Measurements provide the basis for process monitoring and control as well as for model development and validation. Systematic approaches to increase the accuracy and credibility of the empirical data set are therefore of great value. In (bio)chemical conversions, linear conservation relations such as the balance equations for charge, enthalpy, and/or chemical elements, can be employed to relate conversion rates. In a pactical situation, some of these rates will be measured (in effect, be calculated directly from primary measurements of, e.g., concentrations and flow rates), as others can or cannot be calculated from the measured ones. When certain measured rates can also be calculated from other measured rates, the set of equations, the accuracy and credibility of the measured rates can indeed be improved by, respectively, balancing and gross error diagnosis. The balanced conversion rates are more accurate, and form a consistent set of data, which is more suitable for further application (e.g., to calculate nonmeasured rates) than the raw measurements. Such an approach has drawn attention in previous studies. The current study deals mainly with the problem of mathematically classifying the conversion rates into balanceable and calculable rates, given the subset of measured rates. The significance of this problem is illustrated with some examples. It is shown that a simple matrix equation can be derived that contains the vector of measured conversion rates and the redundancy matrix R. Matrix R plays a predominant role in the classification problem. In supplementary articles, significance of the redundancy matrix R for an improved gross error diagnosis approach will be shown. In addition, efficient equations have been derived to calculate the balanceable and/or calculable rates. The method is completely based on matrix algebra (principally different from the graph-theoretical approach), and it is easily implemented into a computer program. (c) 1994 John Wiley & Sons, Inc.
Conservation equations derived from elemental balances, heat balances, and metabolic stoichiometry, can be used to constrain the values of conversion rates of relevant components. In the present work, their use will be discussed for detection and localization of significant errors of the following types: 1.At least one of the primary measurements has a significant error (gross measurement error).2.The system definition is incorrect: a component a.is not included in the system description.b.has a composition different from that specified.3.The specified variances are too small, resulting in a too-sensitive test.The error diagnosis technique presented here, is based on the following: given the conservation equations, for each set of measured rates, a vector of residuals of these equations can be constructed, of which the direction is related to the error source, as its length is a measure of the error size. The similarity of the directions of such a residual vector and certain compare vectors, each corresponding to a specific error source, is considered in a statistical test. If two compare vectors that result from different error sources have (almost) the same direction, errors of these types cannot be distinguished from each other. For each possible error in the primary measurements of flows and concentrations, the compare vector can be constructed a priori, thus allowing analysis beforehand, which errors can be observed. Therefore, the detectability of certain errors likely to occur can be insured by selecting a proper measurement set. The possibility of performing this analysis before experiments are carried out is an important advantage, providing a profound understanding of the detectability of errors. The characteristics of the method with respect to diagnosis of simultaneous errors and error size estimation are discussed and compared to those of the serial elimination method and the serial compensation strategy, published elsewhere. (c) 1994 John Wiley & Sons, Inc.
Main hurdles of lignin valorization are its diverse chemical composition, recalcitrance, and poor solubility due to high-molecular weight and branched structure. Controlled fragmentation of lignin could lead to its use in higher value products such as binders, coatings, fillers, etc. Oxidative enzymes (i.e., laccases and peroxidases) have long been proposed as a potentially promising tool in lignin depolymerization. However, their application was limited to ambient pH, where lignin is poorly soluble in water. A Finnish biotechnology company, MetGen Oy, that designs and supplies industrial enzymes, has developed and brought to market several lignin oxidizing enzymes, including an extremely alkaline lignin oxidase MetZyme® LIGNO™, a genetically engineered laccase of bacterial origin. This enzyme can function at pH values as high as 10–11 and at elevated temperatures, addressing lignin at its soluble state. In this article, main characteristics of this enzyme as well as its action on bulk lignin coming from an industrial process are demonstrated. Lignin modification by MetZyme® LIGNO™ was characterized by size exclusion chromatography, UV spectroscopy, and dynamic light scattering for monitoring particle size of solubilized lignin. Under highly alkaline conditions, laccase treatment not only decreased molecular weight of lignin but also increased its solubility in water and altered its dispersion properties. Importantly, organic solvent-free soluble lignin fragmentation allowed for robust industrially relevant membrane separation technologies to be applicable for product fractionation. These enzyme-based solutions open new opportunities for biorefinery lignin valorization thus paving the way for economically viable biorefinery business.
This article presents a method to test the presence of relatively small systematic measurement errors; e.g., those caused by inaccurate calibration or sensor drift. To do this, primary measurements-flow rates and concentrations-are first translated into observed conversions, which should satisfy several constraints, like the laws of conservation of chemical elements. This study considers three objectives: 1.Modification of the commonly used balancing technique to improve error sensitivity to be able to detect small systematic errors. To this end, the balancing technique is applied sequentially in time.2.Extension of the method to enable direct diagnosis of errors in the primary measurements instead of diagnosing errors in the observed conversions. This was achieved by analyzing how individual errors in the primary measurements are expressed in the residual vector.3.Derivation of a new systematic method to quantitatively determine the sensitivity of the error, is that error size at which the expected value of the chisquare test function equals its critical value.The method is applied to industrial data demonstrating the effectiveness of the approach. It was shown that, for most possible error sources, a systematic errors of 2% to 5% could be detected. In given application, the variation of the N-content of biomass was appointed to be the cause of errors. (c) 1994 John Wiley & Sons, Inc.
Glutamine is a major source of energy, carbon, and nitrogen for mammalian cells. The amount of glutamine present in commercial mammalian cell media is, however, not necessarily balanced with cell requirements. Therefore, the effects of glutamine limitation on the physiology of two mammalian cell lines were studied in steady-state chemostat cultures fed with IMDM medium with 5% serum. The cell lines used were MN12, a mouse-mouse hybridoma, and SP2/0-Ag14, a mouse myeloma often used in hybridoma fusions. Cultures, grown at a fixed dilution rate of 0.03 h −1 , were fed with media containing glutamine concentrations ranging from 0.5 to 4 mmol L −1 . Biomass dry weight and cell number were linearly proportional to the glutamine concentrations fed, between 0.5 and 2 mmol L −1 , and glutamine was completely consumed by both cell lines. From this it was concluded that glutamine was the growthlimiting substrate in this concentration range and that the standard formulation of IMDM medium contains a twofold excess of glutamine. In glutamine-limited cultures, the specific rates of ammonia and alanine production were low compared to glutamine-excess cultures containing 4 mmol L −1 glutamine in the feed medium. The specific consumption rates of nearly all amino acids decreased with increasing glutamine feed, indicating that, in their metabolic function, they may partially be replaced by glutamine. Both cell lines reacted similarly to differences in glutamine feeding in all aspects investigated, except for glucose metabolism. In SP2/0-Ag14 glutamine feed concentrations did not affect the specific glucose consumption, whereas in MN12 this parameter increased with increasing amounts of glutamine fed. This systematic study using controlled culture conditions together with a detailed analysis of culture data shows that, although cells may react similarly in many aspects, cell-line-specific characteristics may be encountered even with respect to fundamental physiological responses like the interaction of the glutamine and glucose metabolism.
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