Allan Adler and Catarina Kiefe. Pseudofinite fields, procyclic fields and model-completion. Pacific journal of mathematics, vol. 62 (1976), pp. 305–309.

1987 ◽  
Vol 52 (4) ◽  
pp. 1055-1055
Author(s):  
Alexander Prestel
Keyword(s):  
Pseudofinite Fields ◽  
Model Completion

scholarly journals Pseudofinite fields, procyclic fields and model-completion

1976 ◽  
Vol 62 (2) ◽  
pp. 305-309 ◽  
Author(s):  
Allan Adler ◽  
Catarina Kiefe
Keyword(s):  
Pseudofinite Fields ◽  
Model Completion

scholarly journals On algebraic closure in pseudofinite fields

2012 ◽  
Vol 77 (4) ◽  
pp. 1057-1066 ◽  
Author(s):  
Özlem Beyarslan ◽  
Ehud Hrushovski
Keyword(s):  
Automorphism Group ◽  
Finite Field ◽  
Algebraic Closure ◽  
Roots Of Unity ◽  
Prime Field ◽  
Almost All ◽  
Pseudofinite Fields

AbstractWe study the automorphism group of the algebraic closure of a substructureAof a pseudo-finite fieldF. We show that the behavior of this group, even whenAis large, depends essentially on the roots of unity inF. For almost all completions of the theory of pseudofinite fields, we show that overA, algebraic closure agrees with definable closure, as soon asAcontains the relative algebraic closure of the prime field.

Function Modeling: A Study of Sequential Model Completion Based on Count and Chaining of Functions

2016 ◽  
Author(s):  
Apurva Patel ◽  
William Kramer ◽  
Joshua D. Summers ◽  
Marissa Shuffler-Porter
Keyword(s):  
Engineering Design ◽  
Mechanical Engineering ◽  
Engineering Students ◽  
Solution Space ◽  
Backward Chaining ◽  
Forward Chaining ◽  
Engineering Design Problems ◽  
Initial Seed ◽  
Function Models ◽  
Model Completion

Function models are widely recognized as a useful tool in mechanical engineering conceptual design as a bridge between problem and solution space. Unlike many other engineering design tools that are collaborative allowing many designers to contribute to the design task, function modeling has not been historically presented as a collaborative tool. This paper presents a controlled experimental study that explores the how different initial function models are completed by novice engineers influence the number of functions added to the model. Eighty-eight senior mechanical engineering students were given partial function models to two similarly complex engineering design problems. Each student was asked to complete the function model to best address the problem presented. The number of added functions was compared considering two variables: percent completed of initial seed model (10%, 40%, and 80%), initial chaining of functions (forward, backward, and nucleation). It was found that models for Backward Chaining and Nucleation at 10% initial seed resulted in the greatest addition of functions by the students. Further, Backward Chaining and Nucleation yielded more added functions than Forward Chaining in all seed configurations. Recognizing that there is a difference between Forward Chaining and Backward Chaining or Nucleation, further study is warranted to understand how individuals create function models and which approach yields more useful models to either understand the problem presented or to explore solution options.

scholarly journals A knowledge-driven approach for crystallographic protein model completion

2008 ◽  
Vol 64 (4) ◽  
pp. 416-424 ◽  
Author(s):  
Krista Joosten ◽  
Serge X. Cohen ◽  
Paul Emsley ◽  
Wijnand Mooij ◽  
Victor S. Lamzin ◽  
...  
Keyword(s):  
Protein Model ◽  
Model Completion

scholarly journals Improved direct-method aided iterative dual-space model completion

2014 ◽  
Vol 70 (a1) ◽  
pp. C332-C332
Author(s):  
Yao He ◽  
Deqiang Yao ◽  
Sheng Huang ◽  
Tao Zhang ◽  
Zhengjiong Lin ◽  
...  
Keyword(s):  
Figure Of Merit ◽  
Dual Space ◽  
Weighting Function ◽  
Direct Method ◽  
Direct Methods ◽  
R Factor ◽  
Phase Constraints ◽  
Sad Phasing ◽  
Model Completion ◽  
Space Phase

It has been proved that direct methods are efficient in providing phase constraints within the dual-space phase-model iterative framework [1]. The program OASIS is used for the direct-method implementation. Two kinds of iterative direct methods are performed by OASIS. One involves the use of SAD/SIR information [2], while the other dose not [3]. Improvements have been made on both kinds of iterative direct methods. First, the Srinivasan's weighting function replaces previously used Sim's weighting function in the direct-method phase derivation leading to better estimation of phases. This affects both kinds of direct-method iteration. Second, the process of the second kind direct-method iteration has been made multi-threaded and parallel. This significantly speeds up the iteration in multi-CPU systems. Finally, a new figure of merit combining the R factor and Srinivasan's weighting function is used to pick up the best partial structure instead of using the R factor alone. The improved procedure has been tested using a set of SIRAS data from the protein LegC3N with Hg-derivative at 5.0Å resolution and native at 2.1Å resolution. With the previous version of OASIS, SAD phasing at 5.0Å resolution was successful but phases were failed to extend to the 2.1Å resolution native data as is described in §3.2 of [1]. However the new version of OASIS has succeeded in extending 5.0Å resolution SAD phases to 2.1Å resolution native phases leading to a nearly complete structure model.

Automatic Model Completion for Web Applications

2020 ◽  
pp. 207-227
Author(s):  
Ruilian Zhao ◽  
Chen Chen ◽  
Weiwei Wang ◽  
Junxia Guo
Keyword(s):  
Web Applications ◽  
Model Completion
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