An optimization‐based undeflated PLS (OUPLS) method to handle missing data in the training set

Advances in sensory systems have led to many industrial applications with large amounts of highly correlated data, particularly in chemical and pharmaceutical processes. With these correlated data sets, it becomes important to consider advanced modeling approaches built to deal with correlated inputs in order to understand the underlying sources of variability and how this variability will affect the final quality of the product. Additional to the correlated nature of the data sets, it is also common to find missing elements and noise in these data matrices. Latent variable regression methods such as partial least squares or projection to latent structures (PLS) have gained much attention in industry for their ability to handle ill‐conditioned matrices with missing elements. This feature of the PLS method is accomplished through the nonlinear iterative PLS (NIPALS) algorithm, with a simple modification to consider the missing data. Moreover, in expectation maximization PLS (EM‐PLS), imputed values are provided for missing data elements as initial estimates, conventional PLS is then applied to update these elements, and the process iterates to convergence. This study is the extension of previous work for principal component analysis (PCA), where we introduced nonlinear programming (NLP) as a means to estimate the parameters of the PCA model. Here, we focus on the parameters of a PLS model. As an alternative to modified NIPALS and EM‐PLS, this paper presents an efficient NLP‐based technique to find model parameters for PLS, where the desired properties of the parameters can be explicitly posed as constraints in the optimization problem of the proposed algorithm. We also present a number of simulation studies, where we compare effectiveness of the proposed algorithm with competing algorithms. Copyright © 2014 John Wiley & Sons, Ltd.     

Comprehensive Review on Application of FTIR Spectroscopy Coupled with Chemometrics for Authentication Analysis of Fats and Oils in the Food Products

Currently, the authentication analysis of edible fats and oils is an emerging issue not only by producers but also by food industries, regulators, and consumers. The adulteration of high quality and expensive edible fats and oils as well as food products containing fats and oils with lower ones are typically motivated by economic reasons. Some analytical methods have been used for authentication analysis of food products, but some of them are complex in sampling preparation and involving sophisticated instruments. Therefore, simple and reliable methods are proposed and developed for these authentication purposes. This review highlighted the comprehensive reports on the application of infrared spectroscopy combined with chemometrics for authentication of fats and oils. New findings of this review included (1) FTIR spectroscopy combined with chemometrics, which has been used to authenticate fats and oils; (2) due to as fingerprint analytical tools, FTIR spectra have emerged as the most reported analytical techniques applied for authentication analysis of fats and oils; (3) the use of chemometrics as analytical data treatment is a must to extract the information from FTIR spectra to be understandable data. Next, the combination of FTIR spectroscopy with chemometrics must be proposed, developed, and standardized for authentication and assuring the quality of fats and oils.     

Estimation of partial linear error-in-variables models for ρ<Superscript>−</Superscript>-mixing dependence data

Consider the partly linear regression model Y = xβ + g(t) + e where the explanatory x is erroneously measured, and both t and the response Y are measured exactly, the random error e is ρ⁻-mixing. Let be a surrogate variable observed instead of the true x in the primary survey data. Assume that in addition to the primary data set containing N observations of , which is ρ⁻-mixing data sets, an independent validation data containing n observations of is available. The exact observations on x may be obtained by some expensive or diffcult procedures for only a small subset of subjects enrolled in the study. In this paper, inspired by Berberan-Santos et al. [J. Math. Chem. 37 (2005)101], a semiparametric method with the primary data is employed to obtain the estimators of β and g(·) based on the least squares criterion with the help of validata. The proposed estimators are proved to be strongly consistent.      

Semiclassical transition state theory/master equation kinetics of HO + CO: Performance evaluation

Previously, master equation (ME) simulations using semiclassical transition state theory (SCTST) and high-accuracy extrapolated ab initio thermochemistry (HEAT) predicted rate constants in excellent agreement with published experimental data over a wide range of pressure and temperatures ≳250 K, but the agreement was not as good at lower temperatures. Possible reasons for this reduced performance are investigated by (a) critically evaluating the published experimental data and by investigating; (b) three distinct ME treatments of angular momentum, including one that is exact at the zero- and infinite-pressure limits; (c) a hindered-rotor model for HOCO that implicitly includes the cis- and trans-conformers; (d) possible empirical adjustments of the thermochemistry; (e) possible empirical adjustments to an imaginary frequency controlling tunneling; (f) including or neglecting the prereaction complex PRC1; and (g) its possible bimolecular reactions. Improvements include better approximations to factors in SCTST and using the Hill and van Vleck treatment of angular momentum coupling. Evaluation of literature data does not reveal any specific shortcomings, but the stated uncertainties may be underestimated. All ME treatments give excellent fits to experimental data at T ≥ 250 K, but the discrepancy at T < 250 K persists. Note that each ME model requires individual empirical energy transfer parameters. Thermochemical adjustments were unable to match the experimental H/D kinetic isotope effects. Adjusting an imaginary frequency can achieve good fits, but the adjustments are unacceptably large. Whether PRC1 and its possible bimolecular reactions are included had little effect. We conclude that none of the adjustments is an improvement over the unadjusted theory. Note that only one set of experimental data exists in the regime of the discrepancy with theory, and data for DO + CO are scanty.     

Poly (ether amide) and silica nanocomposites derived from sol–gel process

The sol–gel derived chemically combined organic–inorganic nanocomposites were synthesized from poly(etheramide) and tetraethoxysilane. Reaction of a mixture of 4-aminophenyl ether and 1,3-phenyldiamine with terephthaloyl chloride (TPC) in dimethylacetamide (DMAc) produced the amide chains. These chains were modified with carbonyl chloride end groups using a slight excess of diacid chloride and were then reacted with aminophenyl trimethoxysilane (APTMOS), where the amine group reacted with carbonyl chloride end groups. Hydrolysis/condensation of tetraethoxysilane (TEOS) and alkoxy groups present in APTMOS developed bonding between the polyamide chains and inorganic silica network generated in situ. By changing the relative proportions of the polymer solution and the amount of TEOS, the composition of hybrid films was varied. Thin hybrid films with various concentrations of silica network obtained after evaporation of the solvent were subjected to mechanical, dynamic mechanical thermal and morphological measurements. The results indicate a gradual increase in the modulus (3.84 GPa) and tensile strength (121 MPa) up to 15-wt.% silica relative to the pure polyamide. The elongation at break point and toughness gradually decrease with addition of silica content. These hybrids were found to be thermally stable up to a temperature of 500 °C. The weight retained above 800 °C was roughly proportional to amount of silica in the matrix. The glass transition temperature and the storage moduli increased with increasing silica concentration. The maximum increase in the T _g value (358 °C) was observed with 15-wt.% silica. Scanning electron micrographs indicated the uniform distribution of silica in the composites with an average particle size ranging from 9 to 47 nm.     

Studies on the analytical performance of a non-covalent coating with N,N-didodecyl-N,N-dimethylammonium bromide for separation of basic proteins by capillary electrophoresis in acidic buffers in 25-and 50-μm capillaries

Capillaries (25-and 50-μm inner diameter) coated with a double-alkyl-chain cationic surfactant N,N-didodecyl-N,N-dimethylammonium bromide (DDAB) were used for the separation of four basic standard proteins in buffers of pH 4 at various ionic strengths. The choice of buffer is critical for the analytical performance. Ammonium ions must be avoided in the buffer used in the non-covalent coating procedure owing to competition with the surfactant. Phosphate buffer gave a better separation performance than some volatile buffers; the reason seems to be a complex formation between the proteins and dihydrogenphosphate ions, which decreases tendencies for adsorption to the capillary surface. The DDAB coating was easy to produce and stable enough to permit, without recoating, consecutive separations of the proteins for up to 100 min with good precision in migration times and peak areas. A strong electroosmotic flow gives rapid separations, which is of special importance when commercial instruments are used, since the choice of the length of the capillary is restricted. Figure EOF stability in 25 micrometer i.d. capillaries. Consecutive injections of mesityloxide performed after an initial coating with 1.0     

On the use of AES data analysis to determine local enrichments of conversion coating elements at intermetallic particles on rolled Al

In this paper, the behaviour of the industrial applied Ti/Zr conversion coating (CC) pretreatment on rolled automotive aluminium samples (AA5182) is analysed. Due to its nanometre lateral and depth resolution, Auger electron spectroscopy (AES) is used to analyse the CC distribution at surface cathodic intermetallic particles. As a result of its high surface sensitivity, the AES technique is very susceptible to differences in the top contamination layer thickness. It is demonstrated that AES point measurements performed on aluminium model samples coated with 1.5 and 3 nm of Ti (oxide) layer cannot differentiate the two-layer thicknesses if a difference in the top contamination thickness is not taken into account. A data analysis methodology is introduced, based on the ratio of normalized peak areas (enrichment ratios), to eliminate the effect of the contamination layer thickness. The experimental validation of the methodology is performed on the model samples, demonstrating errors of 2% on the enrichment ratios on similar samples with different contamination layer thicknesses, while the conventional spectra quantification results in errors of 49%. The methodology is also theoretically substantiated within certain constraints. By the use of the AES methodology, an enriched Ti and Zr deposition is confirmed at the cathodic intermetallic particles at the surface of the industrial no-rinse CC sprayed automotive aluminium sheet samples.     

基于极课大数据的初中化学组卷及试卷评价

为了提高组卷质量,基于极课大数据建立初中化学校本题库,根据双向细目表,利用该系统的出卷功能进行组卷。采用SPSS软件对试卷难度、区分度、信度和效度进行综合分析和评价,可知基于极课所出试卷各项评价指标较优秀,符合考试要求,试卷质量高。     

Structural and luminescence characteristics of CuAlxIn1−xSe2 (0 < x ≤ 0.30) chalcopyrite solid solutions

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~(13)C代谢通量分析

代谢通量分析(metabolic flux analysis,MFA)是通过确定代谢网络中代谢流分布来表征细胞代谢状态的强有力的工具。鉴于计量学代谢通量分析在处理复杂代谢网络时表现出的局限性,发展了以13C标记实验为基础的13C MFA。本文介绍了13C MFA的原理与方法,总结和评述了13C MFA在实验与数据分析方面的最新进展以及MFA在功能基因组研究中的重要地位,同时对代谢通量分析的发展前景进行了展望。