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City information models for optimal EV charging and energy-resilient renaissance
Published 2025-03-01Get full text
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Adipocyte-specific Steap4 deficiency reduced thermogenesis and energy expenditure in mice
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Impact of new coalbed methane wells on old well productivity and its controlling factors: a case study of Shizhuangnan block in Qinshui Basin
Published 2025-01-01“…From the geological and engineering perspectives, countermeasures and suggestions on well deployment were proposed. …”
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Versatile on-chip polarization-sensitive detection system for optical communication and artificial vision
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Providing a General Model for the Successful Implementation of Digital Transformation in Organizations
Published 2024-06-01“…Conclusion Digital transformation extends beyond the mere adoption of emerging technologies such as artificial intelligence and machine learning; it represents a paradigm shift in how traditional management and operational practices are conducted across various functions, including product development, engineering, marketing, sales, and service delivery. …”
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Physically based modelling of glacier evolution under climate change in the tropical Andes
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Investigating the Use of Generative Adversarial Networks-Based Deep Learning for Reducing Motion Artifacts in Cardiac Magnetic Resonance
Published 2025-02-01“…Ze-Peng Ma,1,2,* Yue-Ming Zhu,3,* Xiao-Dan Zhang,4 Yong-Xia Zhao,1 Wei Zheng,3 Shuang-Rui Yuan,1 Gao-Yang Li,1 Tian-Le Zhang1 1Department of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, People’s Republic of China; 2Hebei Key Laboratory of Precise Imaging of inflammation Tumors, Baoding, Hebei Province, 071000, People’s Republic of China; 3College of Electronic and Information Engineering, Hebei University, Baoding, Hebei Province, 071002, People’s Republic of China; 4Department of Ultrasound, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiao-Dan Zhang, Department of Ultrasound, Affiliated Hospital of Hebei University, No. 212 of Yuhua East Road, Lianchi District, Baoding, 071000, People’s Republic of China, Tel +86 17325535302, Email [email protected]: To evaluate the effectiveness of deep learning technology based on generative adversarial networks (GANs) in reducing motion artifacts in cardiac magnetic resonance (CMR) cine sequences.Methods: The training and testing datasets consisted of 2000 and 200 pairs of clear and blurry images, respectively, acquired through simulated motion artifacts in CMR cine sequences. …”
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