dynamic crossover
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Author(s):  
Ian H. Bell ◽  
Stéphanie Delage-Santacreu ◽  
Hai Hoang ◽  
Guillaume Galliero

2021 ◽  
Vol 38 (1) ◽  
pp. 016802
Author(s):  
Shan Zhang ◽  
Weihua Wang ◽  
Pengfei Guan

2020 ◽  
Vol 15 (4) ◽  
pp. 287-299
Author(s):  
Jie Zhang ◽  
Junhong Feng ◽  
Fang-Xiang Wu

Background: : The brain networks can provide us an effective way to analyze brain function and brain disease detection. In brain networks, there exist some import neural unit modules, which contain meaningful biological insights. Objective:: Therefore, we need to find the optimal neural unit modules effectively and efficiently. Method:: In this study, we propose a novel algorithm to find community modules of brain networks by combining Neighbor Index and Discrete Particle Swarm Optimization (DPSO) with dynamic crossover, abbreviated as NIDPSO. The differences between this study and the existing ones lie in that NIDPSO is proposed first to find community modules of brain networks, and dose not need to predefine and preestimate the number of communities in advance. Results: : We generate a neighbor index table to alleviate and eliminate ineffective searches and design a novel coding by which we can determine the community without computing the distances amongst vertices in brain networks. Furthermore, dynamic crossover and mutation operators are designed to modify NIDPSO so as to alleviate the drawback of premature convergence in DPSO. Conclusion: The numerical results performing on several resting-state functional MRI brain networks demonstrate that NIDPSO outperforms or is comparable with other competing methods in terms of modularity, coverage and conductance metrics.


2018 ◽  
Vol 41 (9) ◽  
Author(s):  
Szymon Starzonek ◽  
Aleksandra Kędzierska-Sar ◽  
Aleksandra Drozd-Rzoska ◽  
Mikołaj Szafran ◽  
Sylwester J. Rzoska
Keyword(s):  

2018 ◽  
Vol 232 (7-8) ◽  
pp. 1041-1058 ◽  
Author(s):  
Max Weigler ◽  
Martin Brodrecht ◽  
Hergen Breitzke ◽  
Felix Dietrich ◽  
Matthias Sattig ◽  
...  

AbstractMesoporous silica MCM-41 is prepared, for which the inner surfaces are modified by 3-(aminopropyl)triethoxysilane (APTES) in a controlled manner. Nitrogen gas adsorpition yields a pore diameter of 2.2 nm for the APTES functionalized MCM-41.2H nuclear magnetic resonance (NMR) and broadband dielectric spectroscopy (BDS) provide detailed and consistent insights into the temperature-dependent reorientation dynamics of water in this confinement. We find that a liquid water species becomes accompanied by a solid water species when cooling through ~210 K, as indicated by an onset of bimodal2H spin-lattice relaxation. The reorientation of the liquid water species is governed by pronounced dynamical heterogeneity in the whole temperature range. Its temperature dependence shows a mild dynamic crossover when the solid water species emerges and, hence, the volume accessible to the liquid water species further shrinks. Therefore, we attribute this variation in the temperature dependence to a change from bulk-like behavior towards interface-dominated dynamics. Below this dynamic crossover,2H line-shape and stimulted-echo studies show that water reorientation becomes anisotropic upon cooling, suggesting that these NMR approaches, but also BDS measurements do no longer probe the structural (α) relaxation, but rather a secondary (β) relaxation of water at sufficiently low temperatures. Then, another dynamic crossover at ~180 K can be rationalized in terms of a change of the temperature dependence of theβrelaxation in response to a glassy freezing of theαrelaxation of confined water. Comparing these results for APTES modied MCM-41 with previous findings for mesoporous silica with various pore diameters, we obtain valuable information about the dependence of water dynamics in restricted geometries on the size of the nanoscopic confinements and the properties of the inner surfaces.


2018 ◽  
Vol 700 ◽  
pp. 102-107 ◽  
Author(s):  
J. Bartoš ◽  
B. Zgardzinska ◽  
H. Švajdlenková ◽  
M. Lukešová ◽  
R. Zaleski

2018 ◽  
Vol 100 ◽  
pp. 226-233 ◽  
Author(s):  
Jasnamol Pezhumkattil Palakkal ◽  
Cheriyedath Raj Sankar ◽  
Ajeesh Parayancheri Paulose ◽  
Matjaz Valant ◽  
Artem Badasyan ◽  
...  

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