Statistical discrimination of steroid profiles in doping control with support vector machines

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society.     

Discrimination of Beers by Cyclic Voltammetry Using a Single Carbon Screen-printed Electrode

A fast, simple and costless methodology without sample pre-treatment is proposed for the discrimination of beers. It is based on cyclic voltammetry (CV) using commercial carbon screen-printed electrodes (SPCE) and includes a correction of the signals measured with different SPCE units. Data are submitted to partial least squares discriminant analysis (PLS−DA) and support vector machine discriminant analysis (SVM−DA), which allow a reasonable classification of the beers. Also, CV data from beers can be used to predict their alcoholic degree by partial least squares (PLS) and artificial neural networks (ANN). In general, non-linear methods provide better results than linear ones.     

Year Discrimination of Mild Aroma Chinese Liquors Using Three-Dimensional Fluorescence Spectroscopy Combined with Parallel Factor and Neural NetworkSCIEI北大核心CSCD

Three-dimensional fluorescence spectroscopy coupled with parallel factor analysis and neural network was applied to the year discrimination of mild aroma Chinese liquors. The excitation-emission fluorescence matrices (EEMs) of 120 samples with various years were measured by FLS920 fluorescence spectrometer. The trilinear decomposition of the data array was performed and the loading scores of and the excitation-emission profiles of four components were also obtained. The scores were employed as the inputs of the BP neural networks and the PARAFAC-BP identification model was constructed. 10 samples were collected from 10, 20 and 30 years of liquors respectively, and 30 samples were selected as the test sets. The remaining 90 samples were used as the training sets to build the training model. The year prediction of unknown samples was also carried out, and the prediction accuracy was 90%, 100% and 100%, respectively. Meanwhile, the discrimination analysis method and the multi way partial least squares discriminant analysis were compared, namely PARAFAC-BP and NPLS-DA. The results indicated that parallel factor combined with the neural network (PARAFAC-BP) has higher prediction accuracy. The proposed method can effectively extract the spectral characteristics, and also reduce the dimension of the input variables of neural network. A good year discrimination result was finally achieved.     

费谢尔判别法鉴别原油/燃料油

以多环芳烃作为变量,建立了原油、燃料油属性鉴别的费谢尔判别法。分别测定了来自不同国家和地区的26个原油样品和25个燃料油样品中8种多环芳烃的含量,并将它们作为判别变量。借助SPSS 16.0进行费谢尔判别分析,建立费谢尔判别函数。将未知样品的判别变量值代入后,可以快速地得知样品的类别。结果表明,以多环芳烃作为判别变量进行原油、燃料油费谢尔判别快速而准确。     

长江下游下蜀黄土的稀土元素物源判别

通过对长江下游镇江、福家湾、新港、芜湖、福路镇等地区下蜀黄土中稀土元素的研究,结合长江古漫滩堆积物及北方黄土沉积物,对下蜀黄土进行了物源判别,得出：下蜀黄土与长江河漫滩之间的各稀土元素的 DF 值绝大部分小于0．2,表现出在各个稀土元素上与河漫滩的接近程度较大,而与北方黄土接近程度较小;由物源指数 PI 计算得出,新港、福路镇、镇江下蜀黄土 PI 值均在0．2附近,表现出下蜀黄土与河漫滩在稀土元素总体上的相似程度极高,物源判别为长江河漫滩;福家湾下蜀黄土物源判别为北方黄土,北方黄土对其有一定影响。总体上,长江下游下蜀黄土受到北方黄土与河漫滩的影响,其中以长江河漫滩影响为主。     

Intracellular Entropy‐Driven Multi‐Bit DNA Computing for Tumor Progression Discrimination

Tumor progressions such as metastasis are complicated events that involve abnormal expression of different miRNAs and enzymes. Monitoring these biomolecules in live cells with computational DNA nanotechnology may enable discrimination of tumor progression via digital outputs. Herein, we report intracellular entropy‐driven multivalent DNA circuits to implement multi‐bit computing for simultaneous analysis of intracellular telomerase and microRNAs including miR‐21 and miR‐31. These three biomolecules can trigger respective DNA strand displacement recycling reactions for signal amplification. They are visualized by fluorescence imaging, and their signal outputs are encoded as multi‐bit binary codes for different cell types. The results can discriminate non‐tumorigenic, malignant and metastatic breast cells as well as respective tumors. This DNA computing circuit is further performed in a microfluidic chip to differentiate rare co‐cultured cells, which holds a potential for the analysis of clinical samples.     

中学化学教学中的科学思维与逻辑辨析

化学是一门具有创造性的基础科学,是环境、生命、医药、材料等科学的基础,在思维逻辑上彰显和蕴含了丰富的科学思维方法。系统总结化学科学思维方法,可以有效破解中学化学学习中的“繁,难,乱”。在多年的教学实践中,提出了化学科学多向思维方法体系,强调多层次思维过程中对多因素的立体逻辑思维辨析。重点介绍了与中学化学教学相关的零阶、初阶、中阶和高阶逻辑思维辨析的内涵,期望化学教学中重视化学思维逻辑过程,实现化学教与学在思维模式上的深层次发展与提升。     

共焦显微拉曼光谱技术在墨迹鉴定方面的应用

利用共焦显微拉曼光谱技术,用可见514.5nm和紫外325nm激光器作激发光源,分别测试了不同品牌的黑色圆珠笔,蓝色圆珠笔和黑色签字笔墨迹的拉曼谱图。在可见514.5nm激光器的激发下,黑色和蓝色圆珠笔墨迹都呈现了丰富的拉曼特征峰而黑色签字笔仅出现了碳峰的信号;此时改换325nm激光器来激发,发现黑色签字笔墨迹出现了清晰的拉曼特征谱峰。通过实验数据对比发现:同一类型且不同品牌笔的墨迹拉曼特征谱峰也存在一定的差异,同一种品牌墨迹的拉曼峰都保持了相对的稳定性。实验结果将为鉴定签字笔和圆珠笔油墨种类提供了法庭科学依据。它的最大优点就在于对样品的无损性,其次还有快速、无需对样品预处理和测试方法简单等。     

Chemometric Tools to Point Out Benchmarks and Chromophores in Pigments through Spectroscopic Data Analyses

Spectral preprocessing data and chemometric tools are analytical methods widely applied in several scientific contexts i.e., in archaeometric applications. A systematic classification of natural powdered pigments of organic and inorganic nature through Principal Component Analysis with a multi-instruments spectroscopic study is presented here. The methodology allows the access to elementary and molecular unique benchmarks to guide and speed up the identification of an unknown pigment and its recipe. This study is conducted on a set of 48 powdered pigments and tested on a real-case sample from the wall painting in S. Maria Delle Palate di Tusa (Messina, Italy). Four spectroscopic techniques (X-ray Fluorescence, Raman, Attenuated Total Reflectance and Total Reflectance Infrared Spectroscopies) and six different spectrometers are tested to evaluate the impact of different setups. The novelty of the work is to use a systematic approach on this initial dataset using the entire spectroscopic energy range without any windows selection to solve problems linked with the manipulation of large analytes/materials to find an indistinct property of one or more spectral bands opening new frontiers in the dataset spectroscopic analyses.