2,139 research outputs found
Automatic Look-Up Table Based Real-Time Phase Unwrapping for Phase Measuring Profilometry and Optimal Reference Frequency Selection
For temporal phase unwrapping in phase measuring profilometry, it has recently been reported that two phases with co-prime frequencies can be absolutely unwrapped using a look-up table; however, frequency selection and table construction has been performed manually without optimization. In this paper, a universal phase unwrapping method is proposed to unwrap phase flexibly and automatically by using geometric analysis, and thus we can programmatically build a one-dimensional or two-dimensional look-up table for arbitrary two co-prime frequencies to correctly unwrap phases in real time. Moreover, a phase error model related to the defocus effect is derived to figure out an optimal reference frequency co-prime to the principal frequency. Experimental results verify the correctness and computational efficiency of the proposed method
Universal Phase Unwrapping for Phase Measuring Profilometry Using Geometry Analysis
Traditionally temporal phase unwrapping for phase measuring profilometry needs to employ the phase computed from unit-frequency patterned images; however, it has recently been reported that two phases with co-prime frequencies can be absolutely unwrapped each other. However, a manually man-made look-up table for two known frequencies has to be used for correctly unwrapping phases. If two co-prime frequencies are changed, the look-up table has to be manually rebuilt. In this paper, a universal phase unwrapping algorithm is proposed to unwrap phase flexibly and automatically. The basis of the proposed algorithm is converting a signal-processing problem into a geometric analysis one. First, we normalize two wrapped phases such that they are of the same needed slope. Second, by using the modular operation, we unify the integer-valued difference of the two normalized phases over each wrapping interval. Third, by analyzing the properties of the uniform difference mathematically, we can automatically build a look-up table to record the corresponding correct orders for all wrapping intervals. Even if the frequencies are changed, the look-up table will be automatically updated for the latest involved frequencies. Finally, with the order information stored in the look-up table, the wrapped phases can be correctly unwrapped. Both simulations and experimental results verify the correctness of the proposed algorithm
Proteomic biomarkers of the apnea hypopnea index and obstructive sleep apnea: Insights into the pathophysiology of presence, severity, and treatment response
Obstructive sleep apnea (OSA), a disease associated with excessive sleepiness and increased cardiovascular risk, affects an estimated 1 billion people worldwide. The present study examined proteomic biomarkers indicative of presence, severity, and treatment response in OSA. Participants
ΠΠ±Π»ΡΠΊ Π·ΠΌΡΠ½ΠΈ ΠΏΠ»ΠΎΡ Π»ΡΡΠΎΠ²ΠΈΡ ΡΠ³ΡΠ΄Ρ Ρ ΡΡΡΡΠΊΡΡΡΡ Π·Π΅ΠΌΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΎΠ½Π΄Ρ Π·Π° Ρ Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ°ΠΌΠΈ ΡΡΠΏΡΡΠ½ΠΈΠΊΠΎΠ²ΠΎΠ³ΠΎ Π·Π½ΡΠΌΠΊΠ°
Using the example of a mountainous cultivated land environment, we have shown the use of Earth Remote Sensing Data (ERS) technology to control the change of forest land area due to their being cut down. The footage of the Quick Bird satellite image has been used for a simulation of the change in the forest area structure from "forest land" to "deforestation" in which the forest land area shifts into the cut down (deforested) area. It is proved that the histogram characteristics of the RGB Quick Bird satellite image contain information on changes in forest land are structure from "forest land" to "deforestation". It is shown that the median size of the RGB histogram responds to the change in the area of the forest land. The most sensitive out of all RGB channels to changing area dynamics is the channel Green. Physical explanation of this process is carried out using the test fragments "forest land" and "deforestation". We have found out that due to the different texture of the "forest land" and "deforestation" images, their histogram characteristics, the zones of pixel placement, differ in brightness. In the fragment "forest land" the majority of pixels in the histogram is concentrated in the range of 0β100, while for the fragment "deforestation" it shifts to the right to a range of 100β200. Mean square deviation (MSD) β 24 gives a more homogeneous texture of the deforestation, as it creates a graph with a clearly expressive extremum that becomes more and more visible as the cutting down spreads. An analytical dependence between the dynamics of the areas ΞS change at the boundary between "forest land" and "deforestation" and the number of pixels ΞN per the extremum, is obtained. Its considerably high sensitivity has been shown which allows solving the problems of recording the change of forest land areas in the land resource structure using the characteristics of satellite imagery.ΠΠ° ΠΏΡΠΈΠΊΠ»Π°Π΄Ρ Π³ΡΡΡΡΠΊΠΎΠ³ΠΎ Π°Π³ΡΠΎΠ»Π°Π½Π΄ΡΠ°ΡΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΠ° ΠΏΠΎΠΊΠ°Π·Π°Π½ΠΎ Π·Π°ΡΡΠΎΡΡΠ²Π°Π½Π½Ρ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΡΡ Π΄ΠΈΡΡΠ°Π½ΡΡΠΉΠ½ΠΎΠ³ΠΎ Π·ΠΎΠ½Π΄ΡΠ²Π°Π½Π½Ρ ΠΠ΅ΠΌΠ»Ρ (ΠΠΠ) Π΄ΠΎ ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ Π·ΠΌΡΠ½ΠΈ ΠΏΠ»ΠΎΡ Π»ΡΡΠΎΠ²ΠΈΡ
ΡΠ³ΡΠ΄Ρ ΡΠ΅ΡΠ΅Π· ΡΡ
Π²ΠΈΡΡΠ±ΡΠ²Π°Π½Π½Ρ. ΠΠ° ΠΏΡΠ΄ΡΡΠ°Π²Ρ ΡΡΠΏΡΡΠ½ΠΈΠΊΠΎΠ²ΠΎΠ³ΠΎ Π·Π½ΡΠΌΠΊΠ° QuickBird Π·Π΄ΡΠΉΡΠ½Π΅Π½ΠΎ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ Π²ΠΈΡΡΠ±ΠΎΠΊ Π»ΡΡΠΎΠ²ΠΈΡ
ΡΠ³ΡΠ΄Ρ Ρ ΠΎΡΡΠΈΠΌΠ°Π½ΠΎ Π·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½Π½Ρ ΡΠ΅ΡΠΈΡΠΎΡΡΠΉ Π· ΡΡΠ·Π½ΠΈΠΌΠΈ Π·ΠΎΠ½Π°ΠΌΠΈ Π²ΠΈΡΡΠ±ΠΎΠΊ. ΠΠΌΡΠ½ΠΈ Ρ ΡΡΡΡΠΊΡΡΡΡ ΠΏΠ»ΠΎΡ Π»ΡΡΠΎΠ²ΠΈΡ
ΡΠ³ΡΠ΄Ρ Π²ΡΠ΄Π±ΡΠ²Π°ΡΡΡΡΡ ΡΠΏΠΎΡΠΎΠ±ΠΎΠΌ ΠΏΠ΅ΡΠ΅ΠΌΡΡΠ΅Π½Π½Ρ Π»ΡΠ½ΡΡ ΡΠΎΠ·ΠΌΠ΅ΠΆΡΠ²Π°Π½Π½Ρ "Π»ΡΡΠΎΠ²ΠΈΠΉ ΠΏΠΎΠΊΡΠΈΠ² β Π²ΠΈΡΡΠ±ΠΊΠ°", Π·Π° ΡΠΊΠΎΠ³ΠΎ ΠΏΠ»ΠΎΡΡ Π· Π»ΡΡΠΎΠ²ΠΎΠ³ΠΎ ΠΏΠΎΠΊΡΠΈΠ²Ρ ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄ΡΡΡ Π΄ΠΎ Π·ΠΎΠ½ΠΈ Π²ΠΈΡΡΠ±ΠΎΠΊ. ΠΠΎΠ²Π΅Π΄Π΅Π½ΠΎ, ΡΠΎ Π³ΡΡΡΠΎΠ³ΡΠ°ΠΌΠ½Ρ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ RGB ΡΡΠΏΡΡΠ½ΠΈΠΊΠΎΠ²ΠΎΠ³ΠΎ Π·Π½ΡΠΌΠΊΠ° QuickBird ΠΌΠ°ΡΡΡ ΡΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΡΡΡΡ ΠΏΡΠΎ Π·ΠΌΡΠ½ΠΈ ΠΏΠ»ΠΎΡ Ρ ΡΡΡΡΠΊΡΡΡΡ "Π»ΡΡΠΎΠ²ΠΈΠΉ ΠΏΠΎΠΊΡΠΈΠ² β Π²ΠΈΡΡΠ±ΠΊΠ°". ΠΠΎΠΊΠ°Π·Π°Π½ΠΎ, ΡΠΎ Π²Π΅Π»ΠΈΡΠΈΠ½ΠΈ ΠΌΠ΅Π΄ΡΠ°Π½ ΡΡΡΡ
RGB-ΠΊΠ°Π½Π°Π»ΡΠ² ΠΎΠ΄Π½ΠΎΠ·Π½Π°ΡΠ½ΠΎ ΡΠ΅Π°Π³ΡΡΡΡ Π½Π° Π·ΠΌΡΠ½ΠΈ ΠΏΠ»ΠΎΡ Π»ΡΡΠΎΠ²ΠΎΠ³ΠΎ ΠΏΠΎΠΊΡΠΎΠ²Ρ. ΠΠ°ΠΉΠ±ΡΠ»ΡΡ ΡΡΡΠ»ΠΈΠ²ΠΈΠΌ Π΄ΠΎ Π΄ΠΈΠ½Π°ΠΌΡΠΊΠΈ Π·ΠΌΡΠ½ΠΈ ΠΏΠ»ΠΎΡ Π· ΡΡΡΡ
RGB-ΠΊΠ°Π½Π°Π»ΡΠ² Ρ ΠΊΠ°Π½Π°Π» Green. Π€ΡΠ·ΠΈΡΠ½Π΅ ΠΏΠΎΡΡΠ½Π΅Π½Π½Ρ ΡΡΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡ Π·Π΄ΡΠΉΡΠ½Π΅Π½ΠΎ Π½Π° ΠΏΡΠ΄ΡΡΠ°Π²Ρ ΡΠ΅ΡΡΠΎΠ²ΠΈΡ
ΡΡΠ°Π³ΠΌΠ΅Π½ΡΡΠ² "Π»ΡΡΠΎΠ²ΠΈΠΉ ΠΏΠΎΠΊΡΠΈΠ²" Ρ "Π²ΠΈΡΡΠ±ΠΊΠ°". ΠΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΠΎ Π·Π°Π²Π΄ΡΠΊΠΈ ΡΡΠ·Π½ΡΠΉ ΡΠ΅ΠΊΡΡΡΡΡ "Π»ΡΡΠΎΠ²ΠΎΠ³ΠΎ ΠΏΠΎΠΊΡΠΎΠ²Ρ" Ρ "Π²ΠΈΡΡΠ±ΠΊΠΈ" ΡΡ
Π½Ρ Π³ΡΡΡΠΎΠ³ΡΠ°ΠΌΠ½Ρ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ Π²ΡΠ΄ΡΡΠ·Π½ΡΡΡΡΡΡ Π·ΠΎΠ½Π°ΠΌΠΈ ΡΠΎΠ·ΠΌΡΡΠ΅Π½Π½Ρ ΠΏΡΠΊΡΠ΅Π»ΡΠ² Π·Π° ΡΡΠΊΡΠ°Π²ΡΡΡΡ. ΠΠ»Ρ ΡΡΠ°Π³ΠΌΠ΅Π½ΡΡ "Π»ΡΡΠΎΠ²ΠΈΠΉ ΠΏΠΎΠΊΡΠΈΠ²" ΠΎΡΠ½ΠΎΠ²Π½Π° ΡΠ°ΡΡΠΈΠ½Π° ΠΏΡΠΊΡΠ΅Π»ΡΠ² Ρ Π³ΡΡΡΠΎΠ³ΡΠ°ΠΌΡ Π·ΠΎΡΠ΅ΡΠ΅Π΄ΠΆΠ΅Π½Π° Π² Π΄ΡΠ°ΠΏΠ°Π·ΠΎΠ½Ρ Π· ΠΊΠΎΠ΄ΠΎΠΌ 0β100, ΡΠΎΠ΄Ρ ΡΠΊ Π΄Π»Ρ ΡΡΠ°Π³ΠΌΠ΅Π½ΡΡ "Π²ΠΈΡΡΠ±ΠΊΠ°" Π²ΠΎΠ½Π° Π·ΠΌΡΡΡΡΡΡΡΡ Π²ΠΏΡΠ°Π²ΠΎ Π΄ΠΎ Π΄ΡΠ°ΠΏΠ°Π·ΠΎΠ½Ρ 100β200. ΠΡΠ»ΡΡ ΠΎΠ΄Π½ΠΎΡΡΠ΄Π½Π° ΡΠ΅ΠΊΡΡΡΡΠ° Π²ΠΈΡΡΠ±ΠΎΠΊ Π΄Π°Ρ Π‘ΠΠ 24, ΡΠΎ ΡΡΠ²ΠΎΡΡΡ Π³ΡΠ°ΡΡΠΊ ΡΠ· ΡΡΡΠΊΠΎ Π²ΠΈΡΠ°Π·Π½ΠΈΠΌ Π΅ΠΊΡΡΡΠ΅ΠΌΡΠΌΠΎΠΌ, ΡΠΊΠΈΠΉ ΡΡΠ°Ρ Π΄Π΅Π΄Π°Π»Ρ ΠΏΠΎΠΌΡΡΠ½ΡΡΠΈΠΌ ΡΠ· ΠΏΠΎΡΠΈΡΠ΅Π½Π½ΡΠΌ ΠΏΠ»ΠΎΡΡ Π²ΠΈΡΡΠ±ΠΎΠΊ. ΠΡΡΠΈΠΌΠ°Π½ΠΎ Π°Π½Π°Π»ΡΡΠΈΡΠ½Ρ Π·Π°Π»Π΅ΠΆΠ½ΡΡΡΡ ΠΌΡΠΆ Π΄ΠΈΠ½Π°ΠΌΡΠΊΠΎΡ Π·ΠΌΡΠ½ΠΈ ΠΏΠ»ΠΎΡ ΞS Π½Π° Π³ΡΠ°Π½ΠΈΡΡ "Π»ΡΡΠΎΠ²ΠΈΠΉ ΠΏΠΎΠΊΡΠΈΠ² β Π²ΠΈΡΡΠ±ΠΊΠ°" Ρ ΠΊΡΠ»ΡΠΊΠΎΡΡΡ ΠΏΡΠΊΡΠ΅Π»ΡΠ² NΠ΅ΠΊΡΡΡ, ΡΠΎ ΠΏΡΠΈΠΏΠ°Π΄Π°Ρ Π½Π° Π΅ΠΊΡΡΡΠ΅ΠΌΡΠΌ Π·Π° ΠΊΡΠ»ΡΠΊΡΡΡΡ ΠΏΡΠΊΡΠ΅Π»ΡΠ² Ρ Π΄ΡΠ°ΠΏΠ°Π·ΠΎΠ½Ρ Π³ΡΡΡΠΎΠ³ΡΠ°ΠΌΠΈ 100β200. ΠΠΎΠΊΠ°Π·Π°Π½ΠΎ ΡΡ Π΄ΠΎΡΡΠ°ΡΠ½ΡΠΎ Π²ΠΈΡΠΎΠΊΡ ΡΡΡΠ»ΠΈΠ²ΡΡΡΡ, ΡΠΎ Π΄Π°Ρ Π·ΠΌΠΎΠ³Ρ Π²ΠΈΡΡΡΡΠ²Π°ΡΠΈ Π·Π°Π΄Π°ΡΡ ΠΎΠ±Π»ΡΠΊΡ Π·ΠΌΡΠ½ΠΈ ΠΏΠ»ΠΎΡ Π»ΡΡΠΎΠ²ΠΈΡ
ΡΠ³ΡΠ΄Ρ Ρ ΡΡΡΡΠΊΡΡΡΡ Π·Π΅ΠΌΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΎΠ½Π΄Ρ Π·Π° Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ°ΠΌΠΈ ΡΡΠΏΡΡΠ½ΠΈΠΊΠΎΠ²ΠΎΠ³ΠΎ Π·Π½ΡΠΌΠΊΠ°
Mitofusin2 mutations disrupt axonal mitochondrial positioning and promote axon degeneration
Alterations in mitochondrial dynamics (fission, fusion and movement) are implicated in many neurodegenerative diseases, from rare genetic disorders such as Charcot-Marie-Tooth disease, to common conditions including Alzheimerβs disease. However, the relationship between altered mitochondrial dynamics and neurodegeneration is incompletely understood. Here we show that disease associated MFN2 proteins suppressed both mitochondrial fusion and transport, and produced classic features of segmental axonal degeneration without cell body death, including neurofilament filled swellings, loss of calcium homeostasis, and accumulation of reactive oxygen species. By contrast, depletion of Opa1 suppressed mitochondrial fusion while sparing transport, and did not induce axonal degeneration. Axon degeneration induced by mutant MFN2 proteins correlated with the disruption of the proper mitochondrial positioning within axons, rather than loss of overall mitochondrial movement, or global mitochondrial dysfunction. We also found that augmenting expression of MFN1 rescued the axonal degeneration caused by MFN2 mutants, suggesting a possible therapeutic strategy for Charcot-Marie-Tooth disease. These experiments provide evidence that the ability of mitochondria to sense energy requirements and localize properly within axons is key to maintaining axonal integrity, and may be a common pathway by which disruptions in axonal transport contribute to neurodegeneration
KINETIC CHARACTERISTICS OF CONVECTION DRYING PROCESS OF CAPILLARY-POROUS COLLOIDAL MATERIALS
ΠΠΈΠ·Π½Π°ΡΠ΅Π½ΠΎ, ΡΠΎ ΡΠΊΠ»Π°Π΄Π½ΡΡΡΡ ΡΠ΅ΠΏΠ»ΠΎΠΌΠ°ΡΠΎΠΎΠ±ΠΌΡΠ½Π½ΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΡΠ² Π΄Π΅ΡΠ΅Π²ΠΎΠΎΠ±ΡΠΎΠ±ΠΊΠΈ ΠΏΠΎΠ»ΡΠ³Π°Ρ ΡΠ°ΠΌΠ΅ Ρ ΡΠΊΠ»Π°Π΄Π½ΠΎΡΡΡ ΡΠ²ΠΈΡ ΠΏΠ΅ΡΠ΅Π½Π΅ΡΠ΅Π½Π½Ρ ΡΠ΅ΠΏΠ»ΠΎΡΠΈ Ρ Π²ΠΎΠ»ΠΎΠ³ΠΈ, ΡΠΊ Π²ΡΠ΅ΡΠ΅Π΄ΠΈΠ½Ρ ΠΌΠ°ΡΠ΅ΡΡΠ°Π»Ρ, ΡΠ°ΠΊ Ρ Π½Π° ΠΌΠ΅ΠΆΡ ΡΠΎΠ·ΠΏΠΎΠ΄ΡΠ»Ρ ΡΠ°Π· ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΠ΅ β ΡΠ²Π΅ΡΠ΄Π΅ ΡΡΠ»ΠΎ ΡΠ° ΡΠΊΠ»Π°Π΄Π½ΠΎΡΡΡ Π·ΠΌΡΠ½ΠΈ ΡΡΠ·ΠΈΠΊΠΎ-ΠΌΠ΅Ρ
Π°Π½ΡΡΠ½ΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ Π΄Π΅ΡΠ΅Π²ΠΈΠ½ΠΈ ΠΏΡΠ΄ ΡΠ°Ρ ΡΠ΅ΠΏΠ»ΠΎΠ²ΠΎΠ³ΠΎ ΠΎΠ±ΡΠΎΠ±Π»Π΅Π½Π½Ρ. ΠΠ° Π΄ΠΎΡΠ»ΡΠ΄Π½ΠΈΠΉ ΠΌΠ°ΡΠ΅ΡΡΠ°Π» ΠΏΡΠΈΠΉΠ½ΡΡΠΎ ΡΠΎΡΠ½ΠΎΠ²Ρ ΠΏΠΈΠ»ΠΎΠΌΠ°ΡΠ΅ΡΡΠ°Π»ΠΈ Π·Π°Π²ΡΠΎΠ²ΡΠΊΠΈ 40Β ΠΌΠΌ, ΡΠΊΡ Π²ΠΈΡΡΡΡΡΡΡ ΠΌ'ΡΠΊΠΈΠΌΠΈ ΡΠ΅ΠΆΠΈΠΌΠ°ΠΌΠΈ. Π ΠΎΡΠ½ΠΎΠ²Ρ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ ΠΏΠΎΠΊΠ»Π°Π΄Π΅Π½ΠΎ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²Ρ ΠΊΡΠΈΠ²ΠΎΡ ΡΡΡΡΠ½Π½Ρ, Π΄Π΅ Π²ΠΊΠ°Π·Π°Π½ΠΎ Π½Π° Π·ΠΌΡΠ½Ρ ΡΠ΅ΡΠ΅Π΄Π½ΡΠΎΡ Π²ΠΎΠ»ΠΎΠ³ΠΎΡΡΡ ΡΠ° Π²ΠΎΠ»ΠΎΠ³ΠΎΡΡΡ ΠΏΠΎΠ²Π΅ΡΡ
Π½Π΅Π²ΠΈΡ
Ρ ΡΠ΅Π½ΡΡΠ°Π»ΡΠ½ΠΈΡ
ΡΠ°ΡΡΠ² Π΄Π΅ΡΠ΅Π²ΠΈΠ½ΠΈ ΠΏΡΠ΄ ΡΠ°Ρ ΡΡΡΡΠ½Π½Ρ. ΠΠ° ΡΠΈΠΌΠΈ Π΄Π°Π½ΠΈΠΌΠΈ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½ΠΎ Π²Π΅Π»ΠΈΡΠΈΠ½ΠΈ: ΡΠ²ΠΈΠ΄ΠΊΡΡΡΡ ΡΡΡΡΠ½Π½Ρ, ΠΊΠΎΠ΅ΡΡΡΡΡΠ½ΡΠΈ ΡΡΡΡΠ½Π½Ρ, Π²ΠΎΠ»ΠΎΠ³ΠΎΠΏΡΠΎΠ²ΡΠ΄Π½ΠΎΡΡΡ ΡΠ° Π²ΠΎΠ»ΠΎΠ³ΠΎΠ²ΡΠ΄Π΄Π°ΡΡ, Π° ΡΠ°ΠΊΠΎΠΆ Π²Π΅Π»ΠΈΡΠΈΠ½ΠΈ ΠΌΠ°ΡΠΎΠΎΠ±ΠΌΡΠ½Π½ΠΈΡ
ΠΊΡΠΈΡΠ΅ΡΡΡΠ² ΠΡΡΡΠ΅Π»ΡΡΠ°, Π€ΡΡ'Ρ ΡΠ° ΠΡΡΠΏΡΡΠΎΠ²Π°. ΠΠ° Π²Π΅Π»ΠΈΡΠΈΠ½Π°ΠΌΠΈ ΠΊΠΎΠ΅ΡΡΡΡΡΠ½ΡΠ° ΡΡΡΡΠ½Π½Ρ ΠΌΠΎΠΆΠ½Π° Π²ΠΈΠ·Π½Π°ΡΠΈΡΠΈ ΡΡΠΈΠ²Π°Π»ΡΡΡΡ ΡΡΡΡΠ½Π½Ρ ΠΏΠΈΠ»ΠΎΠΌΠ°ΡΠ΅ΡΡΠ°Π»ΡΠ² Π· Π΄Π΅ΡΠ΅Π²ΠΈΠ½ΠΈ ΡΠΎΡΠ½ΠΈ Π·Π°Π²ΡΠΎΠ²ΡΠΊΠΈ 40Β ΠΌΠΌ Π±ΡΠ΄Ρ-ΡΠΊΠΎΡ ΠΏΠΎΡΠ°ΡΠΊΠΎΠ²ΠΎΡ Ρ ΠΊΡΠ½ΡΠ΅Π²ΠΎΡ Π²ΠΎΠ»ΠΎΠ³ΠΎΡΡΡ ΡΠ° Π·Π° Π²Π΅Π»ΠΈΡΠΈΠ½ΠΎΡ ΠΊΠΎΠ΅ΡΡΡΡΡΠ½ΡΠ° Π²ΠΎΠ»ΠΎΠ³ΠΎΠΏΡΠΎΠ²ΡΠ΄Π½ΠΎΡΡΡ Π±ΡΠ΄Ρ-ΡΠΊΠΈΡ
ΡΠΎΡΠ½ΠΎΠ²ΠΈΡ
ΠΏΠΈΠ»ΠΎΠΌΠ°ΡΠ΅ΡΡΠ°Π»ΡΠ² ΡΡΠ·Π½ΠΎΡ ΡΠΎΠ²ΡΠΈΠ½ΠΈ ΡΠ° ΠΏΠΎΡΠ°ΡΠΊΠΎΠ²ΠΎΡ Ρ ΠΊΡΠ½ΡΠ΅Π²ΠΎΡ Π²ΠΎΠ»ΠΎΠ³ΠΎΡΡΡ ΠΉ ΡΠ½ΡΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΏΡΠΎΡΠ΅ΡΡ ΡΡΡΡΠ½Π½Ρ. ΠΠΈΠ·Π½Π°ΡΠ΅Π½Π½Ρ ΠΌΠ°ΡΠΎΠΎΠ±ΠΌΡΠ½Π½ΠΎΠ³ΠΎ ΠΊΡΠΈΡΠ΅ΡΡΡ ΠΡΡΠΏΡΡΠΎΠ²Π° (ΠΊΡΠΈΡΠ΅ΡΡΡ ΡΡΡΡΠΈΠ½ΠΎΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ) ΠΏΠΎΠΊΠ°Π·ΡΡ Π½Π°ΡΠΊΡΠ»ΡΠΊΠΈ ΠΎΠ±ΡΠ°Π½ΠΈΠΉ ΡΠ΅ΠΆΠΈΠΌ Ρ Π±Π΅Π·ΠΏΠ΅ΡΠ½ΠΈΠΌ Π· ΡΠΎΡΠΊΠΈ Π·ΠΎΡΡ Π²ΠΈΠ½ΠΈΠΊΠ½Π΅Π½Π½Ρ Π½Π°Π΄Π»ΠΈΡΠΊΠΎΠ²ΠΈΡ
Π²Π½ΡΡΡΡΡΠ½ΡΡ
Π½Π°ΠΏΡΡΠΆΠ΅Π½Ρ Ρ Π΄Π΅ΡΠ΅Π²ΠΈΠ½Ρ. ΠΠ° ΠΎΡΡΠΈΠΌΠ°Π½ΠΈΠΌΠΈ Π΄Π°Π½ΠΈΠΌΠΈ ΠΏΠΎΠΊΠ°Π·Π½ΠΈΠΊΡΠ² ΠΊΡΠ½Π΅ΡΠΈΠΊΠΈ ΠΏΡΠΎΡΠ΅ΡΡ ΡΡΡΡΠ½Π½Ρ Ρ ΠΌΠ°ΡΠΎΠΎΠ±ΠΌΡΠ½Π½ΠΈΡ
ΠΊΡΠΈΡΠ΅ΡΡΡΠ² ΠΡΡΡΠ΅Π»ΡΡΠ° ΡΠ° Π€ΡΡ'Ρ Π· Π΄ΠΎΠΏΠΎΠ²Π½Π΅Π½Π½ΡΠΌ Π΄ΠΎ ΡΠΈΡ
Π°Π΅ΡΠΎΠ΄ΠΈΠ½Π°ΠΌΡΡΠ½ΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΡΡΡΠΈΠ»ΡΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π»Π°Π΄Π½Π°Π½Π½Ρ, ΡΠ· Π²ΡΠ°Ρ
ΡΠ²Π°Π½Π½ΡΠΌ ΠΊΡΠΈΡΠ΅ΡΡΡ Π Π΅ΠΉΠ½ΠΎΠ»ΡΠ΄ΡΠ°, ΠΌΠΎΠΆΠ½Π° ΡΠΊΠ»Π°ΡΡΠΈ ΡΡΠ·ΠΈΠΊΠΎ-ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΏΡΠΎΡΠ΅ΡΡ ΡΡΡΡΠ½Π½Ρ ΠΏΠΈΠ»ΠΎΠΌΠ°ΡΠ΅ΡΡΠ°Π»ΡΠ² Ρ Π·Π°Π³ΠΎΡΠΎΠ²ΠΎΠΊ. Π¦Ρ ΡΡΠ·ΠΈΠΊΠΎ-ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½Π° ΠΌΠΎΠ΄Π΅Π»Ρ Π²ΠΈΠ·Π½Π°ΡΠ°Ρ Π²ΠΏΠ»ΠΈΠ² Π½Π° ΠΊΡΠ½Π΅ΡΠΈΠΊΡ ΠΏΡΠΎΡΠ΅ΡΡ ΡΡΡΡΠ½Π½Ρ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡΠ² ΡΡΡΠΈΠ»ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΠ°, ΡΠ΅ΠΏΠ»ΠΎΡΡΠ·ΠΈΡΠ½ΠΈΡ
Π²Π»Π°ΡΡΠΈΠ²ΠΎΡΡΠ΅ΠΉ Π΄Π΅ΡΠ΅Π²ΠΈΠ½ΠΈ ΡΠ° Π°Π΅ΡΠΎΠ΄ΠΈΠ½Π°ΠΌΡΡΠ½ΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΡΡΡΠΈΠ»ΡΠ½ΠΈΡ
ΠΊΠ°ΠΌΠ΅Ρ.ΠΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΎ, ΡΡΠΎ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΡ ΡΠ΅ΠΏΠ»ΠΎΠΌΠ°ΡΡΠΎΠΎΠ±ΠΌΠ΅Π½Π½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π΄Π΅ΡΠ΅Π²ΠΎΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΡΠΎΡΡΠΎΠΈΡ, ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΠΎ, Π² ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΠΈ ΡΠ²Π»Π΅Π½ΠΈΠΉ ΠΏΠ΅ΡΠ΅Π½ΠΎΡΠ° ΡΠ΅ΠΏΠ»Π° ΠΈ Π²Π»Π°Π³ΠΈ, ΠΊΠ°ΠΊ Π²Π½ΡΡΡΠΈ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π°, ΡΠ°ΠΊ ΠΈ Π½Π° Π³ΡΠ°Π½ΠΈΡΠ΅ ΡΠ°Π·Π΄Π΅Π»Π΅Π½ΠΈΡ ΡΠ°Π· ΡΡΠ΅Π΄Π° β ΡΠ²Π΅ΡΠ΄ΠΎΠ΅ ΡΠ΅Π»ΠΎ ΠΈ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠΈΠ·ΠΈΠΊΠΎ-ΠΌΠ΅Ρ
Π°Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ Π²ΠΎ Π²ΡΠ΅ΠΌΡ ΡΠ΅ΠΏΠ»ΠΎΠ²ΠΎΠΉ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ. ΠΠ°ΠΊ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΠΉ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΏΡΠΈΠ½ΡΡΠΎ ΡΠΎΡΡΠ°Π²Π½ΡΠ΅ ΠΏΠΈΠ»ΠΎΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΡΠΎΠ»ΡΠΈΠ½ΠΎΠΉ40Β ΠΌΠΌ, ΠΊΠΎΡΠΎΡΡΠ΅ Π²ΡΡΡΡΠΈΠ²Π°ΡΡΡΡ ΠΌΡΠ³ΠΊΠΈΠΌΠΈ ΡΠ΅ΠΆΠΈΠΌΠ°ΠΌΠΈ. Π ΠΎΡΠ½ΠΎΠ²Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΎ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ ΠΊΡΠΈΠ²ΠΎΠΉ ΡΡΡΠΊΠΈ, Π³Π΄Π΅ ΡΠΊΠ°Π·Π°Π½ΠΎ Π½Π° ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΡΠ΅Π΄Π½Π΅ΠΉ Π²Π»Π°ΠΆΠ½ΠΎΡΡΠΈ ΠΈ Π²Π»Π°ΠΆΠ½ΠΎΡΡΠΈ ΠΏΠΎΠ²Π΅ΡΡ
Π½ΠΎΡΡΠ½ΡΡ
ΠΈ Π²Π½ΡΡΡΠ΅Π½Π½ΠΈΡ
ΡΠ»ΠΎΠ΅Π² Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ Π²ΠΎ Π²ΡΠ΅ΠΌΡ ΡΡΡΠΊΠΈ. ΠΠΎ ΡΡΠΈΠΌ Π΄Π°Π½Π½ΡΠΌ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ Π²Π΅Π»ΠΈΡΠΈΠ½Ρ: ΡΠΊΠΎΡΠΎΡΡΠΈ ΡΡΡΠΊΠΈ, ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΡ ΡΡΡΠΊΠΈ, Π²Π»Π°Π³ΠΎΠΏΡΠΎΠ²ΠΎΠ΄Π½ΠΎΡΡΠΈ ΠΈ Π²Π»Π°Π³ΠΎΠΎΠ±ΠΌΠ΅Π½Π°, Π° ΡΠ°ΠΊΠΆΠ΅ Π²Π΅Π»ΠΈΡΠΈΠ½Ρ ΠΌΠ°ΡΡΠΎΠΎΠ±ΠΌΠ΅Π½Π½ΡΡ
ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΠΡΡΡΠ΅Π»ΡΡΠ°, Π€ΡΡΡΠ΅ ΠΈ ΠΠΈΡΠΏΠΈΡΠ΅Π²Π°. ΠΠ° Π²Π΅Π»ΠΈΡΠΈΠ½Π°ΠΌ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΡΡΡΠΊΠΈ ΠΌΠΎΠΆΠ½ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ ΠΏΡΠΎΠ΄ΠΎΠ»ΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡ ΡΡΡΠΊΠΈ ΠΏΠΈΠ»ΠΎΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΠΎΠ² ΠΈΠ· Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ ΡΠΎΡΠ½Ρ ΡΠΎΠ»ΡΠΈΠ½ΠΎΠΉ40Β ΠΌΠΌΠΊΠ°ΠΊΠΎΠΉ-Π»ΠΈΠ±ΠΎ Π½Π°ΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΈ ΠΊΠΎΠ½Π΅ΡΠ½ΠΎΠΉ Π²Π»Π°ΠΆΠ½ΠΎΡΡΠΈ, Π° ΠΏΠΎ Π²Π΅Π»ΠΈΡΠΈΠ½Π°ΠΌ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° Π²Π»Π°Π³ΠΎΠΏΡΠΎΠ²ΠΎΠ΄Π½ΠΎΡΡΠΈ ΠΌΠΎΠΆΠ½ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ ΠΏΡΠΎΠ΄ΠΎΠ»ΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΊΠ°ΠΊΠΈΡ
β Π»ΠΈΠ±ΠΎ ΡΠΎΡΠ½ΠΎΠ²ΡΡ
ΠΏΠΈΠ»ΠΎΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΠΎΠ² ΡΠ°Π·Π»ΠΈΡΠ½ΠΎΠΉ ΡΠΎΠ»ΡΠΈΠ½Ρ, Π½Π°ΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΈ ΠΊΠΎΠ½Π΅ΡΠ½ΠΎΠΉ Π²Π»Π°ΠΆΠ½ΠΎΡΡΠΈ ΠΈ Π΄ΡΡΠ³ΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΡΡΡΠΊΠΈ. ΠΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΌΠ°ΡΡΠΎΠΎΠ±ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΠΊΡΠΈΡΠ΅ΡΠΈΡ ΠΠΈΡΠΏΠΈΡΠ΅Π²Π° (ΠΊΡΠΈΡΠ΅ΡΠΈΡ ΡΡΠ΅ΡΠΈΠ½ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ) ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°Π΅Ρ Π½Π°ΡΠΊΠΎΠ»ΡΠΊΠΎ ΠΈΠ·Π±ΡΠ°Π½Π½ΡΠΉ ΡΠ΅ΠΆΠΈΠΌ ΡΠΎΡΠ½Ρ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ΅Π½ Ρ ΡΠΎΡΠΊΠΈ Π·ΡΠ΅Π½ΠΈΡ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ ΠΈΠ·Π»ΠΈΡΠ½ΠΈΡ
Π²Π½ΡΡΡΠ΅Π½Π½ΠΈΡ
Π½Π°ΠΏΡΡΠΆΠ΅Π½ΠΈΠΉ Π² Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Π΅. ΠΠΎ ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΠΌ Π΄Π°Π½Π½ΡΠΌΠΈ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΊΠΈΠ½Π΅ΡΠΈΠΊΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΡΡΡΠΊΠΈ ΠΈ ΠΌΠ°ΡΡΠΎΠΎΠ±ΠΌΠ΅Π½Π½ΡΡ
ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΠΡΡΡΠ΅Π»ΡΡΠ° ΠΈ Π€ΡΡΡΠ΅ Ρ Π΄ΠΎΠΏΠΎΠ»Π½Π΅Π½ΠΈΠ΅ΠΌ ΠΊ ΡΡΠΈΠΌ Π΄Π°Π½Π½ΡΠΌ Π°ΡΡΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΡΡΡΠΈΠ»ΡΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΠΎΡΡΠ΄ΠΎΠ²Π°Π½ΠΈΡ, Π²ΠΊΠ»ΡΡΠ°Ρ ΠΊΡΠΈΡΠ΅ΡΠΈΠΉ Π Π΅ΠΉΠ½ΠΎΠ»ΡΠ΄ΡΠ°, ΠΌΠΎΠΆΠ½ΠΎ ΡΠΎΡΡΠ°Π²ΠΈΡΡ ΡΠΈΠ·ΠΈΠΊΠΎ-ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΡΡΡΠΊΠΈ ΠΏΠΈΠ»ΠΎΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΠΎΠ² ΠΈ Π·Π°Π³ΠΎΡΠΎΠ²ΠΎΠΊ. ΠΡΠ° ΠΌΠΎΠ΄Π΅Π»Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅Ρ Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π½Π° ΠΊΠΈΠ½Π΅ΡΠΈΠΊΡ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΡΡΡΠΊΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ² ΡΡΠ΅Π΄Ρ ΡΠ΅ΠΏΠ»ΠΎΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ² Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ ΠΈ Π°ΡΡΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΡΡΡΠΈΠ»ΡΠ½ΡΡ
ΠΊΠ°ΠΌΠ΅Ρ.It is known that the complexity of the heat-and-mass exchange processes in woodworking consists in the complexity of the phenomena of heat-and-moisture transfer both within the material and at the phase interface environment-solid body, as well as the complexity of changing physical-and-mechanical characteristics of wood during heat treatment. The test material was pine lumber with a thickness of 40Β mm, which had been dried by a soft drying schedule. The objective of the study is the construction of the drying curve which indicates the change in the average moisture and the moisture content of the surface and middle layers of wood during drying. By this data, the values were found for drying rate, drying coefficients, moisture conductivity and moisture-yielding ability, as well as mass-exchange numbers of Nusselt, Fourier, and Kirpichov. By the values of the drying coefficient, we can determine the drying time for 40Β mm thick pine-wood lumber of any initial and final moisture content, and by the magnitude of the conductivity coefficient we can determine drying time for any pine wood of various thicknesses and various initial and final moisture and other characteristics of the drying process. Determination of mass exchange number of Kirpichov (criterion of crack formation) shows how the selected mode is safe in terms of the occurrence of excessive internal stresses in wood. Thus, a physical-mathematical model of the process of drying of lumber and blanks can be constructed using the obtained data on the kinetics of the drying process as well as Nusselt's and Fourier's mass exchange criteria, with the addition to this of the aerodynamic characteristics of the drying equipment, including the Reynolds criterion. This physical-mathematical model identifies the influence of the drying environment parameters, the thermophysical properties of the wood and the aerodynamic characteristics of the drying chambers on the kinetics of the drying process
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