Distance versus energy fluctuations and electron transfer in single protein molecules

Stochastic nature due to distance and energy fluctuations of single protein molecules involved in electron-transfer (ET) reactions is studied. Distance fluctuations have been assumed previously for causing the slow fluctuations in the ET rates between a donor-acceptor pair constrained to a native protein. Although the observed t–1/2 power law can be derived using Langevin dynamics with a simple chain model, some discrepancies exist. The friction coefficient and the Rouse segment time constant deduced from experimental data are several orders of magnitude too large, even though the extracted force constant is reasonable. Therefore, questions are raised about the distance-fluctuation mechanism and the activationless ET hypothesis. As an alternative mechanism, we considered fluctuations in activation energy and analyzed the data from two different single protein experiments to determine spectral distribution of energy fluctuations

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

Effective pattern discovery for text mining

Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase) based approaches should perform better than the term-based ones, but many experiments did not support this hypothesis. This paper presents an innovative technique, effective pattern discovery which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance

Three-terminal normal-superconductor junction as thermal transistor

We propose a thermal transistor based on a three-terminal normal-superconductor (NS) junction with superconductor terminal acting as the base. The emergence of heat amplification is due to the negative differential thermal conductance (NDTC) effect for the NS diode in which the normal side maintains a higher temperature. The temperature dependent superconducting energy gap is responsible for the NDTC. By controlling quantum dot levels and their coupling strengths to the terminals, a huge heat amplification factor can be achieved. The setup offers an alternative tuning scheme of heat amplification factor and may find use in cryogenic applications.Comment: 6 pages, 3 figure