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Off-shell test of the Moscow potential of nucleon-nucleon interaction on the basis of data on the reaction gammad sup yields np in the photon-energy region around Esub gamma approx_equal 2 GeV, where this reaction is sensitive to quark effects
Various pieces of evidence in favor of the Moscow potential of nucleon-nucleon interaction are discussed. The formalism of a relativistic potential model as applied to deuteron photodintegration is expounded. The differential cross section calculated for the reaction gammad sup yields np on the basis of the Moscow potential at incident-photon energies Esub gamma between 1.5 and 2.5 GeV are quite in accord with present-day experimental data, which are also described well in the literature on the basis of the model of quark-gluon strings. Further steps in testing the Moscow potential and microscopically substantiating it on the basis of quark modelsmore are indicated. less
TEKHNICHESKIY FIZIKI, No 6(148), Nov-Dec 84) 80 Thermodynamic Potential of Quark -Antiquark Plasma in Constant Chromomagnetic Field CSh. S. Agayev... QUARK -ANTIQUARK PLASMA IN CONSTANT CHROMOMAGNETIC FIELD Tomsk IZVESTIYA VYSSHIKH UCHEBNYKH ZAVEDENIY: FIZIKA in Russian Vol 28, No 1, Jan 85...Automation Institute; Moscow State University imeni M. V. Lomonosov [Abstract] Light-neutral quark -antiquark plasma in a constant optical magnetic
This study aims to classify abstract content based on the use of the highest number of words in an abstract content of the English language journals. This research uses a system of text mining technology that extracts text data to search information from a set of documents. Abstract content of 120 data downloaded at www.computer.org. Data grouping consists of three categories: DM (Data Mining), ITS (Intelligent Transport System) and MM (Multimedia). Systems built using naive bayes algorithms to classify abstract journals and feature selection processes using term weighting to give weight to each word. Dimensional reduction techniques to reduce the dimensions of word counts rarely appear in each document based on dimensional reduction test parameters of 10% -90% of 5.344 words. The performance of the classification system is tested by using the Confusion Matrix based on comparative test data and test data. The results showed that the best classification results were obtained during the 75% training data test and 25% test data from the total data. Accuracy rates for categories of DM, ITS and MM were 100%, 100%, 86%. respectively with dimension reduction parameters of 30% and the value of learning rate between 0.1-0.5.
The function of a non-protein-coding RNA is often determined by its structure. Since experimental determination of RNA structure is time-consuming and expensive, its computational prediction is of great interest, and efficient solutions based on thermodynamic parameters are known. Frequently, however, the predicted minimum free energy structures are not the native ones, leading to the necessity of generating suboptimal solutions. While this can be accomplished by a number of programs, the user is often confronted with large outputs of similar structures, although he or she is interested in structures with more fundamental differences, or, in other words, with different abstract shapes. Here, we formalize the concept of abstract shapes and introduce their efficient computation. Each shape of an RNA molecule comprises a class of similar structures and has a representative structure of minimal free energy within the class. Shape analysis is implemented in the program RNAshapes. We applied RNAshapes to the prediction of optimal and suboptimal abstract shapes of several RNAs. For a given energy range, the number of shapes is considerably smaller than the number of structures, and in all cases, the native structures were among the top shape representatives. This demonstrates that the researcher can quickly focus on the structures of interest, without processing up to thousands of near-optimal solutions. We complement this study with a large-scale analysis of the growth behaviour of structure and shape spaces. RNAshapes is available for download and as an online version on the Bielefeld Bioinformatics Server.
Data of a partial-wave analysis of nucleon-nucleon scattering at energies of up to Esub lab = 3 GeV (lower partial waves) and the properties of the deuteron are described within the relativistic optical model based on deep attractive quasipotentials involving forbidden states (as exemplified by the Moscow potential). Partial-wave potentials are derived by the inverse-scattering-problem method based on the Marchenko equation by using present-day data from the partial-wave analysis of nucleon-nucleon scattering at energies of up to 3 GeV. Channel coupling is taken into account. The imaginary parts of the potentials are deduced from the phase equation of the variable-phasemore approach. The general situation around the manifestation of quark effects in nucleon-nucleon interaction is discussed. less 2ff7e9595c
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