EGFAFS: A Novel Feature Selection Algorithm Based on Explosion Gravitation Field Algorithm

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As a result, they are not suitable to be processed by simple methods, such as the filter-based method. In this study, we propose a novel feature selection algorithm based on the Explosion Gravitation Field Algorithm, called EGFAFS. To reduce the dimensions of the feature space to acceptable dimensions, we constructed a recommended feature pool by a series of Random Forests based on the Gini index. Furthermore, by paying more attention to the features in the recommended feature pool, we can find the best subset more efficiently. To verify the performance of EGFAFS for FS, we tested EGFAFS on eight gene expression datasets compared with four heuristic-based FS methods (GA, PSO, SA, and DE) and four other FS methods (Boruta, HSICLasso, DNN-FS, and EGSG). The results show that EGFAFS has better performance for FS on gene expression data in terms of evaluation metrics, having more than the other eight FS algorithms. The genes selected by EGFAGS play an essential role in the differential co-expression network and some biological functions further demonstrate the success of EGFAFS for solving FS problems on gene expression data.     

Na2S-Mediated One-Pot Selective Deoxygenation of α-Hydroxyl Carbonyl Compounds including Natural Products

A practical method for the deoxygenation of α-hydroxyl carbonyl compounds under mild reaction conditions is reported here. The use of cheap and easy-to-handle Na₂S·9H₂O as the reductant in the presence of PPh₃ and N-chlorosuccinimide (NCS) enables the selective dehydroxylation of α-hydroxyl carbonyl compounds, including ketones, esters, amides, imides and nitrile groups. The synthetic utility is demonstrated by the late-stage deoxygenation of bioactive molecule and complex natural products.     

A Novel Method for Pattern Recognition of GIS Partial Discharge via Multi-Information Ensemble Learning

Partial discharge (PD) is the main feature that effectively reflects the internal insulation defects of gas-insulated switchgear (GIS). It is of great significance to diagnose the types of insulation faults by recognizing PD to ensure the normal operation of GIS. However, the traditional diagnosis method based on single feature information analysis has a low recognition accuracy of PD, and there are great differences in the diagnosis effect of various insulation defects. To make the most of the rich insulation state information contained in PD, we propose a novel multi-information ensemble learning for PD pattern recognition. First, the ultra-high frequency and ultrasonic data of PD under four typical defects of GIS are obtained through experiment. Then the deep residual convolution neural network is used to automatically extract discriminative features. Finally, multi-information ensemble learning is used to classify PD types at the decision level, which can complement the shortcomings of the independent recognition of the two types of feature information and has higher accuracy and reliability. Experiments show that the accuracy of the proposed method can reach 97.500%, which greatly improves the diagnosis accuracy of various insulation defects.     

Packed-Fiber Solid Phase-Extraction Coupled with HPLC-MS/MS for Rapid Determination of Lipid Oxidative Damage Biomarker 8-Iso-Prostaglandin F2α in Urine

The 8-iso-prostaglandin F_2α (8-iso-PGF_2α) biomarker is used as the gold standard for tracing lipid oxidative stress in vivo. The analysis of urinary 8-iso-PGF_2α is challenging when dealing with trace amounts of 8-iso-PGF_2α and the complexity of urine matrixes. A packed-fiber solid-phase extraction (PFSPE)–coupled with HPLC-MS/MS–method, based on polystyrene (PS)-electrospun nanofibers, was developed for the specific determination of 8-iso-PGF_2α in urine and compared with other newly developed LC-MS/MS methods. The method, which simultaneously processed 12 samples within 5 min on a self-made semi-automatic array solid-phase extraction processor, was the first to introduce PS-electrospun nanofibers as an adsorbent for the extraction of 8-iso-PGF_2α and was successfully applied to real urine samples. After optimizing the PFSPE conditions, good linearity in the range of 0.05–5 ng/mL with R² > 0.9996 and a satisfactory limit of detection of 0.015 ng/mL were obtained, with good intraday and interday precision (RSD < 10%) and recoveries of 95.3–103.8%. This feasible method is expected to be used for the batch quantitative analysis of urinary 8-iso-PGF_2α.     

聚合物气体辅助注射成型制品的形态结构

作为一种由常规注射成型发展起来的聚合物加工技术,气体辅助注射成型具有节约原材料、缩短成型周期以及提高制品性能等优点,已得到广泛的应用.由于气辅成型过程是一个在刚、柔双重约束界面条件下进行的多相复杂体系的多次流动过程,因而其形态结构的形成、发展和演化要远比常规注塑成型复杂.然而在气辅成型的形态结构方面,国内外的研究一直以来开展得较少.近年来,作者在聚合物及其共混物、复合材料气辅成型制品的形态结构方面已开展了广泛的研究工作,本文对这些工作和一些重要结果作了总结,并简要分析了成型过程中剪切场对形态演化的影响,最后对该研究方向的发展趋势作了展望.     

Precise electro-reduction of alkyl halides for radical defluorinative alkylation

Reported here is a precise electro-reduction strategy for radical defluorinative alkylation towards the synthesis of gem-difluoroalkenes from α-trifluoromethylstyrenes. According to the redox-potential difference of the radical precursors, direct or indirect electrolysis is respectively adopted to realize the precise reduction. An easy-to-handle, catalyst-and metal-free condition is developed for the reduction of alkyl radical precursors that are generally easier to be reduced than α-trifluorome...     

PVC/MBS/纳米 BaSO4 复合材料的制备及其性能

采用熔融共混法制备聚氯乙烯(PVC)/甲基丙烯酸甲酯-丁二烯-苯乙烯共聚物(MBS)/纳米重晶石(nano-BaSO4)三元复合材料,考察其力学性能和热稳定性能,并用扫描电镜观察冲击断面的形态.结果表明:MBS 与 nano-BaSO4 可协同增韧 PVC;当 MBS、nano-BaSO4 的含量分别为 10%、1%时,材料的韧性和刚性可同时得以改善,其冲击断面表现出典型的韧性断裂特征;热重分析显示添加 1%nano-BaSO4 可显著提高 PVC/MBS 的热稳定性能,其第一降解阶段的初始分解温度和最快分解温度分别提高了 10℃和14℃.     

嵌段共聚物自组装的研究进展

嵌段共聚物自组装在光学、电子、信息、化学及生物领域有着广泛的应用前景.本文从实验观测、理论研究和计算机模拟三个方面概述了嵌段共聚物自组装领域的研究进展.在实验观测方面,着重介绍了嵌段共聚物在体相及膜中的自组装及外场调控作用方面的研究进展;理论方面则分别介绍了强分相理论、弱分相理论、自洽场理论、动态密度泛函方法和元胞动力学等在嵌段共聚物自组装领域的应用;计算机模拟方面就 Monte Carlo 模拟、耗散粒子动力学等方法在该领域的应用作了详细的阐述.     

林杏琴会堂的音质分析及改进设想

采用精密声级计和双通道声学分析仪，对林杏琴会堂的声场分布、噪声本底和混响时间作了分区测试，应用建筑声学理论对会堂的音质状况进行了分析，并提出改善会堂音质的若干建议．     

光纤陀螺温控技术的研究

温度变化将严重地影响干涉型光纤陀螺仪(IFOG)系统的零位漂移.本文在初步研究温控技术的基础上,给出一种实用的温控电路,以用于在测试温度变化所引起的零位漂移中进行温度调节与控制.通过在此电路下实测的两者变化关系曲线采取补偿措施,以减小光纤陀螺的零位漂移.