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

Calorific values and ash contents of different organs of Masson pine (Pinus massoniana) in southern China

Calorific values of plants are important indices for evaluating and reflecting material cycle and energy conversion in forest ecosystems. Based on the data of Masson Pine (Pinus massoniana) in southern China, the calorific values (CVs) and ash contents (ACs) of different plant organs were analyzed systematically using hypothesis test and regression analysis in this paper. The results show: (i) the CVs and ACs of different plant organs are almost significantly different, and the order by AFCV (ash-free calorific value) from the largest to the smallest is foliage (23.55 kJ/g), branches (22.25 kJ/g), stem bark (21.71 kJ/g), root (21.52 kJ/g) and stem wood (21.35 kJ/g); and the order by AC is foliage (2.35%), stem bark (1.44%), root (1.42%), branches (1.08%) and stem wood (0.33%); (ii) the CVs and ACs of stem woods on top, middle and lower sections are significantly different, and the CVs are increasing from top to lower sections of trunk while the ACs are decreasing; (iii) the mean GCV (gross calorific value) and AFCV of aboveground part are larger than those of belowground part (roots), and the differences are also statistically significant; (iv) the CVs and ACs of different organs are related, to some extent, to diameter, height and origin of the tree, but the influence degrees of the factors on CVs and ACs are not the same

Similarity from multi-dimensional scaling: solving the accuracy and diversity dilemma in information filtering

Recommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs. In this paper, we employ the multidimensional scaling (MDS) method to measure the similarities between nodes in user-item bipartite networks. The MDS method can extract the essential similarity information from the networks by smoothing out noise, which provides a graphical display of the structure of the networks. With the similarity measured from MDS, we find that the item-based collaborative filtering algorithm can outperform the diffusion-based recommendation algorithms. Moreover, we show that this method tends to recommend unpopular items and increase the global diversification of the networks in long term

Short-Term Traffic Prediction Based on Genetic Algorithm Improved Neural Network

This paper takes the time series of short-term traffic flow as research object. The delay time and embedding dimension are calculated by C-C algorithm, and the chaotic characteristics of the time series are verified by small data sets method.Then based on the neural network prediction model and the chaotic phase space reconstruction theory, the network topology is determined, and the prediction is conducted by the wavelet neural network and RBF neural network using Lan-Hai expressway experimental data. The results show that the prediction effect of RBF neural network is better. Due to the poor stability of the network caused by the initial parameters randomness, the genetic algorithm is used to optimize the initial parameters. The results show that the prediction error of the optimized wavelet neural network or RBF neural network is reduced by more than 10%, and prediction accuracy of the latter is better

Accuracy of a Novel Non-Invasive technology based EZSCAN system for the diagnosis of diabetes mellitus in Chinese

<p>Abstract</p> <p>Background</p> <p>A new simple technique based on iontophoresis technology (EZSCAN, Impeto Medical, Paris, France) has recently been developed for the screening of diabetes. In the present study, we investigated the accuracy of this system for the diagnosis of diabetes mellitus in Chinese.</p> <p>Methods</p> <p>We performed the EZSCAN test in diabetic and non-diabetic subjects. EZSCAN measures electrochemical conductance (EC) at forehead, hands and feet, and derives a diabetes index with a value ranging from 0 to 100. Diabetes mellitus was defined as a plasma glucose concentration of at least 7 mmol/l at fasting or 11.1 mmol/l at 2 hours after glucose load, or as the use of antidiabetic drugs.</p> <p>Results</p> <p>The 195 study participants (51% men, mean age 52 years) included 75 diabetic patients (use of antidiabetic drugs 81%) and 120 non-diabetic subjects. EC (micro Siemens, μSi) was significantly (<it>P </it>< 0.001) lower in diabetic patients at the hands (44 vs. 61) and feet (51 vs. 69) locations, but not at the forehead (15 vs. 17, <it>P </it>= 0.39). When a diabetes index of 40 (suggested by the manufacturer) was used as the threshold, the sensitivity and specificity for the diagnosis of diabetes mellitus was 85% and 64%, respectively. In 80 patients who underwent an oral glucose tolerance test, EC at hands and feet and the diabetes index were significantly (<it>P </it>< 0.001) associated with both 2-hour post-load plasma glucose and serum glycosylated haemoglobin.</p> <p>Conclusions</p> <p>EZSCAN might be useful in screening diabetes mellitus with reasonable sensitivity and specificity.</p

Non-intact zona improves development of murine preimplantation embryos transfected by an adenovirus vector

The present study explored whether embryos could be transfected by the adenovirus-vector if the zona pellucida (ZP) was not completely removed. An adenovirus vector with green fluorescent protein (pAd-GFP) was used to transfect mouse non-intact zona zygotes (following partial removal of the ZP induced by pronase), zona-free and zona-intact embryos. Non-intact zona and zona-free embryos expressed GFP (confirmed with inverted fluorescence microscopy) after 48 h of culture. The transfection rate of non-intact zona group was up to 51% and the entire zona-free group was transfected. However, none of the zona-intact embryos was transfected. Regardless of whether non-intact zona embryos were transfected by pAd-GFP, their developmental rate (74.3 ± 2.4 and 69.2 ± 3.3% for non-transfected and transfected, respectively; mean ± SEM) was higher (P&lt;0.05) than that of zona-free embryos without and with transfection (54.5 ± 4.3 and 46.7 ± 5.5%). Developmental potential of embryos was decreased for ZP-digestion (non-intact zona 71.8 ± 1.6%; zona-free 50.6 ± 2.2%, P&lt;0.05) or pAd-GFP expression (non-transfected 64.4 ± 1.9%; transfected 56.0 ± 2.1%, P&lt;0.05); therefore, ZP-digestion affected more intensely embryos development than pAd-GFP expression. In summary, non-intact zona murine embryos were readily transfected by the adenovirus-vector, and had much greater development potential than zona-free embryos. Although, the susceptibility of the ZP to digestion by pronase varied among embryos, on average, approximately 3.5 to 4.0 min of digestion resulted in partial removal of the ZP and promoted both transfection and satisfactory embryonic development. It is expected that this method could be used to increase the efficiency of generating transgenic animals.Keywords: Mouse, non-intact zona embryos, adenovirus vector with green fluorescent protein (pAd-GFP), embryos developmen

Membership in social networks and the application in information filtering

During the past few years, users' membership in the online system (i.e. the social groups that online users joined) were widely investigated. Most of these works focus on the detection, formulation and growth of online communities. In this paper, we study users' membership in a coupled system which contains user-group and user-object bipartite networks. By linking users' membership information and their object selection, we find that the users who have collected only a few objects are more likely to be "influenced” by the membership when choosing objects. Moreover, we observe that some users may join many online communities though they collected few objects. Based on these findings, we design a social diffusion recommendation algorithm which can effectively solve the user cold-start problem. Finally, we propose a personalized combination of our method and the hybrid method in [T. Zhou, Z. Kuscsik, J.G. Liu, M. Medo, J.R. Wakeling, Y.C. Zhang, Proc. Natl. Acad. Sci. 107, 4511 (2010)], which leads to a further improvement in the overall recommendation performanc