575 research outputs found
Local rigidity for actions of Kazhdan groups on non commutative -spaces
Given a discrete group , a finite factor and a real
number with we are concerned with the rigidity
of actions of by linear isometries on the -spaces associated to . More precisely, we show that, when and
have both Property (T) and under some natural ergodicity
condition, such an action is locally rigid in the group of linear
isometries of , that is, every sufficiently small perturbation
of is conjugate to under . As a consequence, when is an
ICC Kazhdan group, the action of on its von Neumann algebra , given by conjugation, is locally rigid in the isometry group of
Comment: 20 page
Effect of gamma irradiation on the microbial load, chemical and sensory properties of goat meat
The present study was undertaken to assess the effects of gamma irradiation (0, 2, 4, and 6 kGy) on microbial, chemical, and sensory values of Jabaly Syrian goat meat during storage at 4 Β°C for 1, 3, 4, and 5 weeks. Irradiation was effective in reducing the microbial load and increasing the shelf-life of goat meat. The radiation doses required to reduce the microorganisms by 90 percent (D10) in goat meat were 294 and 400 Gy for Salmonella and E. coli, respectively. The main fatty acids identified from the goat meat were oleic, stearic, and palmitic acids. No significant differences were observed in moisture, crude protein, crude fat, ash, pH value, fatty acids, total acidity, volatile basic nitrogen, and sensory properties (texture, flavour, colour, and taste) of irradiated and non-irradiated goat meat. Lipid peroxidation measured in terms of thiobarbituric acid-reactive substances (TBARS) increased on irradiation and chilled storage. Sensory evaluation showed no significant differences between irradiated and non-irradiated goat meat
Energy release rate of small cracks under finite multiaxial straining
International audienceThe energy release rate of small cracks governs fatigue crack nucleation. A method is presented here to efficiently and accurately evaluate the energy release rate of such cracks, arbitrarily oriented, under general conditions of finite multiaxial loading. As a motivation, the dependence on crack length is then investigated. It is demonstrated that the energy release rate of small cracks is proportional to the crack length and that the proportionality factor is a function of the far-field parameters only. An attempt is then made to search for a general expression of this proportionality factor under simple loading conditions
ΠΠ»Π³ΠΎΡΠΈΡΠΌ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΈΡΠ»Π° Π²ΠΎΠ»ΠΎΠΊΠΎΠ½ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΠΌΡΡ ΠΏΡΠΈ Π²Π½ΡΡΡΠΈΡΠΊΠ°Π½Π΅Π²ΠΎΠΉ ΡΠΎΡΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΡΠ°ΠΊΠ° ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ Π½Π° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ Π΄ΠΈΡΡΡΠ·ΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ
It is essential in interstitial Photodynamic therapy (iPDT) treatment planning to ensure a homogeneous distribution within a tumor volume using cylindrical diffusing fibers while keeping the surrounding tissue intact. Light distribution is simulated through two algorithms based on the diffusion equation assuming diffusers as light sources. The first algorithm analyzes the diffusion equation and studies the effects of different variables (optical properties, delivered power, diffuser length, and position). Next, optical properties of breast were applied to estimate the volume that receives accepted light dose from one diffuser. In the second algorithm, multiple diffusers were simulated in order to find the relation between the volume and the number of required diffusers which are needed to cover cubical or cylindrical volume with sufficient light dose. Throughout this study, real values of optical properties, clinical laser power, and treatment time were considered to evaluate sufficient light doses. This study is in agreement with previous works in that optical properties are the major factors influencing light distribution in iPDT. It is shown that for a homogeneous phantom mimicking breast cancer and cubical or cylindrical shape, the number of required fibers N equal WΓL or D2 respectively.ΠΡΠΈ ΠΏΠ»Π°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ Π²Π½ΡΡΡΠΈΡΠΊΠ°Π½Π΅Π²ΠΎΠΉ ΡΠΎΡΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ (iPDT ) Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΠΈΠ»ΠΈΠ½Π΄ΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄ΠΈΡΡΡΠ·Π½ΡΡ
Π²ΠΎΠ»ΠΎΠΊΠΎΠ½ Π²Π°ΠΆΠ½ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΡΡ ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΡΠ²Π΅ΡΠ° ΠΏΠΎ Π²ΡΠ΅ΠΌΡ ΠΎΠ±ΡΠ΅ΠΌΡ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ, ΡΠΎΡ
ΡΠ°Π½ΠΈΠ² ΠΏΡΠΈ ΡΡΠΎΠΌ ΡΠ΅Π»ΠΎΡΡΠ½ΠΎΡΡΡ ΠΎΠΊΡΡΠΆΠ°ΡΡΠ΅ΠΉ ΡΠΊΠ°Π½ΠΈ. ΠΠ²ΡΠΎΡΡ Π΄Π°Π½Π½ΠΎΠΉ ΡΡΠ°ΡΡΠΈ ΡΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π»ΠΈ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΡΠ²Π΅ΡΠ° Ρ ΠΏΠΎΠΌΠΎΡΡΡ Π΄Π²ΡΡ
Π°Π»Π³ΠΎΡΠΈΡΠΌΠΎΠ², ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΡ
Π½Π° ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΈ Π΄ΠΈΡΡΡΠ·ΠΈΠΈ, Π² ΠΊΠΎΡΠΎΡΡΡ
Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΎΠ² ΡΠ²Π΅ΡΠ° ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡΡΡΡ ΡΠΈΠ»ΠΈΠ½Π΄ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄ΠΈΡΡΡΠ·ΠΎΡΡ. ΠΠ΅ΡΠ²ΡΠΉ Π°Π»Π³ΠΎΡΠΈΡΠΌ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅Ρ ΡΡΠ°Π²Π½Π΅Π½ΠΈΠ΅ Π΄ΠΈΡΡΡΠ·ΠΈΠΈ ΠΈ ΠΈΠ·ΡΡΠ°Π΅Ρ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
(ΠΎΠΏΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ² ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠ°, ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΠΌΠΎΠΉ ΠΌΠΎΡΠ½ΠΎΡΡΠΈ, Π΄Π»ΠΈΠ½Ρ Π΄ΠΈΡΡΡΠ·ΠΎΡΠ° ΠΈ Π΅Π³ΠΎ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΡ). ΠΠ°ΡΠ΅ΠΌ Π±ΡΠ»ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡ ΠΎΠΏΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ² ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΎΠ±ΡΠ΅ΠΌΠ°, ΠΊΠΎΡΠΎΡΡΠΉ ΡΠ°ΡΡΡΠΈΡΡΠ²Π°Π΅Ρ ΡΠ²Π΅ΡΠΎΠ²ΡΡ Π΄ΠΎΠ·Ρ ΠΎΡ ΠΎΠ΄Π½ΠΎΠ³ΠΎ Π΄ΠΈΡΡΡΠ·ΠΎΡΠ°. ΠΠΎ Π²ΡΠΎΡΠΎΠΌ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ΅ Π±ΡΠ»ΠΎ ΡΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΎ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΎ ΡΠ°ΡΡΠ΅ΠΈΠ²Π°ΡΠ΅Π»Π΅ΠΉ Π΄Π»Ρ Π½Π°Ρ
ΠΎΠΆΠ΄Π΅ Π½ΠΈΡ ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ ΠΌΠ΅ΠΆΠ΄Ρ ΠΎΠ±ΡΠ΅ΠΌΠΎΠΌ ΠΈ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎΠΌ ΡΠ°ΡΡΠ΅ΠΈΠ²Π°ΡΠ΅Π»Π΅ΠΉ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΡ
Π΄Π»Ρ ΠΏΠΎΠΊΡΡΡΠΈΡ ΠΊΡΠ±ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ»ΠΈ ΡΠΈΠ»ΠΈΠ½Π΄ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΠΌΠ° Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎΠΉ ΡΠ²Π΅ΡΠΎΠ²ΠΎΠΉ Π΄ΠΎΠ·ΠΎΠΉ. ΠΠ° ΠΏΡΠΎΡΡΠΆΠ΅Π½ΠΈΠΈ Π²ΡΠ΅Π³ΠΎ ΡΡΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π»ΠΈΡΡ ΡΠ΅Π°Π»ΡΠ½ΡΠ΅ Π·Π½Π°ΡΠ΅Π½ΠΈΡ ΠΎΠΏΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ², ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΡΠ½ΠΎΡΡΠΈ Π»Π°Π·Π΅ΡΠ° ΠΈ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ Π»Π΅ΡΠ΅Π½ΠΈΡ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΡΡ
ΡΠ²Π΅ΡΠΎΠ²ΡΡ
Π΄ΠΎΠ·. ΠΡΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΎΠ³Π»Π°ΡΡΠ΅ΡΡΡ Ρ ΠΏΡΠ΅Π΄ΡΠ΄ΡΡΠΈΠΌΠΈ ΡΠ°Π±ΠΎΡΠ°ΠΌΠΈ Π² ΡΠΎΠΌ, ΡΡΠΎ ΠΎΠΏΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ²ΠΎΠΉΡΡΠ²Π° ΡΠ²Π»ΡΡΡΡΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌΠΈ ΡΠ°ΠΊΡΠΎΡΠ°ΠΌΠΈ, Π²Π»ΠΈΡΡΡΠΈΠΌΠΈ Π½Π° ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΡΠ²Π΅ΡΠ°Β ΠΏΡΠΈ iPDT. ΠΠΎΠΊΠ°Π·Π°Π½ΠΎ, ΡΡΠΎ, Π΄Π»Ρ ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΠΎΠ³ΠΎ ΡΠ°Π½ΡΠΎΠΌΠ°, ΠΈΠΌΠΈΡΠΈΡΡΡΡΠ΅Π³ΠΎ ΡΠ°ΠΊ ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ, ΠΊΡΠ±ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ»ΠΈ ΡΠΈΠ»ΠΈΠ½Π΄ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΎΡΠΌΡ, ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΡΡΠ΅Π±ΡΠ΅ΠΌΡΡ
Π²ΠΎΠ»ΠΎΠΊΠΎΠ½ N ΡΠ°Π²Π½ΠΎ WΓL ΠΈΠ»ΠΈ D2 , ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ
Energy release rate of small cracks under finite multiaxial straining
International audienceThe energy release rate of small cracks governs fatigue crack nucleation. A method is presented here to efficiently and accurately evaluate the energy release rate of such cracks, arbitrarily oriented, under general conditions of finite multiaxial loading. As a motivation, the dependence on crack length is then investigated. It is demonstrated that the energy release rate of small cracks is proportional to the crack length and that the proportionality factor is a function of the far-field parameters only. An attempt is then made to search for a general expression of this proportionality factor under simple loading conditions
BriFiSeg: a deep learning-based method for semantic and instance segmentation of nuclei in brightfield images
Generally, microscopy image analysis in biology relies on the segmentation of
individual nuclei, using a dedicated stained image, to identify individual
cells. However stained nuclei have drawbacks like the need for sample
preparation, and specific equipment on the microscope but most importantly, and
as it is in most cases, the nuclear stain is not relevant to the biological
questions of interest but is solely used for the segmentation task. In this
study, we used non-stained brightfield images for nuclei segmentation with the
advantage that they can be acquired on any microscope from both live or fixed
samples and do not necessitate specific sample preparation. Nuclei semantic
segmentation from brightfield images was obtained, on four distinct cell lines
with U-Net-based architectures. We tested systematically deep pre-trained
encoders to identify the best performing in combination with the different
neural network architectures used. Additionally, two distinct and effective
strategies were employed for instance segmentation, followed by thorough
instance evaluation. We obtained effective semantic and instance segmentation
of nuclei in brightfield images from standard test sets as well as from very
diverse biological contexts triggered upon treatment with various small
molecule inhibitor. The code used in this study was made public to allow
further use by the community
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