Consumer’s attitudes and willingness-to-pay for Green food in Beijing

A survey in random-selected supermarkets in Beijing, the capital city of China, is reported to identify the attitudes and perceptions of consumers toward green-labeled milk, as well as their willingness to pay (WTP) for it, and to determine the factors that affect their WTP. The study reveals that the majority of households are quite familiar with green food and most of them take positive attitudes towards them, while with certain anxieties. Both remarkable preferences for location and branding in milk purchase and neglects for quality and safety are found in the consumers’ purchase pattern. The willingness to pay are concentrated in a range of 5 - 10 percent premium than ordinary milk, and age, the perception of green food and the access to information serve as the main factors influencing WTP value

Delay-Energy lower bound on Two-Way Relay Wireless Network Coding

Network coding is a novel solution that significantly improve the throughput and energy consumed of wireless networks by mixing traffic flows through algebraic operations. In conventional network coding scheme, a packet has to wait for packets from other sources to be coded before transmitting. The wait-and-code scheme will naturally result in packet loss rate in a finite buffer. We will propose Enhanced Network Coding (ENC), an extension to ONC in continuous time domain. In ENC, the relay transmits both coded and uncoded packets to reduce delay. In exchange, more energy is consumed in transmitting uncoded packets. ENC is a practical algorithm to achieve minimal average delay and zero packet-loss rate under given energy constraint. The system model for ENC on a general renewal process queuing is presented. In particular, we will show that there exists a fundamental trade-off between average delay and energy. We will also present the analytic result of lower bound for this trade-off curve, which can be achieved by ENC

Screening of quark-monopole in N=4 plasma

We study a quark-monopole bound system moving in N=4 SYM plasma with a constant velocity by the AdS/CFT correspondence. The screening length of this system is calculated, and is smaller than that of the quark-antiquark bound state.Comment: 17 pages, reference and minor correction adde

A New General Allometric Biomass Model

To implement monitoring and assessment of national forest biomass, it is becoming the trend to develop generalized single-tree biomass models suitable for large scale forest biomass estimation. Considering that the theoretical biomass allometric model developed by West et al. [1,2] was statistically different from the empirical one, the two parameters in the most commonly used biomass equation M=aDb were analyzed in this paper. Firstly, based on the knowledge of geometry, the theoretical value of parameter b was deduced, i.e., b=7/3(~2.33), and the comparison with many empirical studies conducted throughout the globe indicated that the theoretical parameter could describe soundly the average allometric relationship between aboveground biomass M and D (diameter on breast height). Secondly, using five datasets of aboveground biomass which consisted of 1441 M-D pairs of sample trees, the new general biomass allometric model was validated. Finally, the relationship between parameter a and wood density p was analyzed, and the linear regression was developed. The new model, which is not only simple but also species-specific, offers a feasible approach on establishment of generalized biomass models for regional and national forest biomass estimation

Bias Correction in Logarithmic Regression and Comparison with Weighted Regression for Nonlinear Models

Non-linear models with heteroscedasticity are commonly used in ecological and forestry modeling, and logarithmic regression and weighted regression are usually employed to estimate the parameters. Using the single-tree biomass data of three large samples, the bias correction in logarithmic regression for non-linear models was studied and comparison between logarithmic regression and weighted regression was discussed in this paper. Firstly, the imminent cause producing bias in logarithmic regression was analyzed, and a new correction factor was presented with which three commonly used bias correction factors were examined together, and the results showed that the correction factors presented here and derived by Baskerville (1972) should be recommended, which could insure the corrected model to be asymptotically consistent with that fitted by weighted regression. Secondly, the fitting results of weighted regression for non-linear models, using the weight function based on residual errors of the model estimated by ordinary least squares (OLS) and the general weight function (w=1/ƒ(x)2) presented by Zeng (1998) respectively, were compared with each other that showed two weight functions worked well and the general function was more applicable. It was suggested that the best way to fit non-linear models with heteroscedasticity would be using weighted regression, and if the total relative error of the estimates from the model fitted by the general weight function was more than a special allowance such as ±3%, a better weight function based on residual errors of the model fitted by OLS should be used in weighted regression

Modeling Compatible Single-Tree Aboveground Biomass Equations of Masson Pine (Pinus massoniana) in South China

In the background of facing up to the global climate change, it is becoming the inevitable demand to add forest biomass estimation to national forest resource monitoring. The biomass equations to be developed for forest biomass estimation should be compatible with volume equations. Based on the tree volume and aboveground biomass data of Masson pine (Pinus Massoniana Lamb.) in south China, the one, two and three-variable aboveground biomass equations and biomass conversion functions compatible with tree volume equations were constructed using the error-in-variable simultaneous equations in this paper. The results showed: (i) the prediction precision of aboveground biomass estimates from one variable equation was more than 95%; (ii) the regressions of aboveground biomass equations improved slightly when tree height and crown width were used together with diameter on breast height, although the contributions to regressions were statistically significant; (iii) for biomass conversion function on one variable, the conversion factor was decreased with growing diameter, but for conversion function on two variables, the factor was increased with growing diameter while decreased with growing tree height

Temporal effects in trend prediction: identifying the most popular nodes in the future

Prediction is an important problem in different science domains. In this paper, we focus on trend prediction in complex networks, i.e. to identify the most popular nodes in the future. Due to the preferential attachment mechanism in real systems, nodes' recent degree and cumulative degree have been successfully applied to design trend prediction methods. Here we took into account more detailed information about the network evolution and proposed a temporal-based predictor (TBP). The TBP predicts the future trend by the node strength in the weighted network with the link weight equal to its exponential aging. Three data sets with time information are used to test the performance of the new method. We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future. The effect of the decay speed in the exponential aging on the results is discussed in detail