CAEFusion: A New Convolutional Autoencoder-Based Infrared and Visible Light Image Fusion Algorithm

To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is proposed.The region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature information.At the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image information.This study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional algorithms.The methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other algorithms.The algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)index.Comprehensive experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.

Unmanned Ship Identification Based on Improved YOLOv8s Algorithm

Aiming at defects such as low contrast in infrared ship images,uneven distribution of ship size,and lack of texture details,which will lead to unmanned ship leakage misdetection and slow detection,this paper proposes an infrared ship detection model based on the improved YOLOv8 algorithm(R_YOLO).The algorithm incorporates the Efficient Multi-Scale Attention mechanism(EMA),the efficient Reparameterized Generalized-feature extraction module(CSPStage),the small target detection header,the Repulsion Loss function,and the context aggregation block(CABlock),which are designed to improve the model’s ability to detect targets at multiple scales and the speed of model inference.The algorithm is validated in detail on two vessel datasets.The comprehensive experimental results demonstrate that,in the infrared dataset,the YOLOv8s algorithm exhibits improvements in various performance metrics.Specifically,compared to the baseline algorithm,there is a 3.1%increase in mean average precision at a threshold of 0.5(mAP(0.5)),a 5.4%increase in recall rate,and a 2.2%increase in mAP(0.5:0.95).Simultaneously,while less than 5 times parameters,the mAP(0.5)and frames per second(FPS)exhibit an increase of 1.7%and more than 3 times,respectively,compared to the CAA_YOLO algorithm.Finally,the evaluation indexes on the visible light data set have shown an average improvement of 4.5%.

Ercao Qinggan decoction regulates apoptosis of hepatocytes in mice with acute liver failure via the TLR4-mediated PI3K/Akt/GSK3βsignal pathway

Background:To clarify the inhibitory effect of Ercao Qinggan decoction(EQD)on acute liver failure(ALF)and its related mechanisms.Methods:HL-7702 hepatocytes were pretreated with TLR4 inhibitor CLI-095,glycogen synthase kinase 3β(GSK3β)inhibitor LiCl and different doses of EQD for 2 hours,and lipopolysaccharide(LPS)(10μg/mL)for 24 hours.Cell apoptosis,TNF-αand IL-6 and GSK3βwere detected by flow cytometry,immunofluorescence,quantitative polymerase chain reaction.After mice were gavaged with different concentrations of EQD for 12 days,ALF mouse models were established intraperitoneal injection of D-Gal/LPS.After 24 hours,the mice were euthanized and the liver tissue was stained with hematoxylin and eosin.Liver cell apoptosis,the serum levels of aspartate aminotransferase,alanine aminotransferase,TNF-αand IL-βwere detected by terminal transferase-mediated dUTP nick end-labelling,enzyme linked immunosorbent assay,quantitative polymerase chain reaction,and Western blotting,respectively.These methods were also used to test the mRNA expression of Bax,Bcl-2 and the protein expression of GSK3β,p-Akt/Akt in livers.Results:CLI-095,LiCl,and EQD significantly inhibited apoptosis induced by LPS,the mRNA expression of IL-6,TNF-αand the nuclear translocation of GSK3βin HL-7702 hepatocytes.EQD dose-dependently inhibited hepatocyte apoptosis,the serum concentration of aspartate aminotransferase and ALT,the expression of TNF-αand IL-β,the ratio of p-GSK3β/GSK3β,p-Akt/Akt in alanine aminotransferase mice.Conclusion:EQD can inhibit hepatocyte apoptosis in ALF mice through regulating TLR4/PI3K/Akt/GSK3βsignaling pathway.

A newly found Paleozoic Japan-type subduction–accretion system

Accretionary orogenic belts are complicated collages composed of magmatic arcs,accretionary complexes,ophiolitic me′langes,fore-arc/back-arc basins and microcontinents formed at convergent plate margins,which are key sites of continental growth through earth history[1].Arcs are important orogenic components of accretionary orogenesis,but the types of active margin with old continental basement and intraoceanic arcs without continental basement and their roles in accretionary orogenesis are different.The Japan-type arc is a special kind of arc

Metapelitic Garnet-Muscovite-Al_2SiO_5-Quartz(GMAQ) Geothermobarometry

The garnet-muscovite geothermometer and garnet-muscovite-Al2SiO5 -quartz （GMAQ） geobarometer have been empirically calibrated under P-T conditions of 1-12 kbar and 460-760 ℃ using natural metapelitic rocks. The chemical compositions of the calibrant muscovite are in the ranges of Fe=0.03-0.21 atoms, Mg=0.02-0.32 atoms and AI VI=1.62-1.96 atoms, respectively, on the ll-oxygen basis per formula unit. The garnet-muscovite thermometer yields similar temperature estimates to the well calibrated garnet-biotite thermometer within error of 4-55 ℃, and successfully discriminates the systematic temperature change of the different zones of either the prograde or inverted metamorphic terranes or thermal contact aureoles. The six formulations of GMAQ barometry yield similar pressure estimates to the well calibrated GASP barometer within error of ±1.2 kbar, and plot the Al2SiOs-bearing metapelite into the correct stability field of the AI2SiOs polymorphs. Moreover, the GMAQ thermobarometers show that the pressure is almost constant for every thermal contact aureole within limited geographic region, which reflects geological condition. The random errors are estimated to be of ca. 4-60 ℃ and 4-1.4 kbar for the geothermometer and geobarometer, respectively. A spreadsheet for applying GMAQ geothermo- barometry is supplied in the Electronic Supplementary Materials.