Mixed Integer Linear Programming Optimization of Gas Supply to a Local Market.

Remote or stranded areas that cannot be supplied by natural gas through transmission pipelines can access gas through terminals for liquefied natural gas (LNG), from where LNG is distributed by trucks or compressed and regasified into regional distribution networks. The gas supply may be further augmented by local biogas or synthetic natural gas. A model for optimization of such regional gas supply chains is presented in the paper, considering a combination of pipeline and truck delivery to a set of customers with given energy demands. After linearization, the task is formulated as a mixed integer linear programming (MILP) problem and is solved by state-of-the-art software. The model is illustrated on a regional energy supply problem considering seasonal variations in the demands. The results of the study demonstrate the role of the price of the local and alternative fuels and the price margins at which it is feasible to build an extensive pipeline network instead of supplying the fuel by trucks to storages connected to pipeline islands. The findings also give information about the influence on investment versus operation costs on the optimal design of the supply chain. The sensitivity of the optimal supply chain on the price of local and alternative fuels as well as on the unit price of pipes and storage tanks is studied to illustrate how optimization can be used to shed light on the feasibility of investment in new infrastructure and to support the decision making processes in the energy sector.

Modeling reveals that dynamic regulation of c-FLIP levels determines cell-to-cell distribution of CD95-mediated apoptosis.

The expression levels of caspase-8 inhibitory c-FLIP proteins play an important role in regulating death receptor-mediated apoptosis, as their concentration at the moment when the death-inducing signaling complex (DISC) is formed determines the outcome of the DISC signal. Experimental studies have shown that c-FLIP proteins are subject to dynamic turnover and that their stability and expression levels can be rapidly altered. Even though the influence of c-FLIP on the apoptotic behavior of a single cell has been captured in mathematical simulation studies, the effect of c-FLIP turnover and stability has not been investigated. In this study, a mathematical model of apoptosis was developed to analyze how the dynamic turnover and stability of the c-FLIP isoforms regulate apoptotic signaling for both individual cells and cell populations. Intercellular parameter and concentration distributions were used to describe the behavior of cell populations. Monte-Carlo simulations of cell populations showed that c-FLIP turnover is a key determinant of death receptor responses. The fact that the developed model simulates the state of whole cell populations makes it possible to validate it by comparison with empirical data. The proposed modeling approach can be used to further determine limiting factors in the DISC signaling process.