scholarly journals Characteristic dynamic rheological responses of nematic poly(p-phenylene terephthalamide) and cholesteric hydroxypropyl cellulose phases

2016 ◽  
Vol 48 (8) ◽  
pp. 869-874 ◽  
Author(s):  
Youngho Eom ◽  
Dae Eon Jung ◽  
Seung Sang Hwang ◽  
Byoung Chul Kim
2021 ◽  
Vol 251 ◽  
pp. 117015
Author(s):  
Mateusz Gosecki ◽  
Harri Setälä ◽  
Tommi Virtanen ◽  
Anthony J. Ryan

2001 ◽  
Vol 279 (11) ◽  
pp. 1139-1143 ◽  
Author(s):  
S. Kunugi ◽  
D. Yoshida ◽  
H. Kiminami

2019 ◽  
Vol 35 ◽  
pp. 140-144 ◽  
Author(s):  
Safa Abd Al Kader Mohamed Hamed ◽  
Mohammad Lotfy Hassan

1981 ◽  
Vol 7 (6) ◽  
pp. 693-716 ◽  
Author(s):  
Gilbert Banker ◽  
Garnet Peck ◽  
Steve Ja ◽  
Pichai Pirakitikulr ◽  
Deeni Taylor

2007 ◽  
Vol 34 (9) ◽  
pp. 1019-1028 ◽  
Author(s):  
Katsufumi Tanaka ◽  
Takatoshi Morina ◽  
Yuichiro Tanabe ◽  
Ryuichi Akiyama

2009 ◽  
Vol 31 (7) ◽  
pp. 1607-1612 ◽  
Author(s):  
Eugene J. OBrien ◽  
Paraic Rattigan ◽  
Arturo González ◽  
Jason Dowling ◽  
Aleš Žnidarič

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Catalina Alvarado-Rojas ◽  
Michel Le Van Quyen

Little is known about the long-term dynamics of widely interacting cortical and subcortical networks during the wake-sleep cycle. Using large-scale intracranial recordings of epileptic patients during seizure-free periods, we investigated local- and long-range synchronization between multiple brain regions over several days. For such high-dimensional data, summary information is required for understanding and modelling the underlying dynamics. Here, we suggest that a compact yet useful representation is given by a state space based on the first principal components. Using this representation, we report, with a remarkable similarity across the patients with different locations of electrode placement, that the seemingly complex patterns of brain synchrony during the wake-sleep cycle can be represented by a small number of characteristic dynamic modes. In this space, transitions between behavioral states occur through specific trajectories from one mode to another. These findings suggest that, at a coarse level of temporal resolution, the different brain states are correlated with several dominant synchrony patterns which are successively activated across wake-sleep states.


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