On Multiplicative Sum connectivity index, Multiplicative Randic index and Multiplicative Harmonic index of some Nanostar Dendrimers

Bhanumathi, M.; Rani, K. Easu Julia

doi:10.26674/ijesacbt/2018/49410

Cited by 8 publications

(4 citation statements)

References 7 publications

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“…Defining the multiplicative Harmonic index (15) and multiplicative sum connectivity index (16) as follows:…”

Section: Methodsmentioning

confidence: 99%

Computation of Multiplicative Descriptors of Some Agricultural Pesticides

Akhila,

Xavier,

Nair

et al. 2023

IJST

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Objective: To examine various degree-based multiplicative descriptors of some agricultural pesticides. Methods: To compute the main results, the method of analytical techniques, degree counting method, edge and vertex partition method, and graphical-theoretical tools is used to evaluate the agricultural pesticides. Findings: Various degree-based multiplicative indices analytical expressions have been obtained. Novelty: Pesticides are combinations of chemicals or mixtures that are primarily used in agriculture and this study creates a simple and exact method of estimating and ranking the potentially hazardous chemicals. The relationship between the chemical compounds and their properties is determined by topological descriptors. The topological indices of agricultural pesticides are plotted and compared with each other.

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“…Defining the multiplicative Harmonic index (15) and multiplicative sum connectivity index (16) as follows:…”

Section: Methodsmentioning

confidence: 99%

Computation of Multiplicative Descriptors of Some Agricultural Pesticides

Akhila,

Xavier,

Nair

et al. 2023

IJST

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“…resulting in multiplicative versions of the directed Zagreb indices (Bozovic et al, 2016;Eliasi and Ghalavand, 2016), directed sum connectivity (Bhanumathi and Rani, 2018), the directed Randić index (Gutman et al, 2018) and the directed harmonic index (Bhanumathi and Rani, 2018). Given their novelty, however, these indices are not considered further here.…”

Section: I(d) Metricsmentioning

confidence: 99%

Non-perennial stream networks as directed acyclic graphs: The R-package streamDAG

Aho¹,

Kriloff²,

Godsey³

et al. 2023

Preprint

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Many conventional stream network metrics are time-invariant and/or do not consider the importance of individual stream locations to network functionality. As a result, they are not well-suited to non-perennial streams, in which hydrologic status (flowing vs. pooled vs. dry) can vary substantially in space and time. To help address this issue, we consider non-perennial streams as directed acyclic graphs (DAGs). DAG metrics allow: 1) summarization of important network characteristics (e.g., centrality, complexity, connectedness, and nestedness) of both particular (local) stream network locations and entire (global) stream networks, and 2) tracking of these characteristics as non-perennial stream networks expand and shrink. We review a large number of graph-theoretic procedures for their utility in the analysis of non-perennial stream DAGs. Approaches we find useful are codified in a new publicly available R-package, streamDAG, which allows straightforward igraph representations of stream networks and easy modification of non-perennial stream DAG topologies based on water presence/absence data. The streamDAG package includes a wide variety of local and global measures for both unweighted and weighted stream digraphs, and provides procedures for generating Bayesian posterior distributions of the probability and the reciprocal probability of surface water presence. We demonstrate streamDAG algorithms using two North American non-perennial streams: Murphy Creek, a simple drainage system in the Owyhee Mountains of southwestern Idaho, and Konza Prairie, a relatively complex stream network in central Kansas.

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“…The research shows various degree-based topological descriptors and multiplicative degree-based topological descriptors, which can be seen in Table 1 [10][11][12][13][14][15][16][17][18][19][20][21][22] and Table 2 [23][24][25][26][27][28][29][30][31], respectively.…”

Section: Preliminaries and Mathematical Terminologiesmentioning

confidence: 99%

Topological Study on Triazine-Based Covalent-Organic Frameworks

Augustine

Santiago

2022

Symmetry

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Most of the research has evidenced that there is a strong natural correlation among the chemical properties of molecular structures. This study analyses supramolecular chemistry and investigates topological indices of supramolecular structures called triazine-based covalent-organic frameworks. The use of degree-based topological indices on these chemical molecular structures can aid material scientists in better understanding their chemical and biological properties, thus compensating for the lack of chemical tests. This study aims to theoretically examine the triazine-based covalent-organic frameworks (TriCF) utilizing degree-based topological indices, specifically multiplicative topological indices and entropy measures. A detailed comparison of the computed topological indices of the aforementioned chemical structures is described using graphical depiction.

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On Multiplicative Sum connectivity index, Multiplicative Randic index and Multiplicative Harmonic index of some Nanostar Dendrimers

Cited by 8 publications

References 7 publications

Computation of Multiplicative Descriptors of Some Agricultural Pesticides

Computation of Multiplicative Descriptors of Some Agricultural Pesticides

Non-perennial stream networks as directed acyclic graphs: The R-package streamDAG

Topological Study on Triazine-Based Covalent-Organic Frameworks

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