Ultrasound-assisted extraction of oil from Moringa oleifera Lam. seed using various solvents

The present research analyzes the extraction of oil from Moringa oleifera Lam. seed using ultrasound-assisted extraction (UAE) technique under different operating conditions such as temperature, solvent type, and time. Three factors with three levels Box-Behnken response surface design was employed to optimize and investigate the effect of process variables on the response (oil yield). The independent variables showed significant effect on the extraction process. Interactive effects of the extraction process variables were analyzed by Pareto analysis of variance (ANOVA), and second-order polynomial model was used to plot the 3D response surface plot. Optimum extraction conditions for the maximizing the extraction yield of oil (59%) was found to be: temperature of 35°C, solvent type of 2, and time of 20 min. FT-IR was used to analysis the oil. From the results, it can be concluded that the UAE is the effective technique to extract the oil from Moringa oleifera Lam. seed.     

Static pentane extraction as a potential alternative to Soxhlet extraction for polypropylene olive oil overall migration limit measurements

Static pentane extraction of olive oil from polypropylene was evaluated as a safer, higher throughput alternative to pentane Soxhlet extraction for the recovery of olive oil from polypropylene for overall migration limit determinations. Static, ambient temperature, pentane extraction achieved quantitative recovery of olive oil from polypropylene plaques prepared by using the OM‐5 overall migration limit protocol. In addition to validation data for static extractions, a modified esterification procedure is presented as a means to accommodate the larger sample sets that are enabled with static extraction.     

Ionic liquid-assisted micellar extraction for the quantitative determination of sesquiterpenic acids in Valeriana officinalis L. (Caprifoliaceae)

ABSTRACT

A series of hydrophilic ionic liquids (ILs) were investigated as extractants for the quantitative determination of valerenic and acetoxyvalerenic acids in Valerianae radix. The influence of different factors, e.g. type of cation and anion, alkyl chain length, concentration, temperature, extraction time and solid–liquid ratio, was investigated. The results obtained showed that the extraction yield is strongly dependent on the cation type. The best outcome was obtained with IL capable of forming micelles in aqueous solution, e.g. 1-decyl-3-methylimidazolium chloride. As a result, an alternative protocol for the quantification of sesquiterpenic acids in valerian was developed and validated.     

Determination of four priority polycyclic aromatic hydrocarbons (4PAHs) by GC-MS in traditional Turkish yoghurts

ABSTRACT

Polycyclic aromatic hydrocarbons (PAHs) are ingested with foods and cause toxicities for humans. Yoghurt is one of the main foods that mediate PAH ingestion. Yan?k yoghurt, a traditional strained yoghurt, can contain PAHs due to its production process. Therefore, the concentration and types of four polycyclic aromatic hydrocarbons were determined by gas chromatography-mass spectrometry (GC-MS). Yan?k yoghurt samples were collected from different shops in Denizli, Turkey. For the method validation, the Eurachem guide (second edition) was adopted. Accordingly, linearity, working range, limits of detection (LOD), quantification (LOQ), precision and trueness values were set. Due to the selected validation parameters, the limit for detection was between 0.03 ng g^?1and 0.05 ng g^?1while the limit for quantification was between 0.10 ng g^?1 and 0.16 ng g^?1. Recovery rates higher than 83.80 % were obtained for four PAHs at two spiked concentrations (2.0 and 5.0 ng g^?1). Five Yan?k yoghurt samples and one commercial concentrated yoghurt sample were successfully analysed using the validated method.     

基于机器视觉的玻璃缺陷检测

随着科学技术的进步,高端显示屏产品对平板玻璃的质量要求越来越高,玻璃的表面缺陷检测技术也因此备受关注。传统的人眼检测方法工作量大且准确率低,已经无法满足生产实际要求。研究了一种基于机器视觉的玻璃质量检测系统,采用先进的CCD成像技术和背光式照明获取图像,用MATLAB图像处理工具箱对采集到的图像进行灰度值化、滤波降噪和阈值分割处理,实现对缺陷区域的特征提取和识别。最后用BP神经网络对玻璃表面的三种缺陷进行分类,该神经网络识别的平均误差率为9.84%,表明此检测方法具有一定的应用价值。     

严重突出煤层穿层钻孔“钻冲筛运”一体化瓦斯治理技术研究与应用

鹤煤公司八矿地质构造复杂、断层褶曲发育,尤其井田深部断层多,并且煤层透气性低且松软,打钻塌孔、喷孔严重,瓦斯抽放效果不好,给煤炭开采和瓦斯综合治理带来了困难。针对鹤煤公司八矿穿层钻孔瓦斯治理技术措施进行井下现场探索与研究,通过在3205底抽巷经过多次技术方案论证、实践,摸索出一套钻冲筛运一体化整套技术流程,并分析高压水力冲孔瓦斯涌出特征、有效影响半径。通过采用高压水力冲孔、振动筛选、转载装运,提高了水力冲孔效果和效率,改善了工作环境。     

Concept for a Hydrometallurgical Processing of a Copper-Cobalt-Nickel Alloy Made from Manganese Nodules

The processing of manganese nodules for the production of raw materials has been a subject of research for many decades. The nodules contain many valuable metals like copper, cobalt and nickel. In recent years, the German Federal Institute for Geoscience and Natural Resources developed a process for the processing of manganese nodules based on a combined pyro- and a hydrometallurgical route. Clausthal University of Technology was assigned to develop the hydrometallurgical process for the treatment of a FeNiCuCo alloy. The developed process consists of pressurized sulfuric acid leaching with the suppression of hydrogen gas formation, precipitation and solvent extraction.     

Experimental study on the effect of lateral concentrated smoke extraction on smoke stratification in the longitudinal ventilated tunnel

Smoke is the main cause of death in tunnel fires. It is one of the important measures to maintain smoke stratification in the early stage of tunnel fire. This article focused on experimentally studying the combined effect of lateral concentrated smoke extraction and longitudinal ventilation on the smoke stratification, which never be revealed before. The velocity of the smoke layer and air layer, vertical temperature distribution, and the flow patterns of the smoke were measured. It was found that the longitudinal ventilation and lateral concentrated smoke extraction would affect the flow of the smoke and change the shear velocity between the smoke layer and air layer, then, the patterns of the smoke layer will be affected. And the flow patterns with Froude (Fr) number can be classified into three categories: (a)Fr < 0.6 , with stable smoke stratification; (b) 0.6 < Fr < 0.85 , with a stable smoke stratification but the blurring interface; and (c) Fr > 0.85 , the smoke layer is completely unstable. The result can provide a reference for ventilation design of immersed tube tunnels.     

煤层软硬分层吸附瓦斯性能差异性及其对瓦斯赋存的影响

为研究煤层软、硬分层吸附瓦斯性能差异性及其对瓦斯赋存的影响,分析了煤层内软分层的形成机理及结构特征,采集了我国多个煤与瓦斯突出矿井的煤样作为试验对象,应用高压容量法开展了软、硬分层煤样吸附瓦斯性能参数的对比试验,探讨了软煤、硬煤吸附性能的差异性。在此基础上,对煤层软、硬分层吸附瓦斯性能差异性与瓦斯赋存特征之间的关联进行了研究,结果表明:试验煤样软分层的极限吸附量均大于硬分层;随着瓦斯压力的增加,试验煤样软、硬分层瓦斯含量的差值逐渐增大,其曲线的变化特征与Langmuir方程类似,并且软、硬分层瓦斯含量数值的差异主要由吸附量差值构成;煤层软、硬分层吸附瓦斯性能的差异不仅对煤层原始瓦斯赋存特征有着显著的影响,同时还将影响煤巷掘进、瓦斯抽采过程中煤体内瓦斯流场的分布规律,需要根据煤层软、硬分层的组合特点,制订切实有效的瓦斯抽采技术方案。     

A process fault diagnosis method using multi-time scale dynamic feature extraction based on convolutional neural network

Unlike many other techniques used in process control, which are widely applied in practice and play significant roles, abnormal situation management (ASM) still relies heavily on human experience, not least because the problem of fault detection and diagnosis (FDD) has not been well addressed. In this paper, a process fault diagnosis method using multi-time scale dynamic feature extraction based on convolutional neural network (CNN) consisting of similarity measurement, variable ranking, and multi-time scale dynamic feature extraction is proposed. The CNN-based model containing the fixed multiple sampling (FMS) layer can extract dynamic characteristics of process data at different time scales. The benchmark Tennessee Eastman (TE) process is used to verify the performance of the proposed method.