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BACKGROUND: The efficient production of a fermentable hydrolyzate is an immensely important requirement in the utilization of lignocellulosic biomass as a feedstock in bioethanol production processes. The identification of the optimal enzyme loading is of particular importance to maximize the amount of glucose produced from lignocellulosic materials while maintaining low costs. This requirement can only be achieved by incorporating reliable methodologies to properly address the optimization problem.

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In this work, a procedure was established to develop a mathematical model considering the effect of temperature on reaction kinetics. Experiments were performed in batch mode in temperatures from 30 to 38 degrees C. The microorganism used was Saccharomyces cerevisiae and the culture media, sugarcane molasses. The objective is to assess the difficulty in updating the kinetic parameters when there are changes in fermentation conditions. We conclude that, although the re-estimation is a time-consuming task, it is possible to accurately describe the process when there are changes in raw material composition if a re-estimation of parameters is performed.

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As a classical analogue of electromagnetically induced transparency, plasmon induced transparency (PIT) has attracted great attention by mitigating otherwise cumbersome experimental implementation constraints. Here, through theoretical design, simulation and experimental validation, we present a novel approach to achieve and control PIT by hybridizing two double split ring resonators (DSRRs) on flexible polyimide substrates. In the design, the large rings in the DSRRs are stationary and mirror images of each other, while the small SRRs rotate about their center axes. Counter-directional rotation (twisting) of the small SRRs is shown to lead to resonance shifts, while co-directional rotation results in splitting of the lower frequency resonance and emergence of a PIT window. We develop an equivalent circuit model and introduce a mutual inductance parameter M whose sign is shown to characterize the existence or absence of PIT response from the structure. This model attempts to provide a quantitative measure of the physical mechanisms underlying the observed PIT phenomenon. As such, our findings can support the design of several applications such as optical buffers, delay lines, and ultra-sensitive sensors.