Ancient Chinese algorithm: The Ying Buzu Shu (method of surplus and deficiency) vs Newton iteration method

Air exploratory discussion of an ancient Chinese algorithm, the Ying Buzu Shu, in about 2nd century BC, known as the rule of double false position in the West is given. In addition to pointing out that the rule of double false position is actually a translation version of the ancient Chinese algorithm, a comparison with well-known Newton iteration method is also made. If derivative is introduced, the ancient Chinese algorithm reduces to the Newton method. A modification of the ancient Chinese algorithm is also proposed, and some of applications to nonlinear oscillators are illustrated.

High-Strength Composite Fibers: Realizing True Potential of Carbon Nanotubes in Polymer Matrix through Continuous Reticulate Architecture and Molecular Level Couplings

Carbon nanotubes have unprecedented mechanical properties as defect-free nanoscale building blocks, but their potential has not been fully realized in composite materials due to weakness at the interfaces. Here we demonstrate that through load-transfer-favored three-dimensional architecture and molecular level couplings with polymer chains, true potential of CNTs can be realized in composites as Initially envisioned. Composite fibers with reticulate nanotube architectures show order of magnitude improvement in strength compared to randomly dispersed short CNT reinforced composites reported before. The molecular level couplings between nanotubes and polymer chains results in drastic differences in the properties of thermoset and thermoplastic composite fibers, which indicate that conventional macroscopic composite theory falls to explain the overall hybrid behavior at nanoscale.

Visual pattern recognition network: Its training algorithm and its optoelectronic architecture

A visual pattern recognition network and its training algorithm are proposed. The network constructed of a one-layer morphology network and a two-layer modified Hamming net. This visual network can implement invariant pattern recognition with respect to image translation and size projection. After supervised learning takes place, the visual network extracts image features and classifies patterns much the same as living beings do. Moreover we set up its optoelectronic architecture for real-time pattern recognition. (C) 1996 Optical Society of America

Origin of Chinese ancient glasses;study on the earliest Chinese ancient glasses

The earliest Chinese ancient glasses before the West Han Dynasty (200 BC) from different regions are studied. The glass samples were unearthed from Hunan, Hubei, Yunnan, Sichuan, Guizhou, Guangdong and Xinjiang of China. The chemical composition of these glasses samples is analyzed by proton induced X-ray emission (PIXE) technique, energy dispersive X-ray fluorescence (EDXRF) method and inductively coupled plasma atomic emission spectrometry (ICP-AES). It is shown that the glass chemical compositions belong to barium-lead silicate BaO-PbO-SiO2, potash soda lime silicate K2O (Na2O)-CaO-SiO2 (K2O/Na2O > 1), soda potash lime silicate Na2O (K2O)-CaO-SiO2 (K2O/Na2O < 1) and potash silicate K2O-SiO2 glass systems, respectively. The origins of the earliest Chinese ancient glasses are discussed from the archaeological and historical points of view. These four types of Chinese ancient glasses were all made in Chinese territory using local raw materials. The glass preparation technology was related to the Chinese ancient bronze metallurgy and proto-porcelain glaze technology. The glass technology relationship between the East and the West is analyzed at the same time.