Concurrent multiresponse non-linear screening: Robust profiling of webpage performance

Profiling engineered data with robust mining methods continues attracting attention in knowledge engineering systems. The purpose of this article is to propose a simple technique that deals with non-linear multi-factorial multi-characteristic screening suitable for knowledge discovery studies. The method is designed to proactively seek and quantify significant information content in engineered mini-datasets. This is achieved by deploying replicated fractional-factorial sampling schemes. Compiled multi-response data are converted to a single master-response effectuated by a series of distribution-free transformations and multi-compressed data fusions. The resulting amalgamated master response is deciphered by non-linear multi-factorial stealth stochastics intended for saturated schemes. The stealth properties of our method target processing datasets which might be overwhelmed by a lack of knowledge about the nature of reference distributions at play. Stealth features are triggered to overcome restrictions regarding the data normality conformance, the effect sparsity assumption and the inherent collapse of the ‘unexplainable error’ connotation in saturated arrays. The technique is showcased by profiling four ordinary controlling factors that influence webpage content performance by collecting data from a commercial browser monitoring service on a large scale web host. The examined effects are: (1) the number of Cascading Style Sheets files, (2) the number of JavaScript files, (3) the number of Image files, and (4) the Domain Name System Aliasing. The webpage performance level was screened against three popular characteristics: (1) the time to first visual, (2) the total loading time, and (3) the customer satisfaction. Our robust multi-response data mining technique is elucidated for a ten-replicate run study dictated by an L₉(3⁴) orthogonal array scheme where any uncontrolled noise embedded contribution has not been necessarily excluded.     

Enhancing signal-to-noise ratio and resolution in low-field NMR relaxation measurements using post-acquisition digital filters

The traditional way to enhance signal-to-noise ratio (SNR) of nuclear magnetic resonance (NMR) signals is to increase the number of scans. However, this procedure increases the measuring time that can be prohibitive for some applications. Therefore, we have tested the use of several post-acquisition digital filters to enhance SNR up to one order of magnitude in time domain NMR (TD-NMR) relaxation measurements. The procedures were studied using continuous wave free precession (CWFP-T₁) signals, acquired with very low flip angles that contain six times more noise than the Carr–Purcell–Meiboom–Gill (CPMG) signal of the same sample and experimental time. Linear (LI) and logarithmic (LO) data compression, low-pass infinity impulse response (LP), Savitzky–Golay (SG), and wavelet transform (WA) post-acquisition filters enhanced the SNR of the CWFP-T₁ signals by at least six times. The best filters were LO, SG, and WA that have high enhancement in SNR without significant distortions in the ILT relaxation distribution data. Therefore, it was demonstrated that these post-acquisition digital filters could be a useful way to denoise CWFP-T₁, as well as CPMG noisy signals, and consequently reducing the experimental time. It was also demonstrated that filtered CWFP-T₁ method has the potential to be a rapid and nondestructive method to measure fat content in beef and certainly in other meat samples.     

血清miRNA提取方法的优化

利用正交试验法优化血清miRNA的提取方法,为进一步研究血清miRNA作为生物标记物提供方法学基础.本文以hsa-miRNA-223-3p,hsa-miRNA-483-5p和hsa-miRNA-16为检测目标,通过比较Trizol法和Trizol+酚/氯仿法的miRNA提取效率和qPCR检测结果,应用正交试验选择出最优实验方案.结果表明血清miRNA的最优提取方法为:血清用DEPC水4倍稀释,离心条件为4℃,12 000r·min-1,离心时间为10min,Trizol法提取.     

基于多变量希尔伯特频域模型的癫痫发作预测

癫痫发作具有突发性和反复性,对患者生命安全构成巨大威胁.为了对癫痫发作进行有效地预测,提出了多变量希尔伯特频域模型的癫痫发作预测方法.将希尔伯特边际谱、希尔伯特边际谱的变化方向和希尔伯特加权频率组成一个三维特征向量作为多变量希尔伯特频域模型,输入到支持相量机中,实现癫痫的发作预测,最后采用癫痫发作预测特征方法对预测结果进行评估.实验结果表明:采用多变量希尔伯特频域模型分析方法预测δ波和θ波的癫痫发作,癫痫预测范围在30~45 min,患者有足够的时间采取措施应对;癫痫发作周期在5~10 min,缩短患者等待时间,降低焦虑程度;与多种相关方法进行比较,该方法具有较低的错误预报率和较高的预测敏感度.     

焦炉上升管内壁结焦炭层的光谱学分析及结焦机理研究

以焦炉上升管内壁结焦炭层块为研究对象，采用X射线荧光光谱仪（XRF）、X射线衍射仪（XRD）、傅里叶红外光谱仪（FTIR）和激光共聚焦拉曼光谱仪（Raman）对结焦炭层的元素组成，以及各结焦炭层的矿物组成、组成结构和分子结构进行测试。分析从结焦炭层块外表面向内表面过渡的各结焦炭层的差异性，揭示焦炉上升管内壁结焦机理。结果表明焦炉上升管内粉尘中Fe，S和Cr极易催化荒煤气中蒽、萘等稠环芳烃化合物成炭，在焦炉上升管内壁形成炭颗粒沉积，为焦油凝结挂壁提供载体，在荒煤气温度降至结焦温度时易结焦积碳。结焦炭层均含有芳香层结构，随着结焦炭层从外表面向内表面过渡，各结焦炭层的面层间距(d₀₀₂)逐渐降低、层片直径(L_a)先降低后增加、层片堆砌高度(Lc)和芳香层数(N)先稳定后增加。结焦炭层石墨化过程是由结焦炭层内表面向外表面进行，主要包括其片层外缘的羧基和部分C-O结构的降解剥离，从而形成高度规整的共轭结构。结焦炭层块中C元素是以结晶碳与无定型碳的混合物形式存在。以上研究为解决焦炉上升管内壁结焦及腐蚀问题，提高换热器换热效率，有效回收焦炉荒煤气显热，降低焦化企业能耗提供实验基础和理论依据。     

正交试验优化手性镍催化不对称反应条件研究

用正交试验法优化手性镍催化二乙基锌对α，β不饱和酮的不对称麦克尔加成反应条件，优化后的不对称麦克尔加成反应的一般条件为：低温(近反应溶剂冰点)，常压，非质子非极性溶剂(环己烷)．