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The literature concerning phenacyl anthranilate, N- phenacylanthranilic acid and phenacyl N-phenacylanthranilate is clarified. Phenacyl anthranilate is dehydrated to 1,5-dihydro-5-oxo-2-pheny 1-4,1-benzoxazepine by treatment with phosphoryl chloride; other examples of this reaction are described. A preparation of 4-methyl-5-oxo-2-phenyloxazolo[3,2-a]quinoline from N-phenacylanthranilic acid and propionic anhydride is reported.  相似文献   
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Reactions of 1,4-diphenyl-1-azabutadiene with allenic esters (1,2) in refluxing benzene furnish the respective cyclohexenone derivatives (3,4) as major products, and presumably proceed via azetidines (B).  相似文献   
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Vinyl acetate and acrylonitrile were copolymerized with Co(acac)3-Al(C2H5)3 catalyst system in benzene at 40°C. The rate of copolymerization is linearly proportional to monomer concentration and catalyst concentrations up to a certain value. The overall activation energy was found to be 11.3 kcal/mole. The effect of hydroquinone on the rate of copolymerization indicates the presence of free radicals in this system. The possibility of simultaneous formation of coordinate anionic and free radical active sites has been proposed.  相似文献   
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A thin-layer chromatographic (TLC) procedure has been developed for the determination of astemizole in plasma as the free and as protein-bound substance. The detection and quantification were performed without using internal standards. In earlier described methods for the estimation of astemizole by high-performance liquid chromatography and radioimmunoassay, only free levels in plasma were quantified, at 3.3% of the total astemizole, with the remaining 96.7% bound to plasma protein and tissue. Our method employs proteolysis of plasma proteins by incubating plasma for 2 h in pepsin. After proteolysis the astemizole is extracted, and a known amount of the extract is spotted on precoated silica gel F 254 plates. Astemizole was quantified using a Shimadzu CS-930 dual-wavelength TLC scanner. The method provides a direct estimate of total astemizole present in the plasma.  相似文献   
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The selection of coarse-grained (CG) mapping operators is a critical step for CG molecular dynamics (MD) simulation. It is still an open question about what is optimal for this choice and there is a need for theory. The current state-of-the art method is mapping operators manually selected by experts. In this work, we demonstrate an automated approach by viewing this problem as supervised learning where we seek to reproduce the mapping operators produced by experts. We present a graph neural network based CG mapping predictor called Deep Supervised Graph Partitioning Model (DSGPM) that treats mapping operators as a graph segmentation problem. DSGPM is trained on a novel dataset, Human-annotated Mappings (HAM), consisting of 1180 molecules with expert annotated mapping operators. HAM can be used to facilitate further research in this area. Our model uses a novel metric learning objective to produce high-quality atomic features that are used in spectral clustering. The results show that the DSGPM outperforms state-of-the-art methods in the field of graph segmentation. Finally, we find that predicted CG mapping operators indeed result in good CG MD models when used in simulation.

We propose a scalable graph neural network-based method for automating coarse-grained mapping prediction for molecules.  相似文献   
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