Metal-to-Oxide Charge Transfer Observed by a Kelvin Probe Force Microscope

The charge transfer from a nanometer-sized transition metal particle to a catalyst support is thought to affect reactions over the metal surface. We propose the application of Kelvin probe force microscope, which is an extension of the atomic force microscope, to observe the charge transfer particle-by-particle. Our recent results on Na adatoms, Cl adatoms, Pt adatoms and particles, and Ni particles evaporated on TiO₂(110) are reviewed.     

On the Nature of Functional Differentiation: The Role of Self-Organization with Constraints

The focus of this article is the self-organization of neural systems under constraints. In 2016, we proposed a theory for self-organization with constraints to clarify the neural mechanism of functional differentiation. As a typical application of the theory, we developed evolutionary reservoir computers that exhibit functional differentiation of neurons. Regarding the self-organized structure of neural systems, Warren McCulloch described the neural networks of the brain as being “heterarchical”, rather than hierarchical, in structure. Unlike the fixed boundary conditions in conventional self-organization theory, where stationary phenomena are the target for study, the neural networks of the brain change their functional structure via synaptic learning and neural differentiation to exhibit specific functions, thereby adapting to nonstationary environmental changes. Thus, the neural network structure is altered dynamically among possible network structures. We refer to such changes as a dynamic heterarchy. Through the dynamic changes of the network structure under constraints, such as physical, chemical, and informational factors, which act on the whole system, neural systems realize functional differentiation or functional parcellation. Based on the computation results of our model for functional differentiation, we propose hypotheses on the neuronal mechanism of functional differentiation. Finally, using the Kolmogorov–Arnold–Sprecher superposition theorem, which can be realized by a layered deep neural network, we propose a possible scenario of functional (including cell) differentiation.     

Swinging and tumbling of fluid vesicles in shear flow

The dynamics of fluid vesicles in simple shear flow is studied using mesoscale simulations of dynamically triangulated surfaces, as well as a theoretical approach based on two variables: a shape parameter and the inclination angle, which has no adjustable parameters. We show that, between the well-known tank-treading and tumbling states, a new "swinging" state can appear. We predict the dynamic phase diagram as a function of the shear rate, the viscosities of the membrane and the internal fluid, and the reduced vesicle volume. Our results agree well with recent experiments.     

Mechanics of a particle near the center of a rotating ring

The equations of motion of a test particle moving near the center of a massive rotating ring are derived up to the post-post-Newtonian order of approximation, by using the metric tensor for many body system which is Minkowskian at spatial infinity. Logarithmic divergences due to self-interaction of the ring appear in the equations of motion. These divergences can be removed by the procedure which is similar to the renormalization method in particle physics. In the equations of motion there appears a force directing to the rotation axis and depending on the angular velocity of the ring. This force vanishes when the magnitude of the gravitational constant times the mass of the ring divided by the radius of the ring is about one tenth of the square of the velocity of light. Under this condition it is shown that the relative magnitude of the Coriolis force to the centrifugal force in the equations of motion agrees with the expected one from the equations of motion in a rotating reference frame.     

A cutting plane algorithm for solving bilinear programs

This paper addresses itself to a special class of nonconvex quadratic program referred to as a bilinear program in the literature. We will propose here a cutting plane algorithm to solve this class of problems. The algorithm is along the lines of H. Tui and K. Ritter, but it differs in its exploitation of the special structure of the problem. Though the algorithm is not guaranteed at this stage of the research to converge to a global optimum, the preliminary results of numerical experiments are encouraging.This research was partially supported by the Office of Naval Research under Contract N-00014-67-A-0112-0011; and U.S. Atomic Energy Commission Contract AT(04-3)-326-PA # 18.     

Estimating the amplitude of measurement noise present in chaotic time series

We propose a method for estimating the amplitude of measurement noise present in chaotic time series. This method is based on the evaluation of initial errors for a given time series and for a new one synthesized by adding an adequate amount of noise to the given one. The method is valid over a much wider range of noise levels than the previous methods are because it is not based on the detail of dynamical structure which generates the data. In addition, it is possible to check if the method is valid for the given data prior to its application. To confirm the effectiveness of the method we show the results of numerical experiments and apply the method to chaotic data obtained from an electrochemical experiment. (c) 1999 American Institute of Physics.     

Family of symplectic implicit Runge-Kutta formulae

A family of formulae for the sympletic IRK method is investigated. Specifically, focus is given to general solutions for formula parameters of IRK under the symplectic and the order conditions. Examples of such formulae are constructed for up to three stages.     

Listening difficulty as a subjective measure for evaluation of speech transmission performance in public spaces

Listening difficulty ratings, using words with high word familiarity, are proposed as a new subjective measure for the evaluation of speech transmission in public spaces to provide realistic and objective results. Two listening tests were performed to examine their validity, compared with intelligibility scores. The tests included a reverberant signal and noise as detrimental sounds. The subject was asked to repeat each word and simultaneously to rate the listening difficulty into one of four categories: (1) not difficult, (2) a little difficult, (3) fairly difficult, and (4) extremely difficult. After the tests, the four categories were reclassified into, not difficult [response (1)] and some level of difficulty, (the other 3 responses). Listening difficulty is defined as the percentage of the total number of responses indicating some level of difficulty [i.e. not (1)]. The results of two listening tests demonstrated that listening difficulty ratings can evaluate speech transmission performance more accurately and sensitively than intelligibility scores for sound fields with higher speech transmission performance.