DM-YOLO: improved YOLOv9 model for tomato leaf disease detection by Abudukelimu Abulizi, Junxiang Ye, Halidanmu Abudukelimu, Wenqiang Guo

“…When evaluated based on the tomato leaf disease dataset, the precision (P) of the model was 92.5%, and the average precision (AP) and the mean average precision (mAP) were 95.1% and 86.4%, respectively, which were 3%, 1.7%, and 1.4% higher than the P, AP, and mAP of YOLOv9, the baseline model, respectively. The proposed detection method had good detection performance and detection potential, which will provide strong support for the development of smart agriculture and disease control.…”
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HCFC-141b (CH3CCl2F) Emission Estimates for 2000–2050 in Eastern China by Dayu Zhang, Jing Wu, Zehua Liu, Tong Wang, Yueling Zhang, Dongmei Hu, Lin Peng

“…Under the control of the Montreal Protocol, China should phase out the production and consumption of HCFC-141b by 2030. This study firstly estimated the HCFC-141b emissions in eastern China based on the bottom-up method during 2000–2019. …”
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