岩石微观结构CT扫描表征技术研究

岩石微观结构特征研究对非常规油气藏的演化规律、油气赋存状态、运移方式、渗流特征等基础地质问题研究具有重要的科学意义.利用CT 扫描技术对油砂、致密砂岩和页岩样品微观结构表征研究,并对比了常规测试方法与CT扫描表征技术的差异性. 对比CT扫描法和筛分法测试油砂矿物的粒度分布,两者结果十分接近,矿物颗粒大小分布总体趋势上差异小,但小于96μm的颗粒矿物分布差异性稍大.CT扫描结果显示致密砂岩样品的裂缝比较发育,还发育溶蚀孔隙. 由于测试方法和样品大小的差异性,CT扫描获得的孔隙度略大于氦气法孔隙度.微米CT 扫描可以表征页岩的层理发育情况,但无法表征内部的微观孔隙结构.与常规测试方法相比,纳米CT 扫描表征页岩中有机质和黄铁矿的含量等方面准确性好,但孔隙度测试结果偏小.纳米CT分辨率还不能完全满足表征页岩的微观孔隙结构的要求,同时有机质和孔隙的灰度值差异较小,两者区分难度大,因此纳米CT还无法完全准确表征页岩微观孔隙结构.      

激光烧蚀下不同颗粒度Al-teflon的反应行为

为研究不同颗粒度对Al-teflon反应行为的影响,以颗粒度25μm、1μm和20～200 nm的Al粉和微米级Teflon粉混合制备的反应材料为研究对象,基于脉冲激光烧蚀实验,结合ICCD相机和光谱仪对反应过程中的自发光成像和发射光谱进行瞬态观测。研究结果表明,Al-teflon反应材料在激光烧蚀下的反应行为体现出典型的二次反应特征,具有持续燃烧特征和明显的后燃效应,也具有较长的能量释放时间;同时,其反应行为与Al粉颗粒度密切相关:初始阶段,反应随Al粉颗粒度的降低加剧,随着反应的进行,纳米级Al粉对应的反应材料后续反应能力逐渐下降,反应强度和反应时间都小于1μm铝粉对应的反应材料。     

基于拓扑描述函数的连续体结构拓扑优化方法

提出了一种利用拓扑描述函数(TDF)作为拓扑设计变量求解连续体结构拓扑优化问题 的新方法. 优化问题的目标函数是结构的整体柔顺性，约束条件为对于可利用材料的体积限 制. 这种方法不仅可以消除拓扑优化中经常出现的棋盘格式等数值不稳定现象，而且能够有 效地抑制传统算法处理此类优化问题时所引发的边界扩散效应. 与其它的基于水平集描述函 数的拓扑优化方法相比，所提出的算法不仅无需求解控制水平集函数演化的双曲守恒方 程，而且合理地考虑了目标函数的拓扑导数信息，因而使得算法的计算效率有了显著的提高.     

l-Lysine-Based Gelators for the Formation of Oleogels in Four Vegetable Oils

Supramolecular oleogel is a soft material with a three-dimensional structure, formed by the self-assembly of low-molecular-weight gelators in oils; it shows broad application prospects in the food industry, environmental protection, medicine, and other fields. Among all the gelators reported, amino-acid-based compounds have been widely used to form organogels and hydrogels because of their biocompatibility, biodegradation, and non-toxicity. In this study, four N^α, N^ε-diacyl-l-lysine gelators (i.e., N^α, N^ε-dioctanoyl-l-lysine; N^α, N^ε-didecanoyl-l-lysine; N^α, N^ε-dilauroyl-l-lysine; and N^α, N^ε-dimyristoyl-l-lysine) were synthesized and applied to prepare oleogels in four kinds of vegetable oils. Gelation ability is affected not only by the structure of the gelators but also by the composition of the oils. The minimum gel concentration (MGC) increased with the increase in the acyl carbon-chain length of the gelators. The strongest gelation ability was displayed in olive oil for the same gelator. Rheological properties showed that the mechanical strength and thermal stability of the oleogels varied with the carbon-chain length of the gelators and the type of vegetable oil. The microstructure of oleogels is closely related to the carbon-chain length of gelators, regardless of oil type. The highest oil-binding capacity (OBC) was obtained in soybean oil for all four gelators, and N^α, N^ε-dimyristoyl-l-lysine showed the best performance for entrapping oils.     

Research Progress on Typical Quaternary Ammonium Salt Polymers

Quaternary ammonium salt polymers, a kind of polyelectrolyte with a quaternary ammonium group, are widely used in traditional and emerging industries due to their good water-solubility, adjustable cationicity and molecular weight, high efficiency and nontoxicity. In this paper, firstly, the properties and several synthesis methods of typical quaternary ammonium salt monomers were introduced. Secondly, the research progress on the synthesis of polymers was summarized from the perspective of obtaining products with high molecular weight, narrow molecular weight distribution and high monomer conversion, and special functional polymers. Thirdly, the relationships between the structures and properties of the polymer were analyzed from the perspectives of molecular weight, charge density, structural stability, and microstructural regulation of the polymer chain unit. Fourthly, typical examples of quaternary ammonium salt polymers in the application fields of water treatment, daily chemicals, petroleum exploitation, papermaking, and textile printing and dyeing were listed. Finally, constructive suggestions were put forward on developing quaternary ammonium salt polymers with high molecular weights, strengthening the research on the relationships between the structures and their properties and pinpointing relevant application fields.     

Computational Drug Repurposing Based on a Recommendation System and Drug–Drug Functional Pathway Similarity

Drug repurposing identifies new clinical indications for existing drugs. It can be used to overcome common problems associated with cancers, such as heterogeneity and resistance to established therapies, by rapidly adapting known drugs for new treatment. In this study, we utilized a recommendation system learning model to prioritize candidate cancer drugs. We designed a drug–drug pathway functional similarity by integrating multiple genetic and epigenetic alterations such as gene expression, copy number variation (CNV), and DNA methylation. When compared with other similarities, such as SMILES chemical structures and drug targets based on the protein–protein interaction network, our approach provided better interpretable models capturing drug response mechanisms. Furthermore, our approach can achieve comparable accuracy when evaluated with other learning models based on large public datasets (CCLE and GDSC). A case study about the Erlotinib and OSI-906 (Linsitinib) indicated that they have a synergistic effect to reduce the growth rate of tumors, which is an alternative targeted therapy option for patients. Taken together, our computational method characterized drug response from the viewpoint of a multi-omics pathway and systematically predicted candidate cancer drugs with similar therapeutic effects.     

Stock Index Prediction Based on Time Series Decomposition and Hybrid Model

The stock index is an important indicator to measure stock market fluctuation, with a guiding role for investors’ decision-making, thus being the object of much research. However, the stock market is affected by uncertainty and volatility, making accurate prediction a challenging task. We propose a new stock index forecasting model based on time series decomposition and a hybrid model. Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) decomposes the stock index into a series of Intrinsic Mode Functions (IMFs) with different feature scales and trend term. The Augmented Dickey Fuller (ADF) method judges the stability of each IMFs and trend term. The Autoregressive Moving Average (ARMA) model is used on stationary time series, and a Long Short-Term Memory (LSTM) model extracts abstract features of unstable time series. The predicted results of each time sequence are reconstructed to obtain the final predicted value. Experiments are conducted on four stock index time series, and the results show that the prediction of the proposed model is closer to the real value than that of seven reference models, and has a good quantitative investment reference value.     

Sensitive electrochemical determination of α-fetoprotein using a glassy carbon electrode modified with in-situ grown gold nanoparticles,graphene oxide and MWCNTs acting as signal amplifiers

The authors describe an electrochemical immunoassay for α-fetoprotein (α-FP) using a glassy carbon electrode (GCE) modified with a nanocomposite made from gold nanoparticles, graphene oxide and multi-walled carbon nanotubes (AuNPs/GO-MWCNTs) and acting as a signal amplification matrix. The nanocomposite was synthesized in a one-pot redox reaction between GO and HAuCl₄ without using an additional reductant. The stepwise assembly of the immunoelectrode was characterized by means of cyclic voltammetry and electrochemical impedance spectroscopy. The interaction of antigen and antibody on the surface of the electrode creates a barrier for electrons and causes retarded electron transfer, this resulting in decreased signals in differential pulse voltammetry of hexacyanoferrate which is added as an electrochemical probe. Using this strategy and by working at a potential of 0.2 V (vs. SCE), a wide analytical range (0.01 - 100 ng∙mL‾¹) is covered. The correlation coefficient is 0.9929, and the limit of detection is as low as 3 pg∙mL‾¹ at a signal-to-noise ratio of 3. This electrochemical immunoassay combines the specificity of an immunological detection scheme with the sensitivity of an electrode modified with AuNPs and GO-MWCNTs.

Schematic illustration of the fabrication procedure of the immunosensor

     

Iron Catalyzed Isomerization of α-Alkyl Styrenes to Access Trisubstituted Alkenes

Stereoselective isomerization of α-alkyl styrenes is accomplished using a new iron catalyst supported by phosphine-pyridine-oxazoline (PPO) ligand.The protocol ...     

The duality between Morrey spaces and its pre-dual spaces characterized by heat kernel

Let L be an elliptic operator, we give arguments about the duality estimate between Morrey spaces and its pre-dual spaces characterized by the heat kernel associated to L that is given in [6],[8].