Measuring Carbon Monoxide With TROPOMI: First Results and a Comparison With ECMWF‐IFS Analysis Data by T. Borsdorff, J. Aan de Brugh, H. Hu, I. Aben, O. Hasekamp, J. Landgraf

“…Using the operational processing algorithm, we analyze six subsequent days of measurements during the commissioning phase. …”
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Study on water quality analysis and early-warning technology based on rough set and evidence theory by ZHU Qiong-yao, ZHANG Guang-xin, FENG Tian-heng, HUANG Ping-jie, HOU Di-bo

“…As it is known to all, there are lots of monitoring parameters in water quality detection, monitoring and information management system, and the evolution principles and changing trends of water quality are difficult to be obtained. …”
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Quantifying Uncertainties in Solar Wind Forecasting due to Incomplete Solar Magnetic Field Information by Stephan G. Heinemann, Jens Pomoell, Ronald M. Caplan, Mathew J. Owens, Shaela Jones, Lisa Upton, Bibhuti Kumar Jha, Charles N. Arge

“…Further comparison with the thermodynamic Magnetohydrodynamic Algorithm outside a Sphere model indicates that uncertainties in the different models can lead to even larger variations in solar wind forecasts compared to those within a single model. …”
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Characteristic, relationship and impact of thermokarst lakes and retrogressive thaw slumps over the Qinghai-Tibetan plateau by Wenwen Li, Denghua Yan, Yu Lou, Baisha Weng, Lin Zhu, Yuequn Lai, Yunzhe Wang

“…We further employed the eXtreme gradient boosting algorithm and ICESat-2 ATL08 laser altimetry data to quantify changes in water storage due to TLs. …”
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An analysis of spatial changes in the manufacturing industry in china’s three major urban clusters from 2015 to 2019 using POI data by Chenxi Jin, Chenjing Fan, Yiwen Gong, Xinran Huang, Shiqi Li, Runhan Liu, Chunwei Guo, Yuxin Liu

“…The evolution of the manufacturing industry at the scale of 451 districts and counties in the urban clusters and the factors driving new entrants in the manufacturing industry were studied. …”
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An Explainable CatBoost Model for Crater Classification Based on Digital Elevation Model by Minghao Zhu, Jialong Lai, Xiaoping Zhang, Yi Xu, Weidong He

“…In this study, we propose a machine-learning-based approach using the CatBoost algorithm to classify craters based on variables extracted from Digital Elevation Model (DEM) data. …”
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Evaluation and optimization of carbon emission for federal edge intelligence network by Peng ZHANG, Yong XIAO, Jiwei HU, Liang LIAO, Jianxin LYU, Zegang BAI

“…In recent years, the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks, the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI), based on edge computing and distributed federated machine learning, has been widely acknowledged as one of the key pathway for implementing network native intelligence.However, evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue, a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently, three carbon emission optimization schemes for FEI networks were presented, including dynamic energy trading (DET), dynamic task allocation (DTA), and dynamic energy trading and task allocation (DETA).Finally, by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets, FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.…”
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Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks by Stefan Hildebrand, Sandra Klinge

“…An extendable, efficient and explainable Machine Learning approach is proposed to represent cyclic plasticity and replace conventional material models based on the Radial Return Mapping algorithm. High accuracy and stability by means of a limited amount of training data is achieved by implementing physics-informed regularizations and the back stress information. …”
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The Current Role and Prospects of Electrophysiological Research Methods in Ophthalmology. Literature Review by V. N. Kazajkin, V. O. Ponomarev, A. V. Lizunov, A. E. Zhdanov, A. Yu. Dolganov, V. I. Borisov

“…This leaves the possibility and the need for the study, optimization and algorithmization of the assessment data of the differentiated criteria inherent for a particular ocular pathology. …”
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Investigating the Prognostic Role of Telomerase-Related Cellular Senescence Gene Signatures in Breast Cancer Using Machine Learning by Qiong Li, Hongde Liu

“…Additionally, pseudo-time trajectory analysis and intercellular communication mapping provided insights into the dynamic evolution of the tumor microenvironment. Immunohistochemical (IHC) validation using data from the Human Protein Atlas confirmed differential protein expression between normal and tumor tissues for several of the selected genes, reinforcing their biological relevance and clinical utility. …”
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Towards complexity in de Sitter space from the doubled-scaled Sachdev-Ye-Kitaev model by Sergio E. Aguilar-Gutierrez

“…We interpret spread complexity in terms of a time difference between antipodal observers in SdS3 space, and a boundary time difference of the dual LdS2 CFTs. …”
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Stellar ejection velocities from the binary supernova scenario: A comparison across population synthesis codes by Tom Wagg, David D. Hendriks, Mathieu Renzo, Katelyn Breivik

“…We present a comparison of the predicted ejection velocities of disrupted binary companions in three different population synthesis codes: COSMIC, COMPAS, and binary_c, which use two independent algorithms for the treatment of natal kicks. …”
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A Convex Adaptive Total Variation Model Based on the Gray Level Indicator for Multiplicative Noise Removal by Gang Dong, Zhichang Guo, Boying Wu

“…Different from the other methods, the parameters in the proposed algorithms are found dynamically.…”
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Early Warning of Nerve Agent Release in Large Indoor Environments Based on Encoder-Decoder Coupling Physics-Informed Neural Network by Shuobei Sun, Yang Peng, An Wang, Yiwen Xie, Yang Hu, Zhongyu Hou

“…Extensive experiments are conducted, and the results indicate that our model attains the highest performance among all the algorithms proposed in this paper. The difference between the actual and predicted results is small, and the scatter points are distributed around the fitted curves. …”
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Research trends and prospects in global riverine carbon fluxes: A bibliometric analysis by Wei Fang, Mohd Remy Rozainy Mohd Arif Zainol, Xianbao Zha, Pingping Luo

“…Future research should further investigate the index quantification, scaling algorithms, and modeling framework of RCFs. This study contributes to holistically understanding the evolution and prevailing trends in the field of RCFs, and better constraining the carbon budgets at the regional or global scales.…”
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Intelligence artificielle et fact-checking en Afrique : entre logiques de dépendance et limites de l’automatisation by Sokhna-Fatou SECK-SARR

“…It appears that the African context provides a different perspective with structural constraints and "cultural" algorithmic biases.…”
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Unbiased High-Precision Cloud Detection for Advanced Himawari Imager Using Automatic Machine Learning by Bochun Liu, Jinming Ge, Qingyu Mu, Chi Zhang, Xiaoyu Hu, Jiajing Du, Yanyan Wu, Bo Wang, Xiang Li, Jianping Huang, Qiang Fu

“…Our results indicate that cloud detection algorithms constructed separately for different surfaces yield better results than those applied uniformly across the entire region by inputting surface feather. …”
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A TMR Sensor Array for Non-Invasive Current Measurement in Three-Phase Cable and Error Analysis by Ruixi Luo, Hui He, Qiang Shi, Junyi Cai, Ziyang Ye, Xiang Zhang

“…The current reconstruction method was introduced by minimizing the difference between the measured and calculated magnetic flux density using a stochastic optimization algorithm. …”
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Numerical Study of Air Cushion Effect in Notched Disk Water Entry Process Using Structured Arbitrary Lagrangian–Eulerian Method by Zhe Zhang, Nana Yang, Jinlong Ju, Xingzhi Bai, Houcun Zhou, Wenhua Wu

“…Systematic analysis of the effects of notch size, water entry velocity, and entry angle on the evolution of the free surface, impact loads, and structural responses uncovers several novel findings. …”
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Underwater Target Localization Method Based on Uniform Linear Electrode Array by Wenjing Shang, Feixiang Gao, Jiahui Liu, Yunhe Pang, Sergey V. Volvenko, Vladimir M. Olshanskiy, Yidong Xu

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