Graphs are (1,Δ+1)-choosable

A graph $G$ is $(k,k^{\prime })$-choosable if the following holds: For any list assignment $L$ which assigns to each vertex $v$ a set $L\left(v\right)$ of $k$ real numbers, and assigns to each edge $e$ a set $L\left(e\right)$ of $k^{\prime }$ real numbers, there is a total weighting $?:V\left(G\right)\cup E\left(G\right)\to R$ such that $?\left(z\right)\in L\left(z\right)$ for $z\in V\cup E$, and ${\sum }_{e\in E\left(u\right)}?\left(e\right)+?\left(u\right)\ne {\sum }_{e\in E\left(v\right)}?\left(e\right)+?\left(v\right)$ for every edge $uv$. This paper proves that if $G$ is a connected graph of maximum degree $\Delta \ge 2$, then $G$ is $(1,\Delta +1)$-choosable.     

The concept of dual roles design in clean organic preparation

Herein we summarized some clean preparation examples to emphasize the concept of dual roles design (or named as “two birds one stone strategy”) in green and sustainable chemistry. In those examples, the reactants and/or solvent play dual roles rendering a cleaner organic preparation process. Consequently, both the chemical waste and manufacturing cost could be reduced.     

A nickel oxide nanoflakes/reduced graphene oxide composite and its high-performance lithium-storage properties

Journal of Solid State Electrochemistry - Since conventional graphite-based anode possesses a low capacity, seeking for high-capacity anode candidates becomes significant for constructing emerging...     

Iteratively weighted thresholding homotopy method for the sparse solution of underdetermined linear equations

Recently, iteratively reweighted methods have attracted much interest in compressed sensing, outperforming their unweighted counterparts in most cases. In these methods, decision variables and weights are optimized alternatingly, or decision variables are optimized under heuristically chosen weights. In this paper,we present a novel weighted l1-norm minimization problem for the sparsest solution of underdetermined linear equations. We propose an iteratively weighted thresholding method for this problem, wherein decision variables and weights are optimized simultaneously. Furthermore, we prove that the iteration process will converge eventually. Using the homotopy technique, we enhance the performance of the iteratively weighted thresholding method. Finally, extensive computational experiments show that our method performs better in terms of both running time and recovery accuracy compared with some state-of-the-art methods.     

Quantifying the quantumness of ensembles via generalized α-z-relative rényi entropy

International Journal of Theoretical Physics - Quantifying the quantumness of ensembles is a vital and practical task in quantum information theory. In this paper, we quantify the quantumness of...     

Stability and control of radial deployment of electric solar wind sail

Nonlinear Dynamics - The paper studies the stability and control of radial deployment of an electric solar wind sail with the consideration of high-order modes of elastic tethers. The electric...     

The extremal irregularity of connected graphs with given number of pendant vertices

Czechoslovak Mathematical Journal - The irregularity of a graph G = (V, E) is defined as the sum of imbalances ∣du ? dv∣ over all edges uv ∈ E, where du denotes the degree...     

A new MnxOy/carbon nanorods derived from bimetallic Zn/Mn metal–organic framework as an efficient oxygen reduction reaction electrocatalyst for alkaline Zn-Air batteries

Journal of Solid State Electrochemistry - In this work, nanorods like bimetallic Zn/Mn metal–organic-frameworks (MOFs) are proposed as the precursor for preparing MnxOy/porous carbon...     

A Stochastic Subgradient Method for Distributionally Robust Non-convex and Non-smooth Learning

Journal of Optimization Theory and Applications - We consider a distributionally robust formulation of stochastic optimization problems arising in statistical learning, where robustness is with...