The non-axisymmetrical configuration of a large-scale solar and stellar magnetic field

in the corona, consisting of an eruptive prominence and/or a magnetic flux region (loop or arcade, or blob) in front of the prominence. Ahead of the piston, there is a compressed flow, which produces a shock front. This high-density region corresponds to the bright feature of the transient. Behind the piston, there is a rarefaction region, which corresponds to the dark feature of the transient. Therefore, both the bright and dark features of the transient may be explained at the same time by the dynamical process of the moving piston.

Ecolabels and certification for small-scale operators

(PDF has 16 pages.)

Changes in Behavior, Movement, and Home Ranges of Largemouth Bass Following Large-scale Hydrilla Removal in Lake Seminole, Georgia

About 1,200 ha of hydrilla ( Hydrilla verticillata L.f. Royle) was eliminated in the Spring Creek embayment of Lake Seminole, Georgia, using a drip-delivery application of fluridone (1- methyl-3-phenyl-5-[3-(trifluoromethl) phenyl]-4(1H)-pyridinone) in 2000 and 2001. Two groups of 15 and 20 largemouth bass (Micropterus salmoides Lacepede) were implanted with 400-day radio tags in February 2000 and 2001 to determine changes in movement and behavior before and after hydrilla reduction.(PDF contains 8 pages.)

Multiple SNP Markers Reveal Fine-Scale Population and Deep Phylogeographic Structure in European Anchovy (Engraulis encrasicolus L.)

10 p.

A Simplified Evaluation Procedure of the Scale of Fluctuation Combined Recurrence Averaging and Weighted Linear Regression

The divergence of properties from one location to another within a soil mass is termed spatial variability, which traditionally includes three parameters the mean, the standard deviation, and the scale of fluctuation, in order to stochastically describe a soil property. Among them, determining the scale of fluctuation in the evaluation of spatial variability of soil profiles is not easy due to soil condition complexity. A simplified procedure is presented in the paper to determine the scale of fluctuation combined recurrence averaging and weighted linear regression. The alternative approach utilizes widely usable spreadsheet to solve the problem more directly and efficiently.

The Relationship between Decision Trees and the Scale of Train Data Set

Decision Trees need train samples in the train data set to get classification rules. If the number of train data was too small, the important information might be missed and thus the model could not explain the classification rules of data. While it is not affirmative that large scale of train data set can get well model. This Paper analysis the relationship between decision trees and the train data scale. We use nine decision tree algorithms to experiment the accuracy, complexity and robustness of decision tree algorithms. Some results are demonstrated.