290 research outputs found
Upper semi-continuity of the Royden-Kobayashi pseudo-norm, a counterexample for H\"olderian almost complex structures
If is an almost complex manifold, with an almost complex structure of
class \CC^\alpha, for some , for every point and every
tangent vector at , there exists a germ of -holomorphic disc through
with this prescribed tangent vector. This existence result goes back to
Nijenhuis-Woolf. All the holomorphic curves are of class \CC^{1,\alpha}
in this case.
Then, exactly as for complex manifolds one can define the Royden-Kobayashi
pseudo-norm of tangent vectors. The question arises whether this pseudo-norm is
an upper semi-continuous function on the tangent bundle. For complex manifolds
it is the crucial point in Royden's proof of the equivalence of the two
standard definitions of the Kobayashi pseudo-metric. The upper semi-continuity
of the Royden-Kobayashi pseudo-norm has been established by Kruglikov for
structures that are smooth enough. In [I-R], it is shown that \CC^{1,\alpha}
regularity of is enough.
Here we show the following:
Theorem. There exists an almost complex structure of class \CC^{1\over
2} on the unit bidisc \D^2\subset \C^2, such that the Royden-Kobayashi
seudo-norm is not an upper semi-continuous function on the tangent bundle.Comment: 5 page
Fractal Graphs and their Properties
The idea of representing urban structure and various communication systems (water and energy supply, telephone and cable TV networks) as fractal objects is not absolutely new. However, known works, devoted to this problem use models and approaches from fractal physics. For example, to simulate urban growth Diffusion Limited Aggregation (DLA) model and Dielectric Breakdown (DB) model are used. This study introduces a different approach. Net structure of communication system is described by a graph of special type called regular G(l,r,n)-graph. Authors provide description of such graph, develop iterative process for its generation and prove its self-similarity, i.e. that every regular graph is a pre-fractal. After the infinite number of steps this process generates a fractal. The devised algorithm for generation and grathical representation of regular G(l,r,n)-graphs with different values of l,r and n has been programmed to receive computer simulations. For optimal graphic presentation of pre-fractals the Optimal Space Ordering method was suggested. It is based on the minimization of the >graph energygraph energy< is directly related to the graph's fractal properties. For G(3,3,n) and G(4,4,n) graphs fractal dimensions calculated by different methods are the same (D=1,5 and D=2 respectively), while topological dimension of both graphs is 1
Π‘ΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΎ-Π±ΡΠ±Π»ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΡΡΡΡΡ Β«ΠΠΈΠ΄Π°ΡΠ½Ρ ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΠΈ Π£ΠΊΡΠ°ΡΠ½ΠΈ ΡΠ° ΡΠ²ΡΡΡΒ» ΡΠ° ΠΉΠΎΠ³ΠΎ Π²ΠΏΠ»ΠΈΠ² Π½Π° ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ ΡΠΈΡΡΠΎΠ²ΠΎΡ Π³ΡΠΌΠ°Π½ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ
The article reveals the specifics of creation, content, functions and value of the electronic information and bibliographic resource "Outstanding Educators of Ukraine and the World" of V. O. Sukhomlynskyi State Scientific and Pedagogical Library of the National Academy of Educational Sciences of Ukraine in a comparative dimension with similar Ukrainian and foreign electronic biographical resources. The goals of the development of the electronic biographical resource have been formulated; the specifics of formation of its content and structure have been characterized; the importance of electronic biographical resources in the domestic and foreign educational and scientific space as a component of digital humanities has been substantiated. The influence of the use of electronic biographical resources on public opinion and on a person in the educational dimension has been investigated. It has been proven that in the context of the digital transformation of the scientific sphere and the integration of the Ukrainian education into the European educational and scientific space, the development of electronic information and specialized bibliographic resources, dedicated to well-known personalities in the sphere of education, history and culture, got significant repercussions. We have substantiated why the electronic resource "Outstanding Educators of Ukraine and the World", containing information about Ukrainian and foreign educators and public figures, is a unique specialist resource without analogues. It is a significant contribution to the development of digital pedagogical biographics and it makes it possible, through the prism of scientific biographies, to trace systematically the development of the Ukrainian and foreign education, pedagogical thought in both macrohistorical and microhistorical dimensions and to contribute to the restoration of the national pedagogical memory. The representation via the electronic resource of the generalized knowledge about the humanistic ideas of the Ukrainian and foreign educators and public figures of the past is of great importance for education in general, in particular for pedagogical education in Ukraine, namely in the system of professional training; it is a source of formation of a pedagogical worldview in students who will be teachers in the future, increasing their spiritual culture in the face of global civilizational challenges. We have revealed that the information and bibliographic resource requires further updating, taking into account the new achievements of the Ukrainian and foreign historical, educational and biographical studies and the latest information technologies. The priority tasks for improving the electronic resource have been identified, in particular: the prospects for the content and the ways of updating information and making qualitative changes in the functionality of the electronic educational resource.Π£ ΡΡΠ°ΡΡΡ ΡΠΎΠ·ΠΊΡΠΈΡΠΎ ΠΎΡΠΎΠ±Π»ΠΈΠ²ΠΎΡΡΡ ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ, Π·ΠΌΡΡΡ, ΡΡΠ½ΠΊΡΡΡ, Π·Π½Π°ΡΠ΅Π½Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠ³ΠΎ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΎ-Π±ΡΠ±Π»ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΡΡΡΡΡ Β«ΠΠΈΠ΄Π°ΡΠ½Ρ ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΠΈ Π£ΠΊΡΠ°ΡΠ½ΠΈ ΡΠ° ΡΠ²ΡΡΡΒ» ΠΠ΅ΡΠΆΠ°Π²Π½ΠΎΡ Π½Π°ΡΠΊΠΎΠ²ΠΎ-ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΡΠ½ΠΎΡ Π±ΡΠ±Π»ΡΠΎΡΠ΅ΠΊΠΈ Π£ΠΊΡΠ°ΡΠ½ΠΈ ΡΠΌΠ΅Π½Ρ Π. Π. Π‘ΡΡ
ΠΎΠΌΠ»ΠΈΠ½ΡΡΠΊΠΎΠ³ΠΎ ΠΠ°ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΎΡ Π°ΠΊΠ°Π΄Π΅ΠΌΡΡ ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΡΠ½ΠΈΡ
Π½Π°ΡΠΊ Π£ΠΊΡΠ°ΡΠ½ΠΈ Ρ ΠΏΠΎΡΡΠ²Π½ΡΠ»ΡΠ½ΠΎΠΌΡ Π²ΠΈΠΌΡΡΡ Π· Π°Π½Π°Π»ΠΎΠ³ΡΡΠ½ΠΈΠΌΠΈ ΡΠ²ΡΡΠΎΠ²ΠΈΠΌΠΈ ΡΠ° ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΈΠΌΠΈ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΠΌΠΈ Π±ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΈΠΌΠΈ ΡΠ΅ΡΡΡΡΠ°ΠΌΠΈ. ΠΠΈΡΠ²Π»Π΅Π½ΠΎ ΠΏΡΠΈΡΠΈΠ½ΠΈ, ΡΡΠΎΡΠΌΡΠ»ΡΠΎΠ²Π°Π½ΠΎ ΡΡΠ»Ρ ΡΠΎΠ·ΡΠΎΠ±Π»Π΅Π½Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΡ
Π±ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΈΡ
ΡΠ΅ΡΡΡΡΡΠ²; ΡΡ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΠΎΠ²Π°Π½ΠΎ ΠΎΡΠΎΠ±Π»ΠΈΠ²ΠΎΡΡΡ ΡΠΎΡΠΌΡΠ²Π°Π½Π½Ρ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡ ΡΠ΅ΡΡΡΡΡΠ², ΡΡ
ΡΡΡΡΠΊΡΡΡΠΈ; Π°ΡΠ³ΡΠΌΠ΅Π½ΡΠΎΠ²Π°Π½ΠΎ Π·Π½Π°ΡΠ΅Π½Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΡ
Π±ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΈΡ
ΡΠ΅ΡΡΡΡΡΠ² Ρ Π²ΡΡΡΠΈΠ·Π½ΡΠ½ΠΎΠΌΡ ΡΠ° Π·Π°ΡΡΠ±ΡΠΆΠ½ΠΎΠΌΡ ΠΎΡΠ²ΡΡΠ½ΡΠΎ-Π½Π°ΡΠΊΠΎΠ²ΠΎΠΌΡ ΠΏΡΠΎΡΡΠΎΡΡ ΡΠΊ ΡΠΊΠ»Π°Π΄Π½ΠΈΠΊΠ° ΡΠΈΡΡΠΎΠ²ΠΎΡ Π³ΡΠΌΠ°Π½ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ. ΠΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½ΠΎ Π²ΠΏΠ»ΠΈΠ² Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΡ
Π±ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΈΡ
ΡΠ΅ΡΡΡΡΡΠ² Π½Π° ΡΡΡΠΏΡΠ»ΡΠ½Ρ Π΄ΡΠΌΠΊΡ ΡΠ° Π»ΡΠ΄ΠΈΠ½Ρ Π² ΠΎΡΠ²ΡΡΠ½ΡΠΎΠΌΡ Π²ΠΈΠΌΡΡΡ. ΠΠΎΠ²Π΅Π΄Π΅Π½ΠΎ, ΡΠΎ Π² ΡΠΌΠΎΠ²Π°Ρ
ΡΠΈΡΡΠΎΠ²ΠΎΡ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΡΡ Π½Π°ΡΠΊΠΎΠ²ΠΎΡ ΡΡΠ΅ΡΠΈ ΡΠ° ΡΠ½ΡΠ΅Π³ΡΠ°ΡΡΡ ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΎΡ ΠΎΡΠ²ΡΡΠΈ Π΄ΠΎ ΡΠ²ΡΠΎΠΏΠ΅ΠΉΡΡΠΊΠΎΠ³ΠΎ ΠΎΡΠ²ΡΡΠ½ΡΠΎ-Π½Π°ΡΠΊΠΎΠ²ΠΎΠ³ΠΎ ΠΏΡΠΎΡΡΠΎΡΡ Π½Π°Π±ΡΠ»ΠΎ Π·Π½Π°ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅Π·ΠΎΠ½Π°Π½ΡΡ ΡΠΎΠ·ΡΠΎΠ±Π»Π΅Π½Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΡ
ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΎ-Π±ΡΠ±Π»ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΈΡ
ΡΠ΅ΡΡΡΡΡΠ² Π³Π°Π»ΡΠ·Π΅Π²ΠΎΠ³ΠΎ ΡΠΏΡΡΠΌΡΠ²Π°Π½Π½Ρ, ΠΏΡΠΈΡΠ²ΡΡΠ΅Π½ΠΈΡ
Π²ΡΠ΄ΠΎΠΌΠΈΠΌ Π΄ΡΡΡΠ°ΠΌ ΠΎΡΠ²ΡΡΠΈ, ΡΡΡΠΎΡΡΡ, ΠΊΡΠ»ΡΡΡΡΠΈ. ΠΡΠ³ΡΠΌΠ΅Π½ΡΠΎΠ²Π°Π½ΠΎ, ΡΠΎ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΠΉ ΡΠ΅ΡΡΡΡ Β«ΠΠΈΠ΄Π°ΡΠ½Ρ ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΠΈ Π£ΠΊΡΠ°ΡΠ½ΠΈ ΡΠ° ΡΠ²ΡΡΡΒ», ΠΊΠΎΡΡΠΈΠΉ ΠΌΡΡΡΠΈΡΡ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡ ΠΏΡΠΎ ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΈΡ
Ρ Π·Π°ΡΡΠ±ΡΠΆΠ½ΠΈΡ
ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΠ² Ρ ΠΎΡΠ²ΡΡΡΠ½, Ρ ΡΠ½ΡΠΊΠ°Π»ΡΠ½ΠΈΠΌ Π³Π°Π»ΡΠ·Π΅Π²ΠΈΠΌ ΡΠ΅ΡΡΡΡΠΎΠΌ, Π°Π½Π°Π»ΠΎΠ³ΡΠ² ΡΠΊΠΎΠΌΡ Π½Π΅ Π·Π½Π°ΠΉΠ΄Π΅Π½ΠΎ. ΠΡΠ½ Ρ Π²Π°Π³ΠΎΠΌΠΈΠΌ Π²Π½Π΅ΡΠΊΠΎΠΌ Ρ ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ ΡΠΈΡΡΠΎΠ²ΠΎΡ ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΡΠ½ΠΎΡ Π±ΡΠΎΠ³ΡΠ°ΡΡΠΊΠΈ ΠΉ Π΄ΠΎΠ·Π²ΠΎΠ»ΡΡ ΠΊΡΡΠ·Ρ ΠΏΡΠΈΠ·ΠΌΡ Π½Π°ΡΠΊΠΎΠ²ΠΈΡ
Π±ΡΠΎΠ³ΡΠ°ΡΡΠΉ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎ ΠΏΡΠΎΡΡΠ΅ΠΆΡΠ²Π°ΡΠΈ ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΎΡ Ρ Π·Π°ΡΡΠ±ΡΠΆΠ½ΠΎΡ ΠΎΡΠ²ΡΡΠΈ, ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΡΠ½ΠΎΡ Π΄ΡΠΌΠΊΠΈ ΡΠΊ Ρ ΠΌΠ°ΠΊΡΠΎΡΡΡΠΎΡΠΈΡΠ½ΠΈΡ
, ΡΠ°ΠΊ Ρ Π² ΠΌΡΠΊΡΠΎΡΡΡΠΎΡΠΈΡΠ½ΠΈΡ
Π²ΠΈΠΌΡΡΠ°Ρ
, ΡΠΏΡΠΈΡΡ Π²ΡΠ΄Π½ΠΎΠ²Π»Π΅Π½Π½Ρ Π½Π°ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΎΡ ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΡΠ½ΠΎΡ ΠΏΠ°ΠΌβΡΡΡ. Π Π΅ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΡΡ Π·Π° Π΄ΠΎΠΏΠΎΠΌΠΎΠ³ΠΎΡ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠ³ΠΎ ΡΠ΅ΡΡΡΡΡ ΡΠ·Π°Π³Π°Π»ΡΠ½Π΅Π½ΠΎΠ³ΠΎ Π·Π½Π°Π½Π½Ρ ΠΏΡΠΎ Π³ΡΠΌΠ°Π½ΡΡΡΠΈΡΠ½Ρ ΡΠ΄Π΅Ρ ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΈΡ
Ρ Π·Π°ΡΡΠ±ΡΠΆΠ½ΠΈΡ
ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΠ² ΡΠΈ ΠΎΡΠ²ΡΡΡΠ½ ΠΌΠΈΠ½ΡΠ»ΠΎΠ³ΠΎ ΠΌΠ°Ρ Π²Π΅Π»ΠΈΠΊΠ΅ Π·Π½Π°ΡΠ΅Π½Π½Ρ Π΄Π»Ρ ΠΎΡΠ²ΡΡΠΈ Π·Π°Π³Π°Π»ΠΎΠΌ, Π·ΠΎΠΊΡΠ΅ΠΌΠ° ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΡΠ½ΠΎΡ ΠΎΡΠ²ΡΡΠΈ Π£ΠΊΡΠ°ΡΠ½ΠΈ, Π° ΡΠ°ΠΌΠ΅ Π² ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΡΠΎΡΠ΅ΡΡΠΉΠ½ΠΎΡ ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ, ΡΠ° Ρ Π΄ΠΆΠ΅ΡΠ΅Π»ΠΎΠΌ ΡΠΎΡΠΌΡΠ²Π°Π½Π½Ρ Π² ΡΡΡΠ΄Π΅Π½ΡΡΠ² β ΠΌΠ°ΠΉΠ±ΡΡΠ½ΡΡ
ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΠ² β ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΡΡΠ½ΠΎΠ³ΠΎ ΡΠ²ΡΡΠΎΠ³Π»ΡΠ΄Ρ, ΠΏΡΠ΄Π²ΠΈΡΠ΅Π½Π½Ρ ΡΡ
Π΄ΡΡ
ΠΎΠ²Π½ΠΎΡ ΠΊΡΠ»ΡΡΡΡΠΈ Π² ΡΠΌΠΎΠ²Π°Ρ
Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΈΡ
ΡΠΈΠ²ΡΠ»ΡΠ·Π°ΡΡΠΉΠ½ΠΈΡ
Π²ΠΈΠΊΠ»ΠΈΠΊΡΠ². ΠβΡΡΠΎΠ²Π°Π½ΠΎ, ΡΠΎ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΎ-Π±ΡΠ±Π»ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΈΠΉ ΡΠ΅ΡΡΡΡ ΠΏΠΎΡΡΠ΅Π±ΡΡ ΠΏΠΎΠ΄Π°Π»ΡΡΠΎΠ³ΠΎ ΠΎΠ½ΠΎΠ²Π»Π΅Π½Π½Ρ Π· ΡΡΠ°Ρ
ΡΠ²Π°Π½Π½ΡΠΌ Π½ΠΎΠ²ΠΈΡ
Π·Π΄ΠΎΠ±ΡΡΠΊΡΠ² ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΈΡ
Ρ Π·Π°ΡΡΠ±ΡΠΆΠ½ΠΈΡ
ΡΡΡΠΎΡΠΈΠΊΠΎ-ΠΎΡΠ²ΡΡΠ½ΡΡ
, ΡΡΡΠΎΡΠΈΡΠ½ΠΈΡ
ΡΠ° Π±ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΈΡ
ΡΡΡΠ΄ΡΠΉ, Π½ΠΎΠ²ΡΡΠ½ΡΡ
ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΈΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΡΠΉ ΡΠΎΡΠΎ. ΠΠΈΠ·Π½Π°ΡΠ΅Π½ΠΎ ΠΏΡΡΠΎΡΠΈΡΠ΅ΡΠ½Ρ Π·Π°Π²Π΄Π°Π½Π½Ρ ΡΠΎΠ΄ΠΎ Π²Π΄ΠΎΡΠΊΠΎΠ½Π°Π»Π΅Π½Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠ³ΠΎ ΡΠ΅ΡΡΡΡΡ, Π·ΠΎΠΊΡΠ΅ΠΌΠ° ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²ΠΈ Π·ΠΌΡΡΡΠΎΠ²ΠΎΠ³ΠΎ Π½Π°ΠΏΠΎΠ²Π½Π΅Π½Π½Ρ, ΡΠ»ΡΡ
ΠΈ ΠΎΠ½ΠΎΠ²Π»Π΅Π½Π½Ρ Π²ΡΠ΄ΠΎΠΌΠΎΡΡΠ΅ΠΉ ΡΠ° Π²Π½Π΅ΡΠ΅Π½Π½Ρ ΡΠΊΡΡΠ½ΠΈΡ
Π·ΠΌΡΠ½ Π΄ΠΎ ΡΡΠ½ΠΊΡΡΠΎΠ½Π°Π»Ρ ΡΠΈΡΡΠΎΠ²ΠΎΠ³ΠΎ Π½Π°ΡΠΊΠΎΠ²ΠΎ-ΠΎΡΠ²ΡΡΠ½ΡΠΎΠ³ΠΎ ΡΠ΅ΡΡΡΡΡ
ΠΠ ΠΠΠΠΠΠΠΠΠΠΠΠ«Π Π‘ΠΠ Π’ Π Π£Π€ΠΠΠ Π ΠΠΠ Π‘ΠΠΠΠ’ΠΠΠ« ΠΠΠ ΠΠ‘ΠΠΠΠ¬ΠΠΠΠΠΠΠ― Π Π‘ΠΠΠΠΠ¦ΠΠΠΠΠ«Π₯ ΠΠ ΠΠΠ ΠΠΠΠΠ₯ Π‘ΠΠΠΠΠΠΠ― ΠΠΠΠ«Π₯ Π€ΠΠ Π Π’ΠΠΠΠ’Π ΠΠΠ― ΠΠΠ©ΠΠ©ΠΠΠΠΠΠ ΠΠ Π£ΠΠ’Π
Priority directions in tomato breeding for protected ground remain stable productivity ness and quality of fruit, early ripeness, resistant to the most harmful diseases. Creating such varieties is a required component of ecological agriculture. Recently, the demand of appropriate species increases and hybrids of tomato with different colouring of the fruit, which is determined by the contents of xanthophylls and various carotenoids (lycopene, Ξ²-carotene, lutein, etc.) with antioxidant properties. According to the state program of research for 2000-2010, the staff of the laboratory of gamete and molecular methods of selection of Federal Scientific Vegetable Center created orange early crop variety Rufina for greenhouses. The article describes the brief history of its creation and characterization on major valuable features. Tomato cultivar Rufina is a source of economically useful traits: early ripeness, resistant to abiotic and biotic stresses, yield, palatability and nutritional value of fruits. Therefore, at present it is used when creating new forms of tomato, adapted to the conditions of various modern technologies protected ground - low-volume cultivation and multi-level narrow column hydroponics (MUG). A perspective starting material was received. These are five productive selection forms for the low-volume technology, haracterized by early ripeness (the beginning of harvesting on the 50-70 day of sowing), the weight of the fruit from 90 to 130 g, resistance to apical rot. For a MUG - two low forms with orange fruits weighing more than 30 grams, created as a result of hybridization with determinants of dwarfish redplant varieties Natasha.ΠΡΠΈΠΎΡΠΈΡΠ΅ΡΠ½ΡΠΌΠΈ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡΠΌΠΈ Π² ΡΠ΅Π»Π΅ΠΊΡΠΈΠΈ ΡΠΎΠΌΠ°ΡΠ° Π΄Π»Ρ Π·Π°ΡΠΈΡΠ΅Π½Π½ΠΎΠ³ΠΎ Π³ΡΡΠ½ΡΠ° ΠΎΡΡΠ°ΡΡΡΡ ΡΡΠ°Π±ΠΈΠ»ΡΠ½Π°Ρ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΈ ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎ ΠΏΠ»ΠΎΠ΄ΠΎΠ², ΡΠ°Π½Π½Π΅ΡΠΏΠ΅Π»ΠΎΡΡΡ, ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡ ΠΊ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²ΡΠ΅Π΄ΠΎΠ½ΠΎΡΠ½ΡΠΌ Π±ΠΎΠ»Π΅Π·Π½ΡΠΌ. ΠΡΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΡΠ°ΠΊΠΈΡ
ΡΠΎΡΡΠΎΠ² ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΡΠΌ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠΌ ΡΠΊΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π·Π΅ΠΌΠ»Π΅Π΄Π΅Π»ΠΈΡ. Π ΠΏΠΎΡΠ»Π΅Π΄Π½Π΅Π΅ Π²ΡΠ΅ΠΌΡ Π²ΠΎΠ·ΡΠ°ΡΡΠ°Π΅Ρ ΡΠΏΡΠΎΡ Π½Π° ΡΠΎΡΡΠ° ΠΈ Π³ΠΈΠ±ΡΠΈΠ΄Ρ ΡΠΎΠΌΠ°ΡΠ° Ρ ΡΠ°Π·Π»ΠΈΡΠ½ΠΎΠΉ ΠΎΠΊΡΠ°ΡΠΊΠΎΠΉ ΠΏΠ»ΠΎΠ΄Π°, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅ΡΡΡ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ΠΌ ΠΊΡΠ°Π½ΡΠΎΡΠΈΠ»Π»ΠΎΠ² ΠΈ ΡΠ°Π·Π½ΡΡ
ΠΊΠ°ΡΠΎΡΠΈΠ½ΠΎΠΈΠ΄ΠΎΠ² (Π»ΠΈΠΊΠΎΠΏΠΈΠ½, Ξ²-ΠΊΠ°ΡΠΎΡΠΈΠ½, Π»ΡΡΠ΅ΠΈΠ½ ΠΈ Π΄Ρ.), ΠΎΠ±Π»Π°Π΄Π°ΡΡΠΈΡ
Π°Π½ΡΠΈΠΎΠΊΡΠΈΠ΄Π°Π½ΡΠ½ΡΠΌΠΈ ΡΠ²ΠΎΠΉΡΡΠ²Π°ΠΌΠΈ. Π ΡΠ°ΠΌΠΊΠ°Ρ
Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ ΠΠΠ Π½Π° 2000-2010 Π³ΠΎΠ΄Ρ ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΠ²ΠΎΠΌ Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠΈΠΈ Π³Π°ΠΌΠ΅ΡΠ½ΡΡ
ΠΈ ΠΌΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΡΠ΅Π»Π΅ΠΊΡΠΈΠΈ Π€ΠΠΠΠ£ ΠΠΠΠΠ‘Π‘ΠΠ (Π½ΡΠ½Π΅ Π€ΠΠΠΠ£ Π€ΠΠ¦Π) Π±ΡΠ» ΡΠΎΠ·Π΄Π°Π½ ΠΎΡΠ°Π½ΠΆΠ΅Π²ΠΎΠΏΠ»ΠΎΠ΄Π½ΡΠΉ ΡΠ°Π½Π½Π΅ΡΠΏΠ΅Π»ΡΠΉ ΡΡΠΎΠΆΠ°ΠΉΠ½ΡΠΉ ΡΠΎΡΡ Π ΡΡΠΈΠ½Π° Π΄Π»Ρ ΠΏΠ»Π΅Π½ΠΎΡΠ½ΡΡ
ΡΠ΅ΠΏΠ»ΠΈΡ. Π ΡΡΠ°ΡΡΠ΅ ΠΏΡΠΈΠ²Π΅Π΄Π΅Π½Π° ΠΊΡΠ°ΡΠΊΠ°Ρ ΠΈΡΡΠΎΡΠΈΡ Π΅Π³ΠΎ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΠΏΠΎ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΠΎ ΡΠ΅Π½Π½ΡΠΌ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌ. Π‘ΠΎΡΡ ΡΠΎΠΌΠ°ΡΠ° Π ΡΡΠΈΠ½Π° ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΎΠΌ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΠΎ ΠΏΠΎΠ»Π΅Π·Π½ΡΡ
ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ²: ΡΠ°Π½Π½Π΅ΡΠΏΠ΅Π»ΠΎΡΡΡ, ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡ ΠΊ Π°Π±ΠΈΠΎΡΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈ Π±ΠΈΠΎΡΠΈΡΠ΅ΡΠΊΠΈΠΌ ΡΡΡΠ΅ΡΡΠ°ΠΌ, ΡΡΠΎΠΆΠ°ΠΉΠ½ΠΎΡΡΡ, Π²ΠΊΡΡΠΎΠ²ΡΠ΅ ΠΊΠ°ΡΠ΅ΡΡΠ²Π° ΠΈ ΠΏΠΈΡΠ΅Π²Π°Ρ ΡΠ΅Π½Π½ΠΎΡΡΡ ΠΏΠ»ΠΎΠ΄ΠΎΠ². ΠΠΎΡΡΠΎΠΌΡ, Π² Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ ΠΎΠ½ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΡΡΡ ΠΊΠ°ΠΊ ΠΏΡΠΈ ΡΠΎΠ·Π΄Π°Π½ΠΈΠΈ Π½ΠΎΠ²ΡΡ
ΡΠΎΡΠΌ ΡΠΎΠΌΠ°ΡΠ°, Π°Π΄Π°ΠΏΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΊ ΡΡΠ»ΠΎΠ²ΠΈΡΠΌ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ Π·Π°ΡΠΈΡΠ΅Π½Π½ΠΎΠ³ΠΎ Π³ΡΡΠ½ΡΠ° - ΠΌΠ°Π»ΠΎΠΎΠ±ΡΠ΅ΠΌΠ½ΠΎΠ΅ Π²ΡΡΠ°ΡΠΈΠ²Π°Π½ΠΈΠ΅ ΠΈ ΠΌΠ½ΠΎΠ³ΠΎΡΡΡΡΠ½Π°Ρ ΡΠ·ΠΊΠΎΡΡΠ΅Π»Π»Π°ΠΆΠ½Π°Ρ Π³ΠΈΠ΄ΡΠΎΠΏΠΎΠ½ΠΈΠΊΠ° (ΠΠ£Π). Π ΡΠ°ΠΌΠΊΠ°Ρ
ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΠ΅Π»Π΅ΠΊΡΠΈΠΎΠ½Π½ΡΡ
ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌ Π½Π° Π΅Π³ΠΎ ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΠΎΠ»ΡΡΠ΅Π½ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΡΠΉ ΠΈΡΡ
ΠΎΠ΄Π½ΡΠΉ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π» Π΄Π»Ρ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ Π°Π΄ΡΠ΅ΡΠ½ΡΡ
ΡΠΎΡΡΠΎΠ². ΠΡΠΎ ΠΏΡΡΡ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΡΡ
ΡΠ΅Π»Π΅ΠΊΡΠΈΠΎΠ½Π½ΡΡ
ΡΠΎΡΠΌ Π΄Π»Ρ ΠΌΠΎΠ»ΠΎΠΎΠ±ΡΠ΅ΠΌΠ½ΠΎΠΉ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΡΡ ΡΠ°Π½Π½Π΅ΡΠΏΠ΅Π»ΠΎΡΡΡΡ (Π½Π°ΡΠ°Π»ΠΎ ΡΠ±ΠΎΡΠ° ΠΏΠ»ΠΎΠ΄ΠΎΠ² Π½Π° 50-70 ΡΡΡΠΊΠΈ ΠΎΡ ΠΏΠΎΡΠ΅Π²Π°), ΠΌΠ°ΡΡΠΎΠΉ ΠΏΠ»ΠΎΠ΄Π° ΠΎΡ 90 Π΄ΠΎ 130 Π³, ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡΡ ΠΊ Π²Π΅ΡΡΠΈΠ½Π½ΠΎΠΉ Π³Π½ΠΈΠ»ΠΈ. ΠΠ»Ρ ΠΠ£Π - Π΄Π²Π΅ Π½ΠΈΠ·ΠΊΠΎΡΠΎΡΠ»ΡΠ΅ ΡΡΠ°ΠΌΠ±ΠΎΠ²ΡΠ΅ ΡΠΎΡΠΌΡ Ρ ΠΎΡΠ°Π½ΠΆΠ΅Π²ΡΠΌΠΈ ΠΏΠ»ΠΎΠ΄Π°ΠΌΠΈ ΠΌΠ°ΡΡΠΎΠΉ Π±ΠΎΠ»Π΅Π΅ 30 Π³, ΡΠΎΠ·Π΄Π°Π½Π½ΡΠ΅ Π² ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ Π³ΠΈΠ±ΡΠΈΠ΄ΠΈΠ·Π°ΡΠΈΠΈ Ρ Π΄Π΅ΡΠ΅ΡΠΌΠΈΠ½Π°Π½ΡΠ½ΡΠΌ ΠΊΠ°ΡΠ»ΠΈΠΊΠΎΠ²ΡΠΌ ΠΊΡΠ°ΡΠ½ΠΎΠΏΠ»ΠΎΠ΄Π½ΡΠΌ ΡΠΎΡΡΠΎΠΌ ΠΠ°ΡΠ°ΡΠ°
Photoactivatable prodrugs of antimelanoma agent Vemurafenib
In this study, we report on novel
photoactivatable caged prodrugs
of vemurafenib. This kinase inhibitor was the first approved drug
for the personalized treatment of BRAF-mutated melanoma and showed
impressive results in clinical studies. However, the occurrence of
severe side effects and drug resistance illustrates the urgent need
for innovative therapeutic approaches. To conquer these limitations,
we implemented photoremovable protecting groups into vemurafenib.
In general, this caging concept provides spatial and temporal control
over the activation of molecules triggered by ultraviolet light. Thus,
higher inhibitor concentrations in tumor tissues might be reached
with less systemic effects. Our study describes the first development
of caged vemurafenib prodrugs useful as pharmacological tools. We
investigated their photochemical characteristics and photoactivation. <i>In vitro</i> evaluation proved the intended loss-of-function
and the light-dependent recovery of efficacy in kinase and cellular
assays. The reported vemurafenib photo prodrugs represent a powerful
biological tool for novel pharmacological approaches in cancer research
Genome-Scale Modeling of Light-Driven Reductant Partitioning and Carbon Fluxes in Diazotrophic Unicellular Cyanobacterium Cyanothece sp. ATCC 51142
Genome-scale metabolic models have proven useful for answering fundamental questions about metabolic capabilities of a variety of microorganisms, as well as informing their metabolic engineering. However, only a few models are available for oxygenic photosynthetic microorganisms, particularly in cyanobacteria in which photosynthetic and respiratory electron transport chains (ETC) share components. We addressed the complexity of cyanobacterial ETC by developing a genome-scale model for the diazotrophic cyanobacterium, Cyanothece sp. ATCC 51142. The resulting metabolic reconstruction, iCce806, consists of 806 genes associated with 667 metabolic reactions and includes a detailed representation of the ETC and a biomass equation based on experimental measurements. Both computational and experimental approaches were used to investigate light-driven metabolism in Cyanothece sp. ATCC 51142, with a particular focus on reductant production and partitioning within the ETC. The simulation results suggest that growth and metabolic flux distributions are substantially impacted by the relative amounts of light going into the individual photosystems. When growth is limited by the flux through photosystem I, terminal respiratory oxidases are predicted to be an important mechanism for removing excess reductant. Similarly, under photosystem II flux limitation, excess electron carriers must be removed via cyclic electron transport. Furthermore, in silico calculations were in good quantitative agreement with the measured growth rates whereas predictions of reaction usage were qualitatively consistent with protein and mRNA expression data, which we used to further improve the resolution of intracellular flux values
Zebrafish Kidney Phagocytes Utilize Macropinocytosis and Ca2+-Dependent Endocytic Mechanisms
Background: The innate immune response constitutes the first line of defense against invading pathogens and consists of a variety of immune defense mechanisms including active endocytosis by macrophages and granulocytes. Endocytosis can be used as a reliable measure of selective and non-selective mechanisms of antigen uptake in the early phase of an immune response. Numerous assays have been developed to measure this response in a variety of mammalian and fish species. The small size of the zebrafish has prevented the large-scale collection of monocytes/macrophages and granulocytes for these endocytic assays. Methodology/Principal Findings: Pooled zebrafish kidney hematopoietic tissues were used as a source of phagocytic cells for flow-cytometry based endocytic assays. FITC-Dextran, Lucifer Yellow and FITC-Edwardsiella ictaluri were used to evaluate selective and non-selective mechanisms of uptake in zebrafish phagocytes. Conclusions/Significance: Zebrafish kidney phagocytes characterized as monocytes/macrophages, neutrophils and lymphocytes utilize macropinocytosis and Ca 2+-dependant endocytosis mechanisms of antigen uptake. These cells do not appear to utilize a mannose receptor. Heat-killed Edwardsiella ictaluri induces cytoskeletal interactions for internalization in zebrafish kidney monocytes/macrophages and granulocytes. The proposed method is easy to implement and should prove especially useful in immunological, toxicological and epidemiological research
Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models
Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here
- β¦