A review of antioxidant analysis in food products

To permit proper usage of antioxidants by the food processor and permit control under applicable governmental regulations, it is necessary to have adequate analytical methods. Such methods should both positively identify and provide a quantitative assay for the additive. Due to the complex nature of foods, analysis of an antioxidant in the very small quantities used presents a very real problem. Solvent extraction and/or steam distillation techniques are employed to separate the antioxidants from the food. Ultraviolet spectra, gas chromatography and colorimetric techniques are used to identify and determine the quantity of each antioxidant present. Slight variations are necessary for each type of food.     

Numerical simulation of gas flow through porous sandstone and its experimental validation

Due to post-lithogenetic fracturing or weathering, sandstone can contain complex dual porosity structure, which makes it difficult to identify the fluid flow behaviour through it. The main objective of this study is to develop a three dimensional numerical model to simulate the flow of gas through porous sandstone under triaxial test condition. For the purpose of the modelling study, laboratory data which have been obtained from triaxial experiments conducted on porous sandstone samples [1] were used. In this study, a commercial reservoir simulator, COMET 3 was used to model the gas flow in the test samples. The COMET 3 model closely predicts the gas flow through the porous sandstone sample for the range of confining and gas injection pressures studied in the laboratory and for low gas flow rates (laminar flow). However the model fails at high flow rates (turbulent flows), due to the fact that the COMET 3 simulator uses Darcy’s law for flow simulations. Therefore, caution is required when interpreting the model results if the assumption of laminar flow does not apply to the flow conditions. An empirical relationship has been developed in this study which can be used to obtain an estimation of the flowrate when the flow has become non-Darcian. It is however important to be able to identify the transition point from Darcy to non-Darcy flow when the assumption of Darcian flow in COMET 3 no longer applies. Experiments conducted by Yi et al. [1] show very clearly the transition points, which are dependent on the injection and confining pressures. The model developed using COMET 3 appeared to give better prediction of the gas flow rate in sandstone sample, under triaxial test condition, than the COMSOL Multiphysics model given in the study in Yi et al. [1].     

Estimation of parameters for a log-normal distribution with truncated measurements

Three methods are developed for estimating the parameters of a log-normal distribution when the experimental data are truncated and particles below a characteristic size are not counted. Two of the methods are iterative and were found to converge, although slowly when only a fraction of the distribution is measured.     

Is Weibull distribution the most appropriate statistical strength distribution for brittle materials?

Strength reliability, one of the critical factors restricting wider use of brittle materials in various structural applications, is commonly characterized by Weibull strength distribution function. In the present work, the detailed statistical analysis of the strength data is carried out using a larger class of probability models including Weibull, normal, log-normal, gamma and generalized exponential distributions. Our analysis is validated using the strength data, measured with a number of structural ceramic materials and a glass material. An important implication of the present study is that the gamma or log-normal distribution function, in contrast to Weibull distribution, may describe more appropriately, in certain cases, the experimentally measured strength data.     

Aerosol nucleation and growth in a turbulent jet using the Stochastic Fields method

The Stochastic Fields transported PDF method for turbulent reacting flows has been used to model the nucleation and growth of dibutyl phthalate particles in a hot, turbulent jet in a colder background for which experimental data is available. The aerosol population is modelled using an assumed log-normal size distribution. It has been found that neglecting the effect of turbulent fluctuations leads to the peak particle concentration being predicted too close to the jet and the concentration downstream underpredicted. However, this effect was small compared to that of adjusting modelled surface tension. Only by adjusting this was it possible to reproduce correctly the downstream evolution of particle number found in experiment. Particle mass mean diameter was significantly underpredicted at the centre of the jet, which may be due to the inability of log-normal size distribution to capture the distribution in detail. Taking account of turbulent fluctuations leads to increased mean particle size at the edge of the plume. The extent of this increase is strongly dependent on the choice of micromixing timescale.     

Electrochemical technique for investigating temporarily protective oil coatings

A wire-beam electrode using mild steel wires has been developed and used to study temporarily preventive oil coatings in terms of the heterogeneous electrochemical states after immersion in a salt solution. It has been found that the electrochemical states on the surface of the wire-beam electrode are homogeneous compared with an oil-painted electrode. The distribution of corrosion potential on oil-painted wire-beam electrodes is heterogeneous and follows a discontinuous binomial probability distribution. Polarization resistance of each oil-coated wire sensor is randomly distributed over a given range of resistance and follows a log-normal probability distribution. The distribution of corrosion potential over a high potential range can be increased, distribution of polarization resistance over a low resistance range can be decreased and eliminated by adding oil-soluble inhibitor. With increasing concentration of oil-soluble inhibitor, the distribution of anodic polarization resistance of oil coatings may change from discontinuous binomial distribution to exponential distribution and to log-normal probability distribution, the distribution of cathodic polarization resistance of oil coatings will transform from discontinuous binomial distribution to log-normal probability distribution.     

Optical Properties of Aluminum Oxide: Determined from Vacuum Ultraviolet and Electron Energy-Loss Spectroscopies

The optical properties of alpha-Al₂O₃ have been determined by two independent methods, vacuum ultraviolet (VUV) spectroscopy and electron energy-loss spectroscopy (EELS) over the energy range from 6 to 142 eV. For each experimental method two sets of high-quality data have been measured and analyzed from alpha-Al₂O₃. The evolution of the differences between the data for each experimental method and its associated analytical method indicate the reliability of the results, and the comparison between the methods emphasizes the relative advantages of each. VUV spectroscopy offers a higher energy resolution, resolving sharper features in the spectra, whereas EELS significantly extends the energy range, which has been exploited here to 140 eV but can be extended even further. Good overall consistency is found, but there are pronounced differences in the valence region from 10 to 30 eV, where strong absorptions are present, increasing the relative variability of the analysis. This demonstrates that accuracy estimates of the optical properties are meaningful only when supplied as a function of energy, because both strong intrinsic absorptions and weak experimental signals make accurate determinations difficult. Moreover, variations in the optical properties are observed most easily in the interband transition strength, J _cv, and are less evident when the optical properties are represented as the complex index of refraction. Because the optical properties can change with specimen origin and preparation and because of the details of data acquisition and numerical analysis procedures, assessing the contributions of each of these methods to our accurate knowledge of the optical constants is essential.     

A weighted zero-inflated Poisson model for estimation of recurrence of adenomas

In this article, a weighted zero-inflated Poisson (W-ZIP) approach to modelling colorectal adenoma data is used in which the number of recurrent adenomas is subject to measurement error and some participants might have their follow-up colonoscopy conducted before the end of trial. The weights are used to adjust for varying follow-up and obtained from a nonparametric survival function derived from the lengths of follow-up. It is shown that logistic regression (LR) and survival analysis tend to underestimate recurrence rate due to measurement error on the status of recurrence. A simulation study shows that the W-ZIP model is robust to the assumption of the underlying distribution of time-to-recurrence and is less affected by misclassification at follow-up colonoscopy when compared with LR and survival analysis approaches. The method described here is illustrated with an example from a colon cancer study.     

Rapid Check of Cascade Impactor Cut-Sizes using a Polydisperse Challenge Aerosol Calibration Method

A method has been developed to check the 50% cut-size values of cascade impactor stages. The method involves generating a broad-size, log-normally distributed aerosol that covers the range of 50% cut-sizes for the impactor being tested. The amount of deposit on each impaction plate is analyzed and a histogram of the resulting aerosol size distribution plotted, using the amount of aerosol collected on each impaction plate and the published values for the cut-sizes of the impactor in question. If the particle size distribution indicated by the histogram does not result in a log-normal distribution, one or more of the assumed cut-sizes of the impactor are in error. The incorrect cut-sizes of the impactor can then be adjusted until the curve is log-normal, and these adjusted cut-sizes are the correct values for the impactor stages.     

沉积型磷矿酸解过程的介微观反应机理

当前,世界磷矿资源日趋枯竭,迫切需要开发利用中低品位磷矿。介绍采用扫描电镜、能谱分析和Ｘ射线衍射等现代测试方法,对沉积型磷矿的酸解动力学过程介微观现象进行了研究,发现已反应完毕的区域与尚未反应的区域之间的反应界面不是一个面,而是一个过渡区域,这一反应区域将逐步向颗粒中心移动。根据固相物质的分形结构与反应机理提出的机理模型能较好地描述这一过程。     

Considerations in estimating Nitrogen Recovery Efficiency by the difference and isotopic dilution methods

Nitrogen Recovery Efficiencies (NRE) as calculated by the Isotopic dilution technique or the difference method are subject to errors under different conditions. The assumptions underlying these methods and the conditions and factors that must be considered while using these methods have been discussed. Majority of the reports suggest that the difference method gives higher values than the isotopic dilution technique. Results of a pot experiment show the importance of accounting the N held in roots for estimating NRE by either of the methods. Although the isotopic dilution technique has been invariably more precise, it was not necessarily representing the true NRE value. Contrary to some earlier reports, it was observed that Added Nitrogen Interaction (ANI) occurred even in field experiments. Guidelines are provided to assist researchers in assessing the validity of using isotopic or difference method in a given situation. For conditions where the NRE values obtained by either of the methods are influenced by ANI, a method of correcting the NRE values has been suggested, to arrive at the most probable value.     

Predicting laminar-turbulent transition in Poiseuille pipe flow for non-Newtonian fluids

We present a new phenomenological approach for quantifying laminar-turbulent transition in pipe flow. This criterion is based on averaging a local Reynolds number to give Re_G. Our localised parameter shows strong radial variations that are maximal at approximately the radial positions where puffs first appear during the first stages of turbulent transition. We present comparative data for experiments conducted with Glycerin, Xanthan and Carbopol solutions, each of which serves to demonstrate the validity of our approach.     

Concurrent phase partition and between‐mode statistical analysis for multimode and multiphase batch process monitoring

The exiting automatic phase partition and phase‐based process monitoring strategies are in general limited to single‐mode multiphase batch processes. In this article, a concurrent phase partition and between‐mode statistical modeling strategy (CPPBM) is proposed for online monitoring of multimode multiphase batch processes. First, the time‐varying characteristics of batch processes are concurrently analyzed across modes so that multiple sequential phases are simultaneously identified for all modes. The feature is that both time‐wise dynamics and mode‐wise variations are considered to get the consistent phase boundaries. Then within each phase, between‐mode statistical analysis is performed where one mode is chosen for the development of reference monitoring system and the relative changes from the reference mode to each alternative mode are analyzed. From the between‐mode perspective, each of the original reference monitoring subspaces, including systematic subspace and residual subspace, are further decomposed into two monitoring subspaces for each alternative mode, which reveal two kinds of between‐mode relative variations. The part which shows significant increases represents the variations that will cause alarm signals if the reference models are used to monitor the alternative modes, whereas the part that shows no increases will not issue alarms. By modeling and monitoring different types of between‐mode relative variations, the proposed CPPBM method can not only efficiently detect faults but also offer enhanced process understanding. It is illustrated with a typical multiphase batch process with multiple modes. © 2013 American Institute of Chemical Engineers AIChE J 60: 559–573, 2014     

MODELING AND SIMULATION OF MEE SYSTEM USED IN THE SUGAR INDUSTRY

In this work, a generalized steady-state mathematical model has been developed for simulation of the multiple effect evaporator (MEE) system, used in the Indian sugar industry. The developed model is capable of handling exhaust steam (saturated/superheated) inputs in more than one effect, vapor bleeding from desired effects, heat loss from each effect, and variations in boiling point rise as well as specific heat capacity with combination, heat transfer coefficient through external empirical correlations, and condensate flashing. The developed model has been solved by the globally convergent method. The results of present investigations have been validated against the data obtained from the Indian sugar industry with seven effects. The predicted exit liquor concentration, vapor body temperature, and amount of vapor bleed from each effect shows close agreement with the industry data within a maximum error band of ±2%. Further, a correlation has been developed for the prediction of overall heat transfer coefficient (OHTC) of each effect. The developed model can be further used to improve the steam economy of the MEE system by the incorporation of flash vapors from condensate stream.     

A general approach to evaluating agreement between two observers or methods of measurement from quantitative data with replicated measurements

We present a general approach to the definition and estimation of coefficients for evaluating agreement between two fixed methods of measurements or human observers. The measured variable is assumed to be continuous with a finite second moment. No other distributional assumptions are made. We introduce the term ;disagreement function' for the function of the observations that is used to quantify the extent of disagreement between the two measurements made on the same subject. The proposed inter-methods agreement coefficients compare the disagreement between measurements made by different methods on the same subject to the corresponding disagreement between replicated measurements made by the same method. Therefore, the new coefficients require data with replications readings. We propose inter-methods agreement coefficients for two practical situations involving two methods that have a measurement error: 1) comparison of a new method to a gold standard (or a reference method), and 2) comparison of two methods where neither method is considered a gold standard. We consider three disagreement functions based on the differences between two measurements: 1) the mean squared difference, 2) the mean absolute difference and 3) the mean relative difference. We then derive non-parametric estimates for the various agreement coefficients. Our approach is illustrated using data from a study comparing systolic blood pressure measurements by a human observer and an automatic monitor. The performance of the new estimates is assessed via stochastic simulations.     

Simulation of Particle Size-Selective Air Samplers Placed in a Polydisperse Aerosol

The results of a numerical simulation of several air sampling instruments are presented. They are assumed to sample the same aerosol, with a log-normal particle-size distribution. Four instruments were studied: the 10-mm nylon cyclone, the MRE 113A gravimetric sampler, the CPM 3, and the CIP 10. The experimental data of particle collection efficiency were reduced by a model for each instrument. The model used combines two cumulative log-normal distribution functions, in order to have a good degree of flexibility necessary for representing the data of some devices that exhibit a maximum in efficiency (CPM 3, CIP 10). The concentrations “measured” by several air samplers were compared with each other; the differences were analyzed as functions of the aerosol parameters: mass median aerodynamic diameter and σ_g. The results that were obtained and those calculated from standard collection efficiencies, defining the conventional alveolar fraction of the aerosol, were also taken into account. This simulation method can be extended to any type of instrument and aerosol, and enables the prediction of the maximal deviations that could be observed between different instruments, or between one instrument and some reference standards.     

On the modified Stefan-Maxwell equation for isothermal multicomponent gaseous diffusion

Understanding multicomponent gaseous diffusion in porous media is crucial to describing the transport of fuel and reaction products in the anode of a solid oxide fuel cell, for which this work was originally pursued. The Stefan-Maxwell approach provides a general theoretical framework so that measured or predicted binary diffusion coefficients may be utilized for multicomponent diffusion (for which Fick's law is invalid). This approach has since been extended to account for a porous solid structure resulting in what is usually referred to as the “modified Stefan-Maxwell equation”, which is the subject of the present work. Using a virtual experiment involving ternary diffusion and the modified Stefan-Maxwell equation, it is shown that multicomponent diffusion in the Knudsen regime (in which wall drag is significant) produces a gradient in total pressure, which then drives the diffusion of gaseous components for which there are no mole fraction gradients. To the author's knowledge, this peculiar phenomenon has not been verified by a real experiment. The analysis also shows that bulk diffusion in the present virtual experiment is equimolar, which contradicts the common assertion that Graham's relation is valid even in conditions where bulk diffusion is dominant. Finally, the present work shows the importance of the term involving the total pressure gradient in the modified Stefan-Maxwell equation. In the literature, the gradient in total pressure is often mistakenly associated only with permeation. This paper demonstrates that it is an essential part of the driving force for diffusion and its omission leads to an erroneous prediction in the present virtual experiment. A detailed derivation of the modified Stefan-Maxwell equation is also provided, underscoring the relevance of the total pressure gradient term.     

The sequential normal scores transformation

The sequential analysis of series often requires nonparametric procedures, where the most powerful ones frequently use rank transformations. Reranking the data sequence after each new observation can become too intensive computationally. This led to the idea of sequential ranks, where only the most recent observation is ranked. However, difficulties finding, or approximating, the null distribution of the statistics may have contributed to the lack of popularity of these methods. In this article, we propose transforming the sequential ranks into sequential normal scores that are independent and asymptotically standard normal random variables. Thus, original methods based on the normality assumption may be used.

A novel approach permits the inclusion of a priori information in the form of quantiles. It is developed as a strategy to increase the sensitivity of the scoring statistic. The result is a powerful convenient method to analyze non normal data sequences. Also, four variations of sequential normal scores are presented using examples from the literature. Researchers and practitioners might find this approach useful to develop nonparametric procedures to address new problems extending the use of parametric procedures when distributional assumptions are not met. These methods are especially useful with large data streams where efficient computational methods are required.     

Determination of lamella thickness distributions in isotactic polypropylene by X-ray line profile analysis

X-ray line profile analysis was used to determine the size distribution of the crystalline lamellae in isotactic polypropylene (iPP) assuming a log-normal size distribution. A comparison with the size distribution as determined by differential scanning calorimetry (DSC) yields an excellent agreement of both methods. It is noted that the agreement depends strongly on whether linear lattice defects, particularly dislocations are taken into account in the X-ray analysis. This is especially true for deformed iPP with a high number of deformation induced dislocations. It was also found that for a multimodal distribution of lamella thickness in the DSC experiment as induced by the introduction of titanium dioxide nanoparticles as filler material the lamella thickness distribution from X-ray profile analysis is still in good agreement with DSC although the model used was only monomodal.     

Using multiple genetic variants as instrumental variables for modifiable risk factors

Mendelian randomisation analyses use genetic variants as instrumental variables (IVs) to estimate causal effects of modifiable risk factors on disease outcomes. Genetic variants typically explain a small proportion of the variability in risk factors; hence Mendelian randomisation analyses can require large sample sizes. However, an increasing number of genetic variants have been found to be robustly associated with disease-related outcomes in genome-wide association studies. Use of multiple instruments can improve the precision of IV estimates, and also permit examination of underlying IV assumptions. We discuss the use of multiple genetic variants in Mendelian randomisation analyses with continuous outcome variables where all relationships are assumed to be linear. We describe possible violations of IV assumptions, and how multiple instrument analyses can be used to identify them. We present an example using four adiposity-associated genetic variants as IVs for the causal effect of fat mass on bone density, using data on 5509 children enrolled in the ALSPAC birth cohort study. We also use simulation studies to examine the effect of different sets of IVs on precision and bias. When each instrument independently explains variability in the risk factor, use of multiple instruments increases the precision of IV estimates. However, inclusion of weak instruments could increase finite sample bias. Missing data on multiple genetic variants can diminish the available sample size, compared with single instrument analyses. In simulations with additive genotype-risk factor effects, IV estimates using a weighted allele score had similar properties to estimates using multiple instruments. Under the correct conditions, multiple instrument analyses are a promising approach for Mendelian randomisation studies. Further research is required into multiple imputation methods to address missing data issues in IV estimation.