QUANTITATIVE ANALYSIS OF RELATIONSHIP BETWEEN ARMILLARIA ROOT ROT AND SITE FACTORS IN PINUS RADIATA PLANTATIONS

Incidence of Armillaria infection was quantified based on site factors in New Zealand Pinus radiata plantations.A linear multiple regression model was derived to predict infection levels of Armillaria root rot.Factors positivily associated with the infection were:previous vegetation（native bush,pine）;soil type（pumice）;landform （valley,gully,flat）and the interaction between them.This model could assist in management planning with regard to the predisposition of particular stand to Armillaria infection.Keywods:Armillaria root rot,Disease incidence,Site factors,Quantification,Pinus radiata.

Correlation between Chromatograph Capacity Factors and Structural Parameters of Indole Derivatives

Sixteen indole derivatives have been computed at B3LYP/6-31 IG^＊＊ level using density functional theory （DFF）. Based on linear solvation energy theory, the structural parameters were employed to present correlation between the parameters of chromatograph capacity factor （CCF） and molecular structural parameters. As a result, the correlation equation of the reversed phased high performance liquid chromatograph capacity factor to the intercept lgk＇w and slope S of CCF were obtained, from which the correlation coefficients of lgk＇w to the structural parameters are r^2 = 0.9596 and q^2 = 0.9262. While the correlation coefficients of the parameter S r^2 q^2 with structures are = 0.9750 and = 0.9252. Moreover, the effect of water as solvent on the present two models was also considered using SCRF method, and the result shows that the predicting capacity of correlation equation of lgkw＇ increases, while that of the model for S decreases slightly. Both two correlation equations achieved in this work are more advantageous than those using theoretical descriptors from molecular connectivity indices.

Main Reasons Causing Chinese Agricultural Crisis in 1959-1961： Quantitative Test on Yifu Lin＇s Hypothesis

The traditional explanation was found to be inconsistent with the empirical evidence that mainly caused the agricultural crisis in 1959-1961, so Yifu Lin tried to explain this catastrophe through using Game Theory based on ＂one-shot game＂. This paper tested the hypothesis through quantitative test. The results showed that system factors mainly resulted in low productivity, and the natural disaster should not be ignored.

Correlation of quantitative perfusion parameters on dynamic contrast-enhanced MRI with prognostic factors and subtypes of breast carcinoma

Objective To investigate whether correlation existsbetween quantitative perfusion parameters obtained from dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)and different prognostic factors or immunohistochemical subtypes of breast cancers.Methods A retrospective analysis of DCE-MRI was performed in

Quantified evaluation of particle shape effects from micro-to-macro scales for non-convex grains

Particle shape plays an important role in both the micro and macro scales responses of a granular assem- bly. This paper presents a systematic way to interpret the shape effects of granular material during quasi-static shearing. A more suitable shape descriptor is suggested for the quantitative analysis of the macroscale strength indexes and contact parameters for non-convex grains, with special consid- eration given to the peak state and critical state. Through a series of numerical simulations and related post-processing analysis, particle shape is found to directly influence the strain localisation patterns, microscale fabric distributions, microscale mobilisation indexes, and probability distribution of the nor- malised contact normal force. Additionally, the accuracy of the stress-force-fabric relationship can be influenced by the average normal force and the distribution of contact vectors. Moreover, particle shape plays a more important role than do the confining pressures in determining the friction angle. Strong force chains and the dilation effect are also found to be strongly influenced by the high confinin~ oressure.

Methods for Population-Based eQTL Analysis in Human Genetics

Gene expression is a critical process in biological system that is influenced and modulated by many factors including genetic variation. Expression Quantitative Trait Loci（e QTL） analysis provides a powerful way to understand how genetic variants affect gene expression. For genome wide e QTL analysis, the number of genetic variants and that of genes are large and thus the search space is tremendous. Therefore, e QTL analysis brings about computational and statistical challenges. In this paper, we provide a comprehensive review of recent advances in methods for e QTL analysis in population-based studies. We first present traditional pairwise association methods, which are widely used in human genetics. To account for expression heterogeneity, we investigate the methods for correcting confounding factors. Next, we discuss newly developed statistical learning methods including Lasso-based models. In the conclusion, we provide an overview of future method development in analyzing e QTL associations. Although we focus on human genetics in this review, the methods are applicable to many other organisms.