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App clone is a serious threat to the mobile app ecosystem, which not only damages the benefits of original developers, but also contributes to spreading malware. App clone detection has received extensive attentions from our research community, and a number of approaches were proposed, which mainly rely on code or visual similarity of the apps. However, the tricky plagiarists in the wild may specifically modify the code or the content of User Interface (UI), which will lead to the ineffectiveness of current methods. In this paper, we propose a robust app clone detection method based on the similarity of UI structure. The key idea behind our approach is based on the finding that content features (e.g., background color) are more likely to be modified by plagiarists, while structure features (e.g., overall hierarchy structure, widget hierarchy structure) are relative stable, which could be used to detect different levels of clone attacks. Experiment results on a labeled benchmark of 4,720 similar app pairs show that our approach could achieve an accuracy of 99.6%. Compare with existing approaches, our approach works in practice with high effectiveness. We have implemented a prototype system and applied it to more than 404,650 app pairs, and we found 1,037 app clone pairs, most of them are piggybacking apps that introduced malicious payloads.

Background/Aims: Inflammatory response is a determinant in the pathological progression of acute pancreatitis (AP). Previous studies have shown that the activation of hedgehog (Hh) signaling is a remarkable change in caerulein-induced AP. However, the relationship between Hh signaling and inflammation is largely ambiguous. Methods: The AP mouse model was induced by injection of cerulein, and histological staining and serum enzymology assays were used to evaluate the establishment of AP. Western blot assay was used to determine the protein levels, cleavage of apoptotic proteins, and activation of the NF-κB signaling pathway. Cytokine array was used to screen inflammatory cytokines, and target cytokines’ transcriptional expression and serum levels were examined by real-time PCR and enzyme-linked immunosorbent assay, respectively. Results: The key transcriptional factor in Hh signaling, Gli2, was upregulated in the pancreas and other tissues during the process of AP, and it seems to be a characteristic feature of local inflammation in pancreatic tissue and systemic inflammatory response in multiple organs. The inflammatory NF-κB pathway is required for the activation of Hh signaling, as blockade of the NF-κB pathway by pyrrolidine dithiocarbamate impaired the Gli2 upregulation. Manipulation of Gli2 expression altered the activation of the NF-κB pathway correspondingly, as well as the cell apoptosis in cerulein-induced AP. Moreover, Gli2 upregulation changed the cytokine expression profile in mouse pancreatic acinar cells, mainly decreasing the pro-inflammatory cytokines interleukin (IL)-6, interferon-γ, and FasL. The anti-inflammatory cytokine IL-10 was upregulated by Gli2 overexpression. Interdiction of Gli2 by the Gli-specific inhibitor GANT61 exacerbated AP in mice and altered the balance of inflammatory cytokines. Conclusions: This study indicates that Hh activation during AP development is a negative feedback of the inflammatory response, restricting inflammatory injury to the pancreas and other tissues. Thus, manipulation of Hh signaling should shed light on limiting inflammation and alleviating AP damage.

Background: With the development of virtual reality (VR) technology, there is a growing need for customized 3D avatars. However, traditional methods for 3D avatar modeling are either time-consuming or fail to retain the similarity to the person being modeled. This study presents a novel framework for generating animatable 3D cartoon faces from a single portrait image. Methods: First, we transferred an input real-world portrait to a stylized cartoon image using StyleGAN. We then proposed a two-stage reconstruction method to recover a 3D cartoon face with detailed texture. Our two-stage strategy initially performs coarse estimation based on template models and subsequently refines the model by nonrigid deformation under landmark supervision. Finally, we proposed a semantic-preserving face-rigging method based on manually created templates and deformation transfer. Conclusions: Compared with prior arts, the qualitative and quantitative results show that our method achieves better accuracy, aesthetics, and similarity criteria. Furthermore, we demonstrated the capability of the proposed 3D model for real-time facial animation.

Abstract Timely and effective diagnosis of fungal keratitis (FK) is necessary for suitable treatment and avoiding irreversible vision loss for patients. In vivo confocal microscopy (IVCM) has been widely adopted to guide the FK diagnosis. We present a deep learning framework for diagnosing fungal keratitis using IVCM images to assist ophthalmologists. Inspired by the real diagnostic process, our method employs a two-stage deep architecture for diagnostic predictions based on both image-level and sequence-level information. To the best of our knowledge, we collected the largest dataset with 96,632 IVCM images in total with expert labeling to train and evaluate our method. The specificity and sensitivity of our method in diagnosing FK on the unseen test set achieved 96.65% and 97.57%, comparable or better than experienced ophthalmologists. The network can provide image-level, sequence-level and patient-level diagnostic suggestions to physicians. The results show great promise for assisting ophthalmologists in FK diagnosis.

AIM: To compare the outcomes of severe congenital ptosis treated with levator shortening and frontalis muscle flap suspension.METHODS: Forty cases(58 eyes)with severe congenital ptosis were retrospective analyzed. Shortening levator muscle of upper eyelid was conducted in 30 eyes, and 28 eyes were treated with frontalis muscle flap suspension. All cases were followed up for 6mo. The ptosis correction rates were analyzed. Post-operative complications such as blepharelosis, hypophasis, exposure keratitis and conjunctival prolapse were recorded.RESULTS: There was no statistically significant difference in the complete correction rate between levator shortening group and frontalis muscle flap suspension group(83% vs 82%, P>0.05). However, the levator shortening had better appearance and fewer complications, such as blepharelosis(0 vs 3), hypophasis(15 vs 23), exposure keratitis(1 vs 2), and conjunctival prolapse(2 vs 3)at 6mo after surgeries.CONCLUSION: Both the operations are effective on the treatment of severe congenital ptosis. However, levator shortening surgery leads to fewer complications and better appearance.