YOLOv8n-SSDW: A Lightweight and Accurate Model for Barnyard Grass Detection in Fields by Yan Sun, Hanrui Guo, Xiaoan Chen, Mengqi Li, Bing Fang, Yingli Cao

“…However, existing deep learning models generally suffer from high parameter counts and computational complexity, limiting their practical application in field scenarios. …”
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GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detectionMendeley Data by Abu Kowshir Bitto, Md. Hasan Imam Bijoy, Kamrul Hassan Shakil, Aka Das, Khalid Been Badruzzaman Biplob, Imran Mahmud, Syed Md. Minhaz Hossain

“…The gastrointestinal (GI) system is fundamental to human health, supporting digestion, nutrient absorption, and waste elimination. Disruptions in GI function, such as Gastroesophageal Reflux Disease (GERD) and gastrointestinal polyps, can lead to significant health complications if not diagnosed and managed early. …”
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Sarcopenia diagnosis using skeleton-based gait sequence and foot-pressure image datasets by Muhammad Tahir Naseem, Na-Hyun Kim, Haneol Seo, JaeMok Lee, Chul-Min Chung, Sunghoon Shin, Chan-Su Lee

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COSMIC-2 RFI Prediction Model Based on CNN-BiLSTM-Attention for Interference Detection and Location by Cheng-Long Song, Rui-Min Jin, Chao Han, Dan-Dan Wang, Ya-Ping Guo, Xiang Cui, Xiao-Ni Wang, Pei-Rui Bai, Wei-Min Zhen

“…Interference reduces the signal reception quality of ground terminals and may even lead to the paralysis of GNSS function in severe cases. In recent years, Low Earth Orbit (LEO) satellites have been highly emphasized for their unique advantages in GNSS interference detection, and related commercial and academic activities have increased rapidly. …”
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A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms by Jangjae Lee, Sangkeun Lee, Supriya Chinthavali, Stephanie Paal

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Determination of stability of the cutting process under dynamic loading conditions by A.S. Manokhin, S.An. Klimenko, S.A. Klimenko, M.Yu. Kopieikina, Yu.O. Melniychuk, A.O. Chumak, A.G. Naidenko

“…The prediction of the dependence is carried out using machine learning based on the XGB method (extreme gradient acceleration). …”
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WSDC-ViT: a novel transformer network for pneumonia image classification based on windows scalable attention and dynamic rectified linear unit convolutional modules by Yu Gu, Haotian Bai, Meng Chen, Lidong Yang, Baohua Zhang, Jing Wang, Xiaoqi Lu, Jianjun Li, Xin Liu, Dahua Yu, Ying Zhao, Siyuan Tang, Qun He

“…Additionally, a convolution-based module equipped with a dynamic ReLU activation function is embedded within the transformer encoder to capture fine-grained local details and adaptively enhance feature expression. …”
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AER U-Net: attention-enhanced multi-scale residual U-Net structure for water body segmentation using Sentinel-2 satellite images by Naga Surekha Jonnala, Shaik Siraaj, Y. Prastuti, P. Chinnababu, B. Praveen babu, Shonak Bansal, Prashant Upadhyaya, Krishna Prakash, Mohammad Rashed Iqbal Faruque, K. S. Al-mugren

“…Residual blocks improve feature learning efficiency while addressing the vanishing gradient issue through the inclusion of skip connections. …”
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STATISTICAL PROCESSING OF RESULTS OF TESTING OF STUDENTS by Yulia V. Gumennikova, Elena N. Ryabinova, Ruzilya N. Chernitsina

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Modern Approaches to Achieving Control over Common Health Disorders in Infants: the Effectiveness of Extensively Hydrolyzed and Amino Acid Formulas by Elena A. Vishneva, Darya S. Chemakina, Yulia G. Levina, Kamilla E. Efendieva, Vera G. Kalugina, Anna A. Alekseeva, Liliya R. Selimzyanova, Elena V. Kaitukova, Vladimir A. Barannik

“…It is the first 1000 days of a child’s life that are critical for neuroontogenesis, the formation of further abilities to acquire and improve various skills, and to learn successfully. It is the first 1000 days of a child’s life that are critical for neuroontogenesis, the formation of further abilities to acquire and improve various skills, and to learn successfully. …”
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A time series algorithm to predict surgery in neonatal necrotizing enterocolitis by Cheng Cui, Ling Qiu, Ling Li, Fei-Long Chen, Xiao Liu, Huan Sun, Xiao-Chen Liu, Lei Bao, Lu-Quan Li

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VISION: a modular AI assistant for natural human-instrument interaction at scientific user facilities by Shray Mathur, Noah van der Vleuten, Kevin G Yager, Esther H R Tsai

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University proceedings. Volga region. Technical sciences by A.V. Kostin, P.P. Makarychev

“…The results of the computational experiments confirmed the prospects of applying the machine learning method using nonparametric regression models based on Fourier functions, piecelinear and nonlinear functions.…”

The concept, essence and role of student project activities and project management office placement in the structure of its management by A. I. Gromova, P. V. Pavlovsky

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Genetic targets related to aging for the treatment of coronary artery disease by Kai Huang, Zijun Chen, Ruting Wang, Hangfeng Ying, Jiahao Duan, Yi Zhang, Qianyuan Shi, Chun Yang, Ling Yang

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Artificial Intelligence in Advancing Algal Bioactive Ingredients: Production, Characterization, and Application by Bingbing Guo, Xingyu Lu, Xiaoyu Jiang, Xiao-Li Shen, Zihao Wei, Yifeng Zhang

“…This review examines the multidimensional mechanisms by which AI enables and optimizes these processes: (1) AI-powered predictive models, integrated with machine learning algorithms (MLAs), Industry 4.0, and other advanced digital systems, support real-time monitoring and control of intelligent bioreactors, allowing for accurate forecasting of cultivation yields and market demand. (2) AI facilitates in-depth analysis of gene regulatory networks and key metabolic pathways, enabling precise control over the biosynthesis of targeted compounds. (3) AI-based spectral imaging and image recognition techniques enable rapid and reliable identification, classification, and quality assessment of active components. (4) AI accelerates the transition from mass production to the development of personalized medical and functional nutritional products. …”
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Sexual Differences in Delayed Postresuscitative Brain Changes (Experimental Study) by A. V. Volkov, M. Sh. Avrushchenko, N. A. Gorenkova, L. N. Shcherbakova, Yu. V. Zarzhetsky

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Conotoxins: Classification, Prediction, and Future Directions in Bioinformatics by Rui Li, Junwen Yu, Dongxin Ye, Shanghua Liu, Hongqi Zhang, Hao Lin, Juan Feng, Kejun Deng

“…In particular, machine learning (ML) techniques have facilitated advancements in sequence-based classification, functional prediction, and de novo peptide design. …”
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Comprehensive Adaptive Enterprise Optimization Algorithm and Its Engineering Applications by Shuxin Wang, Yejun Zheng, Li Cao, Mengji Xiong

“…Experimental findings show that for unimodal functions, the standard deviation of the CAED is almost 0, which reflects its high accuracy and stability. …”
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Gut microbiome-derived bacterial extracellular vesicles in patients with solid tumours by Surbhi Mishra, Mysore Vishakantegowda Tejesvi, Jenni Hekkala, Jenni Turunen, Niyati Kandikanti, Anna Kaisanlahti, Marko Suokas, Sirpa Leppä, Pia Vihinen, Hanne Kuitunen, Kaisa Sunela, Jussi Koivunen, Arja Jukkola, Ilja Kalashnikov, Päivi Auvinen, Okko-Sakari Kääriäinen, T. Peñate Medina, O. Peñate Medina, Juha Saarnio, Sanna Meriläinen, Tero Rautio, Raila Aro, Reetta Häivälä, Juho Suojanen, Mikael Laine, Pande Putu Erawijattari, Leo Lahti, Peeter Karihtala, Terhi S. Ruuska, Justus Reunanen

“…Conclusion: Our findings suggest that bEVs are unique functional entities. There is a need to explore bEVs together with conventional gut microbiome analysis in functional cancer research to decipher the potential of bEVs as cancer diagnostic or therapeutic biomarkers.…”
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