Nothing Special   »   [go: up one dir, main page]

You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (20)

Search Parameters:
Keywords = eccentric connectivity index

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
24 pages, 15975 KiB  
Article
Research on the Relationship between the Structure of Forest and Grass Ecological Spaces and Ecological Service Capacity: A Case Study of the Wuding River Basin
by Yufan Zeng, Qiang Yu, Xiaoci Wang, Jun Ma, Chenglong Xu, Shi Qiu, Wei Liu and Fei Wang
Remote Sens. 2023, 15(9), 2456; https://doi.org/10.3390/rs15092456 - 7 May 2023
Cited by 4 | Viewed by 2233
Abstract
In recent years, the accelerated pace of urbanization has increased patch fragmentation, which has had a certain impact on the structure and ecological environment of forest–grass ecological networks, and certain protection measures have been taken in various regions. Therefore, studying the spatiotemporal changes [...] Read more.
In recent years, the accelerated pace of urbanization has increased patch fragmentation, which has had a certain impact on the structure and ecological environment of forest–grass ecological networks, and certain protection measures have been taken in various regions. Therefore, studying the spatiotemporal changes and correlations of ecological service functions and forest–grass ecological networks can help to better grasp the changes in landscape ecological structure and function. This paper takes the Wuding River Basin as the research area and uses the windbreak and sand fixation service capacity index, soil conservation capacity, and net primary productivity (NPP) to evaluate the ecological service capacity of the research area from the three dimensions of windbreak and sand fixation, soil conservation, and carbon sequestration. The Regional Sustainability and Environment Index (RSEI) is used to extract ecological source areas, and GIS spatial analysis and the minimum cumulative resistance (MCR) model are used to extract potential ecological corridors. Referring to complex network theory, topology metrics such as degree distribution and clustering coefficient are calculated, and their correlation with ecological service capacity is explored. The results show that the overall ecological service capacity of sand fixation, soil fixation, and carbon sequestration in the research area in 2020 has increased compared to 2000, and the ecological flow at the northern and northwest boundaries of the river basin has been enhanced, but there are still shortcomings such as fragmented ecological nodes, a low degree of clustering, and poor connectivity. In terms of the correlation between topology indicators and ecological service functions, the windbreak and sand fixation service capacity index have the strongest correlation with clustering and the largest grasp, while the correlation between soil conservation capacity and eigencentrality is the strongest and has the largest grasp. The correlation between NPP and other indicators is not obvious, and its correlation with eccentricity and eigencentrality is relatively large. Full article
Show Figures

Figure 1

Figure 1
<p>Data processing flow.</p>
Full article ">Figure 2
<p>Overview of the study area (<b>a</b>) and geographical location (<b>b</b>).</p>
Full article ">Figure 3
<p>Ecological resistance factors of the study area in the year 2020. (<b>a</b>) DEM in 2020, (<b>b</b>) Slope in 2020, (<b>c</b>) NDVI in 2020, (<b>d</b>) NDWI in 2020, (<b>e</b>) Land use type in 2020.</p>
Full article ">Figure 3 Cont.
<p>Ecological resistance factors of the study area in the year 2020. (<b>a</b>) DEM in 2020, (<b>b</b>) Slope in 2020, (<b>c</b>) NDVI in 2020, (<b>d</b>) NDWI in 2020, (<b>e</b>) Land use type in 2020.</p>
Full article ">Figure 4
<p>Changes in windbreak and sand fixation in the study area from 2000 to 2020.</p>
Full article ">Figure 5
<p>Changes in soil conservation amounts of the study area from 2000 to 2020.</p>
Full article ">Figure 6
<p>Changes in NPP of the study area from 2000 to 2020.</p>
Full article ">Figure 7
<p>Distribution of ecological source areas in the study area from 2000 to 2020. (<b>a</b>) Ecological source patches in 2000, (<b>b</b>) Ecological source patches in 2010, (<b>c</b>) Ecological source patches in 2015, (<b>d</b>) Ecological source patches in 2020.</p>
Full article ">Figure 7 Cont.
<p>Distribution of ecological source areas in the study area from 2000 to 2020. (<b>a</b>) Ecological source patches in 2000, (<b>b</b>) Ecological source patches in 2010, (<b>c</b>) Ecological source patches in 2015, (<b>d</b>) Ecological source patches in 2020.</p>
Full article ">Figure 8
<p>Cumulative resistance surface in the study area from 2000 to 2020. (<b>a</b>) Cumulative resistance surface in 2000, (<b>b</b>) Cumulative resistance surface in 2010, (<b>c</b>) Cumulative resistance surface in 2015, (<b>d</b>) Cumulative resistance surface in 2020.</p>
Full article ">Figure 9
<p>Ecological corridors in the study area from 2000 to 2020. (<b>a</b>) Ecological corridors in 2000, (<b>b</b>) Ecological corridors in 2010, (<b>c</b>) Ecological corridors in 2015, (<b>d</b>) Ecological corridors in 2020.</p>
Full article ">Figure 10
<p>Degree distribution of the forest–grassland ecological network in the study area from 2000 to 2020.</p>
Full article ">Figure 11
<p>Diameter and average path length of forest–grassland ecological network in the study area from 2000 to 2020.</p>
Full article ">Figure 12
<p>Clustering coefficients of nodes of forest–grassland ecological network in the study area from 2000 to 2020.</p>
Full article ">Figure 13
<p>The correlation between the windbreak and sand fixation service capacity index(<b>a</b>), soil conservation quantity (<b>b</b>), NPP (<b>c</b>) and complex network topology in 2020. (* <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01).</p>
Full article ">
14 pages, 688 KiB  
Article
Applications on Topological Indices of Zero-Divisor Graph Associated with Commutative Rings
by Clement Johnson Rayer and Ravi Sankar Jeyaraj
Symmetry 2023, 15(2), 335; https://doi.org/10.3390/sym15020335 - 25 Jan 2023
Cited by 8 | Viewed by 2419
Abstract
A topological index is a numeric quantity associated with a chemical structure that attempts to link the chemical structure to various physicochemical properties, chemical reactivity, or biological activity. Let R be a commutative ring with identity, and Z*(R) is [...] Read more.
A topological index is a numeric quantity associated with a chemical structure that attempts to link the chemical structure to various physicochemical properties, chemical reactivity, or biological activity. Let R be a commutative ring with identity, and Z*(R) is the set of all non-zero zero divisors of R. Then, Γ(R) is said to be a zero-divisor graph if and only if a·b=0, where a,bV(Γ(R))=Z*(R) and (a,b)E(Γ(R)). We define ab if a·b=0 or a=b. Then, ∼ is always reflexive and symmetric, but ∼ is usually not transitive. Then, Γ(R) is a symmetric structure measured by the ∼ in commutative rings. Here, we will draw the zero-divisor graph from commutative rings and discuss topological indices for a zero-divisor graph by vertex eccentricity. In this paper, we will compute the total eccentricity index, eccentric connectivity index, connective eccentric index, eccentricity based on the first and second Zagreb indices, Ediz eccentric connectivity index, and augmented eccentric connectivity index for the zero-divisor graph associated with commutative rings. These will help us understand the characteristics of various symmetric physical structures of finite commutative rings. Full article
(This article belongs to the Special Issue Advances in Combinatorics and Graph Theory)
Show Figures

Figure 1

Figure 1
<p><math display="inline"><semantics> <mrow> <mo>Γ</mo> <mo stretchy="false">(</mo> <msub> <mi mathvariant="double-struck">Z</mi> <mn>9</mn> </msub> <mrow> <mo>[</mo> <mi>x</mi> <mo>]</mo> </mrow> <mo>/</mo> <mrow> <mo stretchy="false">〈</mo> <msup> <mi>x</mi> <mn>2</mn> </msup> <mo stretchy="false">〉</mo> </mrow> <mo stretchy="false">)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 2
<p><math display="inline"><semantics> <mrow> <mo>Γ</mo> <mo stretchy="false">(</mo> <msub> <mi mathvariant="double-struck">Z</mi> <mn>15</mn> </msub> <mrow> <mo>[</mo> <mi>x</mi> <mo>]</mo> </mrow> <mo>/</mo> <mrow> <mo stretchy="false">〈</mo> <msup> <mi>x</mi> <mn>2</mn> </msup> <mo stretchy="false">〉</mo> </mrow> <mo stretchy="false">)</mo> </mrow> </semantics></math>.</p>
Full article ">
12 pages, 312 KiB  
Article
Comparative Study of Planar Octahedron Molecular Structure via Eccentric Invariants
by Zheng-Qing Chu, Haidar Ali, Didar Abdulkhaleq Ali, Muhammad Nadeem, Syed Ajaz K. Kirmani and Parvez Ali
Molecules 2023, 28(2), 556; https://doi.org/10.3390/molecules28020556 - 5 Jan 2023
Cited by 1 | Viewed by 1552
Abstract
A branch of graph theory that makes use of a molecular graph is called chemical graph theory. Chemical graph theory is used to depict a chemical molecule. A graph is connected if there is an edge between every pair of vertices. A topological [...] Read more.
A branch of graph theory that makes use of a molecular graph is called chemical graph theory. Chemical graph theory is used to depict a chemical molecule. A graph is connected if there is an edge between every pair of vertices. A topological index is a numerical value related to the chemical structure that claims to show a relationship between chemical structure and various physicochemical attributes, chemical reactivity, or, you could say, biological activity. In this article, we examined the topological properties of a planar octahedron network of m dimensions and computed the total eccentricity, average eccentricity, Zagreb eccentricity, geometric arithmetic eccentricity, and atom bond connectivity eccentricity indices, which are used to determine the distance between the vertices of a planar octahedron network. Full article
(This article belongs to the Special Issue Study of Molecules in the Light of Spectral Graph Theory)
Show Figures

Figure 1

Figure 1
<p>Planar Octahedron network <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>O</mi> <mi>H</mi> <mo stretchy="false">(</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>.</p>
Full article ">
9 pages, 263 KiB  
Article
Bounds on the General Eccentric Connectivity Index
by Xinhong Yu, Muhammad Imran, Aisha Javed, Muhammad Kamran Jamil and Xuewu Zuo
Symmetry 2022, 14(12), 2560; https://doi.org/10.3390/sym14122560 - 4 Dec 2022
Cited by 1 | Viewed by 1518
Abstract
The general eccentric connectivity index of a graph R is defined as ξec(R)=uV(G)d(u)ec(u)α, where α is any real number, [...] Read more.
The general eccentric connectivity index of a graph R is defined as ξec(R)=uV(G)d(u)ec(u)α, where α is any real number, ec(u) and d(u) represent the eccentricity and the degree of the vertex u in R, respectively. In this paper, some bounds on the general eccentric connectivity index are proposed in terms of graph-theoretic parameters, namely, order, radius, independence number, eccentricity, pendent vertices and cut edges. Moreover, extremal graphs are characterized by these bounds. Full article
15 pages, 422 KiB  
Article
The Connective Eccentricity Index of Hypergraphs
by Guihai Yu, Renjie Wu and Xingfu Li
Mathematics 2022, 10(23), 4574; https://doi.org/10.3390/math10234574 - 2 Dec 2022
Cited by 3 | Viewed by 1508
Abstract
The connective eccentricity index (CEI) of a hypergraph G is defined as ξce(G)=vV(G)dG(v)εG(v), where εG(v) [...] Read more.
The connective eccentricity index (CEI) of a hypergraph G is defined as ξce(G)=vV(G)dG(v)εG(v), where εG(v) and dG(v) denote the eccentricity and the degree of the vertex v, respectively. In this paper, we determine the maximal and minimal values of the connective eccentricity index among all k-uniform hypertrees on n vertices and characterize the corresponding extremal hypertrees. Finally, we establish some relationships between the connective eccentricity index and the eccentric connectivity index of hypergraphs. Full article
(This article belongs to the Special Issue Advanced Graph Theory and Combinatorics)
Show Figures

Figure 1

Figure 1
<p><span class="html-italic">Transformation I</span>.</p>
Full article ">Figure 2
<p><span class="html-italic">Transformation II</span>.</p>
Full article ">Figure 3
<p><span class="html-italic">Transformation I on <math display="inline"><semantics> <msub> <mi>T</mi> <mn>3</mn> </msub> </semantics></math></span>.</p>
Full article ">Figure 4
<p><span class="html-italic">Transformation II on <math display="inline"><semantics> <msub> <mi>T</mi> <mn>6</mn> </msub> </semantics></math></span>.</p>
Full article ">
18 pages, 534 KiB  
Article
Minimum Zagreb Eccentricity Indices of Two-Mode Network with Applications in Boiling Point and Benzenoid Hydrocarbons
by Ali Al Khabyah, Shahid Zaman, Ali N. A. Koam, Ali Ahmad and Asad Ullah
Mathematics 2022, 10(9), 1393; https://doi.org/10.3390/math10091393 - 21 Apr 2022
Cited by 33 | Viewed by 1739
Abstract
A two-mode network is a type of network in which nodes can be divided into two sets in such a way that links can be established between different types of nodes. The relationship between two separate sets of entities can be modeled as [...] Read more.
A two-mode network is a type of network in which nodes can be divided into two sets in such a way that links can be established between different types of nodes. The relationship between two separate sets of entities can be modeled as a bipartite network. In computer networks data is transmitted in form of packets between source to destination. Such packet-switched networks rely on routing protocols to select the best path. Configurations of these protocols depends on the network acquirements; that is why one routing protocol might be efficient for one network and may be inefficient for a other. Because some protocols deal with hop-count (number of nodes in the path) while others deal with distance vector. This paper investigates the minimum transmission in two-mode networks. Based on some parameters, we obtained the minimum transmission between the class of all connected n-nodes in bipartite networks. These parameters are helpful to modify or change the path of a given network. Furthermore, by using least squares fit, we discussed some numerical results of the regression model of the boiling point in benzenoid hydrocarbons. The results show that the correlation of the boiling point in benzenoid hydrocarbons of the first Zagreb eccentricity index gives better result as compare to the correlation of second Zagreb eccentricity index. In case of a connected network, the first Zagreb eccentricity index ξ1() is defined as the sum of the square of eccentricities of the nodes, and the second Zagreb eccentricity index ξ2() is defined as the sum of the product of eccentricities of the adjacent nodes. This article deals with the minimum transmission with respect to ξi(), for i=1,2 among all n-node extremal bipartite networks with given matching number, diameter, node connectivity and link connectivity. Full article
Show Figures

Figure 1

Figure 1
<p>Networks <math display="inline"><semantics> <msup> <mo>ℵ</mo> <mo>′</mo> </msup> </semantics></math> and <math display="inline"><semantics> <msup> <mo>ℵ</mo> <mrow> <mo>″</mo> </mrow> </msup> </semantics></math>.</p>
Full article ">Figure 2
<p>Networks <span class="html-italic">ℵ</span> and <math display="inline"><semantics> <msup> <mo>ℵ</mo> <mo>*</mo> </msup> </semantics></math>.</p>
Full article ">Figure 3
<p>Networks <span class="html-italic">ℵ</span> and <math display="inline"><semantics> <msup> <mo>ℵ</mo> <mo>*</mo> </msup> </semantics></math>.</p>
Full article ">Figure 4
<p>Networks <math display="inline"><semantics> <mover accent="true"> <mo>ℵ</mo> <mo>¯</mo> </mover> </semantics></math> and <math display="inline"><semantics> <msub> <mo>ℵ</mo> <mn>2</mn> </msub> </semantics></math>.</p>
Full article ">Figure 5
<p>Networks <math display="inline"><semantics> <mover accent="true"> <mo>ℵ</mo> <mo>¯</mo> </mover> </semantics></math> and <math display="inline"><semantics> <msup> <mo>ℵ</mo> <mo>*</mo> </msup> </semantics></math>.</p>
Full article ">Figure 6
<p>Graphs <math display="inline"><semantics> <msubsup> <mo>ℵ</mo> <mn>1</mn> <mo>*</mo> </msubsup> </semantics></math>, <math display="inline"><semantics> <msubsup> <mo>ℵ</mo> <mn>2</mn> <mo>*</mo> </msubsup> </semantics></math> and <math display="inline"><semantics> <msubsup> <mo>ℵ</mo> <mn>3</mn> <mo>*</mo> </msubsup> </semantics></math>.</p>
Full article ">Figure 7
<p>Molecular networks of benzenoid hydrocarbons.</p>
Full article ">Figure 8
<p>The scatter plot of <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>P</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <msub> <mi>ξ</mi> <mn>1</mn> </msub> </semantics></math>.</p>
Full article ">Figure 9
<p>The scatter plot of <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>P</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <msub> <mi>ξ</mi> <mn>2</mn> </msub> </semantics></math>.</p>
Full article ">
9 pages, 759 KiB  
Article
Remarks on Distance Based Topological Indices for -Apex Trees
by Martin Knor, Muhammad Imran, Muhammad Kamran Jamil and Riste Škrekovski
Symmetry 2020, 12(5), 802; https://doi.org/10.3390/sym12050802 - 12 May 2020
Cited by 4 | Viewed by 2191
Abstract
A graph G is called an ℓ-apex tree if there exist a vertex subset A V ( G ) with cardinality such that G A is a tree and there is no other subset of smaller cardinality with this property. [...] Read more.
A graph G is called an ℓ-apex tree if there exist a vertex subset A V ( G ) with cardinality such that G A is a tree and there is no other subset of smaller cardinality with this property. In the paper, we investigate extremal values of several monotonic distance-based topological indices for this class of graphs, namely generalized Wiener index, and consequently for the Wiener index and the Harary index, and also for some newer indices as connective eccentricity index, generalized degree distance, and others. For the one extreme value we obtain that the extremal graph is a join of a tree and a clique. Regarding the other extreme value, which turns out to be a harder problem, we obtain results for = 1 and pose some open questions for higher . Symmetry has always played an important role in Graph Theory, in recent years, this role has increased significantly in several branches of this field, including topological indices of graphs. Full article
(This article belongs to the Special Issue Analytical and Computational Properties of Topological Indices)
Show Figures

Figure 1

Figure 1
<p>A 2-apex graph that turns into a 1-apex graph by introducing an edge.</p>
Full article ">Figure 2
<p>The dumbbell graph <math display="inline"><semantics> <mrow> <msub> <mi>D</mi> <mn>4</mn> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>,</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 3
<p>The graph <math display="inline"><semantics> <mrow> <mi>C</mi> <mo>(</mo> <mn>10</mn> <mo>,</mo> <mn>3</mn> <mo>)</mo> </mrow> </semantics></math>.</p>
Full article ">
23 pages, 5548 KiB  
Review
Properties of Entropy-Based Topological Measures of Fullerenes
by Modjtaba Ghorbani, Matthias Dehmer and Frank Emmert-Streib
Mathematics 2020, 8(5), 740; https://doi.org/10.3390/math8050740 - 7 May 2020
Cited by 10 | Viewed by 3038
Abstract
A fullerene is a cubic three-connected graph whose faces are entirely composed of pentagons and hexagons. Entropy applied to graphs is one of the significant approaches to measuring the complexity of relational structures. Recently, the research on complex networks has received great attention, [...] Read more.
A fullerene is a cubic three-connected graph whose faces are entirely composed of pentagons and hexagons. Entropy applied to graphs is one of the significant approaches to measuring the complexity of relational structures. Recently, the research on complex networks has received great attention, because many complex systems can be modelled as networks consisting of components as well as relations among these components. Information—theoretic measures have been used to analyze chemical structures possessing bond types and hetero-atoms. In the present article, we reviewed various entropy-based measures on fullerene graphs. In particular, we surveyed results on the topological information content of a graph, namely the orbit-entropy Ia(G), the symmetry index, a degree-based entropy measure Iλ(G), the eccentric-entropy Ifσ(G) and the Hosoya entropy H(G). Full article
(This article belongs to the Special Issue Graph Theory at Work in Carbon Chemistry)
Show Figures

Figure 1

Figure 1
<p>Illustration of two cubic graphs: (<b>a</b>) Cuneane; (<b>b</b>) cube.</p>
Full article ">Figure 2
<p>The 2-D graph of zig-zag nanotube <span class="html-italic">T<sub>Z</sub></span>[5,10].</p>
Full article ">Figure 3
<p>Cap <span class="html-italic">B</span>.</p>
Full article ">Figure 4
<p>The presentation of fullerene A<sub>10<span class="html-italic">n</span></sub> as a combining of two copies of <span class="html-italic">B</span> and the nanotube <span class="html-italic">T<sub>Z</sub></span>[5,<span class="html-italic">n −</span> 4].</p>
Full article ">Figure 5
<p>Three-dimensional graph of zig-zag polyhex nanotori.</p>
Full article ">Figure 6
<p>Two-dimensional lattice for <span class="html-italic">T</span>[<span class="html-italic">p,q</span>].</p>
Full article ">Figure 7
<p>The molecular graph of the fullerene C<sub>24<span class="html-italic">n</span>+12</sub>, for <span class="html-italic">n</span> = 3.</p>
Full article ">Figure 8
<p>The molecular graph of the fullerene C<sub>12<span class="html-italic">n</span>+2</sub>.</p>
Full article ">Figure 9
<p>Two vertices with the same total distance which are not <span class="html-italic">H</span>-equivalent.</p>
Full article ">Figure 10
<p>The vertices <span class="html-italic">u</span> and <span class="html-italic">v</span> are not <span class="html-italic">H</span>-equivalent but <span class="html-italic">D</span>(<span class="html-italic">u</span>) = <span class="html-italic">D</span>(<span class="html-italic">v</span>).</p>
Full article ">Figure 11
<p>A cubic co-distance graph of diameter 4 with non-zero <span class="html-italic">H</span>-entropy.</p>
Full article ">Figure 12
<p>The fullerene A<sub>12<span class="html-italic">n</span>+4</sub>.</p>
Full article ">Figure 13
<p>The orbits of the <span class="html-italic">i</span>th layer (2 ≤ <span class="html-italic">i</span> ≤ <span class="html-italic">n</span>)of the fullerene graph A<sub>12<span class="html-italic">n</span>+4</sub>.</p>
Full article ">Figure 14
<p>The subgraph <span class="html-italic">B</span><sub>1</sub>.</p>
Full article ">Figure 15
<p>The subgraph <span class="html-italic">B</span><sub>2</sub>.</p>
Full article ">Figure 16
<p>The 3-dimensional structure of fullerene graph A<sub>12<span class="html-italic">n</span>+4</sub>.</p>
Full article ">Figure 17
<p>The Hosoya-partitions of <span class="html-italic">Tz</span>[6,<span class="html-italic">n</span> − 10].</p>
Full article ">
11 pages, 256 KiB  
Article
On Eccentric Topological Indices Based on Edges of Zero Divisor Graphs
by Ali N. A. Koam, Ali Ahmad and Azeem Haider
Symmetry 2019, 11(7), 907; https://doi.org/10.3390/sym11070907 - 12 Jul 2019
Cited by 21 | Viewed by 2618
Abstract
This article is devoted to the determination of edge-based eccentric topological indices of a zero divisor graph of some algebraic structures. In particular, we computed the first Zagreb eccentricity index, third Zagreb eccentricity index, geometric-arithmetic eccentricity index, atom-bond connectivity eccentricity index and a [...] Read more.
This article is devoted to the determination of edge-based eccentric topological indices of a zero divisor graph of some algebraic structures. In particular, we computed the first Zagreb eccentricity index, third Zagreb eccentricity index, geometric-arithmetic eccentricity index, atom-bond connectivity eccentricity index and a fourth type of eccentric harmonic index for zero divisor graphs associated with a class of finite commutative rings. Full article
14 pages, 413 KiB  
Article
Some Eccentricity-Based Topological Indices and Polynomials of Poly(EThyleneAmidoAmine) (PETAA) Dendrimers
by Jialin Zheng, Zahid Iqbal, Asfand Fahad, Asim Zafar, Adnan Aslam, Muhammad Imran Qureshi and Rida Irfan
Processes 2019, 7(7), 433; https://doi.org/10.3390/pr7070433 - 9 Jul 2019
Cited by 27 | Viewed by 3732
Abstract
Topological indices have been computed for various molecular structures over many years. These are numerical invariants associated with molecular structures and are helpful in featuring many properties. Among these molecular descriptors, the eccentricity connectivity index has a dynamic role due to its ability [...] Read more.
Topological indices have been computed for various molecular structures over many years. These are numerical invariants associated with molecular structures and are helpful in featuring many properties. Among these molecular descriptors, the eccentricity connectivity index has a dynamic role due to its ability of estimating pharmaceutical properties. In this article, eccentric connectivity, total eccentricity connectivity, augmented eccentric connectivity, first Zagreb eccentricity, modified eccentric connectivity, second Zagreb eccentricity, and the edge version of eccentric connectivity indices, are computed for the molecular graph of a PolyEThyleneAmidoAmine (PETAA) dendrimer. Moreover, the explicit representations of the polynomials associated with some of these indices are also computed. Full article
(This article belongs to the Special Issue Computational Methods for Polymers)
Show Figures

Figure 1

Figure 1
<p>Chemical structure of PETAA dendrimer <math display="inline"><semantics> <mrow> <mi>D</mi> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 2
<p>From left to right, <math display="inline"><semantics> <mrow> <mi>D</mi> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> </semantics></math> with <math display="inline"><semantics> <mrow> <mi>n</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>n</mi> <mo>=</mo> <mn>1</mn> <mo>.</mo> </mrow> </semantics></math></p>
Full article ">
17 pages, 7014 KiB  
Article
A Process-Oriented Method for Tracking Rainstorms with a Time-Series of Raster Datasets
by Cunjin Xue, Jingyi Liu, Guanghui Yang and Chengbin Wu
Appl. Sci. 2019, 9(12), 2468; https://doi.org/10.3390/app9122468 - 17 Jun 2019
Cited by 7 | Viewed by 2896
Abstract
Extreme rainstorms have important socioeconomic consequences, but understanding their fine spatial structures and temporal evolution still remains challenging. In order to achieve this, in view of an evolutionary property of rainstorms, this paper designs a process-oriented algorithm for identifying and tracking rainstorms, named [...] Read more.
Extreme rainstorms have important socioeconomic consequences, but understanding their fine spatial structures and temporal evolution still remains challenging. In order to achieve this, in view of an evolutionary property of rainstorms, this paper designs a process-oriented algorithm for identifying and tracking rainstorms, named PoAIR. PoAIR uses time-series of raster datasets and consists of three steps. The first step combines an accumulated rainfall time-series and spatial connectivity to identify rainstorm objects at each time snapshot. Secondly, PoAIR adopts the geometrical features of eccentricity, rectangularity, roundness, and shape index, as well as the thematic feature of the mean rainstorm intensity, to match the same rainstorm objects in successive snapshots, and then tracks the same rainstorm objects during a rainstorm evolution sequence. In the third step, an evolutionary property of a rainstorm sequence is used to extrapolate its spatial location and geometrical features at the next time snapshot and reconstructs a rainstorm process by linking rainstorm sequences with an area-overlapping threshold. Experiments on simulated datasets demonstrate that PoAIR performs better than the Thunderstorm Identification, Tracking, Analysis and Nowcasting algorithm (TITAN) in both rainfall tracking and identifying the splitting, merging, and merging-splitting of rainstorm objects. Additionally, applications of PoAIR to Integrated Multi-satellitE Retrievals for Global Precipitation Mission (GPM/IMERG) final products covering mainland China show that PoAIR can effectively track rainstorm objects. Full article
(This article belongs to the Special Issue Machine Learning Techniques Applied to Geospatial Big Data)
Show Figures

Figure 1

Figure 1
<p>Basic concepts of a rainstorm (<b>a</b>) at a given time snapshot; (<b>b</b>) during the lifespan of the rainstorm. A solid black arrow represents a change from time snapshots T–T+1.</p>
Full article ">Figure 2
<p>The workflow of the process-oriented algorithm for identifying and tracking rainstorms (PoAIR).</p>
Full article ">Figure 3
<p>Three types of linkages with 8-neighborhood. (<b>a</b>) 8-neighborhoods of two rainstorm grid cells, (<b>b</b>) 8-neighborhoods of two rainstorm regions, and (<b>c</b>) the five independent grid cells and four spatial regions.</p>
Full article ">Figure 4
<p>The workflow of the rainstorm reconstruction processes.</p>
Full article ">Figure 5
<p>Temporal relationships between rainstorm sequences. S<sub>1</sub>: Sequence 1; S<sub>2</sub>: Sequence 2.</p>
Full article ">Figure 6
<p>Expressions of linkages between rainstorm sequences. <span class="html-italic">O<sub>S</sub><sup>t</sup></span> represents an object occurring at time <span class="html-italic">t</span> within a rainstorm sequence <span class="html-italic">S</span>, i.e., <span class="html-italic">preS</span>, <span class="html-italic">postS</span>, <span class="html-italic">S1</span>, or <span class="html-italic">S2</span>.</p>
Full article ">Figure 7
<p>Example of a rainstorm reconstruction process.</p>
Full article ">Figure 8
<p>A simulated rainstorm dataset. The colors represent the different rainstorm processes, and the types of lines represent different time snapshots, i.e., T1–T15.</p>
Full article ">Figure 9
<p>Results of the PoAIR and TITAN algorithms. (<b>a</b>) Results of the PoAIR algorithm using simulated data. (<b>b</b>) Results of the TITAN algorithm using simulated data.</p>
Full article ">Figure 10
<p>Research area and remote sensing dataset coverage.</p>
Full article ">Figure 11
<p>The dynamic characteristics of rainstorm processes over mainland China between 18–21 July 2016. The background is rainfall from GPM/IMERG products, the black lines denote rainstorm objects, and the text balloons present spatial and temporal information of rainstorm warnings from stations.</p>
Full article ">Figure 11 Cont.
<p>The dynamic characteristics of rainstorm processes over mainland China between 18–21 July 2016. The background is rainfall from GPM/IMERG products, the black lines denote rainstorm objects, and the text balloons present spatial and temporal information of rainstorm warnings from stations.</p>
Full article ">Figure 12
<p>The dynamic characteristics of a rainstorm sequence which occurred between 22:00 on July 20 and 01:00 on July 21.</p>
Full article ">
9 pages, 338 KiB  
Article
Eccentricity-Based Topological Invariants of Some Chemical Graphs
by Nazeran Idrees, Muhammad Jawwad Saif and Tehmina Anwar
Atoms 2019, 7(1), 21; https://doi.org/10.3390/atoms7010021 - 6 Feb 2019
Cited by 6 | Viewed by 3278
Abstract
Topological index is an invariant of molecular graphs which correlates the structure with different physical and chemical invariants of the compound like boiling point, chemical reactivity, stability, Kovat’s constant etc. Eccentricity-based topological indices, like eccentric connectivity index, connective eccentric index, first Zagreb eccentricity [...] Read more.
Topological index is an invariant of molecular graphs which correlates the structure with different physical and chemical invariants of the compound like boiling point, chemical reactivity, stability, Kovat’s constant etc. Eccentricity-based topological indices, like eccentric connectivity index, connective eccentric index, first Zagreb eccentricity index, and second Zagreb eccentricity index were analyzed and computed for families of Dutch windmill graphs and circulant graphs. Full article
Show Figures

Figure 1

Figure 1
<p>Tris(ethylenediamine)cobalt(III) chloride and tris(ethylenediamine)chromium(III) sulfate.</p>
Full article ">Figure 2
<p>Dutch windmill graph <math display="inline"><semantics> <mrow> <msubsup> <mi>D</mi> <mn>5</mn> <mn>2</mn> </msubsup> </mrow> </semantics></math> with eccentricity of vertices.</p>
Full article ">Figure 3
<p>Dutch windmill graph <math display="inline"><semantics> <mrow> <msubsup> <mi>D</mi> <mn>6</mn> <mn>3</mn> </msubsup> </mrow> </semantics></math> with eccentricity of vertices.</p>
Full article ">
9 pages, 553 KiB  
Article
Degree-Distance Based Topological Indices of Crystal Cubic Carbon Structure
by Hong Yang, Muhammad Kamran Siddiqui, Misbah Arshad and Muhammad Naeem
Atoms 2018, 6(4), 62; https://doi.org/10.3390/atoms6040062 - 15 Nov 2018
Cited by 9 | Viewed by 2979
Abstract
Chemical graph theory comprehends the basic properties of an atomic graph. The sub-atomic diagrams are the graphs that are comprised of particles called vertices and the covalent bond between them are called edges. The eccentricity ϵ u of vertex u in an associated [...] Read more.
Chemical graph theory comprehends the basic properties of an atomic graph. The sub-atomic diagrams are the graphs that are comprised of particles called vertices and the covalent bond between them are called edges. The eccentricity ϵ u of vertex u in an associated graph G, is the separation among u and a vertex farthermost from u. In this article, we consider the precious stone structure of cubic carbon and registered Eccentric-connectivity index ξ ( G ) , Eccentric connectivity polynomial E C P ( G , x ) and Connective Eccentric index C ξ ( G ) of gem structure of cubic carbon for n-levels. Full article
Show Figures

Figure 1

Figure 1
<p>Crystal Structure Cubic Carbon <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <mi>C</mi> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 2
<p>Crystal Structure Cubic Carbon <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <mi>C</mi> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 3
<p>The graphical representation of the Eccentric-connectivity index.</p>
Full article ">Figure 4
<p>The graphical representation of the Eccentric connectivity polynomial.</p>
Full article ">Figure 5
<p>The graphical representation of the Connective Eccentric index.</p>
Full article ">Figure 6
<p>Graphical Comparison of indices of <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <mi>C</mi> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </semantics></math>; <math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </semantics></math> is red, <math display="inline"><semantics> <mrow> <msup> <mi>C</mi> <mi>ξ</mi> </msup> <mrow> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> is blue, and <math display="inline"><semantics> <mrow> <mi>E</mi> <mi>C</mi> <mi>P</mi> <mo>(</mo> <mi>G</mi> <mo>,</mo> <mi>x</mi> <mo>)</mo> </mrow> </semantics></math> is green.</p>
Full article ">
14 pages, 341 KiB  
Article
Computing Eccentricity Based Topological Indices of Octagonal Grid O n m
by Xiujun Zhang, Muhammad Kamran Siddiqui, Muhammad Naeem and Abdul Qudair Baig
Mathematics 2018, 6(9), 153; https://doi.org/10.3390/math6090153 - 31 Aug 2018
Cited by 18 | Viewed by 3034
Abstract
Graph theory is successfully applied in developing a relationship between chemical structure and biological activity. The relationship of two graph invariants, the eccentric connectivity index and the eccentric Zagreb index are investigated with regard to anti-inflammatory activity, for a dataset consisting of 76 [...] Read more.
Graph theory is successfully applied in developing a relationship between chemical structure and biological activity. The relationship of two graph invariants, the eccentric connectivity index and the eccentric Zagreb index are investigated with regard to anti-inflammatory activity, for a dataset consisting of 76 pyrazole carboxylic acid hydrazide analogs. The eccentricity ε v of vertex v in a graph G is the distance between v and the vertex furthermost from v in a graph G. The distance between two vertices is the length of a shortest path between those vertices in a graph G. In this paper, we consider the Octagonal Grid O n m . We compute Connective Eccentric index C ξ ( G ) = v V ( G ) d v / ε v , Eccentric Connective Index ξ ( G ) = v V ( G ) d v ε v and eccentric Zagreb index of Octagonal Grid O n m , where d v represents the degree of the vertex v in G. Full article
Show Figures

Figure 1

Figure 1
<p>The Octagonal grid <math display="inline"><semantics> <msubsup> <mi>O</mi> <mi>n</mi> <mi>m</mi> </msubsup> </semantics></math>.</p>
Full article ">
15 pages, 297 KiB  
Article
Eccentricity-Based Topological Indices of a Cyclic Octahedron Structure
by Manzoor Ahmed Zahid, Abdul Qudair Baig, Muhammad Naeem and Muhammad Razwan Azhar
Mathematics 2018, 6(8), 141; https://doi.org/10.3390/math6080141 - 17 Aug 2018
Cited by 5 | Viewed by 3532
Abstract
In this article, we study the chemical graph of a cyclic octahedron structure of dimension n and compute the eccentric connectivity polynomial, the eccentric connectivity index, the total eccentricity, the average eccentricity, the first Zagreb index, the second Zagreb index, the third Zagreb [...] Read more.
In this article, we study the chemical graph of a cyclic octahedron structure of dimension n and compute the eccentric connectivity polynomial, the eccentric connectivity index, the total eccentricity, the average eccentricity, the first Zagreb index, the second Zagreb index, the third Zagreb index, the atom bond connectivity index and the geometric arithmetic index of the cyclic octahedron structure. Furthermore, we give the analytically closed formulas of these indices which are helpful for studying the underlying topologies. Full article
Show Figures

Figure 1

Figure 1
<p>Structure of an octahedron.</p>
Full article ">Figure 2
<p>Cyclic octahedral structure (<math display="inline"><semantics> <mrow> <mi>C</mi> <mi>Y</mi> <msub> <mi>O</mi> <mn>8</mn> </msub> </mrow> </semantics></math>).</p>
Full article ">Figure 3
<p>Graphical behavior of the eccentric indices of the cyclic octahedron structure with different colors: <math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </semantics></math> is green, <math display="inline"><semantics> <mrow> <mi>ζ</mi> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </semantics></math> is red, <math display="inline"><semantics> <mrow> <mi>a</mi> <mi>v</mi> <mi>e</mi> <mi>c</mi> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </semantics></math> is blue, <math display="inline"><semantics> <mrow> <msubsup> <mi>M</mi> <mrow> <mn>1</mn> </mrow> <mo>∗</mo> </msubsup> <mrow> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>ξ</mi> <mrow> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msubsup> <mi>M</mi> <mrow> <mn>1</mn> </mrow> <mrow> <mo>∗</mo> <mo>∗</mo> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> is black, <math display="inline"><semantics> <mrow> <msubsup> <mi>M</mi> <mrow> <mn>2</mn> </mrow> <mo>∗</mo> </msubsup> <mrow> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> is cyan, <math display="inline"><semantics> <mrow> <mi>G</mi> <msub> <mi>A</mi> <mn>4</mn> </msub> <mrow> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> is gold, and <math display="inline"><semantics> <mrow> <mi>A</mi> <mi>B</mi> <msub> <mi>C</mi> <mn>5</mn> </msub> <mrow> <mo>(</mo> <mi>G</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> is orange.</p>
Full article ">
Back to TopTop