Selective Analysis of Sulfur-Containing Species in a Heavy Crude Oil by Deuterium Labeling Reactions and Ultrahigh Resolution Mass Spectrometry

A heavy crude oil has been treated with deuterated alkylating reagents (CD₃I and C₂D₅I) and directly analyzed without any prior fractionation and chromatographic separation by high-field Orbitrap Fourier Transform Mass Spectrometry (FTMS) and Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) using electrospray ionization (ESI). The reaction of a polycyclic aromatic sulfur heterocycles (PASHs) dibenzothiophene (DBT), in the presence of silver tetrafluoroborate (AgBF₄) with ethyl iodide (C₂H₅I) in anhydrous dichloroethane (DCE) was optimized as a sample reaction to study heavy crude oil mixtures, and the reaction yield was monitored and determined by proton nuclear magnetic resonance spectroscopy (¹H-NMR). The obtained conditions were then applied to a mixture of standard aromatic CH-, N-, O- and S-containing compounds and then a heavy crude oil, and only sulfur-containing compounds were selectively alkylated. The deuterium labeled alkylating reagents, iodomethane-d₃ (CD₃I) and iodoethane-d₅ (C₂D₅I), were employed to the alkylation of heavy crude oil to selectively differentiate the tagged sulfur species from the original crude oil.     

基于特征融合的中文简历解析方法研究

针对基于规则和统计的传统中文简历解析方法效率低、成本高、泛化能力差的缺点，提出一种基于特征融合的中文简历解析方法，即级联Word2Vec生成的词向量和用BLSTM（Bidirectional Long Short-Term Memory）建模字序列生成的词向量，然后再结合BLSTM和CRF（Conditional Random Fields）对中文简历进行解析（BLSTM-CRF）。为了提高中文简历解析的效率，级联包含字序列信息的词向量和用Word2Vec生成的词向量，融合成一个新的词向量表示；再由BLSTM强大的学习能力融合词的上下文信息，输出所有可能标签序列的分值给CRF层；再由CRF引入标签之间约束关系求解最优序列。利用梯度下降算法训练神经网络，使用预先训练的词向量和Dropout优化神经网络，最终完成对中文简历的解析工作。实验结果表明，所提的特征融合方法优于传统的简历解析方法。     

Detection of correlation characteristics between financial time series based on multi-resolution analysis

Interactions between financial time series are complex and changeable in both time and frequency domains. To reveal the evolution characteristics of the time-varying relations between bivariate time series from a multi-resolution perspective, this study introduces an approach combining wavelet analysis and complex networks. In addition, to reduce the influence the phase lag between the time series has on the correlations, we propose dynamic time-warping (DTW) correlation coefficients to reflect the correlation degree between bivariate time series. Unlike previous studies that symbolized the time series only based on the correlation strength, the second-level symbol is set according to the correlation length during the coarse-graining process. This study presents a novel method to analyze bivariate time series and provides more information for investors and decision makers when investing in the stock market. We choose the closing prices of two stocks in China’s market as the sample and explore the evolutionary behavior of correlation modes from different resolutions. Furthermore, we perform experiments to discover the critical correlation modes between the bull market and the bear market on the high-resolution scale, the clustering effect during the financial crisis on the middle-resolution scale, and the potential pseudo period on the low-resolution scale. The experimental results exactly match reality, which provides powerful evidence to prove that our method is effective in financial time series analysis.     

我国煤矿生产事故统计及安全生产措施

我国煤矿生产事故频发,顶板垮落、瓦斯爆炸、机电事故、突水、矿井火灾、放炮等隐患时刻影响着煤矿安全生产,当前矿井开采以井下开采为主,井下开采存在技术要求高、开采难度大的问题,导致煤矿事故发生数和死亡人数相对其他行业居于首位。因此,为了深入研究煤矿事故发生原因和规律,统计了近10 a我国煤矿事故数据,找出当前矿山开采存在的各种安全问题,针对存在的问题提出解决措施,对预防及应对煤矿安全问题具有重要意义。     

Pull out of FRP reinforcement from masonry pillars: Experimental and numerical results

In this paper, debonding phenomena between carbon fiber reinforced polymer (CFRP) strips and masonry support were investigated on the basis of single-lap shear tests, considering different dimensions of the bond length. To capture the post-peak response of the CFRP–masonry joint, the slip between the support and the reinforcement strip was controlled using a clip gauge positioned at the end of the reinforcement. The tests were simulated by means of a finite element model able to capture the post-peak snap-back behavior due to the failure process. The numerical model is based on zero-thickness interface elements and on a proper non-linear cohesive law. The comparison between experimental and numerical results was performed in terms of overall response, measured by both the machine stroke and the clip gauge positioned at the free end of the reinforcement. The cases of effective bond length greater and lesser than the minimum anchorage length, suggested by the CNR Italian recommendation, were considered.     

Profile of Triacylglycerols,Phenols, and Vitamin E of Manjari Medika Grape Seed Oil and Cake: Introducing a Novel Indian Variety

The aim of the study is to investigate the biochemical composition of grapeseed oil and cake from an unexplored Indian grape‐juice cultivar, Manjari Medika (MM). The composition of oil and residual seed cake is evaluated using various chromatographic and spectroscopic techniques. The findings demonstrate that the vitamin E content of MM‐seed oil (1.15–1.35 g kg^?1) is distinctively higher than the Codex standard, suggesting its superior quality as an edible oil. The predominant triacylglycerols include trilinolein (LLL, 43%), dilinoleoyl‐stearylglycerol (LSL, 19%), and dilinoleoyl‐palmitoylglycerol (LLP, 11%), which are earlier recognized as natural antioxidants. The seed‐cake is rich in polyphenols including acylated anthocyanins (e.g., pelargonidin‐3‐O‐coumaroyl glucoside) and certain other flavonoids (e.g., catechin). The profile of phytonutrients in MM seed‐oil and cake is significantly superior to its seeded female parent and two other widely cultivated wine‐grape varieties. In brief, the studied by‐products of this new grape‐juice cultivar can be an important source of high‐value ingredients for use in food supplements, nutraceuticals, and functional foods. Practical applications: This study reports the phytochemical profile of the seed‐oil and seed cake derived from a newly developed grape variety, Manjari Medika. High contents of selective antioxidants: lipids, vitamin E, and phenols in the seed‐oil and cake with health benefits suggest their potential for use in nutraceutical and functional foods. These byproducts can be utilised as ingredients of functional foods and nutraceuticals (e.g., grape seed oil capsule) and also as raw materials in food supply chains (e.g., for production of grape cookies or cake). MM can also be utilized as a colorant in the food industry.     

Application of Vis–NIR hyperspectral imaging in classification between fresh and frozen-thawed pork Longissimus Dorsi muscles

Fresh and frozen-thawed (F-T) pork meats were classified by Vis–NIR hyperspectral imaging. Eight optimal wavelengths (624, 673, 460, 588, 583, 448, 552 and 609 nm) were selected by successive projections algorithm (SPA). The first three principal components (PCs) obtained by principal component analysis (PCA) accounted for over 99.98% of variance. Gray-level-gradient co-occurrence matrix (GLGCM) was applied to extract 45 textural features from the PC images. The correct classification rate (CCR) was employed to evaluate the performance of the partial least squares-discriminate analysis (PLS-DA) models, by using (A) the reflected spectra at full wavelengths and (B) those at the optimal wavelengths, (C) the extracted textures based on the PC images, and (D) the fused variables combining spectra at the optimal wavelengths and textures. The results showed that the best CCR of 97.73% was achieved by applying (D), confirming the high potential of textures for fresh and F-T meat discrimination.     

基于最小维修的石化安全设备区间截尾寿命数据分析

在石化安全关键设备寿命截尾数据的可靠性评估过程中，为避免传统可靠性评估方法未考虑维修对故障间隔时间的影响，以及中值填充法误差较大的缺点，本文提出了一种逆变换区间截尾数据填充方法。首先，在可修系统基于最小维修的假设下，通过非齐次泊松过程描述系统的故障趋势，利用逆变换填充得到监测区间的缺失数据；随后根据蒙特卡罗期望最大化算法，获得填充数据的参数估计值。通过蜡油加氢装置紧急泄压阀的案例分析，该算法能够很好地融合已有数据，得到的形状参数估计值偏差与中值填充法相比缩小4%以上，从而验证了该算法的有效性；这有助于安全关键设备的定量化完整性管理，保障石化装置平稳运行。     

Challenges in the CO2 emissions of the Turkish power sector: Evidence from a two-level decomposition approach

Decarbonization of the energy system is urgent to avert the disruptions in the climate. Considering its share, the low carbon transition of the power sector is pivotal. Growing electricity demand poses unique challenges for Turkey to enact deep decarbonization. It is vital to uncover the contributing causes of emissions to provide strategic oversight for carbon management activities. This study investigates key drivers of CO₂ emissions from the power sector using the Logarithmic Mean Divisia Index decomposition method. While efficiency improvement contributes to sustainable yet minor mitigation, changes in the fossil-fuel share indicate a cycling but significant overall impact.