Exploring Disentangled Content Information for Face Forgery Detection

Convolutional neural network based face forgery detection methods have achieved remarkable results during training, but struggled to maintain comparable performance during testing. We observe that the detector is prone to focus more on content information than artifact traces, suggesting that the detector is sensitive to the intrinsic bias of the dataset, which leads to severe overfitting. Motivated by this key observation, we design an easily embeddable disentanglement framework for content information removal, and further propose a Content Consistency Constraint (C2C) and a Global Representation Contrastive Constraint (GRCC) to enhance the independence of disentangled features. Furthermore, we cleverly construct two unbalanced datasets to investigate the impact of the content bias. Extensive visualizations and experiments demonstrate that our framework can not only ignore the interference of content information, but also guide the detector to mine suspicious artifact traces and achieve competitive performance

Anterolateral thigh perforator flap made by customized 3D-printing fabrication of fixed positioning guide for oromaxillofacial reconstruction:a preliminary study

Oromaxillofacial carcinomas frequently result in serious tissue defect due to enlarged resection for treating their extensive invasion, which require challenging reconstruction. Three-dimensional (3D) printing is an advanced technology which has greatly promoted the progress of craniomaxillofacial reconstructive surgery. This present study aimed to investigate the advantages of anterolateral thigh (ALT) perforator flap manufactured by 3D printing fixed positioning guide template in curing oromaxillofacial defect. Twenty patients with oromaxillofacial defects resulted from severe primary malignant tumors were divided into experimental group assisted by digital technique (n=8) and controlled group conventionally aided by ultrasound (n=12). The therapeutic effectiveness, flap preparation time, amount of bleeding, deviation of perforator vessel location, aesthetic satisfaction of donor site, postoperative complications, adverse symptom of flap, and LEFS scores were compared. For experimental group, flap preparation time was significantly shorter; and it has obviously less bleeding, minor deviation of perforator vessel location, and better aesthetic satisfaction of donor site (P.05). The study suggests 3D printing template of fixed positioning guide provides a brand-new method for orienting perforated vessels of ALT flap, which is more accurate in clinical application. It can improve the operative efficacy, and increase the successful rate of operation as well

Model and Data Agreement for Learning with Noisy Labels

Learning with noisy labels is a vital topic for practical deep learning as models should be robust to noisy open-world datasets in the wild. The state-of-the-art noisy label learning approach JoCoR fails when faced with a large ratio of noisy labels. Moreover, selecting small-loss samples can also cause error accumulation as once the noisy samples are mistakenly selected as small-loss samples, they are more likely to be selected again. In this paper, we try to deal with error accumulation in noisy label learning from both model and data perspectives. We introduce mean point ensemble to utilize a more robust loss function and more information from unselected samples to reduce error accumulation from the model perspective. Furthermore, as the flip images have the same semantic meaning as the original images, we select small-loss samples according to the loss values of flip images instead of the original ones to reduce error accumulation from the data perspective. Extensive experiments on CIFAR-10, CIFAR-100, and large-scale Clothing1M show that our method outperforms state-of-the-art noisy label learning methods with different levels of label noise. Our method can also be seamlessly combined with other noisy label learning methods to further improve their performance and generalize well to other tasks. The code is available in https://github.com/zyh-uaiaaaa/MDA-noisy-label-learning.Comment: Accepted by AAAI2023 Worksho

Finite temperature strong-coupling expansions for the Kondo lattice model

Strong-coupling expansions, to order $(t/J)^8$, are derived for the Kondo lattice model of strongly correlated electrons, in 1-, 2- and 3- dimensions at arbitrary temperature. Results are presented for the specific heat, and spin and charge susceptibilities.Comment: revtex

HGF/c-met/Stat3 signaling during skin tumor cell invasion: indications for a positive feedback loop

<p>Abstract</p> <p>Background</p> <p>Stat3 is a cytokine- and growth factor-inducible transcription factor that regulates cell motility, migration, and invasion under normal and pathological situations, making it a promising target for cancer therapeutics. The hepatocyte growth factor (HGF)/c-met receptor tyrosine kinase signaling pathway is responsible for stimulation of cell motility and invasion, and Stat3 is responsible for at least part of the c-met signal.</p> <p>Methods</p> <p>We have stably transfected a human squamous cell carcinoma (SCC) cell line (SRB12-p9) to force the expression of a dominant negative form of Stat3 (S3DN), which we have previously shown to suppress Stat3 activity. The <it>in vitro </it>and <it>in vivo </it>malignant behavior of the S3DN cells was compared to parental and vector transfected controls.</p> <p>Results</p> <p>Suppression of Stat3 activity impaired the ability of the S3DN cells to scatter upon stimulation with HGF (c-met ligand), enhanced their adhesion, and diminished their capacity to invade <it>in vitro </it>and <it>in vivo</it>. Surprisingly, S3DN cells also showed suppressed HGF-induced activation of c-met, and had nearly undetectable basal c-met activity, as revealed by a phospho-specific c-met antibody. In addition, we showed that there is a strong membrane specific localization of phospho-Stat3 in the wild type (WT) and vector transfected control (NEO4) SRB12-p9 cells, which is lost in the S3DN cells. Finally, co-immunoprecipitation experiments revealed that S3DN interfered with Stat3/c-met interaction.</p> <p>Conclusion</p> <p>These studies are the first confirm that interference with the HGF/c-met/Stat3 signaling pathway can block tumor cell invasion in an <it>in vivo </it>model. We also provide novel evidence for a possible positive feedback loop whereby Stat3 can activate c-met, and we correlate membrane localization of phospho-Stat3 with invasion <it>in vivo</it>.</p

Room-Temperature Sodium-Sulfur Batteries: A Comprehensive Review on Research Progress and Cell Chemistry

Room temperature sodium-sulfur (RT-Na/S) batteries have recently regained a great deal of attention due to their high theoretical energy density and low cost, which make them promising candidates for application in large-scale energy storage, especially in stationary energy storage, such as with electrical grids. Research on this system is currently in its infancy, and it is encountering severe challenges in terms of low electroactivity, limited cycle life, and serious self-charging. Moreover, the reaction mechanism of S with Na ions varies with the electrolyte that is applied, and is very complicated and hard to detect due to the multi-step reactions and the formation of various polysulfides. Therefore, understanding the chemistry and optimizing the nanostructure of electrodes for RT-Na/S batteries are critical for their advancement and practical application in the future. In the present review, the electrochemical reactions between Na and S are reviewed, as well as recent progress on the crucial cathode materials. Furthermore, attention also is paid to electrolytes, separators, and cell configuration. Additionally, current challenges and future perspectives for the RT-Na/S batteries are discussed, and potential research directions toward improving RT-Na/S cells are proposed at the end

Gradient Attention Balance Network: Mitigating Face Recognition Racial Bias via Gradient Attention

Although face recognition has made impressive progress in recent years, we ignore the racial bias of the recognition system when we pursue a high level of accuracy. Previous work found that for different races, face recognition networks focus on different facial regions, and the sensitive regions of darker-skinned people are much smaller. Based on this discovery, we propose a new de-bias method based on gradient attention, called Gradient Attention Balance Network (GABN). Specifically, we use the gradient attention map (GAM) of the face recognition network to track the sensitive facial regions and make the GAMs of different races tend to be consistent through adversarial learning. This method mitigates the bias by making the network focus on similar facial regions. In addition, we also use masks to erase the Top-N sensitive facial regions, forcing the network to allocate its attention to a larger facial region. This method expands the sensitive region of darker-skinned people and further reduces the gap between GAM of darker-skinned people and GAM of Caucasians. Extensive experiments show that GABN successfully mitigates racial bias in face recognition and learns more balanced performance for people of different races.Comment: Accepted by CVPR 2023 worksho

TaqMan probe array for quantitative detection of DNA targets

To date real-time quantitative PCR and gene expression microarrays are the methods of choice for quantification of nucleic acids. Herein, we described a unique fluorescence resonance energy transfer-based microarray platform for real-time quantification of nucleic acid targets that combines advantages of both and reduces their limitations. A set of 3′ amino-modified TaqMan probes were designed and immobilized on a glass slide composing a regular microarray pattern, and used as probes in the consecutive PCR carried out on the surface. During the extension step of the PCR, 5′ nuclease activity of DNA polymerase will cleave quencher dyes of the immobilized probe in the presence of nucleic acids targets. The increase of fluorescence intensities generated by the change in physical distance between reporter fluorophore and quencher moiety of the probes were collected by a confocal scanner. Using this new approach we successfully monitored five different pathogenic genomic DNAs and analyzed the dynamic characteristics of fluorescence intensity changes on the TaqMan probe array. The results indicate that the TaqMan probe array on a planar glass slide monitors DNA targets with excellent specificity as well as high sensitivity. This set-up offers the great advantage of real-time quantitative detection of DNA targets in a parallel array format

Promoted Photocharge Separation in 2D Lateral Epitaxial Heterostructure for Visible‐Light‐Driven CO2 Photoreduction

Photocarrier recombination remains a big barrier for the improvement of solar energy conversion efficiency. For 2D materials, construction of heterostructures represents an efficient strategy to promote photoexcited carrier separation via an internal electric field at the heterointerface. However, due to the difficulty in seeking two components with suitable crystal lattice mismatch, most of the current 2D heterostructures are vertical heterostructures and the exploration of 2D lateral heterostructures is scarce and limited. Here, lateral epitaxial heterostructures of BiOCl @ Bi2O3 at the atomic level are fabricated via sonicating‐assisted etching of Cl in BiOCl. This unique lateral heterostructure expedites photoexcited charge separation and transportation through the internal electric field induced by chemical bonding at the lateral interface. As a result, the lateral BiOCl @ Bi2O3 heterostructure demonstrates superior CO2 photoreduction properties with a CO yield rate of about 30 µmol g−1 h−1 under visible light illumination. The strategy to fabricate lateral epitaxial heterostructures in this work is expected to provide inspiration for preparing other 2D lateral heterostructures used in optoelectronic devices, energy conversion, and storage fields