Storm water runoff studies in built-up watershed areas using curve number and remote sensing techniques by Arati Reddy Nilap, H. N. Rajakumara, Ali Aldrees, Hasan Sh. Majdi, Wahaj Ahmad Khan

“…The model satisfactorily predicted runoff from the simulated data analysis with evaluation criteria NSE = 0.9945, MAE = 5.4121, r = 0.9975, R2 = 0.9949, RMSE = 6.8117 and PBias = 1.1436. …”
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A renewable double plasma mirror for Petawatt-class lasers by Nick Czapla, Derek M. Nasir, Lieselotte Obst-Huebl, Anthony Zingale, Jianhui Bin, Anthony J. Gonsalves, Sven Steinke, Kei Nakamura, Carl B. Schroeder, Eric Esarey, Cameron G. R. Geddes, Douglass W. Schumacher

“…We present the first measurements of a beam reflected from a single or double plasma mirror system using a wavefront sensor, showing a well preserved wavefront and spatial mode. Finally, we introduce a model that predicts the total throughput through this double plasma mirror. …”
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Co‐Occurring Extremes of Fine Particulate Matter (PM2.5) and Ground‐Level Ozone in the Summer of Southern China by Yan Lyu, Haonan Wu, Xiaoran Liu, Fuliang Han, Fengmao Lv, Xiaobing Pang, Jianmin Chen

“…Through combining multi‐source data, Random Forest model well predicts PM2.5‐ozone co‐occurrence and identifies common precursors (e.g., volatile organic compounds) as important variables. …”
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A state-of-the-art review on machine learning techniques for driving behavior analysis: clustering and classification approaches by Mohammad Hassan Mobini Seraji, Sami Shaffiee Haghshenas, Sina Shaffiee Haghshenas, Vladimir Simic, Dragan Pamucar, Giuseppe Guido, Vittorio Astarita

“…The review specifically explains unsupervised methods like fuzzy c-means, k-means, and density-based spatial clustering of applications with noise, as well as supervised techniques such as artificial neural networks, k-nearest neighbors, and support vector machines. …”
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Pervasive glacier retreats across Svalbard from 1985 to 2023 by Tian Li, Stefan Hofer, Geir Moholdt, Adam Igneczi, Konrad Heidler, Xiao Xiang Zhu, Jonathan Bamber

“…Abstract A major uncertainty in predicting the behaviour of marine-terminating glaciers is ice dynamics driven by non-linear calving front retreat, which is poorly understood and modelled. …”
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Suitable scale structures for urban multi-functions: an integrative approach grounded in socio-ecological system analysis by Wuyang Hong, Shuwen Yang, Renzhong Guo, Yelin Li, Lin Jiang, Xiaoming Li

“…Abstract Aims Research on the appropriate scale structure and spatial layout of ecological, urban, and agricultural spaces and the effective and methodical development and protection of urban space can provide a solid foundation for the sustainable development of the complex socio-economic urban environment. …”
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AI-based defect detection and self-healing in metal additive manufacturing by Jan Akmal, Kevin Minet-Lallemand, Jukka Kuva, Tatu Syvänen, Pilvi Ylander, Tuomas Puttonen, Roy Björkstrand, Jouni Partanen, Olli Nyrhilä, Mika Salmi

“…A convolutional neural network was trained (n = 211) and was verified with XCT. The model demonstrated prediction accuracy of 94% for the six classes of unfamiliar defective regions. …”
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Elemental Associations with Groundwater Nitrate in Northeastern Region of Saudi Arabia: Implications for Sustainable Water Management by Al Mamun

“…Future research should focus on elucidating factors influencing nitrate distribution in groundwater systems and developing more robust predictive models based on readily measurable water quality parameters.…”
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Predator guards on nest boxes improve nesting success of birds by Robyn L. Bailey, David N. Bonter

“…Across all species, top models predicting daily nest survival rates suggest a positive influence of predator guards, with a nearly 7% increase in nest success for attempts in boxes with guards versus attempts in boxes without guards. …”
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Significance of Cloud Microphysics and Cumulus Parameterization Schemes in Simulating an Extreme Flood-Producing Precipitation Event in the Central Himalaya by Ujjwal Tiwari, Andrew B. G. Bush

“…Precipitation was concentrated over the sub-Himalaya, and the established forecasting systems failed to predict the event. In this study, we evaluate the performance of six cloud microphysics schemes in the Weather Research and Forecasting (WRF) model forced with the advanced ERA5 dataset. …”
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Differences in the functional use of two migratory stopovers by humpback whales (Megaptera novaeangliae). by Raphael Mayaud, Joshua N Smith, David Peel, Craig Wilson, Wally Franklin, Tim Stevens, Susan Bengtson Nash

“…We examined population structure, behaviour, and habitat segregation, and developed spatial density surface models to predict density distribution patterns at each respective site. …”
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Factor structure and validation of the Motor Imagery Vividness Scale (MIV-S) by Nobuchika Yamaki

“…Exploratory factor analysis (EFA) identified a three-factor structure—Spatial and Temporal Imagery, Emotional and Motivational Imagery, and Sensory Clarity and Flow—explaining 38.6% of the total variance. …”
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Indian summer monsoon’s role in shaping variability in Arctic sea ice by Jiawei Zhu, Zhiwei Wu

“…Additionally, from a dynamic standpoint, low-level wind-driven sea ice drift helps shape the spatial distribution and extent of sea ice cover. …”
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Virtual Reality in Building Evacuation: A Review by Ming-Chuan Hung, Ching-Yuan Lin, Gary Li-Kai Hsiao

“…Future research should integrate VR with artificial intelligence and machine learning for predictive and adaptive evacuation models. Expanding VR applications to underrepresented groups, including individuals with disabilities and the elderly, and collaborating with policymakers and urban planners are vital for translating research into practice. …”
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Comparative analysis of injection rate and spray characteristics of ammonia and diesel from multi-hole diesel injector by Seonho Park, Gyuhan Bae, Seoksu Moon

“…It was further found that the spray penetration of ammonia and diesel can be scaled and predicted based on a conventional momentum-conservation-based spray penetration model.…”
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FAMHE-Net: Multi-Scale Feature Augmentation and Mixture of Heterogeneous Experts for Oriented Object Detection by Yixin Chen, Weilai Jiang, Yaonan Wang

“…Current detectors struggle with integrating spatial and semantic information effectively across scales and often omit necessary refinement modules to focus on salient features. …”
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Environmental drivers of Culicoides phenology: how important is species-specific variation when determining disease policy? by Kate R Searle, James Barber, Francesca Stubbins, Karien Labuschagne, Simon Carpenter, Adam Butler, Eric Denison, Christopher Sanders, Philip S Mellor, Anthony Wilson, Noel Nelson, Simon Gubbins, Bethan V Purse

“…We conclude that the current treatment of Avaritia Culicoides as a single group inhibits understanding of environmentally-driven spatial variation in species phenology and hinders the development of models for predicting the SVFP from environmental factors. …”
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Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution by Bochao Jiang, Michael Dorosan, Justin Wen Hao Leong, Marcus Eng Hock Ong, Sean Shao Wei Lam, Tiing Leong Ang

“…We used convolutional neural network-based models pretrained on large-scale open-domain data to extract spatial features of CE images that were then used in a dense feed-forward neural network classifier. …”
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Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method by Fa Li, Qing Zhu, Kunxiaojia Yuan, Fujiang Ji, Arindam Paul, Peng Lee, Volker C. Radeloff, Min Chen

“…Abstract More frequent and widespread large fires are occurring in the western United States (US), yet reliable methods for predicting these fires, particularly with extended lead times and a high spatial resolution, remain challenging. …”
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Less Is More: Brain Functional Connectivity Empowered Generalizable Intention Classification With Task-Relevant Channel Selection by Haowei Lou, Zesheng Ye, Lina Yao, Yu Zhang

“…Inevitably, the sensory electrodes on the entire scalp would collect signals irrelevant to the particular BCI task, increasing the risks of overfitting in machine learning-based predictions. While this issue is being addressed by scaling up the EEG datasets and handcrafting the complex predictive models, this also leads to increased computation costs. …”
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