Effect of root systems on preferential flow in swelling soil

Permeability problems on irrigated soils may be alleviated by root systems that increase water flow by creating macropores. Infiltration rates have been shown to increase where plant roots decay and serve as preferential flow paths. For low-organic-matter swelling soil, there is a question whether macropores are able to resist the lateral swelling forces of the soil. The objective of this study was to observe preferential water flow paths in a swelling soil under two cropping systems. A Holtville silty clay (clayey-over-loamy, montmorillonitic Typic Torrifluvent) was observed in situ. Two crops, alfalfa (Medicago saliva, L.) and wheat (Triticum turgidum, L.) provided sharply contrasting root systems, with wheat possessing fine, fibrous roots; alfalfa on the other hand, has a taproot system. Macropores were observed after applying soil-adsorbing methylene blue dye to irrigation water. Shrinkage cracks failed to conduct dye after 10 minutes into a flood irrigation. Earthworm (Lubricus terrestris) channels were also not stable. However, decaying roots of alfalfa produced stable macropores, while wheat produced no such macropores. The influence of alfalfa-root-induced macropores was demonstrated by the increase in final infiltration rate during alfalfa cropping which agreed with Meek et al.'s (1989, 1990) findings on sandy loam soils

Nucleotide Frequencies in Human Genome and Fibonacci Numbers

This work presents a mathematical model that establishes an interesting connection between nucleotide frequencies in human single-stranded DNA and the famous Fibonacci's numbers. The model relies on two assumptions. First, Chargaff's second parity rule should be valid, and, second, the nucleotide frequencies should approach limit values when the number of bases is sufficiently large. Under these two hypotheses, it is possible to predict the human nucleotide frequencies with accuracy. It is noteworthy, that the predicted values are solutions of an optimization problem, which is commonplace in many nature's phenomena.Comment: 12 pages, 2 figure

What Do “None,” “Mild,” “Moderate,” “Severe,” and “Very Severe” Mean to Patients With Cancer? Content Validity of PRO-CTCAE™ Response Scales

Accurate capture of the symptom experience is essential to gauging efficacy, safety, and tolerability of cancer treatments. The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) was developed by the National Cancer Institute to allow direct patient self-reporting of symptomatic adverse events in cancer clinical trials. Its content validity has been established in accordance with recommended practices for novel patient-reported outcome (PRO) instruments

Precision Measurement of PArity Violation in Polarized Cold Neutron Capture on the Proton: the NPDGamma Experiment

The NPDGamma experiment at the Los Alamos Neutron Science Center (LANSCE) is dedicated to measure with high precision the parity violating asymmetry in the $\gamma$ emission after capture of spin polarized cold neutrons in para-hydrogen. The measurement will determine unambiguously the weak pion-nucleon-nucleon ($\pi NN$) coupling constant {\it f$^1_{\pi}$}Comment: Proceedings of the PANIC'05 Conference, Santa Fe, NM, USA, October 24-28, 2005, 3 pages, 2 figure

Precision Measurement of the Proton and Deuteron Spin Structure Functions g2 and Asymmetries A2

We have measured the spin structure functions g2p and g2d and the virtual photon asymmetries A2p and A2d over the kinematic range 0.02 < x < 0.8 and 0.7 < Q^2 < 20 GeV^2 by scattering 29.1 and 32.3 GeV longitudinally polarized electrons from transversely polarized NH3 and 6LiD targets. Our measured g2 approximately follows the twist-2 Wandzura-Wilczek calculation. The twist-3 reduced matrix elements d2p and d2n are less than two standard deviations from zero. The data are inconsistent with the Burkhardt-Cottingham sum rule if there is no pathological behavior as x->0. The Efremov-Leader-Teryaev integral is consistent with zero within our measured kinematic range. The absolute value of A2 is significantly smaller than the sqrt[R(1+A1)/2] limit.Comment: 12 pages, 4 figures, 2 table

Measurement of the Proton and Deuteron Spin Structure Functions g2 and Asymmetry A2

We have measured the spin structure functions g2p and g2d and the virtual photon asymmetries A2p and A2d over the kinematic range 0.02 < x < 0.8 and 1.0 < Q^2 < 30(GeV/c)^2 by scattering 38.8 GeV longitudinally polarized electrons from transversely polarized NH3 and 6LiD targets.The absolute value of A2 is significantly smaller than the sqrt{R} positivity limit over the measured range, while g2 is consistent with the twist-2 Wandzura-Wilczek calculation. We obtain results for the twist-3 reduced matrix elements d2p, d2d and d2n. The Burkhardt-Cottingham sum rule integral - int(g2(x)dx) is reported for the range 0.02 < x < 0.8.Comment: 12 pages, 4 figures, 1 tabl

Measurements of the Q2Q^2-Dependence of the Proton and Neutron Spin Structure Functions g1p and g1n

The structure functions g1p and g1n have been measured over the range 0.014 < x < 0.9 and 1 < Q2 < 40 GeV2 using deep-inelastic scattering of 48 GeV longitudinally polarized electrons from polarized protons and deuterons. We find that the Q2 dependence of g1p (g1n) at fixed x is very similar to that of the spin-averaged structure function F1p (F1n). From a NLO QCD fit to all available data we find $\Gamma_1^p - \Gamma_1^n =0.176 \pm 0.003 \pm 0.007$ at Q2=5 GeV2, in agreement with the Bjorken sum rule prediction of 0.182 \pm 0.005.Comment: 17 pages, 3 figures. Submitted to Physics Letters

Evolutionary Computation for Optimal Ensemble Classifier in Lymphoma Cancer Classification

Abstract. Owing to the development of DNA microarray technologies, it is possible to get thousands of expression levels of genes at once. If we make the effective classification system with such acquired data, we can predict the class of new sample, whether it is normal or patient. For the classification system, we can use many feature selection methods and classifiers, but a method cannot be superior to the others absolutely for feature selection or classification. Ensemble classifier has been using to yield improved performance in this situation, but it is almost impossible to get all ensemble results, if there are many feature selection methods and classifiers to be used for ensemble. In this paper, we propose GA based method for searching optimal ensemble of feature-classifier pairs on Lymphoma cancer dataset. We have used two ensemble methods, and GA finds optimal ensemble very efficiently.