adaptive constraints
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2020 ◽  
Vol 109 (3-4) ◽  
pp. 1007-1026 ◽  
Author(s):  
Yongbin Zhang ◽  
Taiyong Wang ◽  
Jingchuan Dong ◽  
Peng Peng ◽  
Yangfan Liu ◽  
...  

2020 ◽  
Vol 32 (18) ◽  
pp. 15119-15129
Author(s):  
Jun Huang ◽  
Zhuliang Le ◽  
Yong Ma ◽  
Xiaoguang Mei ◽  
Fan Fan

Author(s):  
Yao Zhou ◽  
Xuebo Zhao ◽  
Yiwen Li ◽  
Jun Xu ◽  
Aoyue Bi ◽  
...  

AbstractBread wheat expanded its habitats from a small core area of the Fertile Crescent to global environments within ∼10,000 years. Genetic mechanisms of this remarkable evolutionary success are not well understood. By whole-genome sequencing of populations from 25 subspecies within genera Triticum and Aegilops, we identified composite introgression from these wild populations contributing 13%∼36% of the bread wheat genome, which tremendously increased the genetic diversity of bread wheat and allowed its divergent adaptation. Meanwhile, convergent adaption to human selection showed 2- to 16-fold enrichment relative to random expectation in Triticum species despite their drastic differences in ploidy levels and growing zones, indicating the vital importance of adaptive constraints in the success of bread wheat. These results showed the genetic necessities of wheat as a global crop and provided new perspectives on leveraging adaptation success across species for crop improvement.


Measurement ◽  
2020 ◽  
Vol 153 ◽  
pp. 107402 ◽  
Author(s):  
Dongwei Qiu ◽  
Shaofu Li ◽  
Tong Wang ◽  
Qing Ye ◽  
Ruijie Li ◽  
...  

2018 ◽  
Author(s):  
Marjon G. J. de Vos ◽  
Sijmen E Schoustra ◽  
J. Arjan G. M. de Visser

The topography of the adaptive landscape is a major determinant of the course of evolution. In this review we use the adaptive landscape metaphor to highlight the effect of ecology on evolution. We describe how ecological interactions modulate the shape of the adaptive landscape, and how this affects adaptive constraints. We focus on microbial communities as model systems.


Author(s):  
Tommaso Bradde ◽  
STEFANO GRIVET TALOCIA ◽  
Marco De Stefano ◽  
Alessandro Zanco

We propose a theoretical framework and an automated algorithm for the construction of a parameterized reduced-order model of a general LTI system from its sampled input-output responses. The model is cast as a parameterized rational function in Generalized Sanathanan-Koerner form, which allows for implicit parameterization of the model poles. Our main result is the guaranteed enforcement of uniform stability of the model in the parameter space through a sufficient condition, which requires the (strict) positive realness of the denominator subsystem. This condition is enforced through adaptive constraints during the model construction loop. Several applications to the field of Electronic Design Automation are presented.


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