Haiyan Wu

Single image dehazing is a challenging ill-posed problem due to the severe information degeneration. However, existing deep learning based dehazing methods only adopt clear images as positive samples to guide the training of dehazing network while negative information is unexploited. Moreover, most of them focus on strengthening the dehazing network with an increase of depth and width, leading to a significant requirement of computation and memory. In this paper, we propose a novel contrastive regularization (CR) built upon contrastive learning to exploit both the information of hazy images and clear images as negative and positive samples, respectively. CR ensures that the restored image is pulled to closer to the clear image and pushed to far away from the hazy image in the representation space.Furthermore, considering trade-off between performance and memory storage, we develop a compact dehazing network based on autoencoder-like (AE) framework. It involves an adaptive mixup operation and a dynamic feature enhancement module, which can benefit from preserving information flow adaptively and expanding the receptive field to improve the network’s transformation capability, respectively. We term our dehazing network with autoencoder and contrastive regularization as AECR-Net. The extensive experiments on synthetic and real-world datasets demonstrate that our AECR-Net surpass the state-of-the-art approaches. The code is released in https://github.com/GlassyWu/AECR-Net.

The intracellular level of DNA topoisomerase II appears to be reversibly regulated by serum concentration in cultured primary human skin fibroblasts (HSF). Upon serum starvation, the intracellular level of topoisomerase II in HSF, as monitored by immunoblotting with antitopoisomerase II antibodies, gradually decreased to a nondetectable level (less than 10(4) copies/cell) over a period of 72 h. Addition of 10% serum to the starved cells led to a gradual increase of the intracellular topoisomerase II to the original level (approximately 10(6) copies/cell) over a period of 24 h. The intracellular DNA topoisomerase II level in HSF is also sensitive to cell density; minimally a 7-fold decrease was observed when HSF were grown to saturation density in a constant serum concentration. Similarly, the intracellular levels of DNA topoisomerase II in other "nontransformed" cells such as mouse NIH 3T3 and 3T6 cells are also sensitive to both the serum concentration and the cell density. In contrast, topoisomerase II levels in transformed cells such as HeLa cells, L1210 cells, and SV40 T-antigen-transformed COS-1 cells are maintained at high levels (approximately 10(6) copies/cell) and are much less sensitive to growth conditions. The topoisomerase II level in HeLa cells synchronized by a double thymidine block remained relatively constant (less than 2-fold difference) throughout the late G1, S, G2, and M phases of the cell cycle. Our results suggest that the level of DNA topoisomerase II is primarily regulated in the G0-G1 phase of the cell cycle and is elevated to a high level (approximately 10(6) copies/cell) in proliferating cells. In contrast, the intracellular levels of DNA topoisomerase I in these cells were largely unaffected by these growth conditions either in HSF or in HeLa cells.

Abstract Hydroxyl radical ( • OH) and singlet oxygen ( 1 O 2 ) were detected by electron spin resonance (ESR) spectroscopy in a direct current He/O 2 (2%) non‐thermal plasma microjet‐water system. ${}^{ \bullet }{\rm O}_{{\rm 2}}^{- } $ is shown to be the precursor of • OH. The concentrations of 1 O 2 and • OH are evaluated to be around 6 × 10 −4 and 1.2 × 10 −5 M, respectively. The survival rates of S. aureus exposed to plasma for 20 s in 1 ml H 2 O, SOD (100 U, for scavenging ${}^{ \bullet }{\rm O}_{{\rm 2}}^{- } $ ), D ‐Man (0.15 M , for scavenging • OH), and L ‐His (0.15 M , for scavenging • OH and 1 O 2 ) solutions were 0.7, 1.6, 13.4, and 40.9%, respectively, indicating that 1 O 2 contributes the most to the inactivation. magnified image