M²UNet: Multi-Scale Feature Acquisition and Multi-Input Edge Supplement Based on UNet for Efficient Segmentation of Breast Tumor in Ultrasound Images by Lin Pan, Mengshi Tang, Xin Chen, Zhongshi Du, Danfeng Huang, Mingjing Yang, Yijie Chen

“…The experimental results show that our method has made substantial progress in improving accuracy.…”
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Optimizing the screening process for TIRADS could reduce the number of unnecessary thyroid biopsies by Ke Lu, Long Wang, Shuiqing Lai, Zhijiang Chen, Qibo Zhu, Shuzhen Cong, Kehong Gan, Xiaoyan Chen, Chunwang Huang, Jian Kuang

“…Subsequently, several methods derived from the combination of two TIRADS were constructed via serial testing. …”
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Local and global sensitivity analysis of key durability parameters of concrete under chloride environment by Lingjie Wu, Chengjian Yu, Fenfei Shi, Xuping Ni

“…This study investigates the local and global sensitivity of five critical durability parameters affecting concrete performance in chloride environments: concrete cover thickness (d), apparent chloride diffusion coefficient (Dₐₚₚ), surface chloride concentration (Cₛ), critical chloride concentration (Ccr), and age factor (m) for characterizing the time-dependent decay of Dₐₚₚ. By integrating the One-At-a-Time (OAT) method for local sensitivity analysis with the extended Fourier Amplitude Sensitivity Test (EFAST) and Sobol methods for global sensitivity analysis, a systematic evaluation is conducted to identify distinct influence mechanisms of these parameters under deterministic and time-dependent durability life prediction models. …”
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A Computationally Efficient Learning-Based Control of a Three-Phase AC/DC Converter for DC Microgrids by Ran Li, Wendong Feng, Tianhao Qie, Yulin Liu, Tyrone Fernando, Herbert HoChing Iu, Xinan Zhang

“…Experimental results confirm that the proposed method outperforms conventional PI and model predictive controllers in terms of response speed, harmonic suppression, and robustness under parameter variations. …”
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Improving Medical Image Segmentation Using Test-Time Augmentation with MedSAM by Wasfieh Nazzal, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio

“…The method generates several input variations during inference that are combined after, improving robustness and segmentation accuracy without requiring retraining. …”
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MCRS-YOLO: Multi-Aggregation Cross-Scale Feature Fusion Object Detector for Remote Sensing Images by Lu Liu, Jun Li

“…However, remote sensing images typically exhibit the following characteristics: significant variations in object scales, dense small targets, and complex backgrounds. …”
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Study on Tooth Surface Roughness Modeling of Form Grinding Considering the Change of the Local Grinding Condition by Chen Xiaoqi, Tang Cheng, Liao Xianggui, Zhou Weihua, Tang Jinyuan

“…Therefore, this study proposes a method for modeling the surface roughness of gear form grinding, considering the variation of local grinding strips. …”
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Design and CFD simulation of guide vane for multistage Savonius wind turbine by Dionisius Devin, Levin Halim, Bagus Made Arthaya, Jonathan Chandra

“…There are two methods, the first method is computational fluid dynamics (CFD) simulation to evaluate the best performance guide vane angle variations. …”
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Defining and Measuring Engagement and Adherence in Digital Mental Health Interventions: Protocol for an Umbrella Review by Lyen Krenz Yap, Edel Ennis, Maurice Mulvenna, Jorge Martinez-Carracedo

“…Findings will be presented using a mixed methods convergent integrated approach, identifying and synthesizing themes across the included quantitative and qualitative study results. …”
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GIRH-Unet: Improved Residual Tobacco Segmentation Algorithm Based on GhostNetV3-Unet by Jianhua Ye, Yunda Zhang, Pan Li, Ze Guo

“…We employ Focal Loss combined with Intersection over Union (IoU) loss to address the class imbalance challenge between positive and negative pixel classes, thereby improving the segmentation performance in regions with morphological and size variations. Moreover, we designed an image enhancement method based on Poisson fusion to mitigate the difficulties associated with sample labeling. …”
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Spatiotemporal evolution and coupling coordination of multi-objective and multi-dimensional water resources carrying capacity by Zhaoyang Li, Lei Cao, Shuxia Wang, Zhenxin Liu, Mingqian Ma

“…Based on this, the study develops a multi-objective (water resource–socio-economics–ecological environment) and multi-dimensional (water quantity–water quality–watershed–water flow) evaluation framework for WRCC in western Jilin. Using an integrated entropy weight method (EWM)-the technique for order preference by similarity to an ideal solution method (TOPSIS)-the Adversarial Interpretive Structure Modeling (AISM) method, the temporal evolution and spatial differentiation of WRCC in ten counties from 2000 to 2020 were assessed. …”
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Assessment of agricultural watershed water budget considering upstream water budget against reservoir discharge and agricultural water supply by Seokhyeon Kim, Soonho Hwang, Hyunji Lee, Moon Seong Kang

“…This study proposes a watershed baseflow and direct runoff assessment methodology considering agricultural reservoirs, consisting of an assessment method that reflects the upstream water budget in the reservoir water balance and a watershed analysis using a linked modeling technique. …”
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Noninvasive Continuous Glucose Monitoring Using Multimodal Near-Infrared, Temperature, and Pressure Signals on the Earlobe by Jongdeog Kim, Bong Kyu Kim, Mi-Ryong Park, Hyoyoung Cho, Chul Huh

“…A novel Multi-Wavelength Slope Efficiency Near-Infrared Spectroscopy (MW-SE-NIRS) method is introduced, enhancing noise robustness through the slope efficiency-based parameterization of NIR signal dynamics. …”
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Dynamic Heat Transfer Modeling and Validation of Super-Long Flexible Thermosyphons for Shallow Geothermal Applications by Jianhua Liu, Yanghuiqin Ding, Hao Liu, Liying Zheng, Xiaoyuan Wang, Yuezhao Zhu

“…This work offers a semi-empirical dynamic heat transfer modeling method for geothermal thermosyphons, which can be readily incorporated into the overall simulation of a geothermal system that integrates thermosyphons.…”
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Experimental study on catapult take-off and sudden extension of carrier-based aircraft's nose landing gear by CUI Panli, HE Erming, YUAN Qiangbo, YANG Zhengquan, WANG Binwen

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Increasing and maintaining rates of standardized depression screening in youth with childhood-onset systemic lupus erythematosus in a pediatric rheumatology clinic by Emily Datyner, Jodi Dingle, Victoria Newsome, Lisa H. Buckley, Natasha Belsky, Seungweon Park, Manda Mitchell, Brooke Fine, Barron Patterson, T. Brent Graham, Alaina Davis

“…This represents special cause variation, as evidenced by data shifts on our statistical process control chart. …”
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Systemic inflammatory indices and age-dependent severity in acute appendicitis: a retrospective cohort study by Catalin Vladut Ionut Feier, Catalin Vladut Ionut Feier, Andrei Motoc, Calin Muntean, Razvan Constantin Vonica, Razvan Constantin Vonica, Vasile Gaborean, Vasile Gaborean, Sorin Olariu, Sorin Olariu, Marius Sorin Murariu, Marius Sorin Murariu

“…Their integration into clinical practice could improve diagnostic accuracy, especially in older patients affected by immunosenescence.…”
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Hammering Test for Tile Wall Using Deep Learning by Atsushi Ito, Masafumi Koike, Masako Saito, Katsuhiko Hibino

“…The most widely used method for such inspections is the hammering test, in which inspectors analyze the sound variations produced when a hammer strikes a surface. …”
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Adaptive distributed stochastic deep reinforcement learning control for voltage and frequency restoration in islanded AC microgrids with communication noise and delay by Nima Mahdian Dehkordi, Vahab Nekoukar

“…MATLAB/SimPowerSystems simulations demonstrate the proposed method’s improved performance compared to existing techniques across a range of scenarios involving communication noise, time delays, and load variations. …”
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Spatio-Temporal neighbors adaptive learning with two-point differences for ocean subsurface temperature reconstruction from 1960 to 2022 by An Wang, Hua Su

“…By integrating geoscience domain knowledge and utilizing spatiotemporal autocorrelation, ASTEN simultaneously learns the spatial pattern and temporal variation of subsurface temperature, and significantly enhances the interpretability and accuracy of ocean temperature reconstructions over a long time series compared to the DINCAE and DINEOF. …”
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