Targeting the hallmarks of aging: mechanisms and therapeutic opportunities by Fumihiro Sanada, Shinichiro Hayashi, Ryuichi Morishita

“…Aging is a complex biological process characterized by a gradual decline in cellular and physiological function, increasing vulnerability to chronic diseases and mortality. …”
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Adaptive Whole-Brain Dynamics Predictive Method: Relevancy to Mental Disorders by Qian-Yun Zhang, Chun-Wang Su, Qiang Luo, Celso Grebogi, Zi-Gang Huang, Junjie Jiang

“…We also developed an approximate loss function and gradient adjustment mechanism, enhancing parameter fitting accuracy and stability. …”
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Enhanced path planning for robot navigation in Gaussian noise environments with YOLO v10 and depth deterministic strategies by Feng Xiao, Shiwei Chu, Xing Guo, Youhai Zhang, Rubing Huang

“…Recognition accuracy is optimized using cross entropy loss function. The DDPG algorithm is applied to update the path planning strategy, define the state space of robot position, velocity, and Laser Radar (LiDAR) readings, and output possible movement directions and velocities as action outputs. …”
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DSR-YOLO: A lightweight and efficient YOLOv8 model for enhanced pedestrian detection by Mustapha Oussouaddi, Omar Bouazizi, Aimad El mourabit, Zine el Abidine Alaoui Ismaili, Yassine Attaoui, Mohamed Chentouf

“…A second version of the C2f block using SimAM and standard convolutions ensures robust feature extraction in deeper layers with optimized computational efficiency. The WIoUv3 loss function was utilized to reduce the regression loss associated with bounding boxes, further boosting the performance. …”
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YOLOv10-kiwi: a YOLOv10-based lightweight kiwifruit detection model in trellised orchards by Jie Ren, Wendong Wang, Yuan Tian, Jinrong He

“…In addition, a MPDIoU loss function is introduced to overcome the limitations of the traditional CIoU in terms of aspect ratio mismatch and bounding box regression, accelerating convergence and improving detection accuracy. …”
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Dynamic Bidirectional Feature Enhancement Network for Thin Cloud Removal in Remote Sensing Images by Yu Wang, Hao Chen, Ye Zhang, Guozheng Li

“…Then, we present a dynamic enhancement-based bidirectional information flow module to model the dynamic interaction between multitask features, guiding detail recovery and feedback for optimized cloud removal features. Finally, we design a physics-aware joint loss function incorporating atmospheric light consistency constraints to ensure the physical authenticity of cloud-free images. …”
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SWMD-YOLO: A Lightweight Model for Tomato Detection in Greenhouse Environments by Quan Wang, Ye Hua, Qiongdan Lou, Xi Kan

“…Additionally, we introduce Focaler-IoU, a novel loss function that addresses sample imbalance by dynamically re-weighting gradients for partially occluded and multi-scale targets. …”
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Large Language Model-Guided SARSA Algorithm for Dynamic Task Scheduling in Cloud Computing by Bhargavi Krishnamurthy, Sajjan G. Shiva

“…The experimental results validate the inference of mathematical modeling in terms of the convergence rate and better estimation of the heuristic value to optimize the value function of the SARSA learning algorithm.…”
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Tower view object detection based on ECIOU structure embedded in YOLO by QIAN Jide, YAN Hao, LIANG Yan, ZENG Changchang, MOU Yihao

“…Thirdly，the ECIOU Loss is used to replace the original CIOU loss function to improve its detection performance in complex environments. …”
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Application of Improved LSTM Model in Runoff Simulation in Arid Region of Northwest China: A Case Study of the Zuli River by SONG Haiping, TANG Yiran, DANG Wentao, WANG Yibo

“…Using observed runoff, precipitation, and monthly mean temperature data from 1980 to 2020, the research incorporated feature engineering, combined with extreme-value post-processing and mixed loss function optimization. On this basis, the grey wolf optimization (GWO) algorithm was used to optimize the parameters of the LSTM-Attention model, and the GWO-LSTM-Attention model was constructed, enhancing the models' capability to capture the region's complex runoff mechanisms. …”
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SSD-YOLO: a lightweight network for rice leaf disease detection by Canlin Pan, Shen Wang, Shen Wang, Yahui Wang, Chaoyang Liu

“…Furthermore, Shape-aware Intersection over Union (ShapeIoU) Loss replaces the traditional Complete Intersection over Union (CIoU) loss function, boosting model performance in complex environments. …”
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A hybrid zero-reference and dehazing network for joint low-light underground image enhancement by Qing Du, Shihao Zhang, Zhipeng Wang, Jincheng Liang, Shijiao Yang

“…It addresses two key aspects: (1) enhancing low-light images by incorporating higher-order loss curves into the DCE-Net backbone and introducing a new loss function to optimize network learning for improved low-light image quality; (2) addressing the color distortion and blur caused by low light enhancement through post-processing using convolutional neural networks, with AOD-Net enhancing the clarity of downhole images. …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…However, existing recognition methods typically have limitations, such as inadequate modeling capabilities for complex actions, low accuracy under occlusion and perspective changes, and difficulty meeting real-time requirements. The study optimized the single-shot multibox detector algorithm by introducing the focal loss function and other means. …”
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Rapid and accurate detection of peanut pod appearance quality based on lightweight and improved YOLOv5_SSE model by Zhixia Liu, Xilin Zhong, Chunyu Wang, Guozhen Wu, Fengyu He, Jing Wang, Dexu Yang

“…Furthermore, the substitution of various loss functions was investigated, with the Focal-EIoU loss function employed as the regression loss term for predicting bounding boxes, thereby improving inference accuracy.ResultsCompared to the YOLOv5s network model, SSE-YOLOv5s boasts a mere 6.7% of the original model’s parameters, 7.8% of the computation, and an FPS rate 115. 1% higher. …”
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The Application Potential and Advance of Mesenchymal Stem Cell-Derived Exosomes in Myocardial Infarction by Xianyun Wang, Yida Tang, Zhao Liu, Yajuan Yin, Quanhai Li, Gang Liu, Baoyong Yan

“…Myocardial infarction (MI) is a devastating disease with high morbidity and mortality caused by the irreversible loss of functional cardiomyocytes and heart failure (HF) due to the restricted blood supply. …”
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An Interpretable Siamese Attention Res-CNN for Fingerprint Spoofing Detection by Chengsheng Yuan, Zhenyu Xu, Xinting Li, Zhili Zhou, Junhao Huang, Ping Guo

“…Furthermore, to highlight the difference in RCF, a Siamese attention residual network is devised, and the ridge continuity amplification loss function is designed to optimize the training process. …”
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An efficient fire detection algorithm based on Mamba space state linear attention by Yuming Li, Yongjie Wang, Xiaorui Shao, Anbo Zheng

“…Additionally, a dynamic non-monotonic focusing mechanism and distance penalty strategy are employed to refine the loss function, leading to a substantial improvement in bounding box accuracy. …”
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Tailhook Recognition for Carrier-Based Aircraft Based on YOLO with Bi-Level Routing Attention by Aiguo Lu, Pandi Liu, Jie Yang, Zhe Li, Ke Wang

“…Secondly, a bi-level routing attention mechanism was employed to dynamically focus on the regions of the feature map that are more likely to contain the target, leading to more accurate target localization and classification. Additionally, the loss function was optimized to accelerate the bounding box regression process. …”
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Developing a 160 kW continuous wave circulator for the P-band high-frequency system of the Wuhan light source by XIAO Chengcheng, ZHANG Qiang, WANG Cheng, ZHANG Junqiang, FANG Wencheng, XU Yiming

“…In this case, if the reflected power suddenly increases during device operation, the temperature of the circulator cavity will be risen and the parameter characteristics of the gyromagnetic ferrite will be changed in the circulator, and eventually lead to poor absorption of the reflected power by the load.PurposeThis study aims to design and develop a circulator with a temperature compensation control unit, capable of functioning at 499.654 MHz with a 160 kW continuous wave radiofrequency power.MethodsFirstly, the circulator was simulated and optimized using the HFSS software. …”
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SSMM-DS: A semantic segmentation model for mangroves based on Deeplabv3+ with swin transformer by Zhenhua Wang, Jinlong Yang, Chuansheng Dong, Xi Zhang, Congqin Yi, Jiuhu Sun

“…We then employed Swin Transformer as the backbone network, enhancing the capability of global information learning and detail feature extraction. Finally, we optimized the loss function by combining cross-entropy loss and dice loss, addressing the issue of sampling imbalance caused by the small areas of mangroves. …”
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