A Method for Improving CNN-Based Image Recognition Using DCGAN

Image recognition has always been a hot research topic in the scientific community and industry.The emergence of convolutional neural networks(CNN)has made this technology turned into research focus on the field of computer vision,especially in image recognition.But it makes the recognition result largely dependent on the number and quality of training samples.Recently,DCGAN has become a frontier method for generating images,sounds,and videos.In this paper,DCGAN is used to generate sample that is difficult to collect and proposed an efficient design method of generating model.We combine DCGAN with CNN for the second time.Use DCGAN to generate samples and training in image recognition model,which based by CNN.This method can enhance the classification model and effectively improve the accuracy of image recognition.In the experiment,we used the radar profile as dataset for 4 categories and achieved satisfactory classification performance.This paper applies image recognition technology to the meteorological field.

A New Sequential Image Prediction Method Based on LSTM and DCGAN

Image recognition technology is an important field of artificial intelligence.Combined with the development of machine learning technology in recent years,it has great researches value and commercial value.As a matter of fact,a single recognition function can no longer meet people’s needs,and accurate image prediction is the trend that people pursue.This paper is based on Long Short-Term Memory(LSTM)and Deep Convolution Generative Adversarial Networks(DCGAN),studies and implements a prediction model by using radar image data.We adopt a stack cascading strategy in designing network connection which can control of parameter convergence better.This new method enables effective learning of image features and makes predictive models to have greater generalization capabilities.Experiments demonstrate that our network model is more robust and efficient in terms of timing prediction than 3DCNN and traditional ConvLSTM.The sequential image prediction model architecture proposed in this paper is theoretically applicable to all sequential images.

RP11-40C6.2 Inactivates Hippo Signaling by Attenuating YAP1 Ubiquitylation in Hepatitis B Virus-associated Hepatocellular Carcinoma

Background and Aims:Chronic hepatitis caused by hepatitis B virus(HBV)infection is a leading cause of hepatocellular carcinoma(HCC).We investigated the roles of oncogenic HBV infection-associated long noncoding RNAs in HCC.Methods:Bioinformatics analysis of data from the Cancer Genome Atlas(TCGA)was performed to screen potential oncogenic HBV-related lncRNAs.Next,we assessed their expression in clinical samples and investigated their correlation with clinical characteristics.The detailed oncogenic effects were analyzed by performing in vitro and in vivo studies.Results:RP11-40C6.2,an HBV infection-related lncRNA,was identified by analysis of the TCGA–Liver Hepatocellular Carcinoma database.Gene Set Enrichment Analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis of differentially expressed genes revealed a strong association of RP11-40C6.2 with the Hippo signaling pathway.RP11-40C6.2 was overexpressed in HCC patients with HBV infection compared to those without HBV infection.RP11-40C6.2 transcription showed a positive association with HBV-X protein(HBx),but not HBV core protein(HBc)expression,both of which are carcinogenic proteins.Luciferase gene reporter and ChIP assays revealed that YAP1/TAZ/TEADs complex enhanced RP11-40C6.2 transcription by binding to its promoter area.RP11-40C6.2 showed oncogenic characteristics in HCC cell lines and in animal models that were mediated via activation of YAP1.In vitro ubiquitylation assay revealed that RP11-40C6.2 can promote the stabilization of YAP1 by stopping phosphorylation at its s127 residue and further stopping its degradation through binding to 14-3-3.Conclusions:RP11-40C6.2 is an HBV infection-related lncRNA that exerts its oncogenic effects by targeting the Hippo signaling pathway.

腹会阴联合直肠切除术后结肠造口癌一例

腹会阴联合直肠切除术后在结肠造口部位的腺癌非常罕见,本中心报道了1例62岁的女性在腹会阴联合直肠癌根治性切除术后26年在结肠造口部位出现腺癌的病例,因患者有家族性息肉病,肠镜提示全结肠多发腺瘤性息肉,本中心手术切除了全部结肠以及完整的造口肿瘤及周围广泛腹壁,并行右下腹小肠造口。虽然造口癌很罕见,但需要警惕造口术后患者有发生造口癌的风险,有必要更加仔细地观察造口,以及完善结肠镜等检查以进行监测。