70 research outputs found
ΠΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΌΠΎΠ΄ΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠ° Π‘ΡΠΏΠ΅ΡΡΡΠΈΠΌ Π² ΠΌΠ°Π»ΡΡ Π΄ΠΎΠ·Π°Ρ Π½Π° ΡΡΠ°ΠΏΠ΅ Π°Π΄Π°ΠΏΡΠ°ΡΠΈΠΈ ΠΌΠΈΠΊΡΠΎΡΠ°ΡΡΠ΅Π½ΠΈΠΉ ΠΆΠΈΠΌΠΎΠ»ΠΎΡΡΠΈ (Lonicera L.) ΠΏΠΎΠ΄ΡΠ΅ΠΊΡΠΈΠΈ ΡΠΈΠ½Π΅ΠΉ (Caeruleae Rehd.) ΠΊ Π½Π΅ΡΡΠ΅ΡΠΈΠ»ΡΠ½ΡΠΌ ΡΡΠ»ΠΎΠ²ΠΈΡΠΌ Ρ ΡΡΠ΅ΡΠΎΠΌ ΠΏΠΎΡΠ»Π΅Π΄Π΅ΠΉΡΡΠ²ΠΈΡ Π½Π° ΡΡΠ°ΠΏΠ΅ Π΄ΠΎΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ
Relevance. In recent years, interest in the edible honeysuckle culture has increased in Russia, the wide distribution of which is hampered by the lack of quality planting material. The technology of clonal micropropagation allows for a short time to obtain a large amount of honeysuckle planting material, more than a thousand regenerated plants per year from one meristematic apex introduced into an in vitro culture. It is hundreds of times more than in traditional methods of vegetative propagation. Adaptation to non-sterile conditions is the final and most crucial stage of clonal micropropagation, the loss of which can be from 50 to 90%. It should be noted that there is practically no research on how the further development of adapted honeysuckle plants takes place during subsequent growing.Methods. Researching of growth regulators of the new generation Superstim 1 and Superstim 2 effect in low and ultra-low doses on the survival rates and development of honeysuckle plants at the stages of adaptation subsequent growing.Results. Superstim 1 is more effective at physiological concentrations β 1 x 10-7 and in the field of ultra-low doses β 1 x 10-14, 1 x 10-15%. At the stage of subsequent growing, a positive after-effect of physiological concentrations β 1x10-3 and 1x10-7 was observed, and an ultra-low dose β 1x10-17%. The growth regulator Superstim 2 at the stages of adaptation and subsequent growing is effectively used only in one concentration β 1x10-16%. The additional foliar treatments at the stage of subsequent growing are not necessary.Β ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ. Π ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΠ΅ Π³ΠΎΠ΄Ρ Π² Π ΠΎΡΡΠΈΠΈ ΡΠ²Π΅Π»ΠΈΡΠΈΠ²Π°Π΅ΡΡΡ ΠΈΠ½ΡΠ΅ΡΠ΅Ρ ΠΊ ΠΊΡΠ»ΡΡΡΡΠ΅ ΠΆΠΈΠΌΠΎΠ»ΠΎΡΡΠΈ ΡΡΠ΅Π΄ΠΎΠ±Π½ΠΎΠΉ, ΡΠΈΡΠΎΠΊΠΎΠ΅ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΠ΅ ΠΊΠΎΡΠΎΡΠΎΠΉ ΡΠ΄Π΅ΡΠΆΠΈΠ²Π°Π΅ΡΡΡ ΠΈΠ·-Π·Π° Π΄Π΅ΡΠΈΡΠΈΡΠ° ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΡΠ°Π΄ΠΎΡΠ½ΠΎΠ³ΠΎ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π°. Π’Π΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡ ΠΊΠ»ΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΈΠΊΡΠΎΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ Π·Π° ΠΊΠΎΡΠΎΡΠΊΠΈΠΉ ΡΡΠΎΠΊ ΠΏΠΎΠ»ΡΡΠΈΡΡ Π±ΠΎΠ»ΡΡΠΎΠ΅ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΠΏΠΎΡΠ°Π΄ΠΎΡΠ½ΠΎΠ³ΠΎ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π° ΠΆΠΈΠΌΠΎΠ»ΠΎΡΡΠΈ, Π±ΠΎΠ»Π΅Π΅ ΡΡΡΡΡΠΈ ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ-ΡΠ΅Π³Π΅Π½Π΅ΡΠ°Π½ΡΠΎΠ² Π² Π³ΠΎΠ΄ ΠΈΠ· ΠΎΠ΄Π½ΠΎΠ³ΠΎ Π²Π²Π΅Π΄Π΅Π½Π½ΠΎΠ³ΠΎ Π² ΠΊΡΠ»ΡΡΡΡΡ in vitro ΠΌΠ΅ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°ΠΏΠ΅ΠΊΡΠ°, ΡΡΠΎ Π² ΡΠΎΡΠ½ΠΈ ΡΠ°Π· Π±ΠΎΠ»ΡΡΠ΅, ΡΠ΅ΠΌ ΠΏΡΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠΈ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π²Π΅Π³Π΅ΡΠ°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½ΠΈΡ. ΠΠ΄Π°ΠΏΡΠ°ΡΠΈΡ ΠΊ Π½Π΅ΡΡΠ΅ΡΠΈΠ»ΡΠ½ΡΠΌ ΡΡΠ»ΠΎΠ²ΠΈΡΠΌ ΡΠ²Π»ΡΠ΅ΡΡΡ Π·Π°ΠΊΠ»ΡΡΠΈΡΠ΅Π»ΡΠ½ΡΠΌ ΠΈ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΡΠΌ ΡΡΠ°ΠΏΠΎΠΌ ΠΊΠ»ΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΈΠΊΡΠΎΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½ΠΈΡ, ΠΏΠΎΡΠ΅ΡΠΈ Π½Π° ΠΊΠΎΡΠΎΡΠΎΠΌ ΠΌΠΎΠ³ΡΡ ΡΠΎΡΡΠ°Π²Π»ΡΡΡ ΠΎΡ 50 Π΄ΠΎ 90% ΠΌΠ΅ΡΠΈΠΊΠ»ΠΎΠ½ΠΎΠ². Π‘Π»Π΅Π΄ΡΠ΅Ρ ΠΎΡΠΌΠ΅ΡΠΈΡΡ, ΡΡΠΎ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ Π½Π΅Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΠΎ ΡΠΎΠΌ, ΠΊΠ°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ ΠΏΡΠΎΠΈΡΡ
ΠΎΠ΄ΠΈΡ Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠ΅Π΅ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ Π°Π΄Π°ΠΏΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ ΠΆΠΈΠΌΠΎΠ»ΠΎΡΡΠΈ ΠΏΡΠΈ Π΄ΠΎΡΠ°ΡΠΈΠ²Π°Π½ΠΈΠΈ.ΠΠ΅ΡΠΎΠ΄ΠΈΠΊΠ°. ΠΡΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ Π²Π»ΠΈΡΠ½ΠΈΡ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠΎΠ² Π½ΠΎΠ²ΠΎΠ³ΠΎ ΠΏΠΎΠΊΠΎΠ»Π΅Π½ΠΈΡ Π‘ΡΠΏΠ΅ΡΡΡΠΈΠΌ 1 ΠΈ Π‘ΡΠΏΠ΅ΡΡΡΠΈΠΌ 2 Π² ΠΌΠ°Π»ΡΡ
ΠΈ ΡΠ²Π΅ΡΡ
ΠΌΠ°Π»ΡΡ
Π΄ΠΎΠ·Π°Ρ
Π½Π° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ ΠΏΡΠΈΠΆΠΈΠ²Π°Π΅ΠΌΠΎΡΡΠΈ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ ΠΆΠΈΠΌΠΎΠ»ΠΎΡΡΠΈ Π½Π° ΡΡΠ°ΠΏΠ°Ρ
Π°Π΄Π°ΠΏΡΠ°ΡΠΈΠΈ ΠΈ Π΄ΠΎΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΡΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΠΏΡΠ΅ΠΏΠ°ΡΠ°Ρ Π‘ΡΠΏΠ΅ΡΡΡΠΈΠΌ 1 Π±ΠΎΠ»Π΅Π΅ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π΅Π½ Π² ΡΠΈΠ·ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ β 1x10-7% ΠΈ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΡΠ²Π΅ΡΡ
ΠΌΠ°Π»ΡΡ
Π΄ΠΎΠ· β 1x10-14, 1x10-15%. ΠΠ° ΡΡΠ°ΠΏΠ΅ Π΄ΠΎΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ Π²ΡΡΠ²Π»Π΅Π½ΠΎ ΠΏΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎΠ΅ ΠΏΠΎΡΠ»Π΅Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ ΡΠΈΠ·ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΉ β 1x10-3, 1x10-7%, ΠΈ ΡΠ²Π΅ΡΡ
ΠΌΠ°Π»ΠΎΠΉ Π΄ΠΎΠ·Ρ β 1x10-17%. ΠΡΠ΅ΠΏΠ°ΡΠ°Ρ Π‘ΡΠΏΠ΅ΡΡΡΠΈΠΌ 2 Π½Π° ΡΡΠ°ΠΏΠ°Ρ
Π°Π΄Π°ΠΏΡΠ°ΡΠΈΠΈ ΠΈ Π΄ΠΎΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎ ΠΏΡΠΈΠΌΠ΅Π½ΡΡΡ ΡΠΎΠ»ΡΠΊΠΎ Π² ΠΎΠ΄Π½ΠΎΠΉ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ β 1x10-16%. Π Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ
Π½Π΅ΠΊΠΎΡΠ½Π΅Π²ΡΡ
ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠ°Ρ
Π½Π° ΡΡΠ°ΠΏΠ΅ Π΄ΠΎΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ Π½Π΅Ρ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΠΈ.
ΠΠ΅ΡΠ΅Π·ΠΎΠ½Π½ΠΎΠ΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²ΠΎ ΡΠ³ΠΎΠ΄Π½ΠΎΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠΈ ΠΌΠ°Π»ΠΈΠ½Ρ ΠΊΡΠ°ΡΠ½ΠΎΠΉ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ ΠΎΡΠ°ΠΏΠ»ΠΈΠ²Π°Π΅ΠΌΡΡ Π·ΠΈΠΌΠ½ΠΈΡ ΡΠ΅ΠΏΠ»ΠΈΡ
Relevance. Currently, in many countries of the world, the production of non-season raspberry berry products has become widespread. Recently, interest in this technology has arisen in Russia, which has great prospects for the development of industrial gardening. In our opinion, it is promising to develop elements of technology for the non-seasonal production of red raspberries, propagated by the method of clonal micropropagation with a traditional and remontant type of fruiting in the conditions of winter heated greenhouses.Material and methods. The experiments were carried out in the laboratory of clonal micropropagation of garden plants in the fruit growing laboratory of RGAU-MSHA named after K.A. Timiryazev. The objects of research were varieties of red raspberries with a traditional (variety Volnitsa) and remontant (varieties Orangevoe Chudo and Bryanskoe Divo) type of fruiting. The experimental plants were propagated by the method of clonal micropropagation and grown before distillation in open and protected ground; plants propagated by root offspring served as control. Experimental plants were planted in open ground for growing in mid-May, in mid-October they were transplanted into 10 liter containers and transferred to protected ground conditions. Then put in the refrigerator compartment with a temperature of + 1 ... + 5Β°C. For distillation, the raspberry repairing plants were exposed in the winter heated greenhouse on January 20, while the shoots of replacing the aboveground system were normalized: without normalization, 3 shoots per plant, complete pruning of the aboveground system. Raspberries with a traditional type of fruiting were exposed in a winter heated greenhouse in three periods on January 20, February 10, March 2. Accounting for the passage of the phenological phases of development and yield was made for 3 months every 5 days.Results. In the conditions of winter heated greenhouses, efficiency has been shown and elements of technology for non-season production of raspberry berries remontant and berries with a traditional type of fruiting, propagated in vitro and grown before open field distillation are developed. It was revealed that it is necessary to normalize the shoots before distillation of raspberry remontant, and the optimal timing for the start of distillation for raspberries with a traditional type of fruiting has been established.ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ. Π Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ Π²ΠΎ ΠΌΠ½ΠΎΠ³ΠΈΡ
ΡΡΡΠ°Π½Π°Ρ
ΠΌΠΈΡΠ° ΡΠΈΡΠΎΠΊΠΎΠ΅ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΠ΅ ΠΏΠΎΠ»ΡΡΠΈΠ»ΠΎ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²ΠΎ Π½Π΅ΡΠ΅Π·ΠΎΠ½Π½ΠΎΠΉ ΡΠ³ΠΎΠ΄Π½ΠΎΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠΈ ΠΌΠ°Π»ΠΈΠ½Ρ. Π ΠΏΠΎΡΠ»Π΅Π΄Π½Π΅Π΅ Π²ΡΠ΅ΠΌΡ ΠΈΠ½ΡΠ΅ΡΠ΅Ρ ΠΊ Π΄Π°Π½Π½ΠΎΠΉ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π²ΠΎΠ·Π½ΠΈΠΊ ΠΈ Π² Π ΠΎΡΡΠΈΠΈ, ΡΡΠΎ ΠΈΠΌΠ΅Π΅Ρ Π±ΠΎΠ»ΡΡΠΈΠ΅ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Ρ Π΄Π»Ρ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°Π΄ΠΎΠ²ΠΎΠ΄ΡΡΠ²Π°. ΠΠ° Π½Π°Ρ Π²Π·Π³Π»ΡΠ΄, ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΠΎ ΡΠ°Π·ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡ ΡΠ»Π΅ΠΌΠ΅Π½ΡΡ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π½Π΅ΡΠ΅Π·ΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π° ΡΠ³ΠΎΠ΄ ΠΌΠ°Π»ΠΈΠ½Ρ ΠΊΡΠ°ΡΠ½ΠΎΠΉ, ΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΊΠ»ΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΈΠΊΡΠΎΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½ΠΈΡ Ρ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΡΠΌ ΠΈ ΡΠ΅ΠΌΠΎΠ½ΡΠ°Π½ΡΠ½ΡΠΌ ΡΠΈΠΏΠΎΠΌ ΠΏΠ»ΠΎΠ΄ΠΎΠ½ΠΎΡΠ΅Π½ΠΈΡ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
Π·ΠΈΠΌΠ½ΠΈΡ
ΠΎΡΠ°ΠΏΠ»ΠΈΠ²Π°Π΅ΠΌΡΡ
ΡΠ΅ΠΏΠ»ΠΈΡ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ°. ΠΠΏΡΡΡ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Π² Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠΈΠΈ ΠΊΠ»ΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΈΠΊΡΠΎΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½ΠΈΡ ΡΠ°Π΄ΠΎΠ²ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠΈΠΈ ΠΏΠ»ΠΎΠ΄ΠΎΠ²ΠΎΠ΄ΡΡΠ²Π° Π ΠΠΠ£-ΠΠ‘Π₯Π ΠΈΠΌ. Π.Π. Π’ΠΈΠΌΠΈΡΡΠ·Π΅Π²Π°. ΠΠ±ΡΠ΅ΠΊΡΠ°ΠΌΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΡΠ»ΡΠΆΠΈΠ»ΠΈ ΡΠΎΡΡΠ° ΠΌΠ°Π»ΠΈΠ½Ρ ΠΊΡΠ°ΡΠ½ΠΎΠΉ Ρ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΡΠΌ (ΡΠΎΡΡ ΠΠΎΠ»ΡΠ½ΠΈΡΠ°) ΠΈ ΡΠ΅ΠΌΠΎΠ½ΡΠ°Π½ΡΠ½ΡΠΌ (ΡΠΎΡΡΠ° ΠΡΠ°Π½ΠΆΠ΅Π²ΠΎΠ΅ ΡΡΠ΄ΠΎ ΠΈ ΠΡΡΠ½ΡΠΊΠΎΠ΅ Π΄ΠΈΠ²ΠΎ) ΡΠΈΠΏΠΎΠΌ ΠΏΠ»ΠΎΠ΄ΠΎΠ½ΠΎΡΠ΅Π½ΠΈΡ. ΠΠΏΡΡΠ½ΡΠ΅ ΡΠ°ΡΡΠ΅Π½ΠΈΡ Π±ΡΠ»ΠΈ ΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΊΠ»ΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΈΠΊΡΠΎΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½ΠΈΡ ΠΈ Π²ΡΡΠ°ΡΠ΅Π½Ρ ΠΏΠ΅ΡΠ΅Π΄ Π²ΡΠ³ΠΎΠ½ΠΊΠΎΠΉ Π² ΠΎΡΠΊΡΡΡΠΎΠΌ ΠΈ Π·Π°ΡΠΈΡΠ΅Π½Π½ΠΎΠΌ Π³ΡΡΠ½ΡΠ΅, ΠΊΠΎΠ½ΡΡΠΎΠ»Π΅ΠΌ ΡΠ»ΡΠΆΠΈΠ»ΠΈ ΡΠ°ΡΡΠ΅Π½ΠΈΡ, ΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½Π½ΡΠ΅ ΠΊΠΎΡΠ½Π΅Π²ΡΠΌΠΈ ΠΎΡΠΏΡΡΡΠΊΠ°ΠΌΠΈ. Π ΠΎΡΠΊΡΡΡΡΠΉ Π³ΡΡΠ½Ρ ΡΠ°ΡΡΠ΅Π½ΠΈΡ Π±ΡΠ»ΠΈ Π²ΡΡΠ°ΠΆΠ΅Π½Ρ Π² ΡΠ΅ΡΠ΅Π΄ΠΈΠ½Π΅ ΠΌΠ°Ρ, Π² ΡΠ΅ΡΠ΅Π΄ΠΈΠ½Π΅ ΠΎΠΊΡΡΠ±ΡΡ ΠΈΡ
ΠΏΠ΅ΡΠ΅ΡΠ°Π΄ΠΈΠ»ΠΈ Π² ΠΊΠΎΠ½ΡΠ΅ΠΉΠ½Π΅ΡΡ ΠΎΠ±ΡΠ΅ΠΌΠΎΠΌ 10 Π» ΠΈ ΠΏΠ΅ΡΠ΅Π½Π΅ΡΠ»ΠΈ Π² ΡΡΠ»ΠΎΠ²ΠΈΡ Π·Π°ΡΠΈΡΠ΅Π½Π½ΠΎΠ³ΠΎ Π³ΡΡΠ½ΡΠ°. ΠΠ°ΡΠ΅ΠΌ Π²ΡΡΡΠ°Π²ΠΈΠ»ΠΈ Π² Ρ
ΠΎΠ»ΠΎΠ΄ΠΈΠ»ΡΠ½ΡΠΉ ΠΎΡΡΠ΅ΠΊ Ρ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠΎΠΉ 1β¦5Β°C. ΠΠ»Ρ Π²ΡΠ³ΠΎΠ½ΠΊΠΈ ΡΠ°ΡΡΠ΅Π½ΠΈΡ ΠΌΠ°Π»ΠΈΠ½Ρ ΡΠ΅ΠΌΠΎΠ½ΡΠ°Π½ΡΠ½ΠΎΠΉ Π²ΡΡΡΠ°Π²Π»ΡΠ»ΠΈ Π² Π·ΠΈΠΌΠ½ΡΡ ΠΎΡΠ°ΠΏΠ»ΠΈΠ²Π°Π΅ΠΌΡΡ ΡΠ΅ΠΏΠ»ΠΈΡΡ 20 ΡΠ½Π²Π°ΡΡ, ΠΏΡΠΈ ΡΡΠΎΠΌ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΠ»ΠΈ Π½ΠΎΡΠΌΠΈΡΠΎΠ²ΠΊΡ ΠΏΠΎΠ±Π΅Π³ΠΎΠ² Π·Π°ΠΌΠ΅ΡΠ΅Π½ΠΈΡ Π½Π°Π΄Π·Π΅ΠΌΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ: Π±Π΅Π· Π½ΠΎΡΠΌΠΈΡΠΎΠ²ΠΊΠΈ, 3 ΠΏΠΎΠ±Π΅Π³Π° Π½Π° ΡΠ°ΡΡΠ΅Π½ΠΈΠ΅, ΠΏΠΎΠ»Π½Π°Ρ ΠΎΠ±ΡΠ΅Π·ΠΊΠ° Π½Π°Π΄Π·Π΅ΠΌΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ. ΠΠ°Π»ΠΈΠ½Ρ Ρ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΡΠΌ ΡΠΈΠΏΠΎΠΌ ΠΏΠ»ΠΎΠ΄ΠΎΠ½ΠΎΡΠ΅Π½ΠΈΡ Π²ΡΡΡΠ°Π²Π»ΡΠ»ΠΈ Π² Π·ΠΈΠΌΠ½ΡΡ ΠΎΡΠ°ΠΏΠ»ΠΈΠ²Π°Π΅ΠΌΡΡ ΡΠ΅ΠΏΠ»ΠΈΡΡ Π² ΡΡΠΈ ΡΡΠΎΠΊΠ° 20 ΡΠ½Π²Π°ΡΡ, 10 ΡΠ΅Π²ΡΠ°Π»Ρ, 2 ΠΌΠ°ΡΡΠ°. Π£ΡΠ΅ΡΡ ΠΏΡΠΎΡ
ΠΎΠΆΠ΄Π΅Π½ΠΈΡ ΡΠ΅Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ°Π· ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΈ ΠΏΠΎΡΡΡΠΏΠ»Π΅Π½ΠΈΡ ΡΡΠΎΠΆΠ°Ρ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΠ»ΠΈ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ 3 ΠΌΠ΅ΡΡΡΠ΅Π² ΡΠ΅ΡΠ΅Π· ΠΊΠ°ΠΆΠ΄ΡΠ΅ 5 Π΄Π½Π΅ΠΉ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. Π ΡΡΠ»ΠΎΠ²ΠΈΡΡ
Π·ΠΈΠΌΠ½ΠΈΡ
ΠΎΡΠ°ΠΏΠ»ΠΈΠ²Π°Π΅ΠΌΡΡ
ΡΠ΅ΠΏΠ»ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°Π½Π° ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Ρ ΡΠ»Π΅ΠΌΠ΅Π½ΡΡ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π½Π΅ΡΠ΅Π·ΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π° ΡΠ³ΠΎΠ΄ ΠΌΠ°Π»ΠΈΠ½Ρ ΡΠ΅ΠΌΠΎΠ½ΡΠ°Π½ΡΠ½ΠΎΠΉ ΠΈ Ρ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΡΠΌ ΡΠΈΠΏΠΎΠΌ ΠΏΠ»ΠΎΠ΄ΠΎΠ½ΠΎΡΠ΅Π½ΠΈΡ, ΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ΅Π½Π½ΡΡ
in vitro ΠΈ Π²ΡΡΠ°ΡΠ΅Π½Π½ΡΡ
ΠΏΠ΅ΡΠ΅Π΄ Π²ΡΠ³ΠΎΠ½ΠΊΠΎΠΉ Π² ΠΎΡΠΊΡΡΡΠΎΠΌ Π³ΡΡΠ½ΡΠ΅. ΠΡΡΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΠΏΡΠΎΠ²Π΅ΡΡΠΈ Π½ΠΎΡΠΌΠΈΡΠΎΠ²ΠΊΡ ΠΏΠΎΠ±Π΅Π³ΠΎΠ² ΠΏΠ΅ΡΠ΅Π΄ Π²ΡΠ³ΠΎΠ½ΠΊΠΎΠΉ ΠΌΠ°Π»ΠΈΠ½Ρ ΡΠ΅ΠΌΠΎΠ½ΡΠ°Π½ΡΠ½ΠΎΠΉ ΠΈ ΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½Ρ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ ΡΡΠΎΠΊΠΈ Π½Π°ΡΠ°Π»Π° Π²ΡΠ³ΠΎΠ½ΠΊΠΈ Π΄Π»Ρ ΠΌΠ°Π»ΠΈΠ½Ρ Ρ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΡΠΌ ΡΠΈΠΏΠΎΠΌ ΠΏΠ»ΠΎΠ΄ΠΎΠ½ΠΎΡΠ΅Π½ΠΈΡ
EEG Microstate Analysis in Drug-Naive Patients with Panic Disorder
Patients with panic disorder (PD) have a bias to respond to normal stimuli in a fearful way. This may be due to the preactivation of fear-associated networks prior to stimulus perception. Based on EEG, we investigated the difference between patients with PD and normal controls in resting state activity using features of transiently stable brain states (microstates). EEGs from 18 drug-naive patients and 18 healthy controls were analyzed. Microstate analysis showed that one class of microstates (with a right-anterior to left-posterior orientation of the mapped field) displayed longer durations and covered more of the total time in the patients than controls. Another microstate class (with a symmetric, anterior-posterior orientation) was observed less frequently in the patients compared to controls. The observation that selected microstate classes differ between patients with PD and controls suggests that specific brain functions are altered already during resting condition. The altered resting state may be the starting point of the observed dysfunctional processing of phobic stimuli
The Gene Ontology knowledgebase in 2023
The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project
The Gene Ontology resource: enriching a GOld mine
The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations
DESCRIPTION OF THE REPRESENTATIONS OF THE ALGEBRAS GENERATED BY FOUR LINEARLY RELATED IDEMPOTENTS
Electrochemistry of vanadocene dichloride in tetrahydrofuran and general scheme of the electroreduction of metallocene dichlorides of subgroups IVB-VIB
Three-dimensional numerical simulation of tsunami waves based on the navier-stokes equations
A numerical algorithm of solving the three-dimensional system of Navier-Stokes equations to simulate free surface waves and flows with gravity is presented. The main problem here is to ensure that the gravity force is properly accounted in the presence of discontinuities in the medium density. The task is made more complicated due the use of unstructured computational grids with collocated placement of unknown quantities and splitting algorithms based on SIMPLE-type methods. To obtain correctly the hydrostatic pressure, it is suggested that the contribution of the gravitational force in the equation for pressure should be distinguished explicitly; the latter being calculated by using the solution of the two-phase medium gravitational balance problem. To ensure the balance of the gravity force and the pressure gradient in the case of rest an algorithm in which the pressure gradient in the equation of motion is replaced by a modification considering the gravitational force action is suggested. This method is demonstrated by the example of tsunami wave propagation in the real water area of the World Ocean. Β© 2017 - TSUNAMI SOCIETY INTERNATIONAL
Computer technology of the thermal stress state and fatigue life analysis of turbine engine exhaust support frames
An advanced computer technology of the thermal stress state and fatigue life analysis of turbine engine exhaust support frames based on the use of licensed engineering analysis software, as well as some specialized home codes are presented in the paper. The developed technology allows perform simulations for the full model of the structure, not only for the typical fragments models, and increase an accuracy of calculations and significantly reduce a design time
Three-dimensional numerical simulation of tsunami waves based on the navier-stokes equations
A numerical algorithm of solving the three-dimensional system of Navier-Stokes equations to simulate free surface waves and flows with gravity is presented. The main problem here is to ensure that the gravity force is properly accounted in the presence of discontinuities in the medium density. The task is made more complicated due the use of unstructured computational grids with collocated placement of unknown quantities and splitting algorithms based on SIMPLE-type methods. To obtain correctly the hydrostatic pressure, it is suggested that the contribution of the gravitational force in the equation for pressure should be distinguished explicitly; the latter being calculated by using the solution of the two-phase medium gravitational balance problem. To ensure the balance of the gravity force and the pressure gradient in the case of rest an algorithm in which the pressure gradient in the equation of motion is replaced by a modification considering the gravitational force action is suggested. This method is demonstrated by the example of tsunami wave propagation in the real water area of the World Ocean. Β© 2017 - TSUNAMI SOCIETY INTERNATIONAL
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