We apply a modified Convolutional Neural Network (CNN) model in conjunction with transfer learning to predict whether an active region (AR) would produce a ≥C-class or ≥M-class flare within the next 24 hours. We collect line-of-sight magnetogram samples of ARs provided by the SHARP from May 2010 to September 2018, which is a new data product from the HMI onboard the SDO. Based on these AR samples, we adopt the approach of shuffle-and-split cross-validation (CV) to build a database that includes 10 separate data sets. Each of the 10 data sets is segregated by NOAA AR number into a training and a testing data set. After training, validating, and testing our model, we compare the results with previous studies using predictive performance metrics, with a focus on the true skill statistic (TSS). The main results from this study are summarized as follows. First, to the best of our knowledge, this is the first time that the CNN model with transfer learning is used in solar physics to make binary class predictions for both ≥C-class and ≥M-class flares, without manually engineered features extracted from the observational data. Second, our model achieves relatively high scores of TSS = 0.640±0.075 and TSS = 0.526±0.052 for ≥M-class prediction and ≥C-class prediction, respectively, which is comparable to that of previous models. Third, our model also obtains quite good scores in five other metrics for both ≥C-class and ≥M-class flare prediction. Our results demonstrate that our modified CNN model with transfer learning is an effective method for flare forecasting with reasonable prediction performance.

The near real-time speckle masking reconstruction technique has been developed to accelerate the processing of solar images to achieve high resolutions for ground-based solar telescopes. However, the reconstruction of solar subimages in such a speckle reconstruction is very time-consuming. We design and implement a new parallel speckle masking reconstruction algorithm based on the Compute Unified Device Architecture (CUDA) on General Purpose Graphics Processing Units (GPGPU). Tests are performed to validate the correctness of our program on NVIDIA GPGPU. Details of several parallel reconstruction steps are presented, and the parallel implementation between various modules shows a significant speed increase compared to the previous serial implementations. In addition, we present a comparison of runtimes across serial programs, the OpenMP-based method, and the new parallel method. The new parallel method shows a clear advantage for large scale data processing, and a speedup of around 9 to 10 is achieved in reconstructing one solar subimage of 256×256 pixels. The speedup performance of the new parallel method exceeds that of OpenMP-based method overall. We conclude that the new parallel method would be of value, and contribute to real-time reconstruction of an entire solar image.

Phellinus sp. are assigned to the Basidiomycotina, Hymenomycetes, Aphyllophorales and Hymenochaetaceae, and have been shown containing various bioactive substances including triterpenoids, polysaccharides and flavones[1]. Traditional Chinese herbalists believe that Phellinus species are effective in treating many gynecopathic ailments[2] and are also reported to exhibit other pharmacological functions including tumor cell inhibition, antioxidant activity and anti-hepatic fibrosis effects[3]. Polysaccharides of Phellinus sp. has been reported to possess antitumor activities and inhibit tumor recrudescence and metastasis. There are little studies comparing the chemical composition and biological activities difference among polysaccharides from different Phellinus sp and little report about the pure polysaccharide structure analysis. In this study, eight kinds of crude polysaccharides were extracted from Phellinus fruit bodies and their chemical composition and bioactivities were researched. The polysaccharide and protein contents of eight crude polysaccharides had a certain extent differences. Monosaccharide composition and content of amino acids also existed some differences in eight crude polysaccharides. Eight different polysaccharides all showed enhancing splenocyte proliferation effect in vitro. PB-10P and JSHP had high cell proliferation rates with 50㎍/ml concentrations. The results indicated in some extent the immune activity of crude polysaccharides were correlation with the polysaccharide and protein content and composition of each sample. The crude polysaccharides of P. igniarius were further isolated and purified using DEAE Sepharose F. F. and gel-filtration chromatography (Sephacryl S-100-500 ）repeatedly. Five water-soluble homogeneous polysaccharides (P60w1、P60s1、P1SP1、P10SP1and P100SP1) were obtained. Lack of absorption at 280 nm and 260 nm by UV scanning indicated that contained no protein and nucleic acid. HPLC produced a single symmetrical peak, indicated homogeneity and their molecular weigh were 1.71×104 Da、2.07×104 Da、1.48×104 Da、2.20×104 Da and 2.56×104 Da respectively. Structural of P60w-1 were determined using sugar and methylation analysis combined with 1H and 13C NMR spectroscopy, including COSY, TOCSY, NOESY, HSQC and HMBC experiments. The effect of P60w-1 on tumor growth was examined using subcutaneously transplanted H22 and Lewis Lung Carcinoma (LLC) tumor mouse models. Cyclophosphamide or Coriolus versicolor polysaccharopeptide served as positive controls in evaluating tumor response. Results showed that P60w-1 at the most effective dose of 100 mg/kg inhibited the growth of H22 and LLC by 48% and 37%, respectively.