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Tang, Su-Ni,Zhang, Jinhui,Wu, Wei,Jiang, Peixin,Puppala, Manohar,Zhang, Yong,Xing, Chengguo,Kim, Sung-Hoon,Jiang, Cheng,Lü,, Junxuan American Association for Cancer Research 2015 CANCER PREVENTION RESEARCH Vol.8 No.9
<P>We showed previously that daily gavage of <I>Angelica gigas</I> Nakai (AGN) root ethanolic extract starting 8 weeks of age inhibited growth of prostate epithelium and neuroendocrine carcinomas (NE-Ca) in the transgenic adenocarcinoma of mouse prostate (TRAMP) model. Because decursin (D) and its isomer decursinol angelate (DA) are major pyranocoumarins in AGN extract, we tested the hypothesis that D/DA represented active/prodrug compounds against TRAMP carcinogenesis. Three groups of male C57BL/6 TRAMP mice were gavage treated daily with excipient vehicle, AGN (5 mg per mouse), or equimolar D/DA (3 mg per mouse) from 8 weeks to 16 or 28 weeks of age. Measurement of plasma and NE-Ca D, DA, and their common metabolite decursinol indicated similar retention from AGN versus D/DA dosing. The growth of TRAMP dorsolateral prostate (DLP) in AGN- and D/DA-treated mice was inhibited by 66% and 61% at 16 weeks and by 67% and 72% at 28 weeks, respectively. Survival of mice bearing NE-Ca to 28 weeks was improved by AGN, but not by D/DA. Nevertheless, AGN- and D/DA-treated mice had lower NE-Ca burden. Immunohistochemical and mRNA analyses of DLP showed that AGN and D/DA exerted similar inhibition of TRAMP epithelial lesion progression and key cell-cycle genes. Profiling of NE-Ca mRNA showed a greater scope of modulating angiogenesis, epithelial–mesenchymal transition, invasion–metastasis, and inflammation genes by AGN than D/DA. The data therefore support D/DA as probable active/prodrug compounds against TRAMP epithelial lesions, and they cooperate with non-pyranocoumarin compounds to fully express AGN efficacy against NE-Ca. <I>Cancer Prev Res; 8(9); 835–44. ©2015 AACR</I>.</P>
Active Learning on Sparse Graph for Image Annotation
( Minxian Li ),( Jinhui Tang ),( Chunxia Zhao ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.10
Due to the semantic gap issue, the performance of automatic image annotation is still far from satisfactory. Active learning approaches provide a possible solution to cope with this problem by selecting most effective samples to ask users to label for training. One of the key research points in active learning is how to select the most effective samples. In this paper, we propose a novel active learning approach based on sparse graph. Comparing with the existing active learning approaches, the proposed method selects the samples based on two criteria: uncertainty and representativeness. The representativeness indicates the contribution of a sample`s label propagating to the other samples, while the existing approaches did not take the representativeness into consideration. Extensive experiments show that bringing the representativeness criterion into the sample selection process can significantly improve the active learning effectiveness.
A field determination method of D-T neutron source yields based on oxygen prompt gamma rays
Xiongjie Zhang,Bin Tang,Geng Nian,Haitao Wang,Lijiao Zhang,Yan Zhang,Rui Chen,Zhifeng Liu,Jinhui Qu Korean Nuclear Society 2023 Nuclear Engineering and Technology Vol.55 No.7
A field determination method for small D-T neutron source yield based on the oxygen prompt gamma rays was established. A neutron-gamma transport equation of the determination device was developed. Two yield field determination devices with a thickness of 20 mm and 50 mm were made. The count rates of the oxygen prompt gamma rays were calculated using three energy spectra processing approaches, which were the characteristic peak of 6.13 MeV, the overlapping peak of 6.92 MeV and 7.12 MeV, and the total energy area. The R-square of the calibration curve is better than 94% and the maximum error of the yield test is 5.21%, demonstrating that it is feasible to measure the yield of D-T neutron source by oxygen prompt gamma rays. Additionally, the results meet the requirements for field determination of the conventional D-T neutron source yield.
Local Similarity based Discriminant Analysis for Face Recognition
( Xinguang Xiang ),( Fan Liu ),( Ye Bi ),( Yanfang Wang ),( Jinhui Tang ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.11
Fisher linear discriminant analysis (LDA) is one of the most popular projection techniques for feature extraction and has been widely applied in face recognition. However, it cannot be used when encountering the single sample per person problem (SSPP) because the intra-class variations cannot be evaluated. In this paper, we propose a novel method called local similarity based linear discriminant analysis (LS_LDA) to solve this problem. Motivated by the “divide-conquer” strategy, we first divide the face into local blocks, and classify each local block, and then integrate all the classification results to make final decision. To make LDA feasible for SSPP problem, we further divide each block into overlapped patches and assume that these patches are from the same class. To improve the robustness of LS_LDA to outliers, we further propose local similarity based median discriminant analysis (LS_MDA), which uses class median vector to estimate the class population mean in LDA modeling. Experimental results on three popular databases show that our methods not only generalize well SSPP problem but also have strong robustness to expression, illumination, occlusion and time variation.