Conventional enzymatic biofuel cells (EBFCs) use glucose solution or glucose from human body. It is desirable to get glucose from a substance containing glucose because the glucose concentration can be kept at the optimum level. This work developed a biofuel cell that generates electricity from cellulose, which is the main components of plants, by using decomposing enzyme of cellulase. Cellulose nanofiber (CNF) was chosen for the ease of decomposability. It was confirmed by the cyclic voltammetry method that cellulase was effective against CNF. The maximum output of the optimized proposed method was 38.7 μW/cm2, which was 85% of the output by using the glucose solution at the optimized concentration.

It is an important problem in signal processing, system realization and system identification to find linear discrete-time systems which are consistent with given covariance parameters. This problem is formulated as a problem of finding discrete-time positive real functions which interpolate given covariance parameters. Among various solutions to the problem, a recent remarkable one is a parameterization of all the discrete-time strictly positive real functions that interpolate the covariance parameters and have a limited McMillan degree. In this paper, we use more general input-output characteristics than covariance parameters and consider finding discrete-time positive real functions which interpolate such characteristics. The input-output characteristics are given by the coefficients of the Taylor series at some complex points in the open unit disk. Based on our previous work, we present an algorithm to generate all the discrete-time positive real functions that interpolate the input-output characteristics and have a limited McMillan degree. The algorithm is more general and simpler than the previous one, and is an important practical supplement to the previous work. Moreover, the interpolation of the general input-output characteristics can be effectively applied to the frequency-weighted model reduction. Hence, the algorithm makes a contribution to the problem from the practical viewpoint as well as the theoretical viewpoint.

It is an important problem in signal processing, system realization and system identification to find linear discrete-time systems which are consistent with given covariance parameters. This problem is formulated as a problem of finding discrete-time positive real functions which interpolate given covariance parameters. Various investigations have yielded several significant solutions to the problem, while there remains an important open problem concerning the McMillan degree. In this paper, we use more general input-output characteristics than covariance parameters and consider finding discrete-time positive real matrix functions which interpolate such characteristics. The input-output characteristics are given by the coefficients of the Taylor series at some complex points in the open unit disk. Thus our problem is a generalization of the interpolation problem of covariance parameters. We reduce the problem to a directional interpolation problem with a constraint and develop the solution by a state-space based new approach. The main results consist of the necessary and sufficient condition for the existence of the discrete-time positive real matrix function which interpolates the given characteristics and has a limited McMillan degree, and a parameterization of all such functions. These are a contribution to the open problem and a generalization of the previous result.

Exact analytical solutions for the steady-state transmission and reflection characteristics of a nonlinear Fabry-Perot resonator applicable to bistable optical devices are derived. The resonator consists of a Kerr-like nonlinear film sandwiched by reflection mirrors made of a quarter-wave dielectric stack. An equivalent mirrorless model has been introduced to facilitate the analysis. For both positive and negative nonlinear coefficients, the rigorous solutions have been simply expressed in terms of Jacobian elliptic functions.