By applying the method of generating functions, the purpose of this paper is to give several summations of reciprocals related to the quintuple product of the general second-order recurrence \(\{W_{rn}\}\) for arbitrary positive integers \(r\). As applications, some identities involving Fibonacci and Lucas numbers are obtained.

A collection \(\mathcal{S}\) of proper subgroups of a group \(G\) is said to be a cover (or covering) for \(G\) if the union of the members of \(\mathcal{S}\) is all of \(G\). A cover \(\mathcal{C}\) of minimal cardinality is called a minimal cover for \(G\) and \(|\mathcal{C}|\) is called the covering number of \(G\), denoted by \(\sigma(G)\). In this paper we determine the covering numbers of the alternating groups \(A_9\) and \(A_{11}\).

Given a (not necessarily proper) coloring of a digraph \( c:V(D)\rightarrow {N}\), let \( OC(v)\) denote the set of colors assigned to the out-neighbors of \(v\). Similarly, let \( IC(v)\) denote the set of colors assigned to the in-neighbors of \(v\). Then \(c\) is a set coloring of \(D\) provided \((u,v) \in A(D)\) implies \( OC(u) \neq OC(v)\). Analogous to the set chromatic number of a graph given by Chartrand, \(et\) \(al.\) \([3]\), we define \( \chi_s(D) \) as the minimum number of colors required to produce a set coloring of \(D\). We find bounds for \(\chi_s(D)\) where \(D\) is a digraph and where \(D\) is a tournament. In addition we consider a second set coloring, where \((u,v) \in A(D)\) implies \( OC(u) \neq IC(v)\).

Let \(\mathcal{C}\) be a finite family of distinct boxes in \(\mathbb{R}^d\), with \(G\) the intersection graph of \(\mathcal{C}\), and let \(S = \cup\{C : C \in \mathcal{C}\}\). For each block of \(G\), assume that the corresponding members of \(\mathcal{C}\) have a staircase convex union. Then when \(S\) is staircase starshaped, its staircase kernel will be a staircase convex set. Moreover, this result (and others) will hold for more general families \(\mathcal{C}\) as well.

The domination chain \(\iota_r(G) \leq \gamma(G) \leq \iota(G) \leq \beta_o(G) \leq \Gamma(G) \leq IR(G)\), which holds for any graph \(G\), is the subject of much research. In this paper, we consider the maximum number of edges in a graph having one of these domination chain parameters equal to \(2\) through a unique realization. We show that a specialization of the domination chain still holds in this setting.

In this paper, we study further bounds of constant dimension codes in Grassmannian space \(\mathcal{G}_q(n,k)\). There is increasing interest in subspace codes since they are essential for error-correction in networks. Additionally, there is a connection to the theory over finite fields. By revising the specific construction methods of the constant dimension codes in [1], [2], we improve some bounds on \(q\)-ary constant dimension codes in certain cases.

In this paper, we use a recent result of Bryant, Horsley, and Pettersson in [1] to provide an alternate and more straightforward proof of results concerning neighborhood graphs in maximum packings of \(2K_n\) with triples, some of which were only recently obtained.

To set the stage, consider any partial triple system \((V,B)\) of \(2K_n\). In this system, the neighborhood of a vertex \(v\) is defined as the subgraph induced by the set \(\{\{x,y\} \mid \{v,x,y\} \in B\}\). This concept plays a crucial role in the results initially obtained by Colbourn and Rosa for \(n \equiv 0,1 \pmod{3}\) and by Chaffee and Rodger for \(n \equiv 2 \pmod{3}\). These results offer a complete characterization of the possible neighborhoods in a maximum packing of \(2K_n\).

In both of these original papers, the authors employed difference methods—a combinatorial technique that often involves selecting pairs of elements from a group and studying their differences—and a pull-up technique, which is used to modify the neighborhood of a vertex. However, despite the effectiveness of these methods, neither approach seems to lend itself easily to deriving the results of the other.

In our paper, we present a more unified and simplified proof that brings both of these results together. By leveraging the recent findings of Bryant, Horsley, and Pettersson, we can bypass the need for the more complex difference methods and pull-up techniques, instead relying on the underlying principles elucidated in their work. This approach not only simplifies the proof process but also provides a clearer and more direct route to understanding the structure of neighborhood graphs in these maximum packings.

Compressed sensing (CS) has broken through the traditional Nyquist sampling theory as it is a new technique in signal processing. According to CS theory, compressed sensing makes full use of sparsity so that a sparse signal can be reconstructed from very few measurements. It is well known that the construction of CS matrices is the central problem. In this paper, we provide one kind of deterministic sensing matrix by describing a combinatorial design. Then, we obtain two cases by instantiating the RIP framework with the obtained design, with the latter case being the majorization of the former. Finally, we show that our construction has better properties than DeVore’s construction using polynomials over finite fields.

In this paper, with the help of the residue method, we find some interesting formulas relating residue and ordinary Bell polynomials, \(\hat{B}_{n,k}(x_1,x_2,\ldots)\). Further, we prove identities involving some combinatorial numbers to demonstrate the application of the formulas.

We expand the theory of pebbling to graphs with weighted edges. In a weighted pebbling game, one player distributes a set amount of weight on the edges of a graph and his opponent chooses a target vertex and places a configuration of pebbles on the vertices. Player one wins if, through a series of pebbling moves, he can move at least one pebble to the target. A pebbling move of \(p\) pebbles across an edge with weight \(w\) leaves \(\lfloor pw \rfloor\) pebbles on the next vertex. We find the weighted pebbling numbers of stars, graphs with at least \(2|V|-1\) edges, and trees with given targets. We give an explicit formula for the minimum total weight required on the edges of a length-2 path, solvable with \(p\) pebbles, and exhibit a graph that requires an edge with weight \(1/3\) in order to achieve its weighted pebbling number.