A kinetic trap is the metastable species that is transiently or constantly produced during the reaction by trapping in a deep energy well. In most cases, the reactivity of kinetically trapped species is relatively low under the reaction conditions. Herein, we report another type of kinetically trapped species that is an incomplete cage (IC) intermediate produced during the self-assembly of a Pd L cage from ditopic ligand (L) and Pd ions with a certain lifetime, although IC has a high enough reactivity to be converted into the cage with the reaction of free L, which was confirmed by the reaction of the isolated IC and L under the self-assembly conditions. IC was kinetically trapped not because IC lies on the bottom of a deep energy well but because the conversion of the intermediates essential for the conversion of IC to the cage preferentially takes place; IC was kinetically trapped independently of the shape of the energy landscape of the self-assembly.

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The purpose of this paper is to construct a model that represents the human process of understanding metaphors, focusing specifically on similes of the form an "A like B". Generally speaking, human beings are able to generate and understand many sorts of metaphors. This study constructs the model based on a probabilistic knowledge structure for concepts which is computed from a statistical analysis of a large-scale corpus. Consequently, this model is able to cover the many kinds of metaphors that human beings can generate. Moreover, the model implements the dynamic process of metaphor understanding by using a neural network with dynamic interactions. Finally, the validity of the model is confirmed by comparing model simulations with the results from a psychological experiment.

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A new topological approach is proposed for the analysis of change in group structure over time. Special force fields are defined operationally to explain changes in the structure, which are estimated by a method called DYNASCAL, given a set of longitudinal dissimilarity judgements such as longitudinal sociograms.These fields are presumably generated by interactions among individuals.For theoretical simplicity, these fields are supposed to be two-dimensional vector fields, which are described by a system of general nonlinear differential equations.Qualitative theories of the dynamical system such as those of singularities, bifurcations, and structural stability of the vector field are shown to be useful for describibg qualitative aspects of the force fields. Some difficulties in application of our method to empirical data are indicated and ways of overcoming them are discussed.