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Keywords = information function

  • Open Access Research Article
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    Trends Journal of Sciences Research 2014, 1(1), 1-11. http://doi.org/10.31586/Agrochemistry.0101.01
    93 Views 256 Downloads 3 Citations PDF Full-text (461.204 KB)  HTML Full-text
    Abstract
    We present the results of a comprehensive long-term experiment on intensive cultivation of wheat and tomato plants to initially abiogenous mineral substrate. The experiment simulates the primary processes of soil formation. For the first time is established dynamic synergistic and antagonistic interrelations between the chemical elements (Si, Al, Fe, Mg,
    [...] Read more.
    We present the results of a comprehensive long-term experiment on intensive cultivation of wheat and tomato plants to initially abiogenous mineral substrate. The experiment simulates the primary processes of soil formation. For the first time is established dynamic synergistic and antagonistic interrelations between the chemical elements (Si, Al, Fe, Mg, Ca, K, P, S, Cl, Na, Mn, Zn) in various plant tissues (roots, fruits, grain, stems, leaves) under condition of primary soil formation. We have identified the dynamics of accumulation and differentiation of collective state of the chemical elements in different plant tissues by the methods of information theory.  Full article
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    Figure 2 of 6

    References
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    Vernadsky V.I. (1987). Chemical Composition of living Matter in the Context of Chemistry of the Earth?s Crust. Nauka. Moscow.
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    Polynov B.B. (1956). Selected Works. Ed. USSR Academy of Sciences. Moscow.
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    Zvyagintsev D.G. (1974). The interaction of microorganisms with solid surfaces. Ed. Moscow State University.
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    Ermakov E.I., Zvereva T.S. and Rybalchenko O.V. (2000). Change of crushed granite under perennial crops of wheat and tomato. Pochvovedenie. (Euroasian Soil Science). N.12, 1463- 1471.
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    Kovda V.A. (1956). The mineral composition of plants and soil formation. Pochvovedenie. (Euroasian Soil Science). No. 1, 6-38.
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    Rinkis G.Y., Ramana H.K. and Paegle G.V. (1979). Basics of mineral nutrition of plants. In: Macro-and microelements in mineral nutrition of plants. Rinkis G.Y. (ed.). Ed. Zinatne, Riga.
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    Il'in V.B. (1985). Elemental chemical composition of plants. Nauka. Novosibirsk.
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    Barber S.A.(1983). Soil Nutrient Bioavailability. Mechanistic Approach. A.Wiley Interscience Publication, John Wiley and Sons. New York, Chichester, Brisbone, Toronto, Singapore.
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    Kabata-Pendias A. and Pendias H. (1986). Trace Elements in Soils and Plants. CRC Press. Inc. Boca Raton, Florida.
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    Ermakov E.I, Zuev V.S. and Anikina L.M. (2005). Moisture condition at the interface as the indicator of the intensity of the process of primary soil formation. Pochvovedenie, ?2, 195-202.
    [11]
    Ermakov E.I., Anikina L.M. and Chaikovskaya L.A. (1987). Inventor?s Certificate, no. 1303063. Bull. Izobret., no.14.
    [12]
    Mukhomorov V.K. and Anikina L.M. (2011). Dynamics of chemical elements in plants. Primary soil formation. Lambert Academic Publisher. Saarbr?cken. Germany. 2012 (in Russian). 265 p.
    [13]
    Ermakov E.I. and Mukhomorov V.K. (2001). Evolution of diversity measures as a reflection of the process of primary soil formation in a model soil-plant system. Doklady Biochemistry and Biophysics. 379, 297-301.
    [14]
    Ermakov E.I. and Anikina L.M. (2007). Formation of organic compounds and their role in the transformation of mineral rooting medium in a controlled agroecosystem. Russian Agricultural Sciences. ? 6, 30-32.
    [15]
    Samsonova N.E. (2005). Kremniy v pochve i rasteniyakh. (Silicon in soil and plants). AgroKhimia. (Agrochemistry). ?6, 76-86.
    [16]
    Goldschmidt V.M. (1934). The crystal structure and chemical composition. Uspekhi Khimii. 3, 448.
    [17]
    Ermakov E.I., Mukhomorov V.K. and Anikina L.M. (2006). Cause-and-effect relations in the distribution of chemical elements in plant organs during long-term cultivation in a regulated agroecosystem. Russian Agricultural Sciences. no. 3, 1-4.
    [18]
    Mukhomorov V.K. (2013). Dynamics of the information exchange and the causal-and-effect relationships in plants under controlled conditions. World Journal of Agricultural Research. 1, no.1, 18-24.
    [19]
    Mukhomorov V.K. and Anikina L.M. (2011). Information flows between organic matter of the roots environment and elemental chemical composition of plants under primary pedogenic conditions. Russian Agricultural Sciences. 37, no. 4, 322-326.
    [20]
    Ermakov E.I. and Mukhomorov V.K. (2009). Productional process of plants and the diversity of interactions of edaphic factors in a controlled agroecosystem. In: Ermakov E.I. Selected works. Eds. Yakushev V.P., Panova G.G., Stepanova O.A. St.-Petersburg, pp.48-54.
    [21]
    Mac Arthur R. 1955. Fluctuations of animal populations, and a measure of community stability. Ecology. 36, 533-536.
    [22]
    Shannon C. (1963). Works on Information Theory and Cybernetics. Moscow.
    [23]
    Kolmogorov A.N. (1987). Information Theory and Theory of Algorithms. Nauka. Moscow.
    [24]
    Mukhomorov V.K. and Anikina L.M. (2009). Information streams and plant productivity. American-Eurasian Journal of Agricultural & Environmental Sciences. 5, 387-392.
    [25]
    Ermakov E.I. and Medvedeva I.V. (1985). In: Physiological patterns of ontogeny and plant productivity. Leningrad. pp. 155- 185.
  • Open Access Research Article
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    Trends Journal of Sciences Research 2014, 1(1), 17-25. http://doi.org/10.31586/Agrophysical.0101.03
    54 Views 205 Downloads 1 Citations PDF Full-text (221.837 KB)  HTML Full-text
    Abstract
    We result statistical analysis of experimental data on physical modeling of primary soil formation under long and continuous cultivation of plants on initially abiogenous mineral substrates (granite crushed stone, zeolite). The purpose of the experiment was to follow the dynamics of the evolutionary changes in the mineral substrate under condition
    [...] Read more.
    We result statistical analysis of experimental data on physical modeling of primary soil formation under long and continuous cultivation of plants on initially abiogenous mineral substrates (granite crushed stone, zeolite). The purpose of the experiment was to follow the dynamics of the evolutionary changes in the mineral substrate under condition long-term operation. We used the information approach to quantitative analyze of the relationship of primary soil formation process with the vital activity of plants (tomato, spring wheat) under controlled conditions. We analyzed the dynamics of the diversity of emerging organic matter in the mineral substrate and the biotic community. To quantify the diversity of multicomponent systems, we used information function. We have shown that the dynamics of plant productivity was statistically significant related to the parameter of information exchange between emerging organic matter and biotic community. It has been established that the increase in the total content of organic matter in the mineral substrate does not have a statistically significant correlation with the productivity of plants.  Full article
    Figures

    Figure 6 of 7

    References
    [1]
    Mukhomorov V.K., and Anikina L.M. (2012) Dynamics of Mineral Elements in Plants. Primary Soil Formation. LAMBERT Academic Publishing. Saarbr?cken (in Russian).
    [2]
    Assing I.A. (1950) Izv. Akad. Nauk Kazakh. SSR. Ser. Pochv., no.6, 101-108.
    [3]
    Polynov B.K. Selected Works, Academy of Sciences USSR, 1956.
    [4]
    Popov A.I. (2004) Humic Substances: Properties, Structure, and Formation, St.Petersburg (in Russian).
    [5]
    Alexandrova L.N. (1980) Soil Organic Matter and Processes of Its Transformation. Leningrad: Nauka (in Russian).
    [6]
    Ermakov E.I. (1984) USSR Author?s Certificate, Bull. 21.
    [7]
    Ermakov A.I. (1987) Methods of Biochemical Investigation of Plants. Leningrad (in Russian).
    [8]
    Shannon C.E. (1948) A Mathematical Theory of Communication. Bell Sys. Tech. Journal, 27, 379-423, 623-656.
    [9]
    Kolmogorov A.N. (1987) Information Theory and Theory of Algorithms. Nauka, Moscow (in Russian).
    [10]
    Mukhomorov V.K., and Anikina L.M. (2011) Information Flows between Organic Matter of the Roots Environment and Elemental Chemical Composition of Plants under Primary Pedogenic Conditions. Russian Agricultural Sciences, 37, 322-326.
    [11]
    Essays on the Use of Information Theory in Biology. (1953) Kastler H., Ed. Univ. Illinois Press, Urbana.
    [12]
    Mukhomorov V.K., and Anikina L.M. (2014). Evolutionary Dynamics of Intercoupling of the Chemical Elements in Plants and Primary Soil-Forming Processes. Trends Journal of Sciences Research, 1(1), 1-11.
    [13]
    Fleis J. (1973) Statistical Methods for Rates and Proportions. Wiley, New York.
    [14]
    Ermakov E.I., Anikina L.M. and Mukhomorov V.K. (1990). Soderzhaniye nitratov v produktsii ovoshchnykh i zernovykh kul'tur v zavisimosti ot kolichestva organicheskogo veshchestva v korneobitayemykh sredakh (The nitrate content in the production of vegetable and cereal crops, depending on the amount of organic matter in the rooting medium). Doklady Rossiyskoy akademii sel'skokhozyaystvennykh nauk (Reports of the Russian Academy of Agricultural Sciences), no.11,14-17. (in Russian).
  • Open Access Research Article
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    Trends Journal of Sciences Research 2014, 1(1), 38-48. http://doi.org/10.31586/Biochemistry.0101.06
    193 Views 535 Downloads 1 Citations PDF Full-text (962.717 KB)  HTML Full-text
    Abstract
    The biological activity of chemical compounds is analyzed using electronic and information factors. We found a linear interrelation between the electronic and information factors of molecules. Moreover, these molecular factors are calculated from different principles. Electronic factor is determined by the quantum-mechanical method from the molecular pseudopotential, whereas the information
    [...] Read more.
    The biological activity of chemical compounds is analyzed using electronic and information factors. We found a linear interrelation between the electronic and information factors of molecules. Moreover, these molecular factors are calculated from different principles. Electronic factor is determined by the quantum-mechanical method from the molecular pseudopotential, whereas the information factor is determined by using the information function. It is shown that these factors are separated off statistically significant bioactive chemical compounds of inactive chemicals. To determine these factors is sufficient to know only the chemical formula of molecules. We analyzed the chemical compounds for toxicity, antiradiation activity, carcinogenicity, antifungal activities. To identify biologically active chemical compounds we used the statistical conjugation method of qualitative attributes.  Full article
    Figures

    Figure 6 of 8

    References
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    Bacq Z.M., Alexander P. (1961). Fundamentals of Radiobiology. Pergamon Press, Oxford ? New-York ? Paris.
    [2]
    Veljkovi? V., Lalovi? D. (1973). General model pseudopotential for positive ions. Phys. Lett., 45A, 59-60.
    [3]
    Mukhomrov V.K. (2014). Biological Activity of Chemical Compounds and their Molecular Structure ? Information Approach. J. Chem. Eng. Chem. Res., 1(1), 54-65.
    [4]
    Veljkovi? V., Lalovi? D. (1977). Experienta, 33(9), 1228.
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    Sweeney T.R. (1979). Survey of compounds from the antiradiation drug development programm. Washington.
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    Romantzev, E.F. (1968). Radiation and chemical protection. Nauka, Moscow, 1968 (in Russian).
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    F?rster E., R?nz B. (1979). Methoden der Korrelations- und Regressionsanalyse. Verlag Die Wirtschaft. Berlin.
    [8]
    Shannon C. (1948). A Mathematical Theory of Communications. Bell Syst. Techn. Journal. 27, 379-423.
    [9]
    Kolmogorov A.N. (1987). Information Theory and Theory of Algotithms. Nauka. Moscow. (in Russian).
    [10]
    Pustyl?nik E.I. (1968). Statistical Methods of Analysis and Processing Observations. Nauka, Moscow. (in Russian).
    [11]
    Westland R.D. (1968). N-Substituted S-2 Aminoethyl Thiosulfates as Antiradiation agents. J. Med. Chem. 11, 1190-1201.
    [12]
    Mukhomorov V.K. (2013). Linking the Radio-Protective Effects of Tryptamine Analogues with their Electronic and Steric Properties via Quantum Mechanics Calculations. Chem. Rapid Commun. 1(1), 15-20.
    [13]
    Turusov, V.S. (1964). Cancerogenic Substances. Handbook. Nauka, Moscow, (in Russian).
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    Belenkaya I.A., Dyachina Zh.S., Mukhomorov V.K. (1991). Structure-Activity. Association of the Electronic Parameters of Substituted Benzo-2,1,3-Thia- and Selenadiazoles with their Antifungal Activity and Toxicity. Pharm. Chem. Journal.. 25(12), 900-906.
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    Golyshin N.M. (1970). Fungitsidy v sel'skom khozyaystve (Fungicides in Agriculture). M. (in Russian).
  • Open Access Research Article
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    Trends Journal of Sciences Research 2015, 2(1), 13-16. http://doi.org/10.31586/Mathematics.0201.02
    19 Views 455 Downloads PDF Full-text (717.950 KB)  HTML Full-text
    Abstract
    The multiplicative functions characterizing the finite set of positive numbers are introduced in the work. With their help we find the logarithmic identities which connect logarithm of sum of the set numbers and logarithms of numbers themselves. One of them (contained in the work of Shannon) interconnects three information functions:
    [...] Read more.
    The multiplicative functions characterizing the finite set of positive numbers are introduced in the work. With their help we find the logarithmic identities which connect logarithm of sum of the set numbers and logarithms of numbers themselves. One of them (contained in the work of Shannon) interconnects three information functions: information Hartley, entropy and coentropy. Shannon's identity allows better to understand the meaning and relationship of these collective characteristics of information (as the characteristics of finite sets and as probabilistic characteristics). The factorial multiplicative function and the logarithmic factorial identity are formed also from initial set numbers. That identity connects logarithms of factorials of integer numbers and logarithm of factorial of their sum.  Full article
    References
    [1]
    Shannon ?.E. ?athematical Theory of Communications. Bell System Technical Journal 1948 v. 23.
    [2]
    ?ianucci D., Cattaneo G., Ciucci D. Information Entropy and Co-entropy of Crispand Fussy Granulation in ?Application of Fuzzy Sets Theory?. Camogli, 2007.
    [3]
    Vijatkin V.B. Synergetic information theory. Information technology: 2009, 12; Scientific Journal of Kuban Agronomic University: 2008, v.44, p. 10; 2009, v. 45, p. 10; 2009, v.47, p. 3.
    [4]
    Ventzel E.S. Probability Theory. Science, Moscow. M. 1964.
    [5]
    Tribus M. Thermostatic and Thermodynamics. Van Nostrand. N.Y. 1961
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