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Physicochemical Data (physicochemical + data)
Selected AbstractsHabitat use of age 0 Alabama shad in the Pascagoula River drainage, USAECOLOGY OF FRESHWATER FISH, Issue 1 2010P. F. Mickle Mickle PF, Schaefer JF, Adams SB, Kreiser BR. Habitat use of age 0 Alabama shad in the Pascagoula River drainage, USA. Ecology of Freshwater Fish 2010: 19: 107,115. © 2009 John Wiley & Sons A/S Abstract,, Alabama shad (Alosa alabamae) is an anadromous species that spawns in Gulf of Mexico drainages and is a NOAA Fisheries Species of Concern. Habitat degradation and barriers to migration are considered contributing factors to range contraction that has left just the Pascagoula River drainage population in Mississippi. We studied juvenile life history and autecology in three rivers within the drainage. We collected fish, habitat and physicochemical data in three habitat types (sandbar, open channel and bank) from June to October 2004,2006. Sandbar habitat was favoured by smaller individuals early in the year. Catch per unit effort (CPUE) decreased through the summer as larger fish began occupying bank and open channel habitat. The most parsimonious model of abundance included year and river variables, while patterns of presence and absence were best explained by river, habitat type and physiochemical variables. While all three rivers in the drainage contained Alabama shad, fish were less abundant and had lower condition values in the Chickasawhay River. Earlier work suggested the Alabama shad may gradually move downstream towards the Gulf of Mexico in their first year. However, we found no evidence of this and captured large fish high in the drainage late in the year. [source] Evaluation of the evidential value of physicochemical data by a Bayesian network approachJOURNAL OF CHEMOMETRICS, Issue 7-8 2010Grzegorz Zadora Abstract The growing interest in applications of Bayesian networks (BNs) in forensic science raises the question of whether BN could be used in forensic practice for the evaluation of results from physicochemical analysis of a limited number of observations from flammable liquids (weathered kerosene and diesel fuel) by automated thermal desorption gas chromatography mass spectrometry (ATD-GC/MS), car paints by pyrolysis gas chromatography mass spectrometry (Py-GC/MS) and fibres by microspectrophotometry (MSP) in the visible (VIS) range. Therefore, various simple BN models, which allow the evaluation of both discrete and continuous types of data, were studied in order to address questions raised by the representatives of the administration of justice, concerning the identification and classification of objects into certain categories and/or the association between two items. The results of the evaluation performed by BN models were expressed in the form of a likelihood ratio, which is a well-documented measure of evidential value in the forensic field. From the results obtained, it can be concluded that BN models seem to be promising tool for evaluating physicochemical data. Copyright © 2010 John Wiley & Sons, Ltd. [source] Modeling of CO2 absorber using an AMP solutionAICHE JOURNAL, Issue 10 2006Jostein Gabrielsen Abstract An explicit model for carbon dioxide (CO2) solubility in an aqueous solution of 2-amino-2-methyl-1-propanol (AMP) has been proposed and an expression for the heat of absorption of CO2 has been developed as a function of loading and temperature. A rate-based steady-state model for CO2 absorption into an AMP solution has been proposed, using both the proposed expression for the CO2 solubility and the expression for the heat of absorption along with an expression for the enhancement factor and physicochemical data from the literature. The proposed model has successfully been applied to absorption of CO2 into an AMP solution in a packed tower and validated against pilot-plant data from the literature. © 2006 American Institute of Chemical Engineers AIChE J, 2006 [source] Optimal Synthesis of Protein Purification ProcessesBIOTECHNOLOGY PROGRESS, Issue 4 2001Elsa Vásquez-Alvarez There has been an increasing interest in the development of systematic methods for the synthesis of purification steps for biotechnological products, which are often the most difficult and costly stages in a biochemical process. Chromatographic processes are extensively used in the purification of multicomponent biotechnological systems. One of the main challenges in the synthesis of purification processes is the appropriate selection and sequencing of chromatographic steps that are capable of producing the desired product at an acceptable cost and quality. This paper describes mathematical models and solution strategies based on mixed integer linear programming (MILP) for the synthesis of multistep purification processes. First, an optimization model is proposed that uses physicochemical data on a protein mixture, which contains the desired product, to select a sequence of operations with the minimum number of steps from a set of candidate chromatographic techniques that must achieve a specified purity level. Since several sequences that have the minimum number of steps may satisfy the purity level, it is possible to obtain the one that maximizes final purity. Then, a second model that may use the total number of steps obtained in the first model generates a solution with the maximum purity of the product. Whenever the sequence does not affect the final purity or more generally does not impact the objective function, alternative models that are of smaller size are developed for the optimal selection of steps. The models are tested in several examples, containing up to 13 contaminants and a set of 22 candidate high-resolution steps, generating sequences of six operations, and are compared to the current synthesis approaches. [source] | |||||||||||||