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The soil water characteristic curve (SWCC) describes the relationship between matric suction and moisture of soil, the testing process of which is time-consuming. The test time of particle size distribution (PSD), in contrast, is relatively short. Thus, it is quite important to establish a proper model for PSD to forecast SWCC. This paper analyzed PSD of 25 groups of loess by way of laser diffraction technique (LD) and sieve-settlement method. Works were carried out on fitting analysis on PSD with Logarithmic model, Fredlund model, Jaky model, and Gompertz model. Statistical method was used to explain the fitting performance. Meanwhile, an empirical model was put forward. Compared to the four models, the empirical model has fewer parameters, simple model form, and smaller fluctuations of parameters. Results of LD showed higher clay content but lower silt content. It is suggested that Fredlund model or the empirical model be adopted to forecast SWCC of Malan loess.

In the Internet,there are no mechanisms to verify the identity of a message sender,resulting in a large number of forged identity attacks,such as phishing websites.By mapping the user identity into the rightmost 64 bit of the IPv6 address,this paper tries to make every message embedded with an identity,which lay a credible foundation for communications on the Internet.We design and realize a true identity communication system based on source address validation improvement,which can protect the privacy of the users,and ensure the verifiability and authenticity of the user identities.

Firstly three phases of the development of inter-domain SDN internetworking were discussed, then a cooperation based inter-domain SDN technology WE-Bridge was introduced. Finally, an inter-continental inter-domain SDN testbed based on WE-Bridge technology was introduced.

Forest vegetation plays a crucial role in improving the ecological environment and maintaining the regional ecological balance. However, most studies pay little attention to the factors that can impact forest biomass carbon storage (FBCS). This research estimated the FBCS by combining relevant forest inventory data and models of continuous functions for biomass expansion factor. A modeling equation was then established and applied to examine the impact of socioeconomic factors on FBCS in Jiangsu, a coastal province in Eastern China, as a case study. The results showed that Jiangsu’s FBCS increased by 20.28 Tg from 2005 to 2010, showing a prominent carbon sink effect but with spatial imbalance among the changes in carbon storage. Jiangsu’s FBCS is significantly affected by land use factors (e.g., forest area and cultivated area), population factors (e.g., population density and urbanization), and economic development factors (e.g., GDP). Relatively speaking, the forest area and GDP had positive effects on FBCS, while cultivated area, population density, and urbanization had significant negative effects.

Internet architecture was discussed firstly,then the major international research progress of future network architectures was introduced.And the recent development of software defined networking（SDN）was introduced,an abstract model of SDN architecture was proposed.Finally,a FINE architecture for future network innovation environment project was introduced,which was funded by national high-tech R&D program（“863”program）.

Battery electric vehicles (BEVs) reduce energy consumption and air pollution as compared with conventional vehicles. However, the limited driving range and potential long charging time of BEVs create new problems. Accurate charging time prediction of BEVs helps drivers determine travel plans and alleviate their range anxiety during trips. This study proposed a combined model for charging time prediction based on regression and time-series methods according to the actual data from BEVs operating in Beijing, China. After data analysis, a regression model was established by considering the charged amount for charging time prediction. Furthermore, a time-series method was adopted to calibrate the regression model, which significantly improved the fitting accuracy of the model. The parameters of the model were determined by using the actual data. Verification results confirmed the accuracy of the model and showed that the model errors were small. The proposed model can accurately depict the charging time characteristics of BEVs in Beijing.

In this study, we explore the potential contributions of a risk perception framework in understanding public perceptions of unstable ecosystems. In doing so, we characterize one type of common ecological risk- harmful algal blooms (HABs)-in four of the most seriously eutrophicated freshwater lakes in China. These lakes include Chaohu, Dianchi, Hongze, and Taihu, where a total of 2000 residents living near these sites were interviewed. Regional discrepancies existed in the pilot study regarding public perceptions of ecological changes and public concerns for ecological risk. Comparing HABs and other kinds of risks (earthquake, nuclear, and public traffic) through the psychometric paradigm method, Knowledge, Effect, and Trust were three key factors formulating the risk perception model. The results indicated that Knowledge and risk tolerance levels had significant negative correlations in the higher economic situation while correlations in the lower economic situation were significantly positive. Effect and risk tolerance levels had significant negative correlations in the high and middle education situation while correlations in the low education situation were close to zero or insignificant. For residents from Taihu with comparatively higher economic and educational levels, more investment in risk prevention measures and stronger policies are needed. And for residents from Hongze and Dianchi with comparatively low economic and educational levels, improvement of the government's credibility (Trust) was the most important factor of risk tolerance, so efforts to eliminate ecological problems with the stepwise development of economic and educational levels should be implemented and gradually strengthened. In turn, this could prevent public discontent and ensure support for ecological protection policies.

Heavy metal pollution is becoming a serious issue in developing countries such as China, and the public is increasingly aware of its adverse health impacts in recent years. We assessed the potential health risks in a lead-zinc mining area and attempted to identify the key exposure pathways. We evaluated the spatial distributions of personal exposure using indigenous exposure factors and field monitoring results of water, soil, food, and indoor and outdoor air samples. The risks posed by 10 metals and the contribution of inhalation, ingestion and dermal contact pathways to these risks were estimated. Human hair samples were also analyzed to indicate the exposure level in the human body. Our results show that heavy metal pollution may pose high potential health risks to local residents, especially in the village closest to the mine (V1), mainly due to Pb, Cd and Hg. Correspondingly, the residents in V1 had higher Pb (8.14 mg/kg) levels in hair than those in the other two villages. Most of the estimated risks came from soil, the intake of self-produced vegetables and indoor air inhalation. This study highlights the importance of site-specific multipathway health risk assessments in studying heavy-metal exposures in China.