Reactivity and structural patterns of phenylphosphines in acetylene and acetylide carbonyl trinuclear ruthenium clusters

Polyhedron ◽  
2019 ◽  
Vol 161 ◽  
pp. 251-260
Author(s):  
Erik G. Rojo-Gómez ◽  
Abril I. Munguía-Lara ◽  
Daniel O. González-Abrego ◽  
Gloria Sánchez-Cabrera ◽  
José G. Alvarado-Rodríguez ◽  
...  
Keyword(s):  
Ruthenium Clusters ◽  
Structural Patterns

scholarly journals Multi-hop assortativities for network classification

2018 ◽  
Vol 7 (4) ◽  
pp. 603-622 ◽  
Author(s):  
Leonardo Gutiérrez-Gómez ◽  
Jean-Charles Delvenne
Keyword(s):  
Machine Learning ◽  
Scientific Collaboration ◽  
State Of The Art ◽  
Medical Engineering ◽  
Research Field ◽  
Classification Task ◽  
Collaboration Network ◽  
Structural Patterns ◽  
Art Methods

Abstract Several social, medical, engineering and biological challenges rely on discovering the functionality of networks from their structure and node metadata, when it is available. For example, in chemoinformatics one might want to detect whether a molecule is toxic based on structure and atomic types, or discover the research field of a scientific collaboration network. Existing techniques rely on counting or measuring structural patterns that are known to show large variations from network to network, such as the number of triangles, or the assortativity of node metadata. We introduce the concept of multi-hop assortativity, that captures the similarity of the nodes situated at the extremities of a randomly selected path of a given length. We show that multi-hop assortativity unifies various existing concepts and offers a versatile family of ‘fingerprints’ to characterize networks. These fingerprints allow in turn to recover the functionalities of a network, with the help of the machine learning toolbox. Our method is evaluated empirically on established social and chemoinformatic network benchmarks. Results reveal that our assortativity based features are competitive providing highly accurate results often outperforming state of the art methods for the network classification task.

Optimal Structural Patterns of Multi-strand Wire Ropes

2021 ◽  
pp. 111070
Author(s):  
Lei Liu ◽  
Dabiao Liu ◽  
Xinxin Wu ◽  
Yuming He
Keyword(s):  
Structural Patterns ◽  
Wire Ropes

Trinuclear osmium and ruthenium clusters containing ligands formed by dehydration and rearrangement of 1,4-dihydroxybut-2-yne

1981 ◽  
Vol 20 (7) ◽  
pp. 2027-2031 ◽  
Author(s):  
Silvio. Aime ◽  
Antonio. Tiripicchio ◽  
Marisa Tiripicchio. Camellini ◽  
Antony J. Deeming
Keyword(s):  
Ruthenium Clusters

High-accuracy prediction of protein structural classes using PseAA structural properties and secondary structural patterns

Biochimie ◽  
2014 ◽  
Vol 101 ◽  
pp. 104-112 ◽  
Author(s):  
Junru Wang ◽  
Yan Li ◽  
Xiaoqing Liu ◽  
Qi Dai ◽  
Yuhua Yao ◽  
...  
Keyword(s):  
Structural Properties ◽  
High Accuracy ◽  
Structural Patterns ◽  
Structural Classes

Structural patterns in early Hiberno-Latin hagiography

Peritia ◽  
1985 ◽  
Vol 4 ◽  
pp. 67-82 ◽  
Author(s):  
Jean-Michel Picard
Keyword(s):  
Structural Patterns

Structural Patterns in α Helices and β Sheets in Globular Proteins

2009 ◽  
Vol 16 (8) ◽  
pp. 953-960 ◽  
Author(s):  
Nicholus Bhattacharjee ◽  
Parbati Biswas
Keyword(s):  
Globular Proteins ◽  
Structural Patterns
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