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An efficient method for the construction of 2,4‐diarylbenzo[4,5]thieno[3,2‐d]pyrimidines through the base‐promoted one‐pot three‐component tandem reactions of o‐nitrochalcones, benzamidine hydrochlorides, and elemental sulfur is described. The salient features of this protocol are the use of cheap and abundant sulfur source, readily available starting materials, transition‐metal‐free and mild conditions, satisfactory yield, and simple workup procedures. This transformation can also carry out on gram scale. [ABSTRACT FROM AUTHOR]

A concise method for the construction of 1‐sulfonyl‐1H‐indoles by the reactions of N‐(2‐iodoaryl)sulfonamides with calcium carbide is described. The notable features of this protocol are the use of inexpensive and easy‐to‐handle solid alkyne source as a surrogate of flammable and explosive gaseous acetylene, wide scope of substrates, high yield, and simple reaction procedure. This method can also be extended to gram scale. [ABSTRACT FROM AUTHOR]

The study of secretory protein kinase is an emergent research field in recent years. The secretion phenomenon of type II cGMP‐dependent protein kinase (PKG II) was found in our latest research and our previous study confirmed that PKG II inhibited platelet‐derived growth factor receptor β (PDGFRβ) activation induced by platelet‐derived growth factor BB (PDGF‐BB) within the gastric cancer cells. Thus, this study was designed to investigated effect of secretory PKG II on PDGFRβ. Transwell assay and CCK8 assay indicated that secretory PKG II reversed PDGF‐BB‐induced cell migration, invasion, and proliferation. Immunoprecipitation, GST pull down and Western blotting results showed that secretory PKG II combined with extracellular domains of PDGFRβ and phosphorylated it, and thereby inhibited PDGF‐BB‐induced activation of PDGFRβ, and downstream PI3K/Akt and MAPK/ERK pathways. Mutation at Ser254 of PDGFRβ to alanine abolished the above inhibitory effects of secretory PKG II on PDGFRβ, indicating that Ser254 was the specific site phosphorylated by secretory PKG II. In conclusion, secretory PKG II inhibited PDGFRβ activation via Ser254 site. [ABSTRACT FROM AUTHOR]

Summary: It is well known that virtual network (VN) embedding (VNE) aims to solve how to efficiently allocate physical resources to a VN. However, this issue has been proved to be an NP‐hard problem. Besides, as most of the existing approaches are based on heuristic algorithms, which is easy to fall into local optimal. To address the challenge, we formalize the problem as a mixed integer programming problem and propose a novel VNE method based on reinforcement learning in this article. And to solve the problem, we introduce a pointer network to generate virtual node mapping strategies through an attention mechanism, and design a reward function related to link resource consumption to build the connection between node mapping and link mapping stages of VNE. In addition, we present a policy gradient optimization mechanism to leverage the reward information obtained from the sampled solutions, and design an active search based process to automatically update the parameters of the neural network and to obtain near‐optimal embedding solution. The experimental results show that the proposed method can improve the performance in average physical node utilization and long‐term revenue to cost ratio comparing than that of the existing models. [ABSTRACT FROM AUTHOR]

Efficient and fair resource allocation for multitudinous virtual networks running cloud-based applications is crucial to archive dynamic resources multi-tenancy in cloud computing. In order to solve the problem, we propose a novel virtual network embedding (VNE) algorithm to increase revenue and utilization of substrate network as well as to improve acceptance fairness of virtual networks. First, we present a virtual topology pre-transformation mechanism leveraging reusable technology to reduce topology difference and achieve acceptance fairness. Then, because of the Non-deterministic polynomial-time (NP)-hard characteristics of VNE, we model the problem as an integer linear programming problem and solve the VNE problem with a discrete particle swarm optimization-based algorithm. The operations and parameters of particles are well redefined according to the VNE context. Finally, an incentive convergence mechanism is proposed to reduce mapping complexity, which can be used to accelerate convergence and to save more bandwidth by exploiting individual candidate nodes' lists. Simulation results prove that our proposed method is superior to the existing similar algorithms in terms of physical resource utilization, acceptance fairness, revenue/cost ratio, and searching efficiency. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]