN) and Linear Discriminant Analysis (LDA). PCA is first applied to NIR data, and a wavelength importance index is derived based on the PCA loadings. Samples are then categorized using the wavelength with the highest index and the classification accuracy is calculated; next, the wavelength with the second highest index is inserted into the dataset and a new classification is performed. This forward‐based iterative procedure is carried out until all original wavelengths are inserted into the dataset used for classification. The subset of wavelengths leading to the maximum accuracy is chosen as the recommended subset. Our propositions performed remarkably well when applied to four datasets related to food and pharmaceutical products. Copyright © 2016 John Wiley & Sons, Ltd.     

以商圈为中心的O2O动态外卖配送路径优化模型与算法

针对线上到线下(Online to Offline,O2O) 外卖路径优化问题,综合考虑其动态配送需求、货物区分等特点以及时间窗、载货量等约束条件,将商圈看作配送中心,将快递员数量与快递员总行驶时间作为最小化目标,提出了以商圈为中心的O2O动态外卖配送路径优化模型。采用周期性处理新订单的方法将相应的快递员路径的动态调整问题转化为一系列静态TSP子问题,设计了一种分阶段启发式实时配送路径优化算法框架,并给出了一个具体算法和一个数值计算实例。在VRP通用算例的基础上,以商圈为中心生成测试算例,对本文算法进行仿真实验,并与其他算法比较。结果表明：本文算法能充分利用新订单附近的快递员进行配送,并优化其配送路径,有效减少了快递员数量与快递员总行驶时间。     

Synthesis and physical properties of Ca- and Ta-modified (K,Na)NbO3 lead-free piezoelectric ceramics

Polycrystalline samples of lead-free Ca and Ta co-substituted potassium sodium niobate (K_0.5Na_0.5NbO_3, KNN) ceramics have been prepared by solid state reaction technique. X-ray diffraction showed formation of a single-phase perovskite structure with orthorhombic symmetry. Substitution inhibits the grain growth, improves densification and decreases the ferro-paraelectric phase transition temperature. Temperature dependent dielectric permittivity studies demonstrate significant decrease in peak-permittivity values in the substituted samples. Bulk longitudinal piezoelectric coefficient is significantly enhanced, up to ～155 pC/N for (K_0.48Na_0.48Ca_0.02)(Nb_0.85Ta_0.15O₃) as compared to 95 pC/N for pristine KNN ceramic. Local piezoelectric properties have been observed by piezoresponse force microscopy (PFM) technique. Distinct piezocontrast was studied in both vertical and in-plane modes of PFM for all samples. The samples exhibit self-polarization effect in the unpoled state and effective local vertical piezoelectric coefficient was the largest in Ca and Ta co-substituted sample whereas the in-plane piezoelectric coefficient was maximum for Ca-substituted KNN sample. These studies are important for using substituted lead free KNN materials in various piezoelectric applications.     

在SDSS DR8恒星光谱中自动搜寻稀有天体

SDSS DR8海量光谱中包含许多有研究价值的稀有天体,如特殊白矮星(DZ,DQ,DC)、碳星、白矮主序双星、激变变星等,如何在海量光谱中自动搜寻稀有天体有着极其重要的意义。提出一种基于核密度估计和K-近邻(K-nearest neighbor, KNN)相结合的方法在SDSS DR8 信噪比大于5的546 383个恒星光谱中搜寻稀有天体。首先对光谱进行高斯核密度估计,选取概率最小的5 000个光谱作为稀有类,概率最大的300 000个光谱作为普通类,然后进行KNN分类,同时也将5 000个稀有光谱的K个最近邻也作为稀有的天体,结果共有21 193条光谱。为了方便分析,对这些光谱聚类后进行人工检查。这些光谱主要包括由于数据缺失、红化、流量定标不准引起的问题光谱、行星状星云、没有物理联系的光谱双星、类星体、特殊白矮星(DZ,DQ,DC)、碳星、白矮主序双星、激变变星等。通过和SIMBAD,NED,ADS及一些主要的文献交叉验证,我们新发现了3个DZ白矮星、1个白矮主序双星、2个伴星为G型星的激变变星,3个激变变星的候选体、6个DC白矮星,1个DC白矮星候选体和1个 BL Lacertae(BL lac)候选体。还发现了1个有CaⅡ三重发射线和MgⅠ发射线的DA白矮星和1个光谱上表现出发射线的晚M恒星但测光图上像是一个星云或星系。     

Growth and properties of Li,Ta modified (K,Na)NbO3 lead‐free piezoelectric single crystals

Li, Ta modified (K,Na)NbO₃ single crystals with the size of 18 mm × 18 mm × 10 mm were successfully grown by top‐seeded solution growth method, with orthorhombic–tetra‐gonal phase transition temperature ～79 °C and Curie temperature ～276 °C. The electromechanical coupling factors k₃₃ and k_t were found to be ～88% and ～65%, respectively. The piezoelectric coefficient d₃₃ for the [001]_c poled crystals reached 255 pC/N. In addition, the electromechanical coupling factor exhibited high stability over the temperature range of –50 °C to 70 °C, making these lead free crystals good candidates for electromechanical applications. (© 2014 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

脉冲激光沉积BNT和KNN系陶瓷薄膜的比较研究

利用脉冲激光沉积技术(PLD),在不同的制备工艺条件下,分别在Pt/Ti/SiO2/Si基片上制备了Bi0.5Na0.5TiO3(BNT)系列的Bi0.5(Na0.7K0.2Li0.1)0.5TiO3(BNKLT)和K0.5Na0.5NbO3(KNN)系列的Li0.04(Na0.5K0.5)0.96(Nb0.775Ta0.225)O3(KNNLT)无铅压电陶瓷薄膜,并利用X射线衍射仪(XRD)、扫描电镜(SEM)和原子力显微镜(AFM)对薄膜的晶体结构及表面形貌进行了比较研究.研究结果表明:薄膜的衬底温度、沉积室的氧气压力和薄膜的热处理温度对BNT和KNN薄膜结构和形貌都有较大影响,且影响程度不同;在最佳制备工艺参数下,利用PLD制备的BNT和KNN无铅压电陶瓷薄膜都具有精细的表面结构.