n-Bit Quantum Secret Sharing Protocol Using Quantum Secure Direct Communication

International Journal of Theoretical Physics - The proposed quantum secret sharing protocol in this article conveys n bit secret messages from the sender to the n receivers making use of a secure...     

Carbon–carbon coupling reactions catalyzed by supported Pd porphyrins

The tetrakis(4‐N‐methylpyridinium)porphyrinatopalladium(II) iodide, [Pd(TMPyP)]I₄, supported on Dowex 50WX8 and Amberlite IR‐120 ion‐exchange resins, was used as heterogeneous, recyclable and active catalyst for the Suzuki–Miyaura and Heck cross‐coupling reactions. These catalysts were applied to coupling of various aryl halides with phenylboronic acid and styrene in Suzuki and Heck reactions, respectively, and the corresponding products were obtained in excellent yields and short reaction times. The catalysts could be recovered easily by simple filtration and reused several times without significant loss of their catalytic activity. The catalysts were characterized by diffuse‐reflectance UV–visible spectroscopy and scanning electron microscopy, and their stability was confirmed by TGA. Copyright © 2014 John Wiley & Sons, Ltd.     

Finding the shortest path with honey-bee mating optimization algorithm in project management problems with constrained/unconstrained resources

Effective project management requires the development of a realistic plan and a clear communication of the plan from the beginning to the end of the project. The critical path method (CPM) of scheduling is the fundamental tool used to develop and interconnect project plans. Ensuring the integrity and transparency of those schedules is paramount for project success. The complex and discrete nature of the solution domain for such problems causes failing of traditional and gradient-based methods in finding the optimal or even feasible solution in some cases. The difficulties encountered in scheduling construction projects with resource constraints are highlighted by means of a simplified bridge construction problem and a basic masonry construction problem. The honey-bee mating optimization (HBMO) algorithm has been previously adopted to solve mathematical and engineering problems and has proven to be efficient for searching optimal solutions in large-problem domains. This paper presents the HBMO algorithm for scheduling projects with both constrained and unconstrained resources. Results show that the HBMO algorithm is applicable to projects with or without resource constraints. Furthermore, results obtained are promising and compare well with those of well-known heuristic approaches and gradient-based methods.     

Quasinormal and Hyponormal Weighted Composition Operators on $$H^2$$ and $$A^2_{\alpha }$$Aα2 with Linear Fractional Compositional Symbol

In this paper, we study quasinormal and hyponormal composition operators \(W_{\psi ,\varphi }\)  with linear fractional compositional symbol \(\varphi \) on the Hardy and weighted Bergman spaces. We characterize the quasinormal composition operators induced on \(H^{2}\) and \(A_{\alpha }^{2}\) by these maps and many such weighted composition operators, showing that they are necessarily normal in all known cases. We eliminate several possibilities for hyponormal weighted composition operators but also give new examples of hyponormal weighted composition operators on \(H^2\) which are not quasinormal.     

Single and binary catalyst systems based on nickel and palladium in polymerization of ethylene

The catalyst (N,N‐bis(2,6‐dibenzhydryl‐4‐ethoxyphenyl)butane‐2,3‐diimine)nickel dibromide, a late transition metal catalyst, was prepared and used in ethylene polymerization. The effects of reaction parameters such as polymerization temperature, co‐catalyst to catalyst molar ratio and monomer pressure on the polymerization were investigated. The α‐diimine nickel‐based catalyst was demonstrated to be thermally robust at a temperature as high as 90 °C. The highest activity of the catalyst (494 kg polyethylene (mol cat)^?1 h^?1) was obtained at [Al]/[Ni] = 600:1, temperature of 90 °C and pressure of 5 bar. In addition, the performance of a binary catalyst using nickel‐ and palladium‐based complexes was compared with that of the corresponding individual catalytic systems in ethylene polymerization. In a study of the catalyst systems, the average molecular weight and molecular weight distribution for the binary polymerization were between those for the individual catalytic polymerizations; however, the binary catalyst activity was lower than that of the two individual ones. The obtained polyethylenes had high molecular weights in the region of 10⁵ g mol^?1. Gel permeation chromatography analysis showed a narrow molecular weight distribution of 1.44 for the nickel‐based catalyst and 1.61 for the binary catalyst system. The branching density of the polyethylenes generated using the binary catalytic system (30 branches/1000 C) was lower than that generated using the nickel‐based catalyst (51/1000 C). X‐ray diffraction study of the polymer chains showed higher crystallinity with lower branching of the polymer obtained. Also Fourier transform infrared spectra confirmed that all obtained polymers were low‐density polyethylene.     

In Silico Comparison of Low- and High-Risk Human Papillomavirus Proteins

Human papillomavirus (HPV) is an important pathogen which is classified into two, high- and low-risk groups. The proteins of high-risk and low-risk HPV types have different functions. Therefore, there is a need to develop a computational method for predicting these two groups. In the present study, the physiochemical properties of all early (E1, E2, E4, E5, E6, and E7) and late (L1 and L2) proteins in high- and low-risk HPV types have been studied. The concept of receiver operating characteristic analysis and support vector machines methods has been used for comparison of high- and low-risk HPV types. The results demonstrate that amino acid composition, physiochemical, and secondary structure of E2 protein are significantly different between these two groups. The results demonstrate that in silico properties can create useful information to predict high-risk and low-risk HPV types.