Sustainability in pharmaceutical analysis: greenness assessment of HPLC methods for paclitaxel by Ruchita Rajput, Sonal Desai

“…Abstract Sustainability in pharmaceutical analysis is gaining significant attention, driven by global initiatives to reduce environmental impact and enhance operational efficiency. This study evaluates the greenness of HPLC-based methods for paclitaxel quantification using seven assessment tools: NEMI, Complex NEMI, Analytical Eco-Scale, SPMS, ChlorTox, RGBfast, and BAGI. …”
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Research on herd sheep facial recognition based on multi-dimensional feature information fusion technology in complex environment by Fu Zhang, Fu Zhang, Xiaopeng Zhao, Shunqing Wang, Yubo Qiu, Sanling Fu, Yakun Zhang

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Efficient Method of Road Outlier Recognition Using Deep Learning Coupled with Data Augmentation Approach by Sarfaraz Natha, Fareed Ahmed Jokhio, Muhammad Shafique, Naeem Ahmed, Danish Munir Arain

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Shield tunneling efficiency and stability enhancement based on interpretable machine learning and multi-objective optimization by Wenli Liu, Yang Chen, Tianxiang Liu, Wen Liu, Jue Li, Yangyang Chen

“…Adequate control of shield machine parameters to ensure the safety and efficiency of shield construction is a difficult and complex problem. …”
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Genome-wide analyses reveal intricate genetic mechanisms underlying egg production efficiency in chickens by Lizhi Tan, Xinyu Cai, Yuan Kong, Zexuan Liu, Zilong Wen, Lina Bu, Yuzhan Wang, Xiaojun Liu, Zhiwu Zhang, Jianlin Han, Dandan Wang, Yiqiang Zhao

“…Furthermore, our results identified the CNNM2 gene, known for its role in magnesium homeostasis, plays a dual role in egg production variance, promoting variability during the up-stage while reducing it during the sustained-stage to optimize egg production efficiency. Conclusions Collectively, our multiple genome analyses reveal a complex genetic mechanism underlying more efficient and stable egg production, and establish chicken genetics as a model for studying reproductive efficiency across species.…”
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Radar Scattering Analysis of Multi-Scale Complex Targets by Fast VSBR-MoM Method in Urban Scenes by Zhou Cong, Jihong Gu, Ying Zhang, Jie Yang, Dazhi Ding

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Enhanced anomaly traffic detection framework using BiGAN and contrastive learning by Haoran Yu, Wenchuan Yang, Baojiang Cui, Runqi Sui, Xuedong Wu

“…However, existing methods face many challenges when processing complex high-dimensional traffic data. Especially in dealing with redundant features, data sparsity and nonlinear features, traditional methods often suffer from high computational complexity and low detection efficiency. …”
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Classifying IoT Botnet Attacks With Kolmogorov-Arnold Networks: A Comparative Analysis of Architectural Variations by Phuc Hao do, Tran Duc Le, Truong Duy Dinh, van Dai Pham

“…The Original-KAN variant, in particular, excelled in capturing complex, non-linear patterns inherent in IoT botnet traffic, achieving higher accuracy and faster convergence rates. …”
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Increase the effectiveness of radar detection systems by adapting to the spatial orientation of the object of observation by S. N. Yarmolik, M. V. Svinarskiy, A. S. Khramenkov, E. V. Zaiko

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FSDN-DETR: Enhancing Fuzzy Systems Adapter with DeNoising Anchor Boxes for Transfer Learning in Small Object Detection by Zhijie Li, Jiahui Zhang, Yingjie Zhang, Dawei Yan, Xing Zhang, Marcin Woźniak, Wei Dong

“…This approach achieves a balance between computational efficiency for medium-resolution images and the accuracy required for small object detection. …”
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Dynamic response and discrimination of gaseous sarin using a boron‐difluoride complex film‐based fluorescence sensor by Zhijie Zhou, Lei Zhang, Lingya Peng, Yingjie Li, Xiaolin Zhu, Yidi Wu, Zebiao Qiu, Gang He, Molin Qin, Haonan Peng, Yu Fang

“…Abstract This study presents a novel boron‐difluoride complex‐based fluorescent nanofilm sensor capable of detecting sarin vapors in the environment by reporting an output fluorescence signal. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Aiming at the common low accuracy and efficiency problems in underwater target detection, this paper designs an innovative algorithm based on the YOLOv7 framework. …”
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An improved method of AUD-YOLO for surface damage detection of wind turbine blades by Li Zou, Anqi Chen, Xinhua Yang, Yibo Sun

“…Abstract The detection of wind turbine blades (WTBs) damage is crucial for improving power generation efficiency and extending the lifespan of turbines. …”
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FUR-DETR: A Lightweight Detection Model for Fixed-Wing UAV Recovery by Yu Yao, Jun Wu, Yisheng Hao, Zhen Huang, Zixuan Yin, Jiajing Xu, Honglin Chen, Jiahua Pi

“…Even in complex environments with low light, occlusion, or small targets, it can provide more accurate detection results.…”
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Sports video temporal action detection technology based on an improved MSST algorithm by Lai Lixin, Fang Yu

“…Sports videos contain a large number of irrelevant backgrounds and static frames, which affect the efficiency and accuracy of temporal action detection. …”
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BDK-YOLOv8: An Enhanced Algorithm for UAV Infrared Image Object Detection by Nan Xiao, Xianggong Hong, Zixuan Zheng

“…Finally, channel pruning is applied to reduce model parameters and computational complexity, improving detection efficiency.Experimental results show that the proposed algorithm achieves 94.3% mAP50 on the HIT-UAV dataset, a 1.6% improvement over the original YOLOv8n, with a 3% increase in recall. …”
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HGLFNet: Hybrid Global Semantic and Local Detail Feature Network for Lane Detection by Lei Ding, Chunhui Tang, Yi Fang

“…The experimental results comprehensively demonstrate that HGLFNet surpasses the existing state-of-the-art techniques in both accuracy and efficiency, providing a novel and effective solution for lane detection in complex scenarios and showing significant potential in practical applications.…”
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Advancing multi-categorization and segmentation in brain tumors using novel efficient deep learning approaches by Nadenlla RajamohanReddy, G. Muneeswari

“…Brain tumors are most commonly detected by magnetic resonance imaging (MRI) scans. …”
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Self-Supervised Drift-Resilient Classification for Time Series Industrial Anomaly Detection by Myung-Kyo Seo, Byeong Hoon Yoon, Junseung Ryu, Hyung Ju Hwang

“…In modern industrial environments, early detection of anomalies is essential to prevent unplanned downtime and maintain operational efficiency. …”
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Effects of Hybridizing the U-Net Neural Network in Traffic Lane Detection Process by Aron Csato, Florin Mariasiu

“…Similarly, in the Carla dataset (known for the complexity of the generated images), a substantial improvement was recorded, with an increase of +8.0% in mIoU and +5.7% in F1 score, showing better adaptability of the model to geometric structures in complex images. …”
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