Inverse Dynamic Parameter Identification for Remote Sensing of Soil Moisture From SMAP Satellite Observations by Runze Zhang, Adam Watts, Mohamad Alipour

“…In the soil moisture active passive (SMAP) mission&#x0027;s soil moisture retrieval algorithms, the effects of surface roughness and vegetation scattering on the brightness temperature are conventionally modeled using time-invariant parameters: roughness intensity (<italic>h</italic>) and effective scattering albedo (&#x03C9;). …”
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Cosmological Prediction of the Void and Galaxy Clustering Measurements in the CSST Spectroscopic Survey by Yingxiao Song, Qi Xiong, Yan Gong, Furen Deng, Kwan Chuen Chan, Xuelei Chen, Qi Guo, Guoliang Li, Ming Li, Yun Liu, Yu Luo, Wenxiang Pei, Chengliang Wei

“…We generate galaxy mock catalogs from a Jiutian simulation and identify voids using the watershed algorithm for studying the cosmological constraint strength of the China Space Station Telescope spectroscopic survey. …”
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Machine Learning Applications in Use-Wear Analysis: A Critical Review by Anastasia Eleftheriadou, Shannon P. McPherron, João Marreiros

“…By addressing these factors, this paper facilitates the effective use of machine learning, enabling use-wear analysts and archaeologists to develop robust models that automate, accelerate, and improve their research.…”
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A Stabilized Incompressible SPH Method by Relaxing the Density Invariance Condition by Mitsuteru Asai, Abdelraheem M. Aly, Yoshimi Sonoda, Yuzuru Sakai

“…In the ISPH, pressure is evaluated by solving pressure Poisson equation using a semi-implicit algorithm based on the projection method. Even if the pressure is evaluated implicitly, the unrealistic pressure fluctuations cannot be eliminated. …”
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An Intelligent Path Planning System for Urban Airspace Monitoring: From Infrastructure Assessment to Strategic Optimization by Qianyu Liu, Wei Dai, Zichun Yan, Claudio J. Tessone

“…These results highlight the potential of combining infrastructure modeling with DRL to support performance-aware airspace operations and inform future UAM governance systems.…”
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Building Equi-Width Histograms on Homomorphically Encrypted Data by Dragoș Lazea, Anca Hangan, Tudor Cioara

“…Histograms are widely used for summarizing data distributions, detecting anomalies, and improving machine learning models’ accuracy. However, traditional histogram-based methods require access to raw data, raising privacy concerns, particularly in sensitive IoT applications. …”
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Intelligent Counterforce Allocation Method Using Multi-Agent Reinforcement Learning for Ground Operations by Kiwoong Park, Sangheun Shim

“…The MARL agent is implemented using the Soft Actor-Critic algorithm and scaled through a Graph Attention Network to manage over 40 heterogeneous agents (infantry, tanks, and artillery). …”
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A Registration Method for Historical Maps Based on Self-Supervised Feature Matching by Zikang Qin, Yumin Feng, Gang Wu, Qing Dong, Tianxin Han

“…Experimental results indicate that our solution achieves superior performance compared to existing models, with RMSE reduced by up to 20%, ROCC improved by up to 10%, and processing time shortened by at least 15%.…”
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Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations by Sepideh K. Gharamaleki, Brandon Helfield, Hassan Rivaz

“…We further refine the super-resolution map by employing a KDTree algorithm for efficient MB tracking across consecutive frames. …”
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Synergistic Effects of Energy Storage Systems and Demand-Side Management in Optimizing Zero-Carbon Smart Grid Systems by Zeyad A. Almutairi, Ali M. Eltamaly

“…An advanced load and weather-forecasting strategy is introduced for improving grid planning and management. An advanced optimization algorithm enhances grid stability and efficiency. …”
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The class project of cyber-driver by P. S. Sorokoumov

“…In robotic perception models the situation is similar: casual human tasks as image recognition or scene analysis need complex algorithms and huge computer resources if performed by robots. …”
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Human multiethnic radiogenomics reveals low-abundancy microRNA signature in plasma-derived extracellular vesicles for early diagnosis and molecular subtyping of pancreatic cancer by Jianying Xu, Wenjie Shi, Yi Zhu, Chao Zhang, Julia Nagelschmitz, Maximilian Doelling, Sara Al-Madhi, Ujjwal Mukund Mahajan, Maciej Pech, Georg Rose, Roland Siegfried Croner, Guoliang Zheng, Christoph Kahlert, Ulf Dietrich Kahlert

“…Radiomics features were extracted and analyzed using the limma package, with feature selection conducted via the Boruta algorithm and model construction through Least Absolute Shrinkage and Selection Operator regression. …”
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Asymptotic Approximation of the Stationary Solution with Internal Layer for FitzHugh–Nagumo System by A. A. Melnikova, R. L. Argun

“…The application of contrast structures theory to the study of active media models can be used for analytical studies of other such systems, improving existing models and increasing the efficiency of the numerical calculations.…”
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Targeted inhibition of Gus-expressing Enterococcus faecalis to promote intestinal stem cell and epithelial renovation contributes to the relief of irinotecan chemotoxicity by dehyd... by Ruiyang Gao, Bei Yue, Cheng Lv, Xiaolong Geng, Zhilun Yu, Hao Wang, Beibei Zhang, Fangbin Ai, Ziyi Wang, Donghui Liu, Zhengtao Wang, Kaixian Chen, Wei Dou

“…The Partial Least Squares Path Model (PLS-PM) algorithm initially links E. faecalis to dysregulated epithelial renovation. …”
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DIP-UP: Deep Image Prior for Unwrapping Phase by Xuanyu Zhu, Yang Gao, Zhuang Xiong, Wei Jiang, Feng Liu, Hongfu Sun

“…We compared the DIP-refined models to their original versions, as well as to the conventional PRELUDE algorithm from FSL, using both simulated and in vivo brain data. …”
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Simulating urban growth through case-based reasoning by X. Ye, W. W. Yu, W. H. Yu, L. N. Lv

“…However, CBR analyses of land-use changes are difficult to apply in the study of urban growth due to shortcomings in the case structure and model algorithms. In response, this study proposes a three-step urban-growth simulation model based on CBR (UGSCBR). …”
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Nonintrusive Load Disaggregation Based on Attention Neural Networks by Shunfu Lin, Jiayu Yang, Yi Li, Yunwei Shen, Fangxing Li, Xiaoyan Bian, Dongdong Li

“…Specifically, the proposed model shows a 13.85% improvement in mean absolute error (MAE), a 21.27% improvement in signal aggregate error (SAE), and a 26.15% improvement in F1 score over existing algorithms. …”
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Orchard variable-rate spraying method integrating GNSS and wind-excited audio-conducted leaf area density by Hangxing Zhao, Hangxing Zhao, Hangxing Zhao, Shenghui Yang, Shenghui Yang, Shenghui Yang, Wenwei Li, Wenwei Li, Han Feng, Han Feng, Shijie Jiang, Shijie Jiang, Weihong Liu, Weihong Liu, Jingbin Li, Yongjun Zheng, Yongjun Zheng, Songchao Zhang

“…A variable-rate spray control model and algorithm were then constructed to regulate spray flow according to the spatial distribution of leaf area density across the orchard.ResultsField experiments demonstrated that the system achieved a mean relative error of only 5.52% in spray flow rate regulation. …”
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Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma by Li Xu, Stephane Oudard, Catherine Sautes-Fridman, Xiaoping Su, Gabriel G. Malouf, Virginie Verkarre, Salma Kotti, Fangrong Yan, Yann-Alexandre Vano, Wolf Herve Fridman, Cheng-Ming Sun, Xiaofan Lu, Wenxuan Cheng

“…These subgroups were further consolidated into a three-tier risk model that significantly correlated with ICI treatment outcomes. …”
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Predicting child mortality determinants in Uttar Pradesh using Machine Learning: Insights from the National Family and Health Survey (2019–21) by Pinky Pandey, Sacheendra Shukla, Niraj Kumar Singh, Mukesh Kumar

“…Four machine learning algorithms—Random Forests, Logistic Regression, K-Nearest Neighbors (KNN), and Naive Bayes—were applied alongside a traditional logistic regression model. …”
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