Technical Advance and Economic Equilibria

1943 ◽  
Vol 9 (1) ◽  
pp. 55
Author(s):  
B. S. Keirstead
Keyword(s):  
Technical Advance ◽  
Economic Equilibria

The euro zone’s major economic equilibria

2001 ◽  
Vol 64 (4) ◽  
pp. 31-45
Author(s):  
Fabrice Pansard
Keyword(s):  
Economic Equilibria

scholarly journals Zelluläres Tauziehen: Wie Zellen auf mechanischen Stress antworten

BIOspektrum ◽  
2021 ◽  
Vol 27 (4) ◽  
pp. 385-389
Author(s):  
Kai Weissenbruch ◽  
Marc Hippler ◽  
Martin Bastmeyer
Keyword(s):  
Tissue Homeostasis ◽  
Physical Basis ◽  
Technical Advance ◽  
Molecular Scale ◽  
Sense And Respond ◽  
Intracellular Forces

AbstractThe ability of cells to sense and respond to extracellular forces is critical for cellular and tissue homeostasis. Tension or compression act on our body ubiquitously and cells respond to such mechanical cues by producing intracellular forces on their own. In this article, we briefly highlight the cellular and physical basis driving these phenomena and discuss our recent technical advance to stimulate and monitor the cellular mechanoresponse on a molecular scale.

scholarly journals Opening the High-Pressure Domain beyond 2 kbar to Protein and Virus Crystallography—Technical Advance

Structure ◽  
2002 ◽  
Vol 10 (10) ◽  
pp. 1409-1414 ◽  
Author(s):  
Roger Fourme ◽  
Isabella Ascone ◽  
Richard Kahn ◽  
Mohamed Mezouar ◽  
Pierre Bouvier ◽  
...  
Keyword(s):  
High Pressure ◽  
Technical Advance

scholarly journals Resource and Technical Advance papers: expanding our resources

JCI Insight ◽  
2021 ◽  
Vol 6 (11) ◽  
Author(s):  
Kathleen L. Collins
Keyword(s):  
Technical Advance

Synaptic clef segmentation method based on fractal dimension for ATUM-SEM image of mouse cortex

2021 ◽  
pp. 2150038
Author(s):  
Chao Ma ◽  
Lijun Shen ◽  
Hao Deng ◽  
Jialin Li
Keyword(s):  
Fractal Dimension ◽  
Physical Structure ◽  
Noise Performance ◽  
Segmentation Method ◽  
Technical Advance ◽  
Image Stack ◽  
Sem Image ◽  
The Neural Network ◽  
Mouse Cortex ◽  
The Stability

It is well known that neurons communicate through synapses in the nervous system, and the size, morphology, and connectivity of synapses determine the functional properties of the neural network. Therefore, synapses have always been one of the key objects of neuroscience. Due to the technical advance in electron microscope (EM), the physical structure of synapses can be observed at high resolution. Nevbarheless, to date, the automatic analysis of the synapse in EM images is still a challenging task. In this paper, we proposed a fractal dimension-based segmentation method for synaptic clef of mouse cortex on EM image stack. Our method does not require a lot of groundtruth to train the model, and shows better adaptive anti-noise performance. That should be ascribed to the stability of segmentation-related key parameters in the data from same tissue. In this way, we only need to give initial values, and then gradually adjust these key parameters. Experiments reveal that our method achieves the desired results, and reduces the time in artificial annotating, so that researchers can focus more on the analysis of segmentation results.

Sign in / Sign up

Export Citation Format

Share Document