Acoustic Emission-Based Pipeline Leak Detection and Size Identification Using a Customized One-Dimensional DenseNet by Faisal Saleem, Zahoor Ahmad, Muhammad Farooq Siddique, Muhammad Umar, Jong-Myon Kim

“…To further improve signal quality, adaptive thresholding and denoising techniques are applied, filtering out low-amplitude noise while preserving critical diagnostic information. The denoised signals are processed using a DenseNet-based deep learning model, which combines convolutional layers and densely connected feature propagation to extract fine-grained temporal dependencies, ensuring the accurate classification of leak presence and severity. …”
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3D Anisotropic Asymmetric Pyramid (AAP-Net) Network Model for Brain Metastases Segmentation on Multi-Sequence MRI by Omar Farghaly, Priya Deshpande

“…However, most existing approaches utilize 2D images, overlooking spatial information and employing uniform isotropic images, which deviates from real-life conditions where anisotropic images are more common. …”
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DeepECG-Net: a hybrid transformer-based deep learning model for real-time ECG anomaly detection by Manal Alghieth

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ICT-Net: A Framework for Multi-Domain Cross-View Geo-Localization with Multi-Source Remote Sensing Fusion by Min Wu, Sirui Xu, Ziwei Wang, Jin Dong, Gong Cheng, Xinlong Yu, Yang Liu

“…To facilitate practical deployment, we propose a deep embedding clustering algorithm optimized for rapid parsing of geo-localization information. Extensive experiments demonstrate that ICT-Net establishes new state-of-the-art localization accuracy on the CVUSA benchmark, achieving a top-1 recall rate improvement of 8.6% over previous methods. …”
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Book review: Code: from information theory to French theory by Marco Schirone

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PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific by Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li

“…In this paper, we proposed PGTransNet, a novel physics-guided transformer network for 3D Ocean temperature and salinity forecasting. …”
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Discovery and re-use of scholarly literature:Using information resources by Kabale University

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ResTreeNet: A Height-Aware LiDAR Tree Classification Model With Explainable AI for Forestry Applications by Asrat Kaleab Taye, Jeong-Mook Park, Hyung-Ju Cho, Jin-Taek Kang, Yeon-Ok Seo

“…Light detection and ranging (LiDAR) technology, capturing highly detailed 3D structural information of vegetation, has become a powerful tool for automated tree classification. …”
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MACA-Net: Mamba-Driven Adaptive Cross-Layer Attention Network for Multi-Behavior Recognition in Group-Housed Pigs by Zhixiong Zeng, Zaoming Wu, Runtao Xie, Kai Lin, Shenwen Tan, Xinyuan He, Yizhi Luo

“…Furthermore, MACA-Net significantly reduces parameters by 48.4% and FLOPs by 39.5%. …”
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DiffuseGaitNet: Improving Parkinson’s Disease Gait Severity Assessment With a Diffusion Model Framework by Arshak Rezvani, Nasrin Ravansalar, Mohammad Ali Akhaee, Andrew J. Greenshaw, Russell Greiner, Maryam S. Mirian, Muhammad Yousefnezhad, Martin J. McKeown

“…The full codebase is available on GitHub: <uri>https://github.com/arshakRz/DiffuseGaitNet</uri>…”
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Food insecurity status and determinants among Urban Productive Safety Net Program beneficiary households in Addis Ababa, Ethiopia. by Atimen Derso, Hailemichael Bizuneh, Awoke Keleb, Ayechew Ademas, Metadel Adane

“…<h4>Background</h4>Measuring household food insecurity in specific geographic areas provides vital information that enables appropriate and effective intervention measures to be taken. …”
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Neuromorphic, physics-informed spiking neural network for molecular dynamics by Vuong Van Pham, Temoor Muther, Amirmasoud Kalantari Dahaghi

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TomatoPoseNet: An Efficient Keypoint-Based 6D Pose Estimation Model for Non-Destructive Tomato Harvesting by Jipeng Ni, Licheng Zhu, Lizhong Dong, Ruixue Wang, Kaikang Chen, Jianbo Gao, Wenbei Wang, Liming Zhou, Bo Zhao, Jiacheng Rong, Zhenhao Han, Kunlei Lu, Xuguang Feng

“…To address these challenges, we propose a keypoint-based pose estimation model, TomatoPoseNet, tailored to meet the agronomic requirements of tomato harvesting. …”
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Domain-informed CNN architectures for downscaling regional wind forecasts by Alexander M. Campbell, Simon C. Warder, B. Bhaskaran, Matthew D. Piggott

“…Specifically, the proposed approach combines two sequential U-Nets – the first upsamples the input wind fields and expands the number of feature maps, a fusion layer then injects prior static data such as topography, and a second U-Net generates the final output wind field. …”
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Kabale University Students Handbook: General Information and Academic Regulations by Kabale University

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Associations of NETs with inflammatory risk and clinical predictive value in large artery atherosclerosis stroke: a prospective cohort study by Jiang Li, Jiang Li, Lei Liu, Ruxu Zhang, Liqun Pan, Juanying Tan, Mingxin Ou, Xiuju Luo, Jun Peng, Zhongyang Hu, Zhongyang Hu

“…Background and objectiveNeutrophil extracellular traps (NETs) with inflammatory risk are important contributors to cardiovascular disease, but no definitive information is available in large artery atherosclerotic (LAA) stroke. …”
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Scanning The Business Environment For Information: a Grounded Theory approach by Zita Correia, T.D. Wilson

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Typology of out-of-home eaters: a description of sociodemographic, lifestyle, nutritional and environmental characteristics in the NutriNet-Santé cohort by Emma Meyer, Benjamin Allès, Justine Berlivet, Sandrine Péneau, Alice Bellicha, Mathilde Touvier, Brigitte Langevin, Philippe Pointereau, Denis Lairon, Serge Hercberg, Emmanuelle Kesse-Guyot, Julia Baudry

“…Abstract Background The out-of-home (OOH) food sector holds the potential to promote healthier and more sustainable diets on a large scale given the high number of people eating OOH regularly. However, information about socioeconomic and dietary characteristics of OOH eaters is limited. …”
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Health information for the teenage years: what do they want to know? by J. Rolinson

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Textual and chemical information processing: different domains but similar algorithms by Peter Willett

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