Mapping clay fraction oxides in Brazil using Earth observation strategy by Jorge Tadeu Fim Rosas, José A.M. Demattê, Nícolas Augusto Rosin, Raul Roberto Poppiel, Nélida E.Q. Silvero, Merilyn Taynara Accorsi Amorim, Heidy S. Rodríguez-Albarracín, Letícia Guadagnin Vogel, Bruno dos Anjos Bartsch, José João Lelis Leal de Souza, Lucas de Carvalho Gomes, Danilo César de Mello

“…Moreover, this satellite-based technique, supported by ML, presents a plausible approach to predict oxide fraction at high spatial resolution for large areas.…”
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Time-series high spatio-temporal resolution vegetation leaf area index estimation based on NDVI trends by Chen Li, Hongmin Zhou, Jia Tang, Changjing Wang, Ziyu Wang, Jinlin Qi, Bihong Yang, Ruojing Fang

“…To overcome these challenges, a novel data assimilation approach, the ENKF-NDVI (Ensemble Kalman Filter-NDVI) model, was developed to estimate LAI data with 10-m spatial and 5-day temporal resolution. …”
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Aboveground biomass relationship with canopy cover and vegetation to improve carbon change monitoring in rangelands by Chiara Pasut, Jacqueline R. England, Melissa Piper, Stephen H. Roxburgh, Keryn I. Paul

“…Here, results were compiled from extensive field measurements across 431 Australian rangeland sites (covering an area of ~6 million km2) to develop empirical relationships to predict BAG from C and other structural variables. …”
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Arsenic health risk in shallow groundwater of the alluvial plains in the lower Yellow River, China: driving mechanisms of climate change and human activities by Wengeng Cao, Yu Fu, Yu Ren, Xiangzhi Li, Yanyan Wang, Le Song

“…In this study, we developed a robust machine learning model framework to predict the spatial variation of arsenic levels in shallow groundwater within the alluvial plains of the lower Yellow River. …”
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An integrative systems-biology approach defines mechanisms of Alzheimer’s disease neurodegeneration by Matthew J. Leventhal, Camila A. Zanella, Byunguk Kang, Jiajie Peng, David Gritsch, Zhixiang Liao, Hassan Bukhari, Tao Wang, Ping-Chieh Pao, Serwah Danquah, Joseph Benetatos, Ralda Nehme, Samouil Farhi, Li-Huei Tsai, Xianjun Dong, Clemens R. Scherzer, Mel B. Feany, Ernest Fraenkel

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PBC-Transformer: Interpreting Poultry Behavior Classification Using Image Caption Generation Techniques by Jun Li, Bing Yang, Jiaxin Liu, Felix Kwame Amevor, Yating Guo, Yuheng Zhou, Qinwen Deng, Xiaoling Zhao

“…The model employs a multi-head concentrated attention mechanism, Head Spatial Position Coding (HSPC), to enhance spatial information; a learnable sparse mechanism (LSM) and RNorm function to reduce noise and strengthen feature correlation; and a depth-wise separable convolutional network for improved local feature extraction. …”
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The characteristics and functional significance of disulfidptosis-related genes in head and neck squamous cell carcinoma by Haiqian Zhu, Chifeng Zhao, Haoran Zhu, Xuhui Xu, Conglin Hu, Zhenxing Zhang

“…The relative compositions of cells in the tumor microenvironment (TME), mutant landscape, lasso regression analysis, and predicted clinical outcome were performed by analyzing bulk RNA-sequencing data. …”
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Small scale, elevation- and environmental-related differences in life history strategies in a temperate resident songbird by Benjamin R. Sonnenberg, Carrie L. Branch, Angela M. Pitera, Virginia K. Heinen, Lauren E. Whitenack, Joseph F. Welklin, Vladimir V. Pravosudov

“…Due to the harsher and less predictable environmental conditions at higher elevations, this investment strategy in this resident species likely leads to the production of offspring with greater chances of survival. …”
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Study of the dynamics of herbs productivity based on long-term monitoring data by D. A. Ivanov, O. V. Karaseva, M. V. Rublyuk

“…It has been determined that different groups of observation years differ in productivity and in the nature of its spatio-temporal variability, as well as in the factors that determine them and in the conditions that affect these factors. This makes, when predicting the yield of grasses of different ages, to create mathematical models of its dependence on landscape conditions for different time clusters.…”
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A Near-Real-Time Operational Live Fuel Moisture Content (LFMC) Product to Support Decision-Making at the National Level by Akli Benali, Giuseppe Baldassarre, Carlos Loureiro, Florian Briquemont, Paulo M. Fernandes, Carlos Rossa, Rui Figueira

“…Live fuel moisture content (LFMC) significantly influences fire activity and behavior over different spatial and temporal scales. The ability to estimate LFMC is important to improve our capability to predict when and where large wildfires may occur. …”
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Recognition of Maize Tassels Based on Improved YOLOv8 and Unmanned Aerial Vehicles RGB Images by Jiahao Wei, Ruirui Wang, Shi Wei, Xiaoyan Wang, Shicheng Xu

“…The tasseling stage of maize, as a critical period of maize cultivation, is essential for predicting maize yield and understanding the normal condition of maize growth. …”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…Based on the SHAP values, the non-linear relationships between them are further clarified.ResultsThrough the analysis of 3 types of mental health benefits and 5 models, the LightGBM model outperforms other algorithms (such as Random Forest and XGBoost) in terms of prediction accuracy (R 2: 0.523 – 0.642), with its robustness in capturing complex feature interactions being verified. …”
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Deep Learning Approach for Estimating Workability of Self-Compacting Concrete from Mixing Image Sequences by Zhongcong Ding, Xuehui An

“…We propose a deep learning approach to better utilize the spatial and temporal information obtained from image sequences of the self-compacting concrete- (SCC-) mixing process to recover SCC characteristics in terms of the predicted slump flow value (SF) and V-funnel flow time (VF). …”
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High-resolution mapping of on-road vehicle emissions with real-time traffic datasets based on big data by Y. Wang, H. Wang, B. Zhang, P. Liu, X. Wang, S. Si, L. Xue, Q. Zhang, Q. Wang

“…Based on the established emission model, we predicted that the benefits of vehicle electrification in reducing vehicle emissions could reach 40 %–80 %. …”
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Investigating socioeconomic deprivation and antibiotic prescribing among older medicare patients using an instrumental variable approach by Mayar Al Mohajer, David Slusky, David Nix, Catia Nicodemo

“…The IV analysis then examined the relationship between predicted SDI and antibiotic days supplied (ln). Linear regression models estimated associations between SDI and its components, and antibiotic days supplied, adjusting for prescriber, beneficiary, and geographic factors. …”
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Getting NBA Shots in Context: Analysing Basketball Shots with Graph Embeddings by Schmid Marc, Schöpf Moritz, Kolbinger Otto

“…We introduce a graph neural network to process a graph based on player and ball tracking data to compute expected shot quality. We evaluate this model against other models focusing on calibration. …”
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Freeze–Thaw-Induced Degradation Mechanisms and Slope Stability of Filled Fractured Rock Masses in Cold Region Open-Pit Mines by Jun Hou, Penghai Zhang, Ning Gao, Wanni Yan, Qinglei Yu

“…Based on regression fitting using 0–25 FT cycles, regression model predictions indicate that when the number of <i>FT</i> cycles exceeds 42, the slope safety factor drops below 1.0, entering a critical instability state. …”
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cogsworth: A Gala of COSMIC Proportions Combining Binary Stellar Evolution and Galactic Dynamics by Tom Wagg, Katelyn Breivik, Mathieu Renzo, Adrian M. Price-Whelan

“…We provide a detailed explanation of the functionality of cogsworth and demonstrate its capabilities through a series of use cases: (1) we predict the spatial distribution of compact objects and runaways in both dwarf and Milky Way–like galaxies; (2) using a star cluster from a hydrodynamical simulation, we show how supernovae can change the orbits of stars in several ways; and (3) we predict the separation of disrupted binary stellar companions on the sky and create a synthetic Gaia color–magnitude diagram. …”
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WetCH₄: a machine-learning-based upscaling of methane fluxes of northern wetlands during 2016–2022 by Q. Ying, Q. Ying, B. Poulter, J. D. Watts, K. A. Arndt, A.-M. Virkkala, L. Bruhwiler, Y. Oh, Y. Oh, B. M. Rogers, S. M. Natali, H. Sullivan, A. Armstrong, A. Armstrong, E. J. Ward, E. J. Ward, L. D. Schiferl, C. D. Elder, C. D. Elder, O. Peltola, A. Bartsch, A. R. Desai, E. Euskirchen, M. Göckede, B. Lehner, M. B. Nilsson, M. Peichl, O. Sonnentag, E.-S. Tuittila, T. Sachs, T. Sachs, A. Kalhori, M. Ueyama, Z. Zhang, Z. Zhang

“…The most important predictor<span id="page2508"/> variables included near-surface soil temperatures (top 40 cm), vegetation spectral reflectance, and soil moisture. Our results, modeled from 138 site years across 26 sites, had relatively strong predictive skill, with a mean <span class="inline-formula"><i>R</i>²</span> of 0.51 and 0.70 and a mean absolute error (MAE) of 30 and 27 nmol m<span class="inline-formula">⁻²</span> s<span class="inline-formula">⁻¹</span> for daily and monthly fluxes, respectively. …”
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Vegetation greening does not significantly enhance ecosystem resilience in the Northern Hemisphere by Jingjing Zhang, Xingming Hao, Yongchang Liu, Xuewei Li, Qixiang Liang, Fan Sun, Mengtao Ci, Yupeng Li

“…Greening is asynchronous with ecosystem resilience in the context of vegetation restoration, thus highlighting the uncertainty in predicting the future sustainability of ecosystems. …”
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