186 research outputs found

    General GAN-generated image detection by data augmentation in fingerprint domain

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    In this work, we investigate improving the generalizability of GAN-generated image detectors by performing data augmentation in the fingerprint domain. Specifically, we first separate the fingerprints and contents of the GAN-generated images using an autoencoder based GAN fingerprint extractor, followed by random perturbations of the fingerprints. Then the original fingerprints are substituted with the perturbed fingerprints and added to the original contents, to produce images that are visually invariant but with distinct fingerprints. The perturbed images can successfully imitate images generated by different GANs to improve the generalization of the detectors, which is demonstrated by the spectra visualization. To our knowledge, we are the first to conduct data augmentation in the fingerprint domain. Our work explores a novel prospect that is distinct from previous works on spatial and frequency domain augmentation. Extensive cross-GAN experiments demonstrate the effectiveness of our method compared to the state-of-the-art methods in detecting fake images generated by unknown GANs

    Learning Second Order Local Anomaly for General Face Forgery Detection

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    In this work, we propose a novel method to improve the generalization ability of CNN-based face forgery detectors. Our method considers the feature anomalies of forged faces caused by the prevalent blending operations in face forgery algorithms. Specifically, we propose a weakly supervised Second Order Local Anomaly (SOLA) learning module to mine anomalies in local regions using deep feature maps. SOLA first decomposes the neighborhood of local features by different directions and distances and then calculates the first and second order local anomaly maps which provide more general forgery traces for the classifier. We also propose a Local Enhancement Module (LEM) to improve the discrimination between local features of real and forged regions, so as to ensure accuracy in calculating anomalies. Besides, an improved Adaptive Spatial Rich Model (ASRM) is introduced to help mine subtle noise features via learnable high pass filters. With neither pixel level annotations nor external synthetic data, our method using a simple ResNet18 backbone achieves competitive performances compared with state-of-the-art works when evaluated on unseen forgeries

    Deformation characteristics and reactivation mechanism of an old landslide induced by combined action of excavation and heavy rainfall

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    The reactivation mechanism of old landslides has been extensively studied from building load, erosion of the slope toe, heavy rainfall, and slope cutting for existing research. However, previous research on the reactivation of old landslides pays little attention to the combined action of engineering disturbance and heavy rainfall is rarely studied. This paper describes an old landslide in Wushan County, Chongqing, China, that was reactivated in August 2019 due to engineering disturbance and heavy rainfall. The deformation of the old landslide was first observed in 2007 and 2008, resulting from excavation and rainfall, respectively, and remained stable for about 11 years after treatment. In August 2019, the landslide was reactivated by slope cutting and damaged anti-sliding piles at the toe, and entered a state of imminent sliding due to the concentrated heavy rainfall events that occurred from October 4 to 22, 2019. In order to reveal the deformation features and reactivation mechanism of the landslide, field investigations, drilling activities and monitoring were performed. The results showed that tectonic effects and the stratigraphic lithology were the main reasons for the formation of the old Dashuitian landslide. The cut slope and damaged anti-sliding piles at the toe of the landslide provided the sliding space and reduced the anti-sliding force, and therefore resulted in the reactivation of the landslide. Continuous intense rainfall increased the weight of the landslide, decreased the mechanical properties and increased the pore water pressure of the weak interlayer, which accelerated the deformation rate. Therefore, 1.5 million m3 of rock and soil masses slid along the weak interlayer under the action of gravity, threatening the safety of Wuliu Road, Ring Road, National Road G42 and the Wu-Da Expressway. Our research provides a theoretical basis for reducing the hazard of similar engineering projects involving slopes

    Interactive effects of vanadium and phosphorus on their uptake, growth and heat shock proteins in chickpea genotypes under hydroponic conditions

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    The present study was carried out to examine the interaction of vanadium and phosphorus and changes in heat shock genes to optimize the growth of chickpea genotypes. Two sets of hydroponic experiments were carried out using vanadium and phosphorus with five-level central composite design. Five levels of vanadium (0-1180 mu M) and phosphorus (0-100011 mu M) were used to evaluate their interactive effects. Plants fresh biomass and uptake of vanadium and phosphorus were influenced by vanadium and phosphorus application. Enhanced fresh biomass was most likely a result of increased phosphorus uptake by chickpea genotypes. Addition of vanadium induced toxic effects while, higher concentration of phosphorus alleviated its toxic effects. The obtained results also indicated that lower vanadium concentration promoted phosphorus absorption however; higher concentration of vanadium inhibited the phosphorus uptake. The morphological changes in leaves indicated that the cells were deformed and reduced in size when treated with higher vanadium levels with fixed phosphorus while, there was little deformation and reduction in cells size were observed when plants were treated with higher levels of phosphorus with fixed vanadium. Whereas, the proportion of deformation of cells were higher in Balkasar as compared to C-44 genotype. The results also showed that at elevated vanadium with fixed phosphorus, Hsp70 was expressed only in C-44 while, not in Balkasar however, Hsp90 and GAPDH showed non-significant results. (C) 2016 Elsevier B.V. All rights reserved

    Cell Trajectory-Related Genes of Lung Adenocarcinoma Predict Tumor Immune Microenvironment and Prognosis of Patients

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    BackgroundLung adenocarcinoma (LUAD) is the most common subtype of lung cancer which typically exhibits a diverse progression trajectory. Our study sought to explore the cell differentiation trajectory of LUAD and its clinical relevance.MethodsUtilizing a single-cell RNA-sequencing dataset (GSE117570), we identified LUAD cells of distinct differential status along with differentiation-related genes (DRGs). DRGs were applied to the analysis of bulk-tissue RNA-sequencing dataset (GSE72094) to classify tumors into different subtypes, whose clinical relevance was further analyzed. DRGs were also applied to gene co-expression network analysis (WGCNA) using another bulk-tissue RNA-sequencing dataset (TCGA-LUAD). Genes from modules that demonstrated a significant correlation with clinical traits and were differentially expressed between normal tissue and tumors were identified. Among these, genes with significant prognostic relevance were used for the development of a prognostic nomogram, which was tested on TCGA-LUAD dataset and validated in GSE72094. Finally, CCK-8, EdU, cell apoptosis, cell colony formation, and Transwell assays were used to verify the functions of the identified genes.ResultsFour clusters of cells with distinct differentiation status were characterized, whose DRGs were predominantly correlated with pathways of immune regulation. Based on DRGs, tumors could be clustered into four subtypes associated with distinct immune microenvironment and clinical outcomes. DRGs were categorized into four modules. A total of nine DRGs (SFTPB, WFDC2, HLA-DPA1, TIMP1, MS4A7, HLA-DQA1, VCAN, KRT8, and FABP5) with most significant survival-predicting power were integrated to develop a prognostic model, which outperformed the traditional parameters in predicting clinical outcomes. Finally, we verified that knockdown of WFDC2 inhibited proliferation, migration, and invasion but promoted the apoptosis of A549 cells in vitro.ConclusionThe cellular composition and cellular differentiation status of tumor mass can predict the clinical outcomes of LUAD patients. It also plays an important role in shaping the tumor immune microenvironment

    Prognostic Value of MicroRNA-20b in Acute Myeloid Leukemia

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    Acute myeloid leukemia (AML) is a highly heterogeneous disease that requires fine-grained risk stratification for the best prognosis of patients. As a class of small non-coding RNAs with important biological functions, microRNAs play a crucial role in the pathogenesis of AML. To assess the prognostic impact of miR-20b on AML in the presence of other clinical and molecular factors, we screened 90 AML patients receiving chemotherapy only and 74 also undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) from the Cancer Genome Atlas (TCGA) database. In the chemotherapy-only group, high miR-20b expression subgroup had shorter event-free survival (EFS) and overall survival (OS, both P < 0.001); whereas, there were no significant differences in EFS and OS between high and low expression subgroups in the allo-HSCT group. Then we divided all patients into high and low expression groups based on median miR-20b expression level. In the high expression group, patients treated with allo-HSCT had longer EFS and OS than those with chemotherapy alone (both P < 0.01); however, there were no significant differences in EFS and OS between different treatment subgroups in the low expression group. Further analysis showed that miR-20b was negatively correlated with genes in "ribosome," "myeloid leukocyte mediated immunity," and "DNA replication" signaling pathways. ORAI2, the gene with the strongest correlation with miR-20b, also had significant prognostic value in patients undergoing chemotherapy but not in the allo-HSCT group. In conclusion, our findings suggest that high miR-20b expression is a poor prognostic indicator for AML, but allo-HSCT may override its prognostic impact
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