Solar Radio Burst Detection Based on Deformable DETR by Mingming Wang, Guowu Yuan, Hao Zhou, Chengming Tan, Hao Wu

“…First, this study designed a scale-sensitive attention module to better address the scale variations of SRBs. …”
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The Philosophy and Approach on which the PROFILES Project is Based by Jack Holbrook, Miia Rannikmäe

“…The PROFILES project bases the teaching on a theoretically derived, 3 stage model, which is supported through carefully designed PROFILES modules, providing for both the students and the teacher. …”
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InTEIrviews: An ODD for Qualitative Interviews in the Humanities by Marie Puren, Florian Cafiero

“…This ODD is designed to help describe the actual development of the interview, transcribe the interpretations made by the researcher(s), and tackle ethical or anonymity issues.…”
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FUSCANet: Enhancing Skin Disease Classification Through Feature Fusion and Spatial-Channel Attention Mechanisms by Qinyang Liu, Xuan Wang, Hongjiu Liu, Xiangzhen Zang, Lei Li, Zhanlin Ji, Ivan Ganchev

“…Skin diseases represent a prevalent global health issue that significantly impacts the physical and mental well-being of patients. …”
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Channel attention pyramid network for remote physiological measurement by Jing Zhang, Haixin Sun, Yuhao Hu, Guanghao Zhu, Fang Liu, Boyun Yan, Jiahao Pu, Xiaohui Du, Juanxiu Liu, Lin Liu, Ruqian Hao, Xingguo Wang, Yong Liu

“…This method employs a multi-scale deep learning architecture with a Gaussian pyramid to capture facial features at different scales that are often overlooked in prior work. A channel attention module further emphasizes rPPG-rich channels, mitigating the issue of feature dilution caused by excessive channel depth and enhancing the accuracy of physiological signal extraction from facial videos. …”
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Post-approval variations to dossiers for vaccines: analysis of regulatory and methodological approaches used in the Russian Federation and abroad by V. A. Shevtsov, Yu. V. Olefir, V. A. Merkulov, V. P. Bondarev, I. N. Indikova, E. E. Evreinova, A. V. Rukavishnikov, L. M. Khantimirova, D. V. Gorenkov

“…Competent authorities that use the module format of the registration dossier, i.e. the regulatory authorities of the European Union, USA and other members of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH), and the Eurasian Economic Union (EEU), issue guidelines on changes to registration dossiers for pharmaceuticals and biologicals (immunological products). …”
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Central Hyperexcitability in Chronic Musculoskeletal Pain: A Conceptual Breakthrough with Multiple Clinical Implications by Jan Lidbeck

“…Many common chronic musculoskeletal pain syndromes - including regional myofascial pain syndromes, whiplash pain syndromes, refractory work-related neck-shoulder pain, certain types of chronic low back pain, fibromyalgia and others - may essentially be explained by abnormalities in central pain modulation. The growing awareness of dysfunctional central pain modulation may be a conceptual breakthrough leading to a better understanding of common chronic pain disorders. …”
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Software-Defined Visible Light Communication for Internet of Things: A Low-Complexity Approach by Ming Che

“…Simulation results demonstrate that CAP modulation not only delivers high spectral efficiency but also inherently mitigates issues such as IQ imbalance and phase noise, thereby reducing hardware complexity. …”
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STar-DETR: A Lightweight Real-Time Detection Transformer for Space Targets in Optical Sensor Systems by Yao Xiao, Yang Guo, Qinghao Pang, Xu Yang, Zhengxu Zhao, Xianlong Yin

“…Subsequently, the dynamic depthwise shuffle transformer (DDST) feature fusion module is introduced to emphasize the trajectory formed by space target exposure. …”
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YOLOv8-RBean: Runner Bean Leaf Disease Detection Model Based on YOLOv8 by Hongbing Chen, Haoting Zhai, Jinghuan Hu, Hongrui Chen, Changji Wen, Yizhe Feng, Kun Wang, Zhipeng Li, Guangyao Wang

“…Despite the continuous advancement of disease detection technologies, existing legume disease detection models still face significant challenges in identifying small-scale, irregular, and visually insignificant disease types, limiting their practical application. To address this issue, this study proposes an improved detection model, YOLOv8_RBean, based on the YOLOv8n object detection framework, specifically designed for runner bean leaf disease detection. …”
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Frequency Spectrum Adaptor for Remote Sensing Image–Text Retrieval by Ziyi Wan, Enyuan Zhao, Jie Nie, Ze Zhang, Zhiqiang Wei, Nan Zheng, Yuting Zhao

“…Third, a cross-modal spectrum mutual aggregation module was introduced to promote the deep integration of linguistic, spatial, and spectral information. …”
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A weakly-supervised follicle segmentation method in ultrasound images by Guanyu Liu, Weihong Huang, Yanping Li, Qiong Zhang, Jing Fu, Hongying Tang, Jia Huang, Zhongteng Zhang, Lei Zhang, Yu Wang, Jianzhong Hu

“…We propose the Weakly Supervised Follicle Segmentation (WSFS) method, a novel one-stage weakly supervised segmentation technique model designed to enhance the ultrasound images of follicles, which incorporates a Convolutional Neural Network (CNN) backbone augmented with a Feature Pyramid Network (FPN) module for multi-scale feature representation, critical for capturing the diverse sizes and shapes of follicles. …”
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Beyond Hunger: Uncovering the Link between Food Insecurity and Depression, Anxiety, and Stress in Adolescents by Emily Cisneros-Vásquez, Lee Smith, Rodrigo Yañéz-Sepúlveda, Jorge Olivares-Arancibia, Héctor Gutiérrez-Espinoza, Dong Keon Yon, Jae Il Shin, José Francisco López-Gil

“…FI was assessed via the Child Food Security Survey Module, whereas mental health symptoms were evaluated via the Depression, Anxiety, and Stress Scale. …”
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The Voltage-Ear – An Anomaly in Photovoltaic Systems With Undersized Inverters by Ernst Wittmann, Claudia Buerhop-Lutz, Vincent Christlein, Jens Hauch, Christoph J. Brabec, Ian Marius Peters

“…PV installations exhibit the voltage ear under specific conditions where modules generate more power than the inverter can handle. …”
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MSGEGA: Multiscale Gaussian Enhancement and Global-Aware Network for Infrared Small Target Detection by Yuyang Xi, Liuwei Zhang, Ying Jiang, Feng Qian, Fanjiao Tan, Qingyu Hou

“…In recent years, the development of deep learning has significantly improved the performance of infrared small targets detection, particularly in addressing the issue of detecting small infrared targets with high signal-to-clutter ratio (SCR). …”
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Incremental Cotton Diseases Detection Based on Aerial Remote Sensing Image and Blockchain Sharding by Jing Nie, Haochen Li, Yang Li, Jingbin Li, Xuewei Chao, Sezai Ercisli

“…How to improve the efficiency of cotton pest and disease model detection and get better training effect is a key issue in the task of cotton pest and disease management. …”
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TCSRNet: a lightweight tobacco leaf curing stage recognition network model by Panzhen Zhao, Panzhen Zhao, Songfeng Wang, Shijiang Duan, Aihua Wang, Lingfeng Meng, Yichong Hu

“…Secondly, the incorporation of Ghost modules significantly reduces the model’s computational complexity and parameter count through parameter sharing, enabling efficient recognition of tobacco leaf curing stages. …”
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YOLOv5-MDS: Target Detection Model for PCB Defect Inspection Based on YOLOv5 Integrated With Mamba Architecture by Deming Guo, Qi Xi, Long Zhang, Jing Wang, Yilong Ye, Ziyi Zeng

“…Additionally, we optimized the intersection over union (IoU) calculation method and the upsampling module. This strategic integration aims to overcome the inherent limitation of convolutional operations’ local receptive fields, thereby enabling the model to capture features more effectively. …”
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ECAN-Detector: An Efficient Context-Aggregation Network for Small-Object Detection by Gaofeng Xing, Zhikang Xu, Yulong He, Hailong Ning, Menghao Sun, Chunmei Wang

“…Concurrently, a context-augmentation module (CAM) embedded in the shallow layer complements both global and local features relevant to small objects. …”
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Assessment of binary prediction of fraudulent advertisements in ATS candidate tracking cloud systems by V. V. Ligi-Goryaev, G. A. Mankaeva, T. B. Goldvarg, S. S. Muchkaeva, E. N. Dzhakhnaeva

“…Various machine learning algorithms can be employed to address this issue. Traditional classification algorithms, including LSVC (Support Vector Machine), GBT (Gradient Boosting Tree), and RF (Random Forest), have been chosen for this study. …”
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