Fine-Grained Style Alignment and Class Balance for Unsupervised Domain Adaptation in Remote Sensing Image Segmentation by Yousheng Xu, Weiji Wang, Wei Yao, Shengzhou Xu

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Investigation on the Radar Scattering and Doppler Spectrum From Trimaran Based on the Motion of Six Degrees of Freedom by Yuxin Deng, Jinxing Li, Wangqiang Jiang, Min Zhang

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Towards an RFI Mitigation Algorithm in Synthetic Aperture Interferometer Radiometry: Application to the SMOS Space Mission by Ali Khazaal

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A Scale-Aware and Discriminative Feature Learning Network for Fine-Grained Rigid Object Recognition by Yangte Gao, Chenwei Deng, Liang Chen, Zicong Zhu

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A Machine-Learning-Based Ocean-Current Velocity Inversion Model Using OCN From Sentinel-1 Observations by Yang Bai, Yubin Zhang, Xudong Zhang, Xiaofeng Li

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Estimation of Above-Ground Biomass for <italic>Dendrocalamus Giganteus</italic> Utilizing Spaceborne LiDAR GEDI Data by Huanfen Yang, Zhen Qin, Qingtai Shu, Li Xu, Jinge Yu, Shaolong Luo, Zaikun Wu, Cuifen Xia, Zhengdao Yang

“…The outcomes reveal that 1) the results showed that the power function emerged as the most efficacious model, with coefficient of determination (<italic>R</italic>²) &#x003D; 0.87 and root mean square error (RMSE) &#x003D; 0.00051 Mg, in estimating the AGB of <italic>Dendrocalamus giganteus</italic>. 2) Based on the feature importance ranking of Random Forest, five variables were selected from the 40 extracted from GEDI, achieving RMSE &#x003D; 8.21 Mg&#x002F;ha and mean absolute error (MAE) &#x003D; 6.12 Mg&#x002F;ha. …”
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Infrared Satellite Detection Limits for Monitoring Atmospheric Ammonia by Mark W. Shephard, Shailesh K. Kharol, Enrico Dammers, Christopher E. Sioris, Andrew Bell, Rik Jansen, Jerome Caron, Ralph Snel, Emanuela Palombo, Karen E. Cady-Pereira, Chris A. McLinden, Erik Lutsch, Robert O. Knuteson

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Wind Field Retrieval From Co-Polarized SAR Imagery Without External Wind Direction Assistance by Xianen Wei, Jinsong Chong, Yawei Zhao, Lijie Diao, Xuan Jin

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Thermal Characteristics Testing and Analysis of Dry Gear Hobbing Machine on Multivariate Information Fusion by Peng Shengdi, Yang Xiao, Li Benjie, He Lang, Zhang Zhili

“…Through the selection of hardware for the lower computer, the development of software functions for the upper computer, and the integration of test functions, the multi-source fusion test method for the thermal characteristics of dry-cutting and hobbing machine was constructed. …”
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Thermal characteristics testing and analysis of dry gear hobbing machines on multivariate information fusion by PENG Shengdi, YANG Xiao, LI Benjie, HE Lang, ZHANG Zhili

“…Through the selection of hardware for the lower computer, the development of software functions for the upper computer, and the integration of test functions, the multi-source information fusion test method for the thermal characteristics of dry gear hobbing machine was constructed. …”
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Transcriptomic analysis reveals that selenium-enriched Lactobacillus plantarum alleviates high -salinity stress in common carp through lipid metabolism and ferroptosis signalling p... by Xinchi Shang, Xinghua Che, Longwu Geng, Qing Zhang, Haijun Wei, Wang Li, Xiaodan Shi, Wei Xu

“…Inland water resource salinisation is a global problem. High salinity leads to increased pressure on the survival of aquatic animals, severely limiting the development of the aquaculture industry. …”
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Research and practice of SASE cloud security by Chaoyang YE, Xin WANG, Shicong ZHANG, Zhiyong ZHAN, Yisha LIU

“…With the development of the Internet today, earth shaking changes have taken place compared with the traditional network.In today's network reform, ＆quot;cloud＆quot; has become the mainstream direction of the evolution of enterprise IT architecture, so the requirements for cloud security are becoming higher and higher.The practical deployment scheme of SASE cloud security architecture was introduced to solve the problem of cloud security for customers.A unique and complete SASE solution was proposed, which combined security functions with SD-WAN functions, and realized real-time monitoring, intelligent analysis and automatic interception of malware or malicious activities by building a unified management and control platform and centralized deployment of core security resource pool.Practice has proved that the scheme achieves the expected results in unified management and control, intrusion detection and defense, fine access control and so on, and can fully ensure the cloud security of enterprises.…”
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Research and practice of SASE cloud security by Chaoyang YE, Xin WANG, Shicong ZHANG, Zhiyong ZHAN, Yisha LIU

“…With the development of the Internet today, earth shaking changes have taken place compared with the traditional network.In today's network reform, ＆quot;cloud＆quot; has become the mainstream direction of the evolution of enterprise IT architecture, so the requirements for cloud security are becoming higher and higher.The practical deployment scheme of SASE cloud security architecture was introduced to solve the problem of cloud security for customers.A unique and complete SASE solution was proposed, which combined security functions with SD-WAN functions, and realized real-time monitoring, intelligent analysis and automatic interception of malware or malicious activities by building a unified management and control platform and centralized deployment of core security resource pool.Practice has proved that the scheme achieves the expected results in unified management and control, intrusion detection and defense, fine access control and so on, and can fully ensure the cloud security of enterprises.…”
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Barriers and facilitators of fetal heart monitoring with a mobile cardiotocograph (iCTG) device in underserved settings: An exploratory qualitative study from Tanzania. by Dorkasi L Mwakawanga, Sanmei Chen, Yhuko Ogata, Minami Suzuki, Yuryon Kobayashi, Miyuki Toda, Naoki Hirose, Yoko Shimpuku

“…<h4>Background</h4>Fetal monitoring in low-resource settings is often inadequate. A mobile cardiotocograph fetal monitoring device is a digital innovation that could ensure the safety of pregnant women at high risk and their fetuses through early detection and management of fetal distress. …”
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Design of the Field Protection and Signal Priority at Intersection System for Autonomous-rail Rapid Transit by SHI Yangyang, LIU Guangyong, WU Jinyong

“…It provides auxiliary driving information for the driver through automation equipment, realizes the functions of route protection, virtual section occupied/unoccupied detection, signal control, entering/leaving station detection, platform door linkage control, berth status detection and management in deport and so on, which improves system security and reduces driver working intensity. …”
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Ensemble learning driven Kolmogorov-Arnold Networks-based Lung Cancer classification. by Abdul Rahaman Wahab Sait, Eid AlBalawi, Ramprasad Nagaraj

“…Early Lung Cancer (LC) detection is essential for reducing the global mortality rate. …”
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Gene-Environment Interactions in Stress Response Contribute Additively to a Genotype-Environment Interaction. by Takeshi Matsui, Ian M Ehrenreich

“…We measured the growth of all 16 haploid combinations of alleles at these loci in all four possible combinations of carbon source (ethanol or glucose) and temperature (30 or 37°C) in a nearly isogenic population. …”
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Retracted: Study on Modeling Method of Forest Tree Image Recognition Based on CCD and Theodolite by Yeqiong Shi, Sainan Wang, Shuna Zhou, M. M. Kamruzzaman

“…Forest vegetation is the main body that constitutes forest resources. Accurate identification of the types of forest trees can lay the foundation for the research and utilization of forest resources. …”
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mdciao: Accessible Analysis and Visualization of Molecular Dynamics Simulation Data. by Guillermo Pérez-Hernández, Peter W Hildebrand

“…We present mdciao, an open-source command line tool and Python Application-Programming-Interface (API) for easy, one-shot analysis and representation of molecular dynamics (MD) simulation data. …”
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Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

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