Rodlike, olivelike, pineapplelike, and particlelike nanocrystals of theYVO4:Eu (5 at. % Eu) were synthesized by a hydrothermal reaction with different conditions, respectively. The rodlike nanocrystal has a rectangular cross-section with about 35 x 60 nm2 and a length of about 220 nm. The olivelike nanocrystal has an equatorial diameter of approximately 40 nm and a length of approximately 200 nm. The pineapplelike nanocrystal with an equatorial diameter of approximately 200 nm and a length of approximately 300 nm, is a superstructure consisting of self-organized nanorods with a diameter of approximately 20 nm and a length of approximately 50 nm. The particlelike nanocrystals show globular and polyhedral shape with a diameter of approximately 50 nm. Their UV-vis absorption peaks are at 305, 308, 285, and 280 nm, respectively, and there is such a trend that the absorption peaks shift to higher energy as the size of the particles decreases. Compared with other-shape nanocrystals, the luminescence intensity of the olivelike nanocrystals is obviously enhanced. It suggests that we could obtain the function-improved materials by tailoring the size and shape of theYVO4:Eu nanostructures.

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Lasing action in an electrically pumped organic laser device is demonstrated with a high quality factor (Q) microcavity structure formed by two high-reflective and low-loss electrical contacts. A 4-(dicyanomethylene)-2-i-propyl-6-(1,1,7,7-tetramethyljulolidyl-9-enyl)-4H-pyran-doped tris(8-hydroxy-quinoline)aluminum (Alq(3)) film serves as the active layer. A single longitudinal lasing cavity mode is obtained at 621.7 nm with a threshold current density of 860 mA/cm(2) under a room temperature pulse operation.

Background: DNA N6-methyladenine plays an important role in the restriction-modification system to isolate invasion from adventive DNA. The shortcomings of the high time-consumption and high costs of experimental methods have been exposed, and some computational methods have emerged. The support vector machine theory has received extensive attention in the bioinformatics field due to its solid theoretical foundation and many good characteristics. Objective: General machine learning methods include an important step of extracting features. The research has omitted this step and replaced with easy-to-obtain sequence distances matrix to obtain better results Method: First sequence alignment technology was used to achieve the similarity matrix. Then a novel transformation turned the similarity matrix into a distance matrix. Next, the similarity-distance matrix is made positive semi-definite so that it can be used in the kernel matrix. Finally, the LIBSVM software was applied to solve the support vector machine. Results: The five-fold cross-validation of this model on rice and mouse data has achieved excellent accuracy rates of 92.04% and 96.51%, respectively. This shows that the DB-SVM method has obvious advantages compared with traditional machine learning methods. Meanwhile this model achieved 0.943,0.982 and 0.818 accuracy,0.944, 0.982, and 0.838 Matthews correlation coefficient and 0.942, 0.982 and 0.840 F1 scores for the rice, M. musculus and cross-species genome datasets, respectively. Conclusion: These outcomes show that this model outperforms the iIM-CNN and csDMA in the prediction of DNA 6mA modification, which are the lastest research on DNA 6mA.

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