Interpretation of the unprecedentedly long-lived high-energy emission of GRB 130427A

High energy photons (>100 MeV) are detected by the Fermi/LAT from GRB 130427A up to almost one day after the burst, with an extra hard spectral component being discovered in the high-energy afterglow. We show that this hard spectral component arises from afterglow synchrotron-self Compton emission. This scenario can explain the origin of >10 GeV photons detected up to ~30000s after the burst, which would be difficult to be explained by synchrotron radiation due to the limited maximum synchrotron photon energy. The lower energy multi-wavelength afterglow data can be fitted simultaneously by the afterglow synchrotron emission. The implication of detecting the SSC emission for the circumburst environment is discussed.Comment: 4 pages, 2 figures, ApJL in pres

Calculation of the Branching Ratio of B−→hc+K−B^{-}\to h_{c}+K^{-} in PQCD

The branching ratio of $B^-\to h_c+K^-$ is re-evaluated in the PQCD approach. In this theoretical framework all the phenomenological parameters in the wavefunctions and Sudakov factor are priori fixed by fitting other experimental data, and in the whole numerical computations we do not introduce any new parameter. Our results are consistent with the upper bounds set by the Babar and Belle measurements.Comment: 12 pages, 1 figure, version to appear in Phys. Rev.

On the minimum jet power of TEV BL Lac objects in the p-γ\gamma model

We study the requirement on the jet power in the conventional p-$\gamma$ models (photopion production and Bethe-Heitler pair production) for TeV BL Lac objects. We select a sample of TeV BL Lac objects whose SEDs are difficult to be explained by the one-zone leptonic model. Based on the relation between the p-$\gamma$ interaction efficiency and the opacity of $\gamma\gamma$ absorption, we find that the detection of TeV emission poses upper limits on the p-$\gamma$ interaction efficiencies in these sources and hence minimum jet powers can be derived accordingly. We find that the obtained minimum jet powers exceed the Eddington luminosity of the supermassive black holes. Implications for the accretion mode of the supermassive black hole in these BL Lac objects and the origin of their TeV emissions are discussed.Comment: 11 pages, 4 figures, 2 tables, accepted for publication in Ap

Iterative Object and Part Transfer for Fine-Grained Recognition

The aim of fine-grained recognition is to identify sub-ordinate categories in images like different species of birds. Existing works have confirmed that, in order to capture the subtle differences across the categories, automatic localization of objects and parts is critical. Most approaches for object and part localization relied on the bottom-up pipeline, where thousands of region proposals are generated and then filtered by pre-trained object/part models. This is computationally expensive and not scalable once the number of objects/parts becomes large. In this paper, we propose a nonparametric data-driven method for object and part localization. Given an unlabeled test image, our approach transfers annotations from a few similar images retrieved in the training set. In particular, we propose an iterative transfer strategy that gradually refine the predicted bounding boxes. Based on the located objects and parts, deep convolutional features are extracted for recognition. We evaluate our approach on the widely-used CUB200-2011 dataset and a new and large dataset called Birdsnap. On both datasets, we achieve better results than many state-of-the-art approaches, including a few using oracle (manually annotated) bounding boxes in the test images.Comment: To appear in ICME 2017 as an oral pape

Mobile Platform with Dynamic Optimization of the Pattern in Education in Colleges Through the Perspective of Network Informatization

The combination of mobile learning platforms and network informatization offers numerous benefits to learners, educators, and institutions. Learners can take control of their learning journey, accessing educational materials at their convenience and engaging in collaborative learning activities with peers from diverse backgrounds. This paper aims to explore the integration of mobile learning platforms and network informatization, examining their impact on educational practices, learner engagement, and the overall learning experience. The network informatization is assessed and monitored with Dynamic Programming Optimization (DPO) to compute the feature in reverse osmosis in English education. The attributes and features in the English language are computed and estimated for the periodic information update within the system. The DPO process is implemented along with the mandhani fuzzy set for the estimation of features in English education in colleges and universities. The information processed is updated in the mobile learning platform for the computation of the features in the English language and classification is performed with the deep learning model. Simulation analysis stated that constructed model is effective for the estimation and computation of the features and patterns in English language teaching in colleges and universities