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Mesozoic fossils of Psephenidae are sparse. Here we characterise, describe and figure a new genus and species of Psephenidae from the Albian/Cenomanian Burmese amber, Pseudomataeopsephus burmensis gen. et sp. nov, based on an adult male. Pseudomataeopsephus has an interesting combination of characters, including filiform antennae in male, pronotum with crenulate basal rim, scutellum and elytra with smooth basal rims, mesoventral process with emarginate apex, and abdomen with five ventrites. This unique character combination is unknown in any extant psephenid subfamilies, suggesting that Pseudomataeopsephus may represent an early-diverging lineage in Psephenidae.

Variable weights analysis and its applications in fuzzy systems and especially in fuzzy decision making are researched in detail in this paper. After the background of variable weights is summarized, an empirical variable weights formula is discussed. Based on the empirical formula, the principles of variable weights are explored, and an axiomatic definition on variable weights is given. Then, an important idea, balance function about variable weights, is defined, and its structure is considered. And some kinds of variable weights are also introduced, which should often be used in many real cases. Especially, Weber-Fechner's law with respect to variable weights is pointed out.

In this paper, the particular model that describes the thin-plate flow of incompressible non-Newtonian viscous fluids is investigated. This model, which arises from polymer processing, concerns the initial boundary problem of nonstationary thin-plate flow of non-Newtonian viscous incompressible fluids. By using monotone operator theory and Schauder's fixed-point theorem, an existence and uniqueness theorem for a generalized solution is obtained, and the regularity for this solution is tested.

This paper proposes an analog circuit approach for the singular value decomposition (SVD). The proposed analog computational model can be considered a specialized analog computer. The key features of the proposed analog computational model are asynchronous parallel processing, continuous-time dynamics and high-speed computational capability. We show analytically and by simulations that the proposed circuit can provide the desired singular vectors of a given matrix A with an arbitrarily small error during an elapsed time of only a few characteristic time constants of the circuit.

This paper proposes an analog circuit approach to computing in real time the eigenvectors corresponding to all the eigenvalues of a class of positive definite matrices. We show analytically and by simulations that the proposed circuit can provide the desired eigenvectors with arbitrarily small error during an elapsed time of only a few characteristic time constants of the circuit.

This paper presents a neural network approach to solving in real-time the linear prediction (LP) equation under the total least squares (TLS) criterion for the frequency estimation problem. We show both analytically and by simulations that this proposed neural network is guaranteed to be stable and to provide the results arbitrarily close to the accurate TLS solution of the LP equation within an elapsed time of only a few characteristic time constants of the circuit. The parameters such as the interconnection strengths of this proposed network can be obtained from the available data without any computation.