Mild autonomous cortisol secretion leads to reduced volumetric BMD at lumbar spine in patients with primary aldosteronism by Nabeel Mansour, Denise Bruedgam, Daniel Heinrich, Ulrich Dischinger, Nicole Reisch, Friederike Völter, Friederike Völter, Isabel Stüfchen, Elisabeth Nowak, Stephanie Zopp, Victoriya Vasileva, Osman Öcal, Moritz Wildgruber, Max Seidensticker, Jens Ricke, Martin Bidlingmaier, Martin Reincke, Juínia Ribeiro de Oliveira Longo Schweizer

“…Lumbar volumetric bone mineral density (vBMD) was extracted by a novel convolutional neural network (CNN)-based framework (SpineQ software v1.0) applied to routine CT data, incorporated into the diagnostic protocol for PA. …”
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Satellite Image Time-Series Classification with Inception-Enhanced Temporal Attention Encoder by Zheng Zhang, Weixiong Zhang, Yu Meng, Zhitao Zhao, Ping Tang, Hongyi Li

“…Secondly, IncepTAE adopts one-branch architecture, which reinforces the interaction and congruity of different temporal information. Thirdly, the proposed IncepTAE is more lightweight due to the use of group convolutions. …”
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Total lesion glycolysis of primary tumor and lymphnodes is a strong predictor for development of distant metastases in oropharyngeal carcinoma patients with independent validation... by Sebastian Zschaeck, Marina Hajiyianni, Patrick Hausmann, Pavel Nikulin, Emily Kukuk, Christian Furth, Paulina Cegla, Elia Lombardo, Joanna Kazmierska, Adrien Holzgreve, Iosif Strouthos, Carmen Stromberger, Claus Belka, Michael Baumann, Mechthild Krause, Guillaume Landry, Witold Cholewinski, Jorg Kotzerke, Daniel Zips, Jörg van den Hoff, Frank Hofheinz

“…Lesions were manually delineated in the explorative group and automatically delineated by a convolutional neuronal network (CNN) in the validation group. …”
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FAULT DIAGNOSIS OF GEARBOX UNDER VARIABLE WORKING CONDITION BASED ON WEIGHTED SUBDOMAIN ADAPTIVE ADVERSARIAL NETWORK by ZHANG Huiyun, ZUO Fangjun, YU Xi, YANG Ting

“…Subsequently, a self-calibrated convolutions network (SCNet) incorporating an efficient channel attention (ECA) mechanism acted as a feature extractor, dynamically adjusting the interactions and dependencies between multi-source heterogeneous signals to balance the scale differences between the source and target domain heterogeneous data. …”
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Tactile Augmentation of Material Classification via Imperceptible On‐Skin Triboelectricity Collection by Junting Huang, Stanley Gong Sheng Ka, Haydn Cheong, Yaru Zhang, Daping Chu, Sohini Kar‐Narayan, Wenyu Wang, Yan Yan Shery Huang

“…However, collecting these signals without disrupting normal skin functions and convoluting motion artifacts remains challenging. Additionally, person‐to‐person signal variance complicates data processing. …”
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Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine Learning and Simulations by Jonah C. Rose, Paul Torrey, Francisco Villaescusa-Navarro, Mariangela Lisanti, Tri Nguyen, Sandip Roy, Kassidy E. Kollmann, Mark Vogelsberger, Francis-Yan Cyr-Racine, Mikhail V. Medvedev, Shy Genel, Daniel Anglés-Alcázar, Nitya Kallivayalil, Bonny Y. Wang, Belén Costanza, Stephanie O’Neil, Cian Roche, Soumyodipta Karmakar, Alex M. Garcia, Ryan Low, Shurui Lin, Olivia Mostow, Akaxia Cruz, Andrea Caputo, Arya Farahi, Julian B. Muñoz, Lina Necib, Romain Teyssier, Julianne J. Dalcanton, David Spergel

“…The DREAMS project can be extended further to include different DM models, galaxy formation physics, and astrophysical targets. …”
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A systematic review on the associations between built environment and mental health among older people by Yongkang Chen, Lizhen Xu, Xiangfen Cui, Haoran Yang, Haoran Yang, Yiling Liu, Xin Gao, Jianhong Huang

“…Furthermore, a higher proportion of green spaces, improved facility accessibility, and shorter travel times and distances to destinations are positively linked with better MH of older adults.DiscussionWhile these associations are becoming increasingly evident, research on the effects of density, diversity, and design elements in relation to older adults’ MH remains limited and may varied significantly across different regions. Future research should focus on designing quasi-natural experimental studies to enhance our understanding of the convoluted and elaborate relationship between the BE and MH.…”
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L’impérialisme humanitaire de Michael Ignatieff : le cas d’un « liberal hawk » by Pierre Guerlain

“…Though he often ends up in agreement with neoconservative or neoliberal imperialists his justifications are more intellectual and convoluted and therefore address a different audience.…”
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The Impact of Integrating Shallow and Deep Information on Knowledge Distillation by Yilin Miao, Yuhong Tang, Huangliang Ren, Jianjun Li

“…To address these issues, we propose a shallow feature extraction module (SFEM) that enriches the receptive field of images through dilated convolutions and captures information at different scales, while reducing parameter counts and optimizing computational resources. …”
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MSLKSTNet: Multi-Scale Large Kernel Spatiotemporal Prediction Neural Network for Air Temperature Prediction by Feng Gao, Jiaen Fei, Yuankang Ye, Chang Liu

“…The core module of this network, Multi-scale Spatiotemporal Attention (MSSTA), decomposes large kernel convolutions from multi-scale perspectives, capturing spatial feature information at different scales, and focuses on the evolution of multi-scale spatial features over time, encompassing both global smooth changes and local abrupt changes. …”
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L2-GNN: Graph neural networks with fast spectral filters using twice linear parameterization by Siying Huang, Xin Yang, Zhengda Lu, Hongxing Qin, Huaiwen Zhang, Yiqun Wang

“…To improve learning on irregular 3D shapes, such as meshes with varying discretizations and point clouds with different samplings, we propose L2-GNN, a new graph neural network that approximates the spectral filters using twice linear parameterization. …”
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Compressive Sensing Network Deeply Induced by Visual Mechanism by Mingkun Feng, Xiaole Han, Kai Zheng

“…Furthermore, by introducing dilated convolutions with varying dilation rates, we enable multi-scale feature to be learned, which enhance rich feature and expressive power without increasing model complexity. …”
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WTSM-SiameseNet: A Wood-Texture-Similarity-Matching Method Based on Siamese Networks by Yizhuo Zhang, Guanlei Wu, Shen Shi, Huiling Yu

“…First, to address the issue that fixed receptive fields cannot adapt to textures of different sizes, a multi-receptive field fusion feature extraction network was designed. …”
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GGLA-NeXtE2NET: A Dual-Branch Ensemble Network With Gated Global-Local Attention for Enhanced Brain Tumor Recognition by Adnan Saeed, Khurram Shehzad, Shahzad Sarwar Bhatti, Saim Ahmed, Ahmad Taher Azar

“…Due to the limited availability of training data, the diverse shapes of brain tumors among different patients, inter-class similarity, and intra-class variation, achieving high recognition accuracy and speed in deep learning-based brain tumor recognition remains challenging. …”
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Green Apple Detection Method Based on Multidimensional Feature Extraction Network Model and Transformer Module by Wei Ji, Kelong Zhai, Bo Xu, Jiawen Wu

“…Firstly, an improved DETR network main feature extraction module adopts the ResNet18 network and replaces some residual layers with deformable convolutions (DCNv2), enabling the model to better adapt to pollution-free fruit changes at different scales and angles, while eliminating the impact of microbial contamination on fruit testing; Subsequently, the extended spatial pyramid pooling model (DSPP) and multiscale residual aggregation module (FRAM) are integrated, which help reduce feature noise and minimize the loss of underlying features during the feature extraction process. …”
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Buried penis; what buried the penis? by Mohamed Fawzy, Ahmed T. Hadidi

“…Patients were divided into 3 groups; group A: 13 patients with BP, group B: 14 patients with different grades of distal Hypospadias, and group C with 13 patients who were referred for circumcision (control group). …”
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A novel deep learning method for large-scale analysis of bone marrow adiposity using UK Biobank Dixon MRI data by David M. Morris, Chengjia Wang, Giorgos Papanastasiou, Calum D. Gray, Wei Xu, Samuel Sjöström, Sammy Badr, Julien Paccou, Scott IK Semple, Tom MacGillivray, William P. Cawthorn

“…Bone marrow (BM) segmentation was automated using a new lightweight attention-based 3D U-Net convolutional neural network that improved segmentation of small structures from large volumetric data. …”
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Reconstruction of human dispersal during Aurignacian on pan-European scale by Yaping Shao, Christian Wegener, Konstantin Klein, Isabell Schmidt, Gerd-Christian Weniger

“…However, human dispersal is a highly convoluted process which is until today not well understood. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…The grayscale subtraction method identifies regions of particle motion by calculating differences in grayscale values between consecutive frames and separately analyzing the centroids of moving particles in each frame. …”
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HyperTaste Lab—A Notebook with a Machine Learning Pipeline for Chemical Sensor Arrays by Gianmarco Gabrieli, Michal Muszynski, Matteo Manica, Joris Cadow-Gossweiler, Patrick W. Ruch

“…The cross-sensitivity of materials in low-selective sensor arrays, namely e-noses and e-tongues, results in a convoluted sensor array response, which renders traditional analytical methods for data processing ineffective. …”
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