色谱分析发展简史及其给我们的启示

简要回顾了色谱分析技术的发展史，厘清了某些中文文献中的不妥表述。通过分析色谱发展过程中的几个重要突破，总结了在科学技术创新方面给我们的启示：（1）基础研究始终是色谱技术进步的源泉；（2）社会发展的需求是各种色谱方法创新的驱动力；（3）学科交叉是色谱分析技术创新的重要途径；（4）不懈坚持和勇于探索是科学技术创新的必要条件。最后对色谱发展的前景作了展望。     

物理有机化学的现状和在我国的进展

本文评述了当前物理有机化学各个主要领域的研究工作,指出物理有机化学是甚为重要的基础学科,数十年来在深度和广度两方面皆有很大的发展。回顾了我国第一届和第二届物理有机讨论会情况,扼要地介绍了物理有机化学在我国的主要进展。     

Expert systems for method development and validation in HPLC

ESCA, Expert Systems Applied to Chemical Analysis, started its research in March 1987, with the aim of building prototype expert systems for HPLC method development. Results of this research have been published as the work has progressed. The project is now completed and this paper summarises some of the overall project conclusions. Seven different expert systems have been built which tackle problems throughout the process of method development, four stand-alone systems and three integrated systems. The object of ESCA was to evaluate the applicability of expert system technology to analytical chemistry and not all the systems were built for commercial uses. Many of the systems tackle problems specific to one or more of the partners and thus may not be useful outside this environment. However, the results of the work are still pertinent to analysts wishing to build their own systems. These results are described, however, the emphasis of the paper is on those systems developed for method validation.Method validation for HPLC is a complex task which requires many characteristics of the method to be tested, e.g. accuracy, precision, etc. The expert systems built within ESCA concern the validation of precision. Two systems were developed for repeatability testing and ruggedness testing. The method validation process can be divided into several discrete stages, these include: (1) The selection of the method feature to test, for instance which factors can influence the ruggedness of a method. (2) The definition of a test procedure, for instance an efficient statistical design. (3) The execution of experiments and the interpretation of results. (4) A diagnosis of any observed problem. This paper describes these two systems in some detail and summarises some of the results obtained from their evaluation. It concludes that expert systems can be useful in solving analytical problems and the integration of several expert systems can provide extremely powerful tools for the analyst.     

环氧化橡胶及其合金的研究与应用

综述了国内外环氧化橡胶及其合金的研究现状和应用趋势,重点介绍了环氧化天然橡胶、环氧化聚丁二烯、环氧化苯乙烯-丁二烯-苯乙烯三嵌段共聚物及其合金的优点,以及影响其物理机械性能的因素和环氧化橡胶的发展方向。     

Development of new and robust LC-MS method for simultaneous quantification of polyphenols from Sambucus ebulus fruits

A new and simple LC-MS method for analysis of flavonoids from Sambucus ebulus berry extracts was developed and validated. Successfully were quantitated seven polyphenols: epicatechin, epigallocatechin gallate, rutin, resveratrol, myricetin, quercetin, and kaempferol.

Two detectors, working in parallel, were used: photodiode-array and single quadrupole mass-detector. The mass detection was used for identification and quantification of the analytes, while the diode-array detector was as confirmation tool. The following m/z were tracked: 457.15 (epigallocatechin gallate); 289.06 (epicatechin); 609.13 (rutin); 227.05 (resveratrol); 317.0 (myricetin); 301.02 (quercetin); 285.02 (kaempferol). For optimization the chromatographic separation three wavelengths 205?nm, 305?nm, 272?nm were monitored. The method was capable to detect in one run compounds with no UV or fluorescence chromophore and with very similar structures, such as plant polyphenols. The linearity was from 0.05?mg/L to 50?mg/L (R² 0.9962–0.9987). The recoveries for all tested analytes were between 81.6% and 104.7%.

The method was applied for analysis of crude extract of Sambucus ebulus ripe fruits. Three major polyphenols – epicatechin (0.84?mg/100gFW), quercetin (0.15?mg/100gFW) and kaempferol (0.05?mg/100gFW) were identified and quantified.

The proposed method could be successfully used for routine analysis of epigallocatechin gallate, epicatechin, rutin, resveratrol, myricetin, quercetin, and kaempferol in Sambucus ebulus extracts.     

光催化研究与发展的文献计量分析

对ＣＡ１９６１－１９９６年期间卷双期号期刊中收录的与光催化有关的各种文献进行了详细的统计,结果表明,光催化研究正处于快速的发展期,以消除环境污染为目的应用研究是该快速发展期中的主题,日本,美国,俄罗斯和中国发表文献量居世界前４位。     

含水合物沉积物多相渗流特性研究进展

天然气水合物作为一种储量大、无污染的清洁能源近些年受到了广泛关注.近20年来,中国进行了较大范围的陆海域天然气水合物储层勘探与储量预测. 2017年,中国地质调查局牵头对南海神狐海域的天然气水合物进行了基于降压渗流原理的试验性开采.国内外已进行的水合物试采工程面临着气体产量低、出砂较多等问题,其最主要的原因之一是开发过程中沉积物内复杂多相渗流机理尚不明晰.本文综述了平行毛细管模型、Kozeny模型等广泛应用于天然气水合物开发渗流分析的理论模型,对比分析了水合物开发多尺度渗流过程模拟方法,简述了国内外含水合物沉积物渗透率测试、渗流过程中沉积物物性演变以及水合物开采室内模拟等方面的渗流实验进展,总结了矿场尺度的天然气水合物储层开采过程中产气数值模拟手段,展望了多相渗流模型、储层原位含水合物样品室内测试及结构与物性演化、矿场尺度数值模拟与水平井压裂技术等应用研究的未来方向与挑战.     

Predicting Bitcoin (BTC) Price in the Context of Economic Theories: A Machine Learning Approach

Bitcoin (BTC)—the first cryptocurrency—is a decentralized network used to make private, anonymous, peer-to-peer transactions worldwide, yet there are numerous issues in its pricing due to its arbitrary nature, thus limiting its use due to skepticism among businesses and households. However, there is a vast scope of machine learning approaches to predict future prices precisely. One of the major problems with previous research on BTC price predictions is that they are primarily empirical research lacking sufficient analytical support to back up the claims. Therefore, this study aims to solve the BTC price prediction problem in the context of both macroeconomic and microeconomic theories by applying new machine learning methods. Previous work, however, shows mixed evidence of the superiority of machine learning over statistical analysis and vice versa, so more research is needed. This paper applies comparative approaches, including ordinary least squares (OLS), Ensemble learning, support vector regression (SVR), and multilayer perceptron (MLP), to investigate whether the macroeconomic, microeconomic, technical, and blockchain indicators based on economic theories predict the BTC price or not. The findings point out that some technical indicators are significant short-run BTC price predictors, thus confirming the validity of technical analysis. Moreover, macroeconomic and blockchain indicators are found to be significant long-term predictors, implying that supply, demand, and cost-based pricing theories are the underlying theories of BTC price prediction. Likewise, SVR is found to be superior to other machine learning and traditional models. This research’s innovation is looking at BTC price prediction through theoretical aspects. The overall findings show that SVR is superior to other machine learning models and traditional models. This paper has several contributions. It can contribute to international finance to be used as a reference for setting asset pricing and improved investment decision-making. It also contributes to the economics of BTC price prediction by introducing its theoretical background. Moreover, as the authors still doubt whether machine learning can beat the traditional methods in BTC price prediction, this research contributes to machine learning configuration and helping developers use it as a benchmark.     

The Advantage of Case-Tailored Information Metrics for the Development of Predictive Models,Calculated Profit in Credit Scoring

This paper compares model development strategies based on different performance metrics. The study was conducted in the area of credit risk modeling with the usage of diverse metrics, including general-purpose Area Under the ROC curve (AUC), problem-dedicated Expected Maximum Profit (EMP) and the novel case-tailored Calculated Profit (CP). The metrics were used to optimize competitive credit risk scoring models based on two predictive algorithms that are widely used in the financial industry: Logistic Regression and extreme gradient boosting machine (XGBoost). A dataset provided by the American Fannie Mae agency was utilized to conduct the study. In addition to the baseline study, the paper also includes a stability analysis. In each case examined the proposed CP metric that allowed us to achieve the most profitable loan portfolio.     

Development of Novel Pyridine-Thiazole Hybrid Molecules as Potential Anticancer Agents

Novel pyridine-thiazole hybrid molecules were synthesized and subjected to physico-chemical characterization and screening of their cytotoxic action towards a panel of cell lines derived from different types of tumors (carcinomas of colon, breast, and lung, glioblastoma and leukemia), and normal human keratinocytes, for comparison. High antiproliferative activity of the 3-(2-fluorophenyl)-1-[4-methyl-2-(pyridin-2-ylamino)-thiazol-5-yl]-propenone 3 and 4-(2-{1-(2-fluorophenyl)-3-[4-methyl-2-(pyridin-2-ylamino)-thiazol-5-yl]-3-oxopropylsulfanyl}-acetylamino)-benzoic acid ethyl ester 4 was revealed. The IC₅₀ of the compound 3 in HL-60 cells of the acute human promyelocytic leukemia was 0.57 µM, while in the pseudo-normal human cell lines, the IC₅₀ of this compound was >50 µM, which suggests that the compounds 3 and 4 might be perspective anticancer agents. The detected selectivity of the derivatives 3 and 4 for cancer cell lines inspired us to study the mechanisms of their cytotoxic action. It was shown that preincubation of tumor cells with Fluzaparib (inhibitor of PARP1) reduced the cytotoxic activity of the derivatives 3 and 4 by more than twice. The ability of these compounds to affect DNA nativity and cause changes in nucleus morphology allows for the suggestion that the mechanism of action of the novel pyridine-thiazole derivatives might be related to inducing the genetic instability in tumor cells.