The question of how nonspecific reversible intermolecular protein interactions affect solution rheology at high concentrations is fundamentally rooted in the translation of nanometer-scale interactions into macroscopic properties. Well-defined solutions of purified monoclonal antibodies (mAbs) provide a useful system with which to investigate the manifold intricacies of weak protein interactions at high concentrations. Recently, characterization of self-associating IgG1 antibody (mAb2) solutions has established the direct role of protein clusters on concentrated mAb rheology. Expanding on our earlier work with three additional mAbs (mAb1, mAb3, and mAb4), the observed concentration-dependent static light scattering and rheological data present a substantially more complex relationship between protein interactions and solution viscosity at high concentrations. The four mAb systems exhibited divergent correlations between cluster formation (size) and concentrated solution viscosities dependent on mAb primary sequence and solution conditions. To address this challenge, well-established features of colloidal cluster phenomena could be applied as a framework for interpreting our observations. The initial stages of mAb cluster formation were investigated with small-angle X-ray scattering (SAXS) and ensemble-optimized fit methods, to uncover shifts in the dimer structure populations which are produced by changes in mAb interaction modes and association valence under the different solution conditions. Analysis of mAb average cluster number and effective hydrodynamic radii at high concentrations revealed cluster architectures can have a wide range of fractal dimensions. Collectively, the static light scattering, SAXS, and rheological characterization demonstrate that nonspecific and anisotropic attractive intermolecular interactions produce antibody clusters with different quinary structures to regulate the rheological properties of concentrated mAb solutions.

This research intends to investigate the patent activity on water pollution and treatment in China (1985China ( -2007, and then compares the results with patents data about Triadic patents, South Korea, Brazil and India over the same periods, patents data were collected from Derwent World Patents Index between 1985 and May 2008. For this study, 169,312 patents were chosen and examined. Total volume of patents, technology focus, assignee sector, priority date and the comparison with other countries are analyzed. It is found that patents on water pollution and treatment filed at China have experienced a remarkable increase and the increase rate of patents filed at China change simultaneous with the percentage of domestic applications. However, the number of high quality Triadic patents with priority country as China remains small. Furthermore, in addition to individual patent assignees, both Chinese universities and enterprises also play important roles in patent activity of water pollution and treatment. In addition, the pattern of South Korea's development can provide short-term implications for China and the regularity in Triadic patents' development can provide some guidance to China's long-term development. In contrast, the development pattern of Brazil and India is less influential to China's development. Furthermore, China's technology focuses on water pollution and treatment seem to parallel global and triadic patent trends. This research provides a comprehensive picture of China's innovation capability in the area of water pollution and treatment. It will help China's local governments to improve their regional S&T capability and will provide support the National Water Pollution Control and Treatment Project in China.

Along with the once again leap development of science and technology, wireless sensor network technology by a great number of agency predicted to be the core technology of power to change the world, has become the one of the important research field both at home and abroad, has wide application background. It is in special scenario application especially, due to the special restrictions on target area, making the advantages of wireless sensor network system well. In this article, through the research of wireless sensor network system, key technologies and difficulties in the design of the Internet of things system for wireless sensor network solution, and describes in detail the system each function module in detail.

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Forestry industry is an important part of nation's economy. In this paper, a machine vision system is presented as a key module of Camellia oleifera pluck robot. In order to cut fruit image up from complicate background, SOFM neural network and gray thresh is used in image segmentation. In SOFM method, take R-B,G-R,G-B and hue H tunnel as input feature vectors, use self-organization network to clustering can get the best effect. in gray threshold method can take various of method to get the best threshold, such as PSO and GA algorithm, and MATLAB includes the toolboxes. At last use noise ratio, area ratio, divided time, Fourier boundary descriptors and other indicators to assess the accuracy of segmentation. The methods have the significance to the current and subsequent research of forestry pluck device.