Dual Defense: Adversarial, Traceable, and Invisible Robust Watermarking against Face Swapping

The malicious applications of deep forgery, represented by face swapping, have introduced security threats such as misinformation dissemination and identity fraud. While some research has proposed the use of robust watermarking methods to trace the copyright of facial images for post-event traceability, these methods cannot effectively prevent the generation of forgeries at the source and curb their dissemination. To address this problem, we propose a novel comprehensive active defense mechanism that combines traceability and adversariality, called Dual Defense. Dual Defense invisibly embeds a single robust watermark within the target face to actively respond to sudden cases of malicious face swapping. It disrupts the output of the face swapping model while maintaining the integrity of watermark information throughout the entire dissemination process. This allows for watermark extraction at any stage of image tracking for traceability. Specifically, we introduce a watermark embedding network based on original-domain feature impersonation attack. This network learns robust adversarial features of target facial images and embeds watermarks, seeking a well-balanced trade-off between watermark invisibility, adversariality, and traceability through perceptual adversarial encoding strategies. Extensive experiments demonstrate that Dual Defense achieves optimal overall defense success rates and exhibits promising universality in anti-face swapping tasks and dataset generalization ability. It maintains impressive adversariality and traceability in both original and robust settings, surpassing current forgery defense methods that possess only one of these capabilities, including CMUA-Watermark, Anti-Forgery, FakeTagger, or PGD methods

Enhancing Muscle Membrane Repair by Gene Delivery of MG53 Ameliorates Muscular Dystrophy and Heart Failure in δ-Sarcoglycan-deficient Hamsters

Muscular dystrophies (MDs) are caused by genetic mutations in over 30 different genes, many of which encode for proteins essential for the integrity of muscle cell structure and membrane. Their deficiencies cause the muscle vulnerable to mechanical and biochemical damages, leading to membrane leakage, dystrophic pathology, and eventual loss of muscle cells. Recent studies report that MG53, a muscle-specific TRIM-family protein, plays an essential role in sarcolemmal membrane repair. Here, we show that systemic delivery and muscle-specific overexpression of human MG53 gene by recombinant adeno-associated virus (AAV) vectors enhanced membrane repair, ameliorated pathology, and improved muscle and heart functions in δ-sarcoglycan (δ-SG)-deficient TO-2 hamsters, an animal model of MD and congestive heart failure. In addition, MG53 overexpression increased dysferlin level and facilitated its trafficking to muscle membrane through participation of caveolin-3. MG53 also protected muscle cells by activating cell survival kinases, such as Akt, extracellular signal-regulated kinases (ERK1/2), and glycogen synthase kinase-3β (GSK-3β) and inhibiting proapoptotic protein Bax. Our results suggest that enhancing the muscle membrane repair machinery could be a novel therapeutic approach for MD and cardiomyopathy, as demonstrated here in the limb girdle MD (LGMD) 2F model

Digital crowdsourced intervention to promote HIV testing among MSM in China: study protocol for a cluster randomized controlled trial.

BACKGROUND: Men who have sex with men (MSM) are an important HIV key population in China. However, HIV testing rates among MSM remain suboptimal. Digital crowdsourced media interventions may be a useful tool to reach this marginalized population. We define digital crowdsourced media as using social media, mobile phone applications, Internet, or other digital approaches to disseminate messages developed from crowdsourcing contests. The proposed cluster randomized controlled trial (RCT) study aims to assess the effectiveness of a digital crowdsourced intervention to increase HIV testing uptake and decrease risky sexual behaviors among Chinese MSM. METHODS: A two-arm, cluster-randomized controlled trial will be implemented in eleven cities (ten clusters) in Shandong Province, China. Targeted study participants will be 250 MSM per arm and 50 participants per cluster. MSM who are 18 years old or above, live in the study city, have not been tested for HIV in the past 3 months, are not living with HIV or have never been tested for HIV, and are willing to provide informed consent will be enrolled. Participants will be recruited through banner advertisements on Blued, the largest gay dating app in China, and in-person at community-based organizations (CBOs). The intervention includes a series of crowdsourced intervention materials (24 images and four short videos about HIV testing and safe sexual behaviors) and HIV self-test services provided by the study team. The intervention was developed through a series of participatory crowdsourcing contests before this study. The self-test kits will be sent to the participants in the intervention group at the 2nd and 3rd follow-ups. Participants will be followed up quarterly during the 12-month period. The primary outcome will be self-reported HIV testing uptake at 12 months. Secondary outcomes will include changes in condomless sex, self-test efficacy, social network engagement, HIV testing social norms, and testing stigma. DISCUSSION: Innovative approaches to HIV testing among marginalized population are urgently needed. Through this cluster randomized controlled trial, we will evaluate the effectiveness of a digital crowdsourced intervention, improving HIV testing uptake among MSM and providing a resource in related public health fields. TRIAL REGISTRATION: ChiCTR1900024350 . Registered on 6 July 2019

Iterative Methods for Computing the Resolvent of Composed Operators in Hilbert Spaces

The resolvent is a fundamental concept in studying various operator splitting algorithms. In this paper, we investigate the problem of computing the resolvent of compositions of operators with bounded linear operators. First, we discuss several explicit solutions of this resolvent operator by taking into account additional constraints on the linear operator. Second, we propose a fixed point approach for computing this resolvent operator in a general case. Based on the Krasnoselskii⁻Mann algorithm for finding fixed points of non-expansive operators, we prove the strong convergence of the sequence generated by the proposed algorithm. As a consequence, we obtain an effective iterative algorithm for solving the scaled proximity operator of a convex function composed by a linear operator, which has wide applications in image restoration and image reconstruction problems. Furthermore, we propose and study iterative algorithms for studying the resolvent operator of a finite sum of maximally monotone operators as well as the proximal operator of a finite sum of proper, lower semi-continuous convex functions

A Preconditioning Technique for First-Order Primal-Dual Splitting Method in Convex Optimization

We introduce a preconditioning technique for the first-order primal-dual splitting method. The primal-dual splitting method offers a very general framework for solving a large class of optimization problems arising in image processing. The key idea of the preconditioning technique is that the constant iterative parameters are updated self-adaptively in the iteration process. We also give a simple and easy way to choose the diagonal preconditioners while the convergence of the iterative algorithm is maintained. The efficiency of the proposed method is demonstrated on an image denoising problem. Numerical results show that the preconditioned iterative algorithm performs better than the original one

PTEN in osteosarcoma: Recent advances and the therapeutic potential

Osteosarcoma is the most common primary malignant bone tumor, predominantly occurring in children and adolescents. Despite treated with surgery and neoadjuvant chemotherapy, osteosarcoma has a high potential of local recurrence and lung metastasis. Overall survival rates for osteosarcoma have plateaued in the past four decades, therefore, identification of novel targets and development of more effective treatment strategies are urgent. Phosphatase and tensin homolog (PTEN) is a tumor suppressor gene that negatively regulates the phosphatidylinositol 3-kinase (PI3K)/ protein kinase B (AKT)/ mammalian target of rapamycin (mTOR) pathway. Over half of clinical osteosarcoma samples presented loss or low expression of PTEN, which usually indicated an advanced stage of tumor and a poor prognosis. The expression of PTEN is regulated by epigenetic silence, transcription regulation, post-translational modifications, and protein interactions in osteosarcoma. Therefore, explicating regulations to restore the anti-tumor function of PTEN might provide novel targeted therapies for osteosarcoma. Preclinical evidence suggested directly targeting the altered PTEN in osteosarcoma was promising. Current clinical application of PTEN related therapies in osteosarcoma are PI3K/mTOR inhibitors, and these drugs have shown the favorable efficacy in patients with advanced osteosarcoma