基于RFID技术的电子铅封管理系统研究

根据目前各种计量仪表传统的铅封现状及存在的主要问题,提出了一个科学、简便、有效的智能电子防伪表封解决方案。该系统采用RFID技术对计量仪表进行电子表封,然后通过RFID阅读器完成对仪表数据的管理。从而在根本上解决对表封的私拆、故意损坏、伪造及被施封物品的非正常开启的识别和验证。     

基于Kronecker积的无线通信系统参量分离方法

针对无线通信系统中发射机非线性与多径衰落信道问题,提出了一种根据接收无线信号联合估计无线设备功率放大器(PA)非线性与无线信道单位脉冲响应的方法.首先,根据通信帧训练符号及发射机非线性模型构造卷积矩阵;接着,采用一次最小二乘(LS),根据接收信号估计PA的非线性模型系数与实际发送符号;然后,再采用一次LS,得到无线信道的单位脉冲响应估计;两估计可迭代或直接加取平均进行积累.理论推导与实验结果显示,采用过采样技术,所提方法可应用于单载波或多载波通信,实现PA非线性与无线信道单位脉冲响应的有效分离.新方法在无线通信的物理层射频指纹认证与信号可靠传输中具有应用价值.     

面阵探测器相连缺陷元识别定位

面阵探测器相连缺陷元的光电信号与正常元基本相同,因此采用现有面阵测试方法无法识别相连缺陷元.针对相连缺陷元的特点,提出了借助改变面阵探测器光电响应的方法来实现相连缺陷元的识别定位.实验结果表明,该方法使面阵探测器分为两个不同透过率探测单元,多元相连缺陷元响应电压是相对应的两个不同透过率探测单元响应电压之和的平均值.采用MATLAB软件对测试数据进行分析处理,分析结果清晰给出缺陷元诸如个数、形状和位置等详细信息.采用本方法面阵探测器相连缺陷元可以被显著识别定位.研究结果为今后的面阵探测器评测与可靠性提高提供了参考.     

Use of DSC and TG for identification and quantification of the dosage form

Thermal analysis techniques, DSC and TG can advantageously be used in quality control of drug products.The methods are commonly used in preformulation for the study of polymorphism and for the study of the interactions drug substance-excipients, since these physical interactions can be the basis of the dosage form performance.For routine control of the drug products, DSC and TG methods which are quick, which require only few mg of the samples and which are automated, are very attractive for routine analysis of drug products. A single scan can give several qualitative and quantitative informations.DSC offer analytical possibilities only if the drug substance and the excipients do not have physical interactions or limited interactions (e.g. eutectic behaviour). About twenty marketed products have been analyzed by DSC and TG. In most of them identification of drug substance is easy. Several excipients could be identified in a tablet. Quantitations are demonstrated for some drug substances and excipients. DSC purity calculations have been applied to acetyl salicylic acid, paracetamol, cimetidine, pindolol, ibuprofen.     

高效液相色谱-四极杆飞行时间质谱检测中国杨树型蜂胶、巴西绿蜂胶和杨树胶中的酚类化合物及真伪鉴别

建立了用于检测中国杨树型蜂胶、巴西绿蜂胶和杨树胶中23种酚类化合物的高效液相色谱-四极杆飞行时间质谱（HPLC/Q-TOF MS）法，并进行了差异性分析。蜂胶和树胶样品用甲醇-水（1：1，v/v）溶解后，过0.45 μm有机相滤膜后进样。采用Agilent Eclipse Plus C₁₈色谱柱分离，以乙腈和0.1%（体积分数）甲酸水溶液为流动相进行梯度洗脱，电喷雾正离子模式全扫描方式检测，扫描范围为m/z 100~1000，外标法定量。结果表明，23种酚类化合物在10~200 μg/L范围内线性关系良好，相关系数均大于0.99。桔皮素和刺芒柄花素的检出限和定量限分别为0.2和1 μg/L，其他化合物的检出限和定量限分别为2和10 μg/L。在10、25和50 mg/kg 3个添加水平下，23种酚类化合物在3种样品基质中的提取回收率为70.2%~122.6%，RSD值均小于10%。水杨苷、肉桂酸、咖啡酸和香豆酸可以作为中国杨树型蜂胶掺假鉴别的特征化合物，咖啡酸、阿魏酸、白杨素、咖啡酸苯乙酯、松属素、高良姜素、香豆酸、异鼠李素、山柰素和阿替匹林C可以作为辨别中国杨树型蜂胶和巴西绿蜂胶的特征化合物。该结果对蜂胶产品的质量控制具有一定的参考意义。     

Interpretation of mass spectrometry data for high-throughput proteomics

Recent developments in proteomics have revealed a bottleneck in bioinformatics: high-quality interpretation of acquired MS data. The ability to generate thousands of MS spectra per day, and the demand for this, makes manual methods inadequate for analysis and underlines the need to transfer the advanced capabilities of an expert human user into sophisticated MS interpretation algorithms. The identification rate in current high-throughput proteomics studies is not only a matter of instrumentation. We present software for high-throughput PMF identification, which enables robust and confident protein identification at higher rates. This has been achieved by automated calibration, peak rejection, and use of a meta search approach which employs various PMF search engines. The automatic calibration consists of a dynamic, spectral information-dependent algorithm, which combines various known calibration methods and iteratively establishes an optimised calibration. The peak rejection algorithm filters signals that are unrelated to the analysed protein by use of automatically generated and dataset-dependent exclusion lists. In the "meta search" several known PMF search engines are triggered and their results are merged by use of a meta score. The significance of the meta score was assessed by simulation of PMF identification with 10,000 artificial spectra resembling a data situation close to the measured dataset. By means of this simulation the meta score is linked to expectation values as a statistical measure. The presented software is part of the proteome database ProteinScape which links the information derived from MS data to other relevant proteomics data. We demonstrate the performance of the presented system with MS data from 1891 PMF spectra. As a result of automatic calibration and peak rejection the identification rate increased from 6% to 44%.Abbreviations 2-DE Two-dimensional gel electrophoresis - MALDI Matrix-assisted laser desorption ionisation - PMF Peptide mass fingerprinting - MS Mass spectrometry - TOF Time of flight     

原位电离质谱技术在食品质量安全检测中的应用

原位电离质谱技术能够在常压环境下直接分析各种食品样品,无需或仅需极少的食品制备,大大提高了分析效率,已经成为一种重要的食品快速分析方法。本文对原位电离质谱的离子化技术和工作流程进行了介绍,从食品污染物检测、非法添加物筛查、食品真伪鉴别和品质评价等方面出发,综述了该技术在食品质量安全检测中的应用。讨论了其应用于食品分析领域时面临的挑战和未来发展趋势。     

水上溢油的气相色谱-质谱法鉴别

利用气相色谱－质谱法分析水上溢油样品和可凝溢油源样品，通过比较溢油样品和可疑溢油源样品的总离子流图的轮廓、m/z 191和m/z 217质量色谱图指纹和姥鲛烷（Pr)与峰面积比值APr/APh,建立了水上溢油的GC－MS鉴别方法。     

裂解气相色谱-质谱分析火场残留物中助燃剂

通过对火灾现场助燃剂及其燃烧残留物进行分析，开展了基于裂解气相色谱-质谱法（PyGC-MS）的火场助燃剂分析方法。选取了汽油和柴油2种助燃剂以及棉布和聚对苯二甲酸乙二醇酯（PET）塑料2类载体，制备了助燃剂与载体的混合燃烧残留物。利用热分析技术确定样品的特征性温度，并对分析条件进行优化与选择。通过闪蒸分析和裂解分析的分步裂解方法，对样品进行了PyGC-MS分析。实验结果表明，PET载体原样燃烧残留物的裂解产物共有35个组分，而PET载体与汽油混合燃烧残留物和PET载体与柴油混合燃烧残留物的裂解产物只有25个组分，且各裂解产物的种类和含量均不相同。该法可对同一载体的自身燃烧残留物和与助燃剂混合燃烧残留物进行区分，适用于火灾残留物中助燃剂的分析，可对火场中是否存在助燃剂进行判别，为火灾性质的判断和火灾调查工作提供科学依据。