Let $kgeq 1$ be an integer, and $G=(V,E)$ be a finite and simplegraph. The closed neighborhood $N_G[e]$ of an edge $e$ in a graph$G$ is the set consisting of $e$ and all edges having a commonend-vertex with $e$. A signed Roman edge $k$-dominating function(SREkDF) on a graph $G$ is a function $f:E rightarrow{-1,1,2}$ satisfying the conditions that (i) for every edge $e$of $G$, $sum _{xin N[e]} f...

let $d$ be a digraph with vertex set $v(d)$. for vertex $vin v(d)$, the degree of $v$,denoted by $d(v)$, is defined as the minimum value if its out-degree and its in-degree.now let $d$ be a digraph with minimum degree $deltage 1$ and edge-connectivity$lambda$. if $alpha$ is real number, then the zeroth-order general randic index is definedby $sum_{xin v(d)}(d(x))^{alpha}$. a digraph is maximall...

free book of your choice* such as the 25th Anniversary Edition of Crisis and Leviathan: Critical Episodes in the Growth of American Government, by Founding Editor Robert Higgs. This quarterly journal, guided by co-editors Christopher J. Coyne, and Michael C. Munger, and Robert M. Whaples offers leading-edge insights on today’s most critical issues in economics, healthcare, education, law, histo...

free book of your choice* such as the 25th Anniversary Edition of Crisis and Leviathan: Critical Episodes in the Growth of American Government, by Founding Editor Robert Higgs. This quarterly journal, guided by co-editors Christopher J. Coyne, and Michael C. Munger, and Robert M. Whaples offers leading-edge insights on today’s most critical issues in economics, healthcare, education, law, histo...

We propose a multi-focus image fusion method. The energy of Laplacian of input images is obtained to decide which portions of the input images are in better focus, and the majority filter offers a means of spreading the focused regions to neighborhood. The edge-preserving guided image filter is applied to reduce the block effect. We conduct several experiments which demonstrate that it provided...

Convolutional neural networks (CNNs) are good at extracting contexture features within certain receptive fields, while transformers can model the global long-range dependency features. By absorbing advantage of transformer and merit CNN, Swin Transformer shows strong feature representation ability. Based on it, we propose a cross-modality fusion model, <bold xmlns:mml="http://www.w3.org/1998/Ma...

We describe the mission and practices of the Language Sciences Research Lab, a fully functional research lab embedded within a science museum. Within this environment, we integrate cutting-edge research, formal instruction, informal learning, and outreach to the public so that our work in each domain interacts with and enriches the others. We are guided by core concepts from the field of inform...

We have explored mechanisms for converting organizations to an edge type organization. Beyond structural differences, organizations differ in information flow network and information sharing strategies. We review organizational adaptation. A model of computational organization and reorganization is presented using dynamic roles. In addition to self-organization, our model allows human oversight...

We explore using relevant tweets of a given news article to help sentence compression for generating compressive news highlights. We extend an unsupervised dependency-tree based sentence compression approach by incorporating tweet information to weight the tree edge in terms of informativeness and syntactic importance. The experimental results on a public corpus that contains both news articles...

Effective growth of multiwalled boron nitride nanotubes (BNNTs) has been obtained by thermal chemical vapor deposition (CVD). This is achieved by a growth vapor trapping approach as guided by the theory of nucleation. Our results enable the growth of BNNTs in a conventional horizontal tube furnace within an hour at 1200 °C. We found that these BNNTs have an absorption band edge of 5.9 eV, appro...