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Continued innovations in the polymer industry have made polymer surface modification methods a subject of intense research. The importance and necessity of surface modification of plastics are explained, and the advantages of physical surface treatments over the less-sophisticated chemical methods are outlined. Currently available physical surface modification methods for food packaging polymers are reviewed from the food packaging perspective. These physical surface modification methods include flame, corona discharge, UV, gamma-ray, electron beam, ion beam, plasma, and laser treatments. The principle of operation of each method is briefly described, and the advantages and disadvantages of each technique are cited. The extent to which each of these methods can produce the specific modifications desired is discussed. Furthermore, the effects of each treatment on barrier, mechanical, and adhesion properties of food packaging polymers are also examined. Finally, an overview of economic aspects of sophisticated surface modification techniques, including ion beam, plasma, and laser treatments, is presented.

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The problem of operating a tray freeze dryer to obtain a desired final bound water content in minimum time is formulated as an optimal control problem with the use of the rigorous unsteady state mathematical model of Sadikoglu and Liaois 191 that has been found to describe satisfactorilv the exoerimental dvnamic . . . behavior of the primary and secondary drying stages of bulk solution freeze drying of pharmaceuticals in trays. The heat input to the material being dried and 400 SADIKOGLU. LIAPIS. AND CROSSER the drying chamber pressure are considered to be control variables. Constraints are placed on the system state variables by the melting and scorch temperatures during primary drying, and by the scorch temperature during secondary drying. Necessary conditions of optimality for both the primary and secondary drying stages are derived and presented, and an approach for constructing the optimal control policies that would minimize the drying times for both the primary and secondary drying stages, is presented. The theoretical approach presented in this work was applied in the freeze drying of skim milk, and significant reductions in the drying times of primary and secondary drying were obtained, when compared with the drying times obtained using the operational policies reported in the literature, by using the optimal control policies constructed from the theory presented in this work. Furthermore, it is shown that the optimal control policy leads to the desired in practice result of having at the end of secondary drying temperature and bound water concentration profiles (in the dried layer) whose gradients are very small. It is also shown that by using the optimal control policy and an excipient capable of increasing the melting temperature without affecting product quality, one can significantly reduce the drying time of the primary drying stage.

Since metabolome data are derived from the underlying metabolic network, reverse engineering of such data to recover the network topology is of wide interest. Lyapunov equation puts a constraint to the link between data and network by coupling the covariance of data with the strength of interactions (Jacobian matrix). This equation, when expressed as a linear set of equations at steady state, constitutes a basis to infer the network structure given the covariance matrix of data. The sparse structure of metabolic networks points to reactions which are active based on minimal enzyme production, hinting at sparsity as a cellular objective. Therefore, for a given covariance matrix, we solved Lyapunov equation to calculate Jacobian matrix by a simultaneous use of minimization of Euclidean norm of residuals and maximization of sparsity (the number of zeros in Jacobian matrix) as objective functions to infer directed small-scale networks from three kingdoms of life (bacteria, fungi, mammalian). The inference performance of the approach was found to be promising, with zero False Positive Rate, and almost one True positive Rate. The effect of missing data on results was additionally analyzed, revealing superiority over similarity-based approaches which infer undirected networks. Our findings suggest that the covariance of metabolome data implies an underlying network with sparsest pattern. The theoretical analysis forms a framework for further investigation of sparsity-based inference of metabolic networks from real metabolome data.

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A novel dynamic pressure rise method is developed as a remote sensing procedure for determining at different times during the primary drying stage of the freeze drying process (i) the temperature of the moving interface between the dried and frozen layers of the product, (ii) the temperature close to the upper surface of the dried layer of the product. (iii) the temperature of the bonom surface of the frozen layer of the product, and (iv) the temperature profile of the frozen layer of the product. Funhermore, by knowing the temperature ofthe heating plate and determiningthe value of the temperature of the moving interface from the dynamic pressure rise method, the value of the position of the moving interface could be determined by an expression presented in this work.