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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Indian summer monsoon’s role in shaping variability in Arctic sea ice by Jiawei Zhu, Zhiwei Wu

“…This enhanced comprehension holds promise for enhancing predictions of changes in summertime Arctic sea ice extent.…”
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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

“…Furthermore, a detector head that lacks a meticulous design may face limitations in fully understanding and accurately predicting based on the enriched feature representations. …”
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Mapping global distributions, environmental controls, and uncertainties of apparent topsoil and subsoil organic carbon turnover times by L. Zhang, L. Zhang, L. Yang, T. W. Crowther, C. M. Zohner, S. Doetterl, G. B. M. Heuvelink, G. B. M. Heuvelink, A. M. J.-C. Wadoux, A.-X. Zhu, Y. Pu, F. Shen, H. Ma, Y. Zou, C. Zhou, C. Zhou

“…The prediction uncertainties of the <span class="inline-formula"><i>τ</i></span> maps were quantified for better user applications. …”
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A Physics-Informed Machine Learning Framework for Permafrost Stability Assessment by Polina Pilyugina, Timofey Chernikov, Maria Smirnova, Alexey Zaytsev, Alexander Bulkin, Evgeny Burnaev, Ilya S. Belalov, Nazar Sotiriadi, Albert Efimov, Yury Maximov, Oleg Anisimov

“…Purely data-driven models also face limitations due to the spatial and temporal sparsity of observational data. …”
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Spatiotemporal Differences in Dominants of Dryness/Wetness Changes in Southwest China by Shujia Zhou, Shanlei Sun, Wanrong Shi, Jiazhi Wang, Jinjian Li, Guojie Wang, Weiping Lou

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Geospatial SHAP interpretability for urban road collapse susceptibility assessment: a case study in Hangzhou, China by Bofan Yu, Hui Li, Huaixue Xing, Weiya Ge, Liling Zhou, Jinrui Zhang, Meijun Xu, Cheng Yu

“…In addition to interpreting the contributions of evaluation factors through traditional SHAP summaries and bar plots, we displayed the SHAP values for each evaluation factor using map visualizations, and discussed the model’s sensitivity to different values. To validate the alignment between model predictions and physical collapse mechanisms, our study selected typical collapse cases, interpreted these cases combining map visualizations, SHAP force plots at collapse points, and the physical mechanisms of collapse. …”
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Coinfection of hepatitis B, tuberculosis, and HIV/AIDS in Beijing from 2016 to 2023: a surveillance data analysis by Chao Wang, Yunping Shi, Yang Liu, Ying Zhou, Jing Du, Xiao Hu, Wei Li, Jiaze Li, Yanlin Gao, Gang Li

“…The multivariate logistic model shown that males were more susceptible to be coinfected (ORs ranged from 1.50 to 27.81). …”
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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

“…They serve as a decision support system, partially automating the diagnosis process by providing probability predictions for abnormalities. Methods: We demonstrated the use of deep learning models in CE image analysis, specifically by piloting a bowel preparation model (BPM) and an abnormality detection model (ADM) to determine frame-level view quality and the presence of abnormal findings, respectively. …”
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Accurate and Efficient Fluid Flow Regime Classification Using Localized Texture Descriptors and Machine Learning by Manimaran Renganathan, Palani Thanaraj Krishnan, C. Christopher Columbus, T. Sunil Kumar

“…This paper presents an image-based framework for classifying fluid flow regimes into low and high-speed states by utilizing spatially localized texture features combined with machine learning techniques. …”
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APPLICATION OF THE GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) METHOD IN FORECASTING THE CONSUMER PRICE INDEX IN FIVE CITIES OF SOUTH SULAWESI PROVINCE by Ahmad Zaki, Lutfiah Shafruddin, Irwan Thaha

“…CPI forecasting is one way to predict future inflation values. This study aims to develop the best GSTAR model for forecasting CPI data for five cities in South Sulawesi, a topic that has not been extensively covered in previous research. …”
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The radial spreading of volcanic umbrella clouds deduced from satellite measurements by Fred Prata, Andrew T. Prata, Rebecca Tanner, Roy G. Grainger, Michael Borgas, Thomas J. Aubry

“…This model also predicts the observed radial velocities. …”
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On the Brink: Mapping the Last Strongholds of the Critically Endangered Flapper Skate (Dipturus intermedius) by Sophie L. Loca, Patrick C. Collins, Amy Garbett, Ryan McGeady, James Thorburn, Chris McGonigle

“…Location The NE Atlantic shelf region. A Bayesian spatial binomial GAMM was used to model the distribution of flapper skate across the NE Atlantic shelf. …”
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Spatio-Temporal Paths and Influencing Factors of Residential Mobility in Guangzhou: A Micro-Level Perspective of Newly Employed College Graduates by Xiangjun Dai, Chunshan Zhou, Xiong He

“…Residential mobility within cities reflects the spatio-temporal patterns of individual or household relocation behaviors and serves as an effective tool for interpreting urban socio-spatial differentiation from a micro-level perspective. …”
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Kernel density change: A new bitemporal lidar metric for directly mapping wildland fire fuel consumption by Michael J. Campbell, Andrew T. Hudak, T. Ryan McCarley, Benjamin C. Bright, Philip E. Dennison

“…In this study, we compared MFLC to a new modeling approach that directly predicts consumption from a suite of bitemporal point cloud structural change metrics. …”
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An Ensemble of Convolutional Neural Networks for Sound Event Detection by Abdinabi Mukhamadiyev, Ilyos Khujayarov, Dilorom Nabieva, Jinsoo Cho

“…An ensemble approach combines predictions from three models, achieving F1 scores of 71.5% for segment-based metrics and 46% for event-based metrics. …”
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A diffusion tensor imaging-based multidimensional study of brain structural changes after long-term high-altitude exposure and their relationships with cognitive function by Ning Liu, Li Feng, Shuangwei Chai, Hailong Li, Yuanyuan He, Yongyue Guo, Xin Hu, Hengyan Li, Xiangwei Li, Zan Zhou, Xiaomei Li, Yonghong Huang, Wanlin He, Xiaoqi Huang, Xiaoqi Huang, Yunhong Wu, Jinli Meng

“…The tract-based spatial statistics (TBSS) method was used to analyze the DTI parameters of the white matter fiber tracts of the two groups. …”
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