Full counting statistics of transport electrons through a two-level quantum dot with spin–orbit coupling

We study the full counting statistics of transport electrons through a semiconductor two-level quantum dot with Rashba spin–orbit (SO) coupling, which acts as a nonabelian gauge field and thus induces the electron transition between two levels along with the spin flip. By means of the quantum master equation approach, shot noise and skewness are obtained at finite temperature with two-body Coulomb interaction. We particularly demonstrate the crucial effect of SO coupling on the super-Poissonian fluctuation of transport electrons, in terms of which the SO coupling can be probed by the zero-frequency cumulants. While the charge currents are not sensitive to the SO coupling.     

Metabolomics techniques applied in the investigation of phenolic acids from the agro-industrial by-product of Carapa guianensis Aubl

Processing of Carapa guianensis seeds to obtain oil on an industrial scale generates a significant amount of by-product, approximately 66% w/w, which is called cake and is a potential source of biomolecules, including simple phenolic structures. For this reason, studies were carried out on the chemical profiles of hydrolyzed extract from this agro-industrial by-product through High Performance Thin-Layer Chromatography (HPTLC) and Gas Chromatography coupled to Mass Spectrometry (GC–MS). These techniques were used to detect metabolic classes and/or groups, and to identify, for the first time, thirteen simple phenolic acids in this by-product. The sample antioxidant capacity was determined by methods of 2,2-diphenyl-1-picrylhydrazyl (DPPH)and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS⁺) radicals direct sequestration. The hydrolyzed fraction showed a total of 63.47% in the relative abundance of the total of compounds, standing out: p-hydroxybenzoic acid (39.19%) and protocatechuic acid (3,4-dihydroxybenzoic acid) (5.62%), both from hydroxybenzoic acids and 3-(3,4-dihydroxyphenyl)lactic acid, (7.76%) hydroxycinnamic acids derivatives. In these results, the fraction rich in simple phenolic acids was obtained, attributing the prominent behavior of this matrix antioxidant activity, expressed by (IC₅₀: of 16.42 µg/mL and 6.52 µg/mL for DPPH and ABTS⁺ radicals, respectively). The research demonstrated an alternative to applicability that involves sustainability from agro-industrial. These techniques were used to detect metabolic classes and/or groups, and to identify, for the first time, thirteen simple phenolic acids in this by-product, generating a process capable of converting biomass into a bioproduct, consisting of bioactive compounds, in addition to adding value to the industrial chain.     

Studies on metabolites and metabolic pathways of bulleyaconitine A in rat liver microsomes using LC‐MSn combined with specific inhibitors

Bulleyaconitine A (BLA) from Aconitum bulleyanum plants is usually used as anti‐inflammatory drug in some Asian countries. It has a variety of bioactivities, and at the same time some toxicities. Since the bioactivities and toxicities of BLA are closely related to its metabolism, the metabolites and the metabolic pathways of BLA in rat liver microsomes were investigated by HPLC–MSⁿ. In this research, the 12 metabolites of BLA were identified according to the results of HPLC‐MSⁿ data and the relevant literature. The results showed that there are multiple metabolites of BLA in rat liver microsomes, including demethylation, deacetylation, dehydrogenation deacetylation and hydroxylation. The major metabolic pathways of BLA in rat liver microsomes were clarified by HPLC‐MS combined with specific inhibitors of CYP450 isoforms. As a result, CYP3A and 2C were found to be the principal CYP isoforms contributing to the metabolism of BLA. Moreover, CYP2D6 and 2E1 are also more important CYP isoforms for the metabolism of BLA. While CYP1A2 only affected the formation rate of M11, its effect on the metabolism of BLA is very small. Copyright © 2014 John Wiley & Sons, Ltd.     

基于串联两阶段网络DEA模型的供应链规模收益分析

数据包络分析(DEA)是评价供应链系统(Supply chain system)间相对有效性的一种重要的工具,但是传统的DEA不考虑供应链的内部结构,对系统效率评价偏高;而本文所研究两阶段串联供应链系统,考虑把部分中间产品作为最终产品输出,增加额外中间投入的情形.基于所提出的供应链系统结构,本文建立相应的串联结构下的网络DEA模型,并针对所建立模型进行相关理论的研究,给出了串联结构下的生产可能集和规模收益情况判定方法.最后,进行数值实验,以验证我们提出的结论.     

Development and validation of a reversed‐phase HPLC method for CYP1A2 phenotyping by use of a caffeine metabolite ratio in saliva

CYP1A2 is important for metabolizing various clinically used drugs. Phenotyping of CYP1A2 may prove helpful for drug individualization therapy. Several HPLC methods have been developed for quantification of caffeine metabolites in plasma and urine. Aim of the present study was to develop a valid and simple HPLC method for evaluating CYP1A2 activity during exposure in xenobiotics by the use of human saliva. Caffeine and paraxanthine were isolated from saliva by liquid‐liquid extraction (chlorophorm/isopropanol 85/15v/v). Extracts were analyzed by reversed‐phase HPLC on a C₁₈ column with mobile phase 0.1% acetic acid/methanol/acetonitrile (80/20/2 v/v) and detected at 273nm. Caffeine and paraxanthine elution times were <13min with no interferences from impurities or caffeine metabolites. Detector response was linear (0.10–8.00µg/ml, R²>0.99), recovery was >93% and bias <4.47%. Intra‐ and inter‐day precision was <5.14% (n=6). The limit of quantitation was 0.10µg/ml and the limit of detection was 0.018±0.002µg/mL for paraxanthine and 0.032±0.002µg/ml for caffeine. Paraxanthine/caffeine ratio of 34 healthy volunteers was significantly higher in smokers (p<0.001). Saliva paraxanthine/caffeine ratios and urine metabolite ratios were highly correlated (r=0.85, p<0.001). The method can be used for the monitoring of CYP1A2 activity in clinical practice and in studies relevant to exposure to environmental and pharmacological xenobiotics. Copyright © 2015 John Wiley & Sons, Ltd.     

Sobolev Stability of Plane Wave Solutions to the Nonlinear Schrödinger Equation

This article explores the questions of long time orbital stability in high order Sobolev norms of plane wave solutions to the NLSE in the defocusing case.     

基于深度学习的ELM实时识别研究

基于深度学习的方法，在HL-2A装置上开发出了一套边缘局域模(ELM)实时识别算法。算法使用5200次放电数据(约24.19万数据切片)进行学习，得到一个深度为22层的卷积神经网络。为衡量算法的识别能力，识别了HL-2A装置自2009年实现稳定ELMy H模放电以来所有历史数据(约26000次放电数据)，共识别出1665次H模放电，其中误识别35次，误报率为2.10%。在实际的1634次H模放电中，漏识别4次，漏识别率为0.24%。该误报率和漏报率可以满足ELM实时识别的精度要求。识别算法在实时控制环境下，对单个时间点的平均计算时间为0.46ms，可以满足实时控制的计算速度要求。