激发-发射矩阵荧光光谱用于鉴别百合掺假的研究

为了能够快速判别百合是否掺假,利用激发-发射矩阵（EEM）荧光技术对纯百合和掺假百合样品进行了荧光光谱分析,并构建了百合及其掺假百合的荧光指纹特征图谱;然后借助主成分分析-线性判别分析（PCA-LDA）和偏最小二乘-判别分析（PLS-DA）两种化学模式识别方法,对百合中掺假粉末的种类进行了快速鉴别和分类。实验结果表明：两个分类模型均能根据百合样本的EEM荧光光谱数据准确识别掺假百合样本,且正确分类率均高达95%。利用PCA-LDA和PLS-DA成功建立了快速判别百合掺假的新方法,同时完善了百合荧光指纹特征图谱,有望为建立更全面、更准确地评价百合药材的质量标准体系打下基础。     

Automatic identification in packaging — radio frequency identification in multiway systems

With regard to the increasing environmental awareness all over the world, many companies replace their one‐way packaging systems by reusable systems in order to save energy and resources and to reduce waste. But complex multiway networks entail several problems concerning the availability of returned empties and the control of the flow of materials. In order to guarantee a failure‐free operation of the logistic network at low cost, a complete tracking and tracing of the package based on efficient identification technologies is crucial. Concerning multiway systems, the requirements of a continuous information flow often exceed the capacity of barcode technologies. Radio frequency identification (RFID) technologies can fill this gap by offering the wide range of features necessary for disposition and control. This paper sets out the requirements and benefits connected with the use of RFID technologies using multiway systems that represent new results from current research projects. Copyright © 1999 John Wiley & Sons, Ltd.     

Engineering Protein Nanoparticles Out from Components of the Human Microbiome

Nanoscale protein materials are highly convenient as vehicles for targeted drug delivery because of their structural and functional versatility. Selective binding to specific cell surface receptors and penetration into target cells require the use of targeting peptides. Such homing stretches should be incorporated to larger proteins that do not interact with body components, to prevent undesired drug release into nontarget organs. Because of their low interactivity with human body components and their tolerated immunogenicity, proteins derived from the human microbiome are appealing and fully biocompatible building blocks for the biofabrication of nonreactive, inert protein materials within the nanoscale. Several phage and phage‐like bacterial proteins with natural structural roles are produced in Escherichia coli as polyhistidine‐tagged recombinant proteins, looking for their organization as discrete, nanoscale particulate materials. While all of them self‐assemble in a variety of sizes, the stability of the resulting constructs at 37 °C is found to be severely compromised. However, the fine adjustment of temperature and Zn²⁺ concentration allows the formation of robust nanomaterials, fully stable in complex media and under physiological conditions. Then, microbiome‐derived proteins show promise for the regulatable construction of scaffold protein nanomaterials, which can be tailored and strengthened by simple physicochemical approaches.     

Computing sensitivity and selectivity in parallel factor analysis and related multiway techniques: the need for further developments in net analyte signal theory

Sensitivity and selectivity are important figures of merit in multiway analysis, regularly employed for comparison of the analytical performance of methods and for experimental design and planning. They are especially interesting in the second-order advantage scenario, where the latter property allows for the analysis of samples with a complex background, permitting analyte determination even in the presence of unsuspected interferences. Since no general theory exists for estimating the multiway sensitivity, Monte Carlo numerical calculations have been developed for estimating variance inflation factors, as a convenient way of assessing both sensitivity and selectivity parameters for the popular parallel factor (PARAFAC) analysis and also for related multiway techniques. When the second-order advantage is achieved, the existing expressions derived from net analyte signal theory are only able to adequately cover cases where a single analyte is calibrated using second-order instrumental data. However, they fail for certain multianalyte cases, or when third-order data are employed, calling for an extension of net analyte theory. The results have strong implications in the planning of multiway analytical experiments.     

An automated finite element analysis of the initiation and growth of damage in carbonfibre composite materials

The analysis and prediction of the development of damage in composite materials up to the point of final failure is important in the assessment of whether composite structures and components are fit for their purpose. Progressive damage modelling, using finite element analysis, has demonstrable potential as a tool for this.

If this approach is to be of real value, it needs to be automated so that the application of specialist knowledge is minimized. The ABAQUS finite element (FE) code has been used to develop fully-automated, threedimensional modelling of damage development in carbon fibre composites under tensile loading.

This paper describes the approach used in the development of these models. It covers work on the development of suitable FE meshes, the identification of suitable criteria to control the onset and effects of local damage, and the extension of the methodology to real component geometries.     

Analysis of nonhuman N-glycans as the minor constituents in recombinant monoclonal antibody pharmaceuticals

Minor N-linked glycans containing N-glycolylneuraminic acid residues and/or α-Gal epitopes (i.e., galactose-α1,3-galactose residues) have been reported to be present in recombinant monoclonal antibody (mAb) therapeutics. These contaminations are due to their production processes using nonhuman mammalian cell lines in culture media containing animal-derived materials. In case of the treatment of tumors, we inevitably use such mAbs by careful risk-benefit considerations to prolong patients' lives. However, expanding their clinical applications such as for rheumatism, asthma, and analgesia demands more careful evaluation of the product characteristics. The present work for detailed evaluations of N-glycans demonstrates the methods using capillary electrophoresis with laser-induced fluorescence detection (CE-LIF) and a combination of high-performance liquid chromatography and electrospray ionization time-of-flight mass spectrometry. The CE-LIF method provides excellent separation of both major and minor N-glycans from six commercial mAb pharmaceuticals within 30 min and clearly indicates that a possible trigger of immunogenicity in humans due to the presence of nonhuman N-glycans is present. We strongly believe that the proposed method will be a powerful tool for the analysis of N-glycans of recombinant mAb products in various development stages, such as clone selection, process control, and routine release testing to ensure safety and efficacy of the products.     

Metabolomics profiling of cell culture media leading to the identification of riboflavin photosensitized degradation of tryptophan causing slow growth in cell culture

As more protein biopharmaceuticals are produced using mammalian cell culture techniques, it becomes increasingly important for the biopharmaceutical industry to have tools to characterize the cell culture media and evaluate its impact on the cell culture performance. Exposure of the cell culture media to light, temperature stress, or adventitious introduction of low-level organisms during preparation can lead to the generation of chemical degradants or metabolites of the media components, which are potentially detrimental to the cell culture process. In this work, we applied a liquid chromatography-mass spectrometry based metabolomics methodology for the investigation of a media lot used for a mammalian cell culture process that had resulted in low growth rate and failure to meet required viable cell density (VCD). The study led to the observation of increased levels of tryptophan oxidation products and a riboflavin degradant, lumichrome, in the malfunctioning media lot, relative to working media lots. A compound found 7-fold higher in the working media lots appeared to be tetrahydropentoxyline, a condensation product of glucose and tryptophan. A second compound found at an over 50-fold higher level in the malfunctioning media lot with a proposed molecular formula of C(21)H(17)N(3)O(3) from high-resolution mass spectrometry (HRMS) analysis remains unknown, although it is confirmed to be a degradant of tryptophan in the media. A study of the cell culture media performed under stress conditions using fluorescent light and heat showed that the media powder was highly resistant to light-induced degradation, while solution media could be easily degraded after brief light exposure. It is therefore suspected that inadvertent exposure of the media to light during preparation and storage has resulted in the poor performance of the media causing the low growth and VCD in the cell culture process.     

The fatigue of aircraft structures

Current procedures for fatigue design and for fatigue life estimation, substantiation and monitoring of aircraft structures are reviewed. Major gaps in the present state of knowledge are identified and further research directed towards filling these gaps is discussed.Brief reference is made to the major fields of basic or fundamental research connected with the fatigue of structures including, the application of fracture mechanics to the theory of crack propagation, elevated temperature behaviour of aircraft materials, atmospheric turbulence, reliability based design and aeroelastic behaviour.It is seen that with the present advances in aircraft design and utilisation the fatigue assessment of aircraft structures is an increasingly complex problem for which no general method of solution has yet been established. At present reliance is placed on extensive testing of design details and components, usually in conjunction with a full scale fatigue test, to validate the fatigue analysis and substantiate, or provide the essential data used for fatigue life monitoring. There is however a well developed trend for basic studies of the various aspects of fatigue behaviour, to find increasing application in the interpretation of experimental results for fatigue life assessment and improved methods of fatigue design.     

Automation of BSI PD 6539 high temperature assessment procedure

The reliable and efficient assessment of flaws in components and welded fabrications is essential for the competitive deployment of many critical structures. Fitness-for-purpose analysis methods such as BSI PD 6493 and R6 have provided a basis for the safe assessment of flaws, using fracture mechanics principles. The development of related high temperature procedures, such as BSI PD 6539 and R5, extend these methods to components operating in the creep regime. This paper considers some of the factors that are important for automation of these procedures, including software design, quality assurance, validation, maintenance and user requirements. In addition, the development of a database of high temperature material properties for generic groups of commonly used structural materials is described.     

Comparability problems in the analysis of multiway data

Almost all methods for the analysis of multiway data assume that the comparison of any two entries in the data array under study reflects or represents meaningful content-specific information. This is especially the case if one wants the data analysis to yield insight into the real mechanisms underlying the data. Violation of this assumption may imply data-analytic results that are of doubtful quality at best and worthless in the worst-case scenario. In the present paper, we first clarify why comparability is a key assumption in most methods for multiway data analysis. Next, we list a number of reasons why this assumption is very often violated in practice. We then review a few possible approaches that have been advanced to deal with problems of comparability, and discuss their advantages and shortcomings. We conclude by clarifying that any satisfactory solution to comparability problems requires a very careful reflection about the data collection and the ultimate goal of the data analysis.     

Meeting the challenges related to material issues in chemical industries

Reliable performance and profitability are two important requirements for any chemical industry. In order to achieve high level of reliability and excellent performance, several issues related to design, materials selection, fabrication, quality assurance, transport, storage, inputs from condition monitoring, failure analysis etc. have to be adequately addressed and implemented. Technology related to nondestructive testing and monitoring of the plant is also essential for precise identification of defect sites and to take appropriate remedial decision regarding repair, replacement or modification of process conditions. The interdisciplinary holistic approach enhances the life of critical engineering components in chemical plants. Further, understanding the failure modes of the components through the analysis of failed components throws light on the choice of appropriate preventive measures to be taken well in advance, to have a control over the overall health of the plant. The failure analysis also leads to better design modification and condition monitoring methodologies, for the next generation components and plants. At the Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam, a unique combination of the expertise in design, materials selection, fabrication, NDT development, condition monitoring, life prediction and failure analysis exists to obtain desired results for achieving high levels of reliability and performance assessment of critical engineering components in chemical industries. Case studies related to design, materials selection and fabrication aspects of critical components in nuclear fuel reprocessing plants, NDT development and condition monitoring of various components of nuclear power plants, and important failure investigations on critical engineering components in chemical and allied industries are discussed in this paper. Future directions are identified and planned approaches are briefly described     

Latent Structures-Based Multivariate Statistical Process Control: A Paradigm Shift

ABSTRACT

The basic fundamentals of statistical process control (SPC) were proposed by Walter Shewhart for data-starved production environments typical in the 1920s and 1930s. In the 21st century, the traditional scarcity of data has given way to a data-rich environment typical of highly automated and computerized modern processes. These data often exhibit high correlation, rank deficiency, low signal-to-noise ratio, multistage and multiway structures, and missing values. Conventional univariate and multivariate SPC techniques are not suitable in these environments. This article discusses the paradigm shift to which those working in the quality improvement field should pay keen attention. We advocate the use of latent structure–based multivariate statistical process control methods as efficient quality improvement tools in these massive data contexts. This is a strategic issue for industrial success in the tremendously competitive global market.     

Nontarget analysis of urine by electrospray ionization-high field asymmetric waveform ion mobility-tandem mass spectrometry

Nearly a decade after first commercialization, high field asymmetric waveform ion mobility spectrometry (FAIMS) has yet to find its place in routine chemical analysis. Prototypes have been used to demonstrate the utility of this separation technique combined with mass spectrometry (MS). Unfortunately, first generation commercial FAIMS instruments have gone practically unused by early adopters. Here, we show this to be due to poor ion transmission in the FAIMS-MS source interface. We present simple instrumental modifications and optimization of experimental conditions to achieve good performance from the first generation commercial FAIMS device (the Ionalytics Selectra) coupled to a high resolution Q-TOF-MS. In combination with nanospray ionization, we demonstrate for the first time the nontarget analysis of urine by FAIMS with minimal sample preparation. We show the unique suitability of electrospray ionization (ESI)-FAIMS-MS for identification of low abundance species such as urinary biomarkers of damage of nucleic acids in a complex biological matrix. The elimination of electrospray noise and matrix components by FAIMS and the continuous flow of analytes through FAIMS for accurate and tandem mass analysis produce high quality spectral data suitable for structural identification of unknowns. These characteristics make ESI-FAIMS-MS ideal for nontarget identification, even when compared to high efficiency LC-ESI-MS.     

The chemical rank estimation for excitation-emission matrix fluorescence data by region-based moving window subspace projection technique and Monte Carlo simulation

A novel method, region-based on moving window subspace projection technique (RMWSPT) coupled with Monte Carlo simulation, was developed for the chemical rank estimation of excitation-emission matrix (EEM) fluorescence data arrays. RMWSPT determines the chemical rank by performing singular value decomposition (SVD) on the unfolded matrices of original data array and the subarrays yielded by a moving window, and through employing the subspace projection technique on the difference between the corresponding sub-bands of the significant eigenvectors and those of subarrays. Compared with the traditional methods, it utilizes the information from eigenvectors combined with the projection residual sum of squares values to estimate the rank of the EEM data arrays instead of using the eigenvalues. Two simulated and two real EEM data arrays were analyzed to demonstrate the excellent performance of the RMWSPT. Moreover, its performance was compared with that of other three factor-determining methods, i.e., factor indicator function (IND), the core consistency diagnostic (CORCONDIA) test and two-mode subspace comparison (TMSC) approaches. The results showed that the newly proposed method can accurately and quickly determine the chemical rank to fit the trilinear model, and it can deal with more complex situations in the presence of severe collinearity and trace concentration. The RMWSPT method thus lights a new avenue to determine the chemical rank of EEM data arrays and may hold great potential to be extended as a promising alternative for the chemical rank estimation.     

The application of multidimensional analysis to assessment of the quality of food products and their packaging

The aim of this work was to analyse the effect of quality features of both products and their packaging on customer preferences. The experimental materials were different kinds of fruit juices offered by various producers. Subsequently, physico‐chemical and sensory properties of the fruit juices were determined. Packaging quality was ascertained by testing its physical and mechanical features and visual evaluation of its general appearance. The results obtained in these researches were analysed by multidimensional methods (factor analysis, discriminant function analysis). These results indicate that product analysis has to comprise assessment of both food quality and attractiveness of its packaging. Sensory properties of a product and quality of its packaging are of fundamental importance, so foodstuff manufacturers should seriously consider customers' preferences in this regard. This study demonstrated the potential of multidimensional analysis (MDA) for extracting the most significant components among quality features of a product and its packaging, as well as the interrelations between them. Copyright © 2000 John Wiley & Sons, Ltd.     

Differentiation of prostate cancer cells using flexible fluorescent polymers

Using water-soluble, fluorescent, flexible polymers, we have devised a novel methodology for identification and differentiation of prostate cancer cells. Using a stepwise linear discriminant analysis, we demonstrate that the differential modulations of the polymer emission intensities in the presence of conditioned cell culture media can be used to distinguish between prostate cancer subtypes and between cancerous and noncancer cells. The differences in the compositions of the conditioned cell culture media are likely contributing to different fluorescence spectral patterns of the polymers. This in vitro approach may provide a novel platform for the development of an alternative prostate cancer diagnostic and subtyping technique.     

一种零件综合质量评定方法研究

零件的质量评定是柔性智能制造中十分重要的环节。现有的自动化识别装置一般采用非人工接触的光学检测系统,但由于工况环境复杂,诸多干扰因素均会影响零件质量检测与评定的准确性。另外,工业现场的连续作业对工控机硬件的运行速度、光学检测系统的环境适应性以及质量评定算法的预测准确性都提出了更高的要求。基于此,提出一种基于机器视觉与机器学习的零件综合质量评定方法。首先,借助机器视觉技术完成被测零件图像的实时采集与处理,并利用灰度匹配算法与几何匹配算法对零件的图像与CAD（computer aided design,计算机辅助设计）机械加工图进行比较,求解得到灰度匹配分数与几何匹配分数这2个几何特征参数。然后,针对零件表面的缺陷（如划伤、磨损、边缘缺料及锈蚀等）,在图像预处理（灰度化、图像增强、高斯降噪和二值化）的基础上,求解得到图像灰度的均值和标准差这2个表面缺陷特征参数。最后,借助主成分分析（principal component analysis, PCA）对零件的四维特征数据集进行降维处理,并利用K最近邻（K-nearest neighbor, KNN）算法对降维后的数据集进行训练和预测,完成零件综合质量评定;在此基础上,比较KNN算法与其他机器学习算法的准确率、召回率和特异度等指标,以验证其可行性。实验结果表明,所搭建的光学检测与处理系统在不同光源条件下的识别准确率达到96.15%以上;当相机的快门时间设定为100 μs时,该系统的图像处理速度达到45.2 帧/s。所提出的零件综合质量评定方法具有较高的准确率与处理速度,适用于复杂工况下零件的综合质量评定。     

Mechanical models of cellular solids: Parameters identification from experimental tests

Cellular materials have large use in many components acting as impact energy absorbers. These components have to be designed on the basis of the kind of impact, of the involved energy amount and of the maximum admissible load. The choice of the most suitable density for the selected type of foam is based on stress–strain behaviour, obtained by means of experimental tests and/or models. Only a few micro-mechanical models, as the Gibson model, take into account the density effects. These models could result quite complex to manage because of the need of, at least, a rough analysis of the actual foam structure. Conversely, most of the models used for numerical simulations are phenomenological models and have simple parameter identification based on fitting of experimental data, but they do not account for density effect.