Enhanced Magnetoresistance Effect and Magnetic Properties of Double Perovskite La2−xSrxMnRuO6 (0 ≤ x ≤ 1.0)

Journal of Superconductivity and Novel Magnetism - Double perovskite La2?xSrxMnRuO6 (x?=?0, 0.3, 0.5, 0.8, 1.0) samples were synthesized by the standard solid-state reaction...     

超临界CO2对低渗透煤层渗透率影响试验研究

在对低渗透煤层进行煤层气开采时,由于低渗透煤层的"三低"特性,煤层气的开采效率很低.而由于超临界CO2具有降低分压、竞争驱替、可萃取小分子有机化合物等优点,利用注入超临界CO2改善煤储层渗透性的呼声越来越高.通过实验室渗流试验检测系统试验的方法来研究超临界CO2对低渗透煤层的增透效果,试验结果表明:经超临界CO2作用后煤样的渗透性大幅升高,且其对煤储层渗透性的影响主要集中在前10 d.     

Co-optimization of CO2 sequestration and enhanced oil recovery in extra-low permeability reservoir in Shanbei

This article put forward a theoretical system, which is used to analyze co-optimization of CO₂ sequestration and enhanced oil recovery by using the methods or theories including the design of experiments, numerical simulation, net present value, and the response surface methods. A CO₂ flooding operation in an immiscible water-alternating-gas process of Shanbei extra-low permeability reservoir was estimated preliminarily by using the methods proposed in this article. The result shows that optimized values obtained from predicted values were in good agreement with the values obtained from the simulation model and it is possible to optimize a coupled CO₂ sequestration and enhanced oil recovery project.     

Least Squares Identification for Hammerstein Multi-input Multi-output Systems Based on the Key-Term Separation Technique

System modeling and parameter estimation are basic for system analysis and controller design. This paper considers the parameter identification problem of a Hammerstein multi-input multi-output (H-MIMO) system. In order to avoid the product terms in the identification model, we derive a pseudo-linear identification model of the H-MIMO system through separating a key term from the output equation of the system and present a hierarchical generalized least squares (LS) algorithm for estimating the parameters of the system. Moreover, we present a new LS algorithm to reduce the computational burden. The proposed algorithms are simple in principle and can achieve a higher computational efficiency than the over-parameterization-based LS estimation algorithm. Finally, we test the proposed algorithms by the simulation example and show their effectiveness.     

The Yeast ATF1 Acetyltransferase Efficiently Acetylates Insect Pheromone Alcohols: Implications for the Biological Production of Moth Pheromones

Many moth pheromones are composed of mixtures of acetates of long‐chain (≥10 carbon) fatty alcohols. Moth pheromone precursors such as fatty acids and fatty alcohols can be produced in yeast by the heterologous expression of genes involved in insect pheromone production. Acetyltransferases that subsequently catalyze the formation of acetates by transfer of the acetate unit from acetyl‐CoA to a fatty alcohol have been postulated in pheromone biosynthesis. However, so far no fatty alcohol acetyltransferases responsible for the production of straight chain alkyl acetate pheromone components in insects have been identified. In search for a non‐insect acetyltransferase alternative, we expressed a plant‐derived diacylglycerol acetyltransferase (EaDAcT) (EC 2.3.1.20) cloned from the seed of the burning bush (Euonymus alatus) in a yeast system. EaDAcT transformed various fatty alcohol insect pheromone precursors into acetates but we also found high background acetylation activities. Only one enzyme in yeast was shown to be responsible for the majority of that background activity, the acetyltransferase ATF1 (EC 2.3.1.84). We further investigated the usefulness of ATF1 for the conversion of moth pheromone alcohols into acetates in comparison with EaDAcT. Overexpression of ATF1 revealed that it was capable of acetylating these fatty alcohols with chain lengths from 10 to 18 carbons with up to 27‐ and 10‐fold higher in vivo and in vitro efficiency, respectively, compared to EaDAcT. The ATF1 enzyme thus has the potential to serve as the missing enzyme in the reconstruction of the biosynthetic pathway of insect acetate pheromones from precursor fatty acids in yeast.     

Analyzing market performance via social media: a case study of a banking industry crisis

Analyzing market performance via social media has attracted a great deal of attention in the finance and machine-learning disciplines.However,the vast majority of research does not consider the enormous influence a crisis has on social media that further affects the relationship between social media and the stock market.This article aims to address these challenges by proposing a multistage dynamic analysis framework.In this framework,we use an authorship analysis technique and topic model method to identify stakeholder groups and topics related to a special firm.We analyze the activities of stakeholder groups and topics in different periods of a crisis to evaluate the crisis’s influence on various social media parameters.Then,we construct a stock regression model in each stage of crisis to analyze the relationships of changes among stakeholder groups/topics and stock behavior during a crisis.Finally,we discuss some interesting and significant results,which show that a crisis affects social media discussion topics and that different stakeholder groups/topics have distinct effects on stock market predictions during each stage of a crisis.     

Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis

To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.