336 research outputs found
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 , 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 3Ⲡamino-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, 5Ⲡnuclease 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 VisibleâLightâDriven 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 BiOClâ@âBi2O3 at the atomic level are fabricated via sonicatingâassisted 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 BiOClâ@âBi2O3 heterostructure demonstrates superior CO2 photoreduction properties with a CO yield rate of about 30 Âľmol gâ1 hâ1 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
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