Knowledge embedding and interpretable machine learning optimize comprehensive benefits for water treatment by Yu-Qi Wang, Wenchong Tian, Hao-Lin Yang, Yun-Peng Song, Jia-Ji Chen, Qiong-Ying Xu, Wan-Xin Yin, Le-Qi Ding, Xi-Qi Li, Han-Tao Wang, Ai-Jie Wang, Hong-Cheng Wang

“…Through real experimental validation and simulation extrapolation, the RF-KE model can reduce turbidity by 16.36% and dosing cost by 9.64%. …”
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Runoff evolution characteristics and its response to climate change in the middle and lower reaches of Shule River Basin, Northwest China by Dongyuan Sun, Yiru Wang, Lanzhen Wu, Xingfan Wang, Yanqiang Cui, Heping Shu, Yali Ma

“…Abrupt changes occurred in 1998 (STBR) and 2005 (DHR), with average annual runoff increasing by 52.01 % and 38.69 %, respectively, primarily driven by changes in underlying surface conditions. The Random Forest (RF)-Adaptive Boosting (AdaBoost) model outperformed the standalone RF model, showing higher simulation accuracy and generalization ability in arid inland basins. …”
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Calibração e aplicação do modelo MUSLE em uma microbacia hidrográfica nos Tabuleiros Costeiros brasileiros Calibration and application of the MUSLE model in a small watershed of th... by Junior C. Avanzi, Marx L. N. Silva, Nilton Curi, Carlos R. de Mello, Sebastião Fonseca

“…The objective of this study was to adopt a semi-empirical hydrological model to surface runoff and peak discharge, applying the Modified Universal Soil Loss Equation (MUSLE) to a small watershed occupied by eucalyptus plantations and native forest, in the Coastal Table Land region, Aracruz, in the State of Espírito Santo, Brazil. …”
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Quantifying the Effects of Water Status on Grapevine Vegetative Growth, Yield, and Grape Composition Through a Collaborative Analysis by David Uriarte, Luis Gonzaga Santesteban, José Manuel Mirás-Avalos, Ignacio Buesa, Javier José Cancela, Juan Luis Chacón, José Mariano Escalona, Diego Sebastiano Intrigliolo, Miriam Lampreave, Amelia Montoro, Luis Rivacoba, Fernando Visconti, Jesús Yuste, Carlos Miranda

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Assessing and predicting the value of ecosystem services in Sanya City, Hainan Island, China by Peihong Song, Qiu Yang, Wenyin Wu, Tianyan Su, Yamin Jiang, Jingli Lu, Zhongyi Sun, Jie Zhang, Rui Yu, Peng Wang, Lan Wu, Huai Yang, Wenjie Liu

“…Additionally, the Future land-use simulation (FLUS) model was employed to predict land-use changes in 2030 under five different scenarios. …”
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Diff-Tree: A Diffusion Model for Diversified Tree Point Cloud Generation with High Realism by Haifeng Xu, Yongjian Huai, Xiaoying Nie, Qingkuo Meng, Xun Zhao, Xuanda Pei, Hao Lu

“…Three-dimensional (3D) virtual trees play a vital role in modern forestry research, enabling the visualization of forest structures and supporting diverse simulations, including radiation transfer, climate change impacts, and dynamic forest management. …”
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LeafGen: Leaf generation in 3D tree models by Pietari Mönkkönen, Wouter Van den Broeck, Simo Ali‐Löytty, Kim Calders, Pasi Raumonen

“…This method enhances the reproducibility and cost‐effectiveness of studies on leaf–environment interactions and can be applied to various applications, including forest remote sensing, light transfer modelling and tree growth simulations.…”
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Hiking Trails Facilitate the Spread of a Native High‐Arctic Species by Deborah Zani, Heike Lischke, Jonas Åkerman, Veiko Lehsten

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Assessing expandable Global Positioning System collars for moose neonates by Tyler R. Obermoller, Glenn D. Delgiudice, William J. Severud

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IMPORTANCE OF DEMOGRAPHIC PARAMETERS TO ANNUAL CHANGES IN WILD TURKEY ABUNDANCE by Steven D. Roberts, William F. Porter

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Pressurized Water Reactor Transient Detection With Artificial Intelligence to Support Reactor Operators by Ceyhun Yavuz, Senem Şentürk Lüle

“…When accuracy, precision, recall, and F1-score are compared together, the random forest method showed the best performance.…”
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Quantification of backwater effect in Jingjiang Reach due to confluence with Dongting Lake using a machine learning model by Hai-xin Shang, Jun-qiang Xia, Chun-hong Hu, Mei-rong Zhou, Shan-shan Deng

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Characteristics of Flux Footprint over Typical Underlying Surface of Qinghai-Xizang Plateau by Zixin WANG, Lei ZHONG, Yaoming MA, Yunfei FU

“…The heterogeneity of the underlying surface affects the accuracy and representativeness of the land-atmosphere flux observation.The study on the flux footprint distribution of complex underlying surface over Qinghai-Xizang Plateau （QXP） is of great significance to the observation and simulation of land-atmosphere interaction and its influence on weather and climate.Flux footprint analysis plays a pivotal role in investigating the spatial representativeness of flux observation information.The Flux Footprint Prediction （FFP） model represents a proficient methodology for computing the flux footprint.Based on the observation data from multiple research stations， including the Qomolangma Atmospheric and Environmental Observation and Research Station， the Ngari Desert Observation and Research Station， the Nam Co Monitoring and Research Station for Multisphere Interactions， the Muztagh Ata Westerly Observation and Research Station， the Southeast Tibet Observation and Research Station for the Alpine Environment in 2013， the FFP model was utilized to investigate the sensitivity of model parameters concerning flux footprint distribution.Additionally， the spatiotemporal characteristics and specific influencing factors of flux footprint distribution at different stations were discussed， thereby providing valuable insights for the erection of future observing stations.The results reveal that the primary determinants of flux footprint are measurement height， wind speed and wind direction.Characterized by an underlying surface of evergreen coniferous forest， flux footprint at Linzhi station exhibits greater sensitivity to measurement height and planetary boundary layer depth compared to the other stations.In the QXP， the spatial extent of the flux footprint derived from the ultrasonic anemometer measurements ranges from approximately 250 m to 500 m.Among the five stations， Qomo station exhibited the lowest frequency of stable stratification times during daytime， representing 15.69% of the daytime data points， whereas Ali station had the lowest occurrence of unstable stratification times during nighttime， comprising for 13.32% of the nighttime data points.At these five stations on the TP， the nocturnal flux footprints demonstrate greater width and extent compared to their daytime counterparts.In summer， due to the influence of monsoon， the axis of flux footprint tends to be more consistent.Lake-land breeze at Nam Co station is the main factor affecting flux footprint， whereas glacier wind at Qomo station is the dominant factor.Linzhi station possesses the smallest footprint due to the smallest mean wind speed， thus demonstrating the highest level of representativeness among these five stations.Lowering the height of observation instruments at Qomo and Nam Co stations could potentially enhance the representativeness of in situ measurements.…”
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Energy Efficiency Optimization for UAV Distribution and Resource Allocation in NOMA and Multi-UAV Assisted Wireless Networks by Yuan Ren, Jieyu Wang, Yulong Xiao, Xuewei Zhang, Fan Jiang, Junxuan Wang, Jing Jiang, Guangyue Lu

“…When natural disasters, such as earthquake, flood and forest fire, occur, it is important to deploy emergency wireless infrastructures to recover the destroyed communication system. …”
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Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Nutrient Cycling at a Coastal Terrestrial‐Aquatic Interface by Bing Li, Zhi Li, Jianqiu Zheng, Peishi Jiang, James Holmquist, Peter J. Regier, Glenn E. Hammond, Nicholas D. Ward, Allison Myers‐Pigg, Roy Rich, Wei Huang, Theresa A. O’Meara, Stephanie C. Pennington, Patrick Megonigal, Vanessa L. Bailey, Xingyuan Chen

“…We used a transect in the Chesapeake Bay region that spans zones of open water, coastal wetland, transition, and upland forest. We designed several simulation scenarios to parse the effects of the individual controlling factors and the sensitivity of carbon cycling to reaction rate parameters derived from laboratory experiments. …”
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Variation characteristics and influencing mechanisms of CO2 flux from grassland ecosystem in the Central Tianshan Mountains, China by Kun Zhang, Yu Wang, Ali Mamtimin, Yongqiang Liu

“…Multiple environmental factors were integrated for an attribution analysis of CO2 flux using advanced systems, including random forest model, hyperbolic tangent model, future scenario simulation, and stepwise multiple regression model. …”
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Machine Learning Aided Tapered Four-Port MIMO Antenna for V2X Communications With Enhanced Gain and Isolation by Nagesh Kallollu Narayanaswamy, Yazeed Alzahrani, Krishna Kanth Varma Penmatsa, Ashish Pandey, Ajay Kumar Dwivedi, Vivek Singh, Manoj Tolani

“…The fabricated antenna is modeled, and measured findings are found to be in coherence with simulated findings.…”
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An integrative process-based model of fruit growth as a function of carbon and water fluxes modulated by endogenous abscisic acid in blueberry fruit by Sun Woo Chung, Kyungdahm Yun, Soo-Hyung Kim

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Assessing infrastructure exposure to mountain wave wind events in the Southern Appalachians by Marcus D. Williams, Bradford D. Johnson, Zachary Cope, Craig Ramseyer, David Hotz, Jeremy Buckles

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Computable General Equilibrium Model for Analysis of the Payment for Environmental Services in the Brazilian Cerrado by Attawan Guerino Locatel Suela, Cicero Zanetti de Lima, Rayan Wolf, Ian Michael Trotter

“…The forest conversion in the Cerrado, particularly in the MATOPIBA region, demands immediate solutions. …”
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