In the past, image retrieval was the mainstream solution for cross-view geolocation and UAV visual localization tasks. In a nutshell, the way of image retrieval is to obtain the final required information, such as GPS, through a transitional perspective. However, the way of image retrieval is not completely end-to-end. And there are some redundant operations such as the need to prepare the feature library in advance, and the sampling interval problem of the gallery construction, which make it difficult to implement large-scale applications. In this article we propose an end-to-end positioning scheme, Finding Point with Image (FPI), which aims to directly find the corresponding location in the image of source B (satellite-view) through the image of source A (drone-view). To verify the feasibility of our framework, we construct a new dataset (UL14), which is designed to solve the UAV visual self-localization task. At the same time, we also build a transformer-based baseline to achieve end-to-end training. In addition, the previous evaluation methods are no longer applicable under the framework of FPI. Thus, Metrelevel Accuracy (MA) and Relative Distance Score (RDS) are proposed to evaluate the accuracy of UAV localization. At the same time, we preliminarily compare FPI and image retrieval method, and the structure of FPI achieves better performance in both speed and efficiency. In particular, the task of FPI remains great challenges due to the large differences between different views and the drastic spatial scale transformation.
Fibrosis is a persistent inflammatory response that causes scarring and tissue sclerosis by stimulating myofibroblasts to create significant quantities of extracellular matrix protein deposits in the tissue. Oxidative stress has also been linked to the development of fibrosis in several studies. The nuclear erythroid 2-related factor 2 (NRF2) transcription factor controls the expression of several detoxification and antioxidant genes. By binding to antioxidant response elements, NRF2 is activated by oxidative or electrophilic stress and promotes its target genes, resulting in a protective effect on cells. NRF2 is essential for cell survival under oxidative stress conditions. This review describes Kelch-like epichlorohydrin-associated protein 1 (KEAP1)/NRF2 signaling mechanisms and presents recent research advances regarding NRF2 and its involvement in primary fibrotic lesions such as pulmonary fibrosis, hepatic fibrosis, myocardial fibrosis, and renal fibrosis. The related antioxidant substances and drugs are described, along with the mechanisms by which KEAP1/NRF2 regulation positively affects the therapeutic response. Finally, the therapeutic prospects and potential value of NRF2 in fibrosis are summarized. Further studies on NRF2 may provide novel therapeutic approaches for fibrosis.
Inspired by the hierarchical chiral assembly of porphyrin-proteins in photosynthetic systems, the hierarchical self-assembly of porphyrin-amino acids/ peptides provides a novel strategy for constructing functional materials. How to artificially simulate...
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