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    Efficiency of lung cancer screening in early diagnosis and treatment program among community residents in Nanshan district, Shenzhen city: a cross-sectional and 2-year follow-up su... by Yarui YANG, Xujun GUO, Yuzheng FAN, Han WANG, Shengbin LI, Juan HE, Chang MA, Junbo BAI, Shengyuan LIU

    Published 2024-11-01
    “…Participants identified as being at high risk for lung cancer underwent low-dose spiral computed tomography (LDCT) of the lungs. Participants at high risk for lung cancer who did not undergo LDCT were followed up. …”
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    Capturing Bone Signal in MRI of Pelvis, as a Large FOV Region, Using TWIST Sequence and Generating a 5-Class Attenuation Map for Prostate PET/MRI Imaging by Mehdi Shirin Shandiz PhD, Hamid Saligheh Rad PhD, Pardis Ghafarian PhD, Khadijeh Yaghoubi MSc, Mohammad Reza Ay PhD

    Published 2018-07-01
    “…As such, a bilinear (µ-map CT-ref ), 5 (µ-map CT-5c ), and 4 class µ-map (µ-map CT-4c ) based on computed tomography (CT) images were generated. Finally, simulated PET data were corrected using µ-map MR-5c (PET-MRAC5c), µ-map MR-4c (PET-MRAC4c), µ-map CT-5c (PET-CTAC5c), and µ-map CT-ref (PET-CTAC). …”
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    Numerical Semigroups with a Fixed Fundamental Gap by María Ángeles Moreno-Frías, José Carlos Rosales

    Published 2024-12-01
    “…</mo></mrow></semantics></math></inline-formula> In particular, we will give an algorithm to compute all the elements of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="script">B</mi><mo>(</mo><mi>a</mi><mo>)</mo></mrow></semantics></math></inline-formula> with a given genus. …”
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    Grape Recognition and Localization Method Based on 3C-YOLOv8n and Depth Camera by LIU Chang, SUN Yu, YANG Jing, WANG Fengchao, CHEN Jin

    Published 2024-11-01
    “…This enhancement increased the receptive field and guided the reconstruction process based on input features while maintaining low parameter and computational complexity, thereby forming the 3C-YOLOv8n model. …”
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    The high-resolution global shipping emission inventory by the Shipping Emission Inventory Model (SEIM) by W. Yi, X. Wang, T. He, H. Liu, Z. Luo, Z. Lv, K. He

    Published 2025-01-01
    “…Subsequently, integrating real-time vessel positions and speeds from AIS data with static technical parameters, emission factors, and other computational parameters, SEIM simulated ship emissions on a ship-by-ship, signal-by-signal basis. …”
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