Abstract
The BC-subtree (a subtree in which any two leaves are at even distance apart) number index is the total number of non-empty BC-subtrees of a graph, and is defined as a counting-based topological index that incorporates the leaf distance constraint. In this paper, we provide recursive formulas for computing the BC-subtree generating functions of multi-fan and multi-wheel graphs. As an application, we obtain the BC-subtree numbers of multi-fan graphs, r multi-fan graphs, multi-wheel (wheel) graphs, and discuss the change of the BC-subtree numbers between different multi-fan or multi-wheel graphs. We also consider the behavior of the BC-subtree number in these structures through the study of extremal problems and BC-subtree density. Our study offers a new perspective on understanding new structural properties of cyclic graphs.
1. Introduction
A topological index is a numerical graph invariant that can quantitatively characterize the properties of the corresponding structure. Topological indices in general have applications in numerous areas such as network design, compounds synthesis, pharmacology, and biology. Consequently a large number (approximately four hundred) of topological indices have been introduced during previous decades.
Among various topological indices, distance-based [1,2,3,4], degree-based [5,6,7,8], counting-based [9,10,11,12,13] have received much attention [14,15,16,17], and many indices have been employed as tools for characterization of molecular topology [18,19,20,21].
Compared to the subtree number index [22,23,24,25,26], the BC-subtree number index is a counting-based topological index that incorporates leaf distance constraint. First of all, a BC-tree is a tree in which any two leaves are at even distance apart. This important structure was introduced by F. Harary et al. [27,28]. The BC-subtree number index or simply the BC-subtree index was first introduced in [13], as the number of all non-empty BC-subtrees (subtrees that are also BC-trees) of a graph.
Much work has been done on the BC-trees and BC-subtree number index. Some examples include generic chemical structures storage problem [29,30], fault-tolerant computing and parallel scheduling [31,32], recognizing and identifying special substructures [33,34,35], the flow network simplification [36], Markovian queueing systems decomposition [37], matching problem [38,39], extremal and density problems [13,40], and enumerating algorithm design [13,41].
We are particularly interested in the enumeration of BC-subtrees. Using a generating functional approach proposed by Yan and Yeh in [12] (for general subtrees), Yang et al. [13] presented algorithms of enumerating BC-subtrees of trees. Later Yang et al. [41] solved the BC-subtree enumeration problem on uni-cyclic and edge-disjoint bicyclic graphs and further generalized this study to spiro and polyphenyl hexagonal chains [40].
Previous studies show that the multi-fan and multi-wheel graphs (Definitions 1 and 2) have many interesting properties and applications in circuit layout and interconnection network design. The is also useful in designing efficient wireless ad hoc networks [42]. The wheel-transposition graphs (graphs generated by wheel graphs) could be used in parallel and distributed system [43]. Both the multi-fan graphs and the wheel graphs are among the graphs that can be determined by its Laplacian spectra [44,45]. Moreover, the Hilbert series of fan graphs, multi-fan graphs and multi-wheel graphs were derived in [46]. Subtrees of Fan Graphs, Wheel Graphs, and “Partitions” of Wheel Graphs under Dynamic Evolution was studied in [47]. In this paper we will consider the BC-subtree number index for these two structures.
We first introduce related preliminary information in Section 2. The BC-subtree generating functions of multi-fan graphs and multi-wheel graphs are provided in Section 3 and Section 4. Some special cases are also discussed as immediate consequences. In Section 5 we make use of our findings to consdier the behavior of the BC-subtree number in the above mentioned structures. Extremal problems are studied. We summarize our work in Section 6.
2. Preliminaries
Before introducing our main results there are quite some preparations to do. Let be a weighted graph with vertex set , edge set , vertex-weight function ( and are the odd, even weight of , respectively) and edge-weight function for . First we list the necessary notations and terminologies.
2.1. Basic Notations
- : the distance between and .
- : the graph after removing Y from G.
- : the leaf set of T.
- , : the odd, even weight of , respectively.
- : the subtree set of G containing X, where X can be a vertex set or an edge set (or both), or a subtree of G.
- : the subtree set of G containing v such that all leaves (excluding v) have odd distance from v; the subtrees in are called the -subtrees of G.
- : the subtree set of G containing v such that all leaves (excluding v) have even distance from v; Note that the single vertex tree v itself is included in this set and we call subtrees in the -subtrees of G.
- , : the , weight of subtree , respectively.
- : the BC-subtree set of G.
- : the set of BC-subtrees of G containing X, where X can be a vertex set or an edge set (or both), or a subtree of G.
- : the BC-weight of .
- : the sum of BC-weight of BC-subtrees in .
- : the number of BC-subtrees in set .
Given and v a fixed vertex of , let
and
Then:
- the weight of , denoted by , is:
- -
- If is a weighted single vertex v, then ;
- -
- otherwise,
- the weight of , denoted by , is defined as:
- -
- If is a weighted single vertex v, then ;
- -
- otherwise, .
The odd, even generating function of are respectively defined as
and
Similarly, for a given BC-subtree of a weighted graph G, we define
and
where .
The BC-weight of is
and the BC-subtree generating function of G is
Similarly,
Let (resp. ) denote the number of -subtrees (resp. -subtrees) in (resp. ). Then
and
2.2. Facts
With the above notations we introduce some previously established results that will be used in our arguments.
Let be a weighted tree of order with vertex weight function for and edge weight function for , assume be a pendant vertex and the pendant edge of T, let of order be the weighted tree constructed from T through “contracting” as follows: , , and
for any , and for any .
Lemma 1
([13]). Following the above notations, we have and .
Lemma 2
([13]). Let be a path on n vertices with vertex weight function for all and edge weight function for all . Then,
Lemma 3
([13]). Let be a star on vertices with vertex weight function for all and edge weight function for all . Then,
A unicyclic graph is a connected graph whose number of edges is equal to the number of vertices.
Lemma 4
([41]). Let be a weighted unicyclic graph of order n with no pendant vertices, whose vertex weight function for all and edge weight function for all . Then,
2.3. Observations
We now move on to establish some new observations to facilitate our discussion of the main results later.
Let be a weighted tree on vertices, with the vertex weight function for and the edge weight function for . Let be a subtree of T and define the weighted subtree constructed from T through contracting leaves of T recursively with , and as follows:
- Choose a pendant vertex and let denote the pendant edge;
- Update the odd, even weight of , and edge weight with rule as described in Lemma 1;
- Remove the vertex , edge and set ;
- Repeat the contracting process until the remaining tree is the weighed tree , with , and .
From Lemma 1 we have the following two observations as immediate consequences. We skip the repetitive details.
Theorem 1.
Given a subtree of containing vertex v, and let be the weighted subtree defined above, then, the odd and even generating functions of , denoted by and , respectively, are
where , and .
Theorem 2.
Given a subtree of , and let be the weighted subtree obtained from T defined above, then, the BC-subtree generating function of T containing the subtree is
where is a leaf, , and .
We now establish the following for general graphs.
Theorem 3.
Let graph be obtained from and by identifying the unique common vertex c (see Figure 1), with the vertex weight function for and the edge weight function for . Then
Figure 1.
Weighted graph G.
If the vertex weight function for , then we have
Proof.
We will prove the claimed expression by considering different cases of the BC-subtrees of G containing c:
where
- (i)
- is the set of BC-subtrees in such that all edges of each BC-subtree are only in ;
- (ii)
- is the set of BC-subtrees in such that all edges of each BC-subtree are only in ;
- (iii)
- is the set of BC-subtrees in such that edges of each BC-subtree are in both and .
It is easy to see that the BC-subtree generating function of and are
and
Next, note that
where
- (a)
- , where are the trees obtained from and by identifying the vertex c;
- (b)
- , where are the trees obtained from and by identifying their vertex c.
From these cases we can obtain the BC-subtree generating function of BC-subtree in as
The theorem thus follows. □
Through similar analysis we can also obtain the odd and even generating functions of . We skip the technical details.
Theorem 4.
Let graph be obtained from and with the unique common vertex c (see Figure 1), with the vertex weight function for and the edge weight function for . Then
and
If the vertex weight function for , then we have
and
2.4. Further Definitions
We now introduce the graph structures under consideration in this paper.
Recall that is a star on vertices, is a path on n vertices, and is a cycle on n vertices. A fan graph, denoted by , is a graph formed by adding an additional vertex adjacent to every vertex of . A wheel graph is a graph formed from a cycle by adding a vertex adjacent to every vertex of .
Assume and are two disjoint graphs, a graph is called the disjoint union of and , if and . Moreover, let the product denote the graph obtained from by adding edges with and . In the specifal case when is a single vertex c, we write as .
Definition 1.
Let , and () be k distinct paths on vertices, and each has copies with , then, the graph
is called a multi-fan graph, where is the disjoint union of paths and is the center vertex (see Figure 2).
Figure 2.
The multi-fan graph .
Clearly, in the case of and , the multi-fan graph is just the fan graph . For convenience we call the subgraph () of multi-fan graph the sub-fan graph . It is easy to see that the fan graph is the single vertex for the case , and is an edge for the case .
Definition 2.
Let and () be k distinct cycles on vertices. Suppose each has copies with . Then, the graph
is called a multi-wheel graph, where is the disjoint union of cycles and is the center vertex.
Clearly, in the case of and , the multi-wheel graph is just the wheel graph . Similarly, we call the subgraph () of multi-wheel graph the sub-wheel graph .
Definition 3.
Let be the multi-fan graph with . Then we also call G the multi-fan graph, and is denoted by .
If , then let , , , and we call the r quasi-regular multi-fan graph.
Otherwise, let , , and we call the r regular multi-fan graph.
3. BC-Subtree Generating Functions of Multi-Fan Graphs
We now move on to study the BC-subtree generating functions. First we consider the multi-fan graphs in this section.
Theorem 5.
Let be a multi-fan graph with center vertex , the vertex weight function for and the edge weight function for . For convenience we denote by and by . Then
and
with
and , , .
Proof.
First we consider two cases for the BC-subtrees of multi-fan graph :
- (i)
- ones not containing the center ;
- (ii)
- ones containing the center .
With Lemma 2, we have the BC-subtree generating function of case (i) as
With slightly more complicated structure analysis, Theorems 3 and 4, we have the BC-subtree generating function of case (ii) as
Similarly, the odd and even generating functions, the BC-subtree generating functions of multi-fan graph () containing are, respectively,
We now label the non-center vertices of the sub-fan graph () as in counterclockwise order. In what follows, we further focus on computing the odd and even generating functions, and the BC-subtree generating functions of () containing .
Let , then we have
and
where
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , but not or ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , , but not ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , , but not ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , and .
We now study each case:
- (a)
- ;
- (b)
- , where is the tree obtained from , by attaching an edge at vertex ;
- (c)
- The set can be written as
where ;
- (d)
- Evidently, each must not contain the edge . We further consider these subtrees by cases of containing edges but not , for , which can be rewritten as:
where . Note that is the single vertex .
By the definitions of weight, weight, odd, even generating function of subtrees containing a fixed vertex, (a)–(d), and Theorem 1, we have the followings.
with , .
Similarly for the BC-subtrees, through case analysis of BC-subtree generating function, BC-weight of , and by Theorem 2, we have
and
Next we consider the BC-subtree generating function of some special cases of multi-fan graphs. First of all the BC-subtree generating function of the r multi-fan graph () follows from Theorem 5.
Theorem 6.
Let ( is a positive integer) be the r multi-fan graph defined in Definition 3 with vertex weight function for and the edge weight function for , then
with
and , , .
Letting in the above statements we immediately have the following two consequences.
Corollary 1.
Let be a multi-fan graph, then the BC-subtree number of G is
with
and
and .
Corollary 2.
The BC-subtree number of the r multi-fan graph (see Definition 3), the fan graph (), and the fan graph () containing are, respectively, the following:
with
.
Remark 1.
From Corollary 2 we have for the case of 1 multi-fan graph (i.e., the star ), agreeing with Lemma 3.
4. BC-Subtree Generating Functions of Multi-Wheel Graphs
We now study the BC-subtree generating functions of the multi-wheel graphs (Definition 2).
Theorem 7.
Proof.
Firstly, consider the BC-subtrees of multi-wheel graph in two cases:
- (i)
- ones not containing the center ;
- (ii)
- ones containing the center .
From Lemma 4, we have the BC-subtree generating function for case (i) as
Similar to the previous section, we have the BC-subtree generating function of case (ii) as
where
Now label the non-center vertices of wheel graph () with . For convenience we let (), and (). We partition the set of and into five cases:
where
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , but not ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contains and , but neither nor ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , and , but not ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , , and ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , and , but not .
Studying each cases, we have:
(a) ;
(b) . Note that , thus we have , where ;
(c) . Similarly, , where ;
(d) We can further divide the subtree set into cases of subtrees containing edge set , but not (recursively for ). That is,
where ;
(e) is the subtree set of . Denote by the graph after removing edge set from . Thus and evidently ,
Similar to the previous case, we partition the set of and into four cases:
where
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , but not or ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain and , but not ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain , and ;
- (resp. ) is the set of subtrees (resp. BC-subtrees) that contain and , but not .
Again, we have that is the graph obtained from after removing edge set . Clearly, .
We also have
and
From the cases (a)–(e), Theorem 1, and by the definitions of weight, weight, odd, even generating function of subtrees containing a fixed vertex, we have
where ;
where .
Thus, by Equations (29), (30) and (62)–(67) we have
and
with , as in Equations (29) and (30), respectively, and , .
Through similar reasoning, we have
where .
The BC-subtree generating function of the wheel graph (where n is a positive integer) follows from Theorem 7 and Lemma 4.
Theorem 8.
Letting in Theorems 7 and 8, respectively, we immediately have the following.
Corollary 3.
Corollary 4.
The BC-subtree number of is
where
and
with .
Directly from Corollary 4 we may generate the BC-subtree number of (see Table 1).
Table 1.
The BC-subtree number of wheel graph ().
5. The Behavior of the BC-Subtrees
With the theoretical foundation that was established in the previous sections, we will study the behavior of the BC-subtree number in the multi-fan and multi-wheel graphs. We first mention an extremal result as a simple consequence. We also briefly discuss the change of the BC-subtree numbers between different multi-fan or multi-wheel graphs. Lastly we consider the BC-subtree density in these structures.
5.1. BC-Subtree Number of
The extremely problems with respect to a topological index concerns finding the extremal structures, among a given class of graphs, that maximize or minimize the index. These graphs always possess the best or worst of some desired properties [48,49,50]. We first point out the following simple fact.
Proposition 1.
The has BC-subtrees, fewer than any other ; the has more BC-subtrees than any other .
It is often interesting to know, when studying extremal problems, which graph structures have the second or third largest or smallest values of a certain index. To shed some light on this we ran some simulation, whose result is shown in Figure 3, with Cartesian and semi-log (Log-Y) coordinate, respectively.
Figure 3.
BC-subtree numbers of with , r from 1 to n, respectively.
From Figure 3a, it appears that among all , seems to have the second largest BC-subtree number, and the seems to be the third largest BC-subtree number for odd (or sufficient large) n.
It is also interesting to observe the change of the BC-subtree number as r changes, with the “local minimum” spread out for smaller values of r.
From Corollary 4 we can obtain data of similar nature for . Figure 4 confirms the simple fact that the BC-subtree numbers of increase very fast. The asymptotic expression of the BC-subtree number of seems to be . This is something that can be further verified through analytic combinatorics approaches.
Figure 4.
Original BC-subtree number and the corresponding data fitted by linear regression of .
5.2. BC-Subtree Density
The generating function approach provides us with much more information than just the BC-subtree number. In particular, we will examine the BC-subtree density here, for r multi-fan graph () and , respectively. For some of the work on this topic one may see [40].
Definition 4
([40]). Assume G is a graph with n vertices and k BC-subtrees of orders , then denotes the average order of BC-subtrees of G, and the BC-subtree density of G is defined as .
First it is easy to see that
Letting in Theorem 6 and Theorem 8, we could obtain the so called edge generating function of BC-subtrees of and , respectively, i.e., and ).
By the definition of BC-subtree density and Equation (83), the BC-subtree density of ( or ) is simply
Figure 5.
BC-subtree densities of r multi-fan .
Table 2.
Data related to BC-subtrees of , with and .
Similarly, with Theorem 8 we obtain the generating function . Together with Equation (84) we can obtain the BC-subtree densities of (see Figure 6 and Table 3).
Figure 6.
BC-subtree densities of wheel graph .
Table 3.
Data related to BC-subtrees of wheel graph .
6. Concluding Remarks
Motivated from the past studies of BC-trees, BC-subtrees, as well as the applications of structural properties of network graphs [51], we provide recursive formulae for computing the BC-subtree generating functions of multi-fan and multi-wheel graphs, and also derive the BC-subtree numbers of multi-fan graphs, r multi-fan graphs, multi-wheel (wheel) graphs. Moreover, the behavior of the BC-subtree numbers between different multi-fan or multi-wheel graphs, and extremal problems and BC-subtree density are also briefly discussed. These findings are likely useful in further understanding the properties and behaviors of these graphs. For future work it would be interesting to consider other well known topological indices on the multi-fan and multi-wheel graphs and compare their behaviors with that of the BC-subtree number.
Author Contributions
H.W. and W.W. contribute for supervision, project administration and formal analysis. L.L. and Y.Y. contribute for methodology and writing original draft preparation. The final draft we written by H.W. and Y.Y. All authors have read and agreed to the published version of the manuscript.
Funding
This work is supported by the National Natural Science Foundation of China (grant nos. 61702291,11801371); the Program for Science & Technology Innovation Talents in Universities of Henan Province (grant no. 19HASTIT029), the Key Research Project in Universities of Henan Province (grant nos. 19B110011, 19B630015),the Scientific Research Starting Foundation for High-Level Talents of Pingdingshan University (grant no.PXY-BSQD2017006).
Conflicts of Interest
The authors declare no conflict of interest.
References
- Wiener, H. Structural determination of paraffin boiling points. J. Am. Chem. Soc. 1947, 1, 17–20. [Google Scholar] [CrossRef]
- Xu, K.; Das, K.C. On Harary index of graphs. Discret. Appl. Math. 2011, 159, 1631–1640. [Google Scholar] [CrossRef]
- Sun, Q.; Ikica, B.; Škrekovski, R.; Vukašinović, V. Graphs with a given diameter that maximise the Wiener index. Appl. Math. Comput. 2019, 356, 438–448. [Google Scholar] [CrossRef]
- Binu, M.; Mathew, S.; Mordeson, J. Wiener index of a fuzzy graph and application to illegal immigration networks. Fuzzy Sets Syst. 2020, 384, 132–147. [Google Scholar] [CrossRef]
- Dimitrov, D.; Milosavljević, N. Efficient computation of trees with minimal atom-bond connectivity Index revisited. Match Commun. Math. Comput. Chem. 2018, 79, 431–450. [Google Scholar]
- Milovanović, E.; Milovanović, I.; Matejić, M. Remark on spectral study of the geometric–arithmetic index and some generalizations. Appl. Math. Comput. 2018, 334, 206–213. [Google Scholar] [CrossRef]
- Sah, A.; Sawhney, M. On the Discrepancy Between Two Zagreb Indices. Discret. Math. 2018, 341, 2575–2589. [Google Scholar] [CrossRef]
- Zhang, X.; Yang, Y.; Wang, H.; Zhang, X. Maximum atom-bond connectivity index with given graph parameters. Discret. Appl. Math. 2016, 215, 208–217. [Google Scholar] [CrossRef]
- Chen, X.; Zhang, J.; Sun, W. On the Hosoya index of a family of deterministic recursive trees. Phys. Stat. Mech. Its Appl. 2017, 465, 449–453. [Google Scholar] [CrossRef]
- De Ita Luna, G.; Raymundo Marcial-Romero, J.; Bello Lopez, P.; Contreras Gonzalez, M. Linear-time algorithms for computing the Merrifield-Simmons index on polygonal trees. Match Commun. Math. Comput. Chem. 2018, 79, 55–78. [Google Scholar]
- Huang, Y.; Shi, L.; Xu, X. The Hosoya index and the Merrifield–Simmons index. J. Math. Chem. 2018, 56, 3136–3146. [Google Scholar] [CrossRef]
- Yan, W.; Yeh, Y. Enumeration of subtrees of trees. Theor. Comput. Sci. 2006, 369, 256–268. [Google Scholar] [CrossRef]
- Yang, Y.; Liu, H.; Wang, H.; Makeig, S. Enumeration of BC-subtrees of trees. Theor. Comput. Sci. 2015, 580, 59–74. [Google Scholar] [CrossRef]
- Lin, W.; Chen, J.; Wu, Z.; Dimitrov, D.; Huang, L. Computer search for large trees with minimal ABC index. Appl. Math. Comput. 2018, 338, 221–230. [Google Scholar] [CrossRef]
- Wagner, S.G. Correlation of graph-theoretical indices. SIAM J. Discret. Math. 2007, 21, 33–46. [Google Scholar] [CrossRef]
- Yang, Y.; Liu, H.; Wang, H.; Deng, A.; Magnant, C. On Algorithms for Enumerating Subtrees of Hexagonal and Phenylene Chains. Comput. J. 2017, 60, 690–710. [Google Scholar] [CrossRef]
- Zhou, Q.; Wang, L.; Lu, Y. Wiener index and Harary index on Hamilton-connected graphs with large minimum degree. Discret. Appl. Math. 2018, 247, 180–185. [Google Scholar] [CrossRef]
- Joiţa, D.M.; Jäntschi, L. Extending the characteristic polynomial for characterization of C20 fullerene congeners. Mathematics 2017, 5, 84. [Google Scholar] [CrossRef]
- García-Pereira, I.; Zanni, R.; Galvez-Llompart, M.; Galvez, J.; García-Domenech, R. DesMol2, an effective tool for the construction of molecular libraries and its application to QSAR using molecular topology. Molecules 2019, 24, 736. [Google Scholar] [CrossRef]
- Bonchev, D. The overall Wiener index–a new tool for characterization of molecular topology. J. Chem. Inf. Model. 2001, 41, 582–592. [Google Scholar]
- Bonchev, D. Chapter 3—On the Concept for Overall Topological Representation of Molecular Structure. In Advances in Mathematical Chemistry and Applications; Basak, S.C., Restrepo, G., Villaveces, J.L., Eds.; Bentham Science Publishers: Sharjah, UAE, 2015; pp. 42–75. [Google Scholar]
- Yang, Y.; Sun, X.J.; Cao, J.Y.; Wang, H.; Zhang, X.D. The expected subtree number index in random polyphenylene and spiro chains. Discret. Appl. Math. 2020, 285, 483–492. [Google Scholar] [CrossRef]
- Sills, A.V.; Wang, H. The minimal number of subtrees of a tree. Graphs Comb. 2015, 31, 255–264. [Google Scholar] [CrossRef]
- Székely, L.; Wang, H. On subtrees of trees. Adv. Appl. Math. 2005, 34, 138–155. [Google Scholar] [CrossRef]
- Zhang, X.; Zhang, X. The minimal number of subtrees with a given degree sequence. Graphs Comb. 2015, 31, 309–318. [Google Scholar] [CrossRef]
- Zhang, X.; Zhang, X.; Gray, D.; Wang, H. The number of subtrees of trees with given degree sequence. J. Graph Theory 2013, 73, 280–295. [Google Scholar] [CrossRef]
- Harary, F.; Plummer, M. On the core of a graph. Proc. Lond. Math. Soc. 1967, 17, 249–257. [Google Scholar] [CrossRef]
- Harary, F.; Prins, G. The block-cutpoint-tree of a graph. Publ. Math. Debr. 1966, 13, 103–107. [Google Scholar]
- Nakayama, T.; Fujiwara, Y. BCT Representation of Chemical Structures. J. Chem. Inf. Comput. Sci. 1980, 20, 23–28. [Google Scholar] [CrossRef]
- Nakayama, T.; Fujiwara, Y. Computer representation of generic chemical structures by an extended block-cutpoint tree. J. Chem. Inf. Comput. Sci. 1983, 23, 80–87. [Google Scholar] [CrossRef]
- Frederickson, G.N.; Hambrusch, S.E. Planar linear arrangements of outerplanar graphs. IEEE Trans. Circuits Syst. 1988, 35, 323–333. [Google Scholar] [CrossRef]
- Wada, K.; Luo, Y.; Kawaguchi, K. Optimal fault-tolerant routings for connected graphs. Inf. Process. Lett. 1992, 41, 169–174. [Google Scholar] [CrossRef]
- Gagarin, A.; Labelle, G. Two-connected graphs with prescribed three-connected components. Adv. Appl. Math. 2009, 43, 46–74. [Google Scholar] [CrossRef][Green Version]
- Heath, L.; Pemmaraju, S. Stack and queue layouts of directed acyclic graphs: Part II. SIAM J. Comput. 1999, 28, 1588–1626. [Google Scholar] [CrossRef][Green Version]
- Paton, K. An algorithm for the blocks and cutnodes of a graph. Commun. ACM 1971, 14, 468–475. [Google Scholar] [CrossRef]
- Misiolek, E.; Chen, D.Z. Two flow network simplification algorithms. Inf. Process. Lett. 2006, 97, 197–202. [Google Scholar] [CrossRef]
- Fox, D. Block cutpoint decomposition for markovian queueing systems. Appl. Stoch. Model. Data Anal. 1988, 4, 101–114. [Google Scholar] [CrossRef]
- Barefoot, C. Block-cutvertex trees and block-cutvertex partitions. Discret. Math. 2002, 256, 35–54. [Google Scholar] [CrossRef][Green Version]
- Mkrtchyan, V. On trees with a maximum proper partial 0–1 coloring containing a maximum matching. Discret. Math. 2006, 306, 456–459. [Google Scholar] [CrossRef]
- Yang, Y.; Liu, H.; Wang, H.; Sun, S. On Spiro and polyphenyl hexagonal chains with respect to the number of BC-subtrees. Int. J. Comput. Math. 2017, 94, 774–799. [Google Scholar] [CrossRef]
- Yang, Y.; Liu, H.; Wang, H.; Feng, S. On algorithms for enumerating BC-subtrees of unicyclic and edge-disjoint bicyclic graphs. Discret. Appl. Math. 2016, 203, 184–203. [Google Scholar] [CrossRef]
- Yang, Z.; Liu, Y.; Li, X.Y. Beyond trilateration: On the localizability of wireless ad hoc networks. IEEE/ACM Trans. Netw. (ToN) 2010, 18, 1806–1814. [Google Scholar] [CrossRef]
- Tu, J.; Zhou, Y.; Su, G. A kind of conditional connectivity of Cayley graphs generated by wheel graphs. Appl. Math. Comput. 2017, 301, 177–186. [Google Scholar] [CrossRef]
- Liu, X.; Zhang, Y.; Gui, X. The multi-fan graphs are determined by their Laplacian spectra. Discret. Math. 2008, 308, 4267–4271. [Google Scholar] [CrossRef]
- Zhang, Y.; Liu, X.; Yong, X. Which wheel graphs are determined by their Laplacian spectra? Comput. Math. Appl. 2009, 58, 1887–1890. [Google Scholar] [CrossRef]
- Kumar, A.; Sarkar, R. Hilbert series of binomial edge ideals. Commun. Algebra 2019, 47, 3830–3841. [Google Scholar] [CrossRef]
- Yang, Y.; Wang, A.; Wang, H.; Zhao, W.T.; Sun, D.Q. On Subtrees of Fan Graphs, Wheel Graphs, and “Partitions” of Wheel Graphs Under Dynamic Evolution. Mathematics 2019, 5, 472. [Google Scholar] [CrossRef]
- Cao, S.; Dehmer, M.; Shi, Y. Extremality of degree-based graph entropies. Inf. Sci. 2014, 278, 22–33. [Google Scholar] [CrossRef]
- Székely, L.A.; Wang, H. Extremal values of ratios: Distance problems vs. subtree problems in trees. Electron. J. Comb. 2013, 20, P67. [Google Scholar] [CrossRef]
- Wang, H. The extremal values of the Wiener index of a tree with given degree sequence. Discret. Appl. Math. 2008, 156, 2647–2654. [Google Scholar] [CrossRef]
- Allen, B.; Lippner, G.; Chen, Y.T.; Fotouhi, B.; Momeni, N.; Yau, S.T.; Nowak, M.A. Evolutionary dynamics on any population structure. Nature 2017, 544, 227. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).