Optimal Mutual Location of Compact Sets in Spaces Endowed with Euclidean Invariant Gromov–Hausdorif Metric

2018 ◽  
Vol 73 (5) ◽  
pp. 182-189
Author(s):  
O. S. Malysheva
Keyword(s):  
Author(s):  
Ehud Hrushovski ◽  
François Loeser

This chapter introduces the concept of stable completion and provides a concrete representation of unit vector Mathematical Double-Struck Capital A superscript n in terms of spaces of semi-lattices, with particular emphasis on the frontier between the definable and the topological categories. It begins by constructing a topological embedding of unit vector Mathematical Double-Struck Capital A superscript n into the inverse limit of a system of spaces of semi-lattices L(Hsubscript d) endowed with the linear topology, where Hsubscript d are finite-dimensional vector spaces. The description is extended to the projective setting. The linear topology is then related to the one induced by the finite level morphism L(Hsubscript d). The chapter also considers the condition that if a definable set in L(Hsubscript d) is an intersection of relatively compact sets, then it is itself relatively compact.


2017 ◽  
pp. 63-67
Author(s):  
L. A. Vaganov ◽  
A. Yu. Sencov ◽  
A. A. Ankudinov ◽  
N. S. Polyakova

The article presents a description of the settlement method of necessary injection rates calculation, which is depended on the injected water migration into the surrounding wells and their mutual location. On the basis of the settlement method the targeted program of geological and technical measures for regulating the work of the injection well stock was created and implemented by the example of the BV7 formation of the Uzhno-Vyintoiskoe oil field.


1982 ◽  
Vol 8 (2) ◽  
pp. 455
Author(s):  
Akemann ◽  
Bruckner

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3237
Author(s):  
Artem A. Mitrofanov ◽  
Petr I. Matveev ◽  
Kristina V. Yakubova ◽  
Alexandru Korotcov ◽  
Boris Sattarov ◽  
...  

Modern structure–property models are widely used in chemistry; however, in many cases, they are still a kind of a “black box” where there is no clear path from molecule structure to target property. Here we present an example of deep learning usage not only to build a model but also to determine key structural fragments of ligands influencing metal complexation. We have a series of chemically similar lanthanide ions, and we have collected data on complexes’ stability, built models, predicting stability constants and decoded the models to obtain key fragments responsible for complexation efficiency. The results are in good correlation with the experimental ones, as well as modern theories of complexation. It was shown that the main influence on the constants had a mutual location of the binding centers.


1993 ◽  
Vol 36 (4) ◽  
pp. 407-413 ◽  
Author(s):  
Jonathan M. Borwein ◽  
Simon Fitzpatrick

AbstractWe show that L1(μ) has a weak Hadamard differential)le renorm (i.e. differentiable away from the origin uniformly on all weakly compact sets) if and only if μ is sigma finite. As a consequence several powerful recent differentiability theorems apply to subspaces of L1.


2012 ◽  
Vol 263 (4) ◽  
pp. 1098-1102
Author(s):  
Surjit Singh Khurana

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