Potential distribution of endemic lizards from Brazilian restingas: The present announcing the end by Hugo Andrade, Luisa Maria Diele‐Viegas Costa Silva, Carlos Frederico Duarte Rocha, Antônio Jorge Suzart Argôlo, Eduardo José dos Reis Dias

“…We conducted ecological niche modeling to predict the potential distribution of Brazilian restingas‐endemic lizards. …”
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Late Quaternary fluctuation in upper range limit of trees shapes endemic flora diversity on the Tibetan Plateau by Jinfeng Xu, Tao Wang, Xiaoyi Wang, Christian Körner, Xianyong Cao, Eryuan Liang, Yongping Yang, Shilong Piao

“…We integrated satellite-derived upper range limit of trees, dendrochronological data, and fossil pollen records with a paleoclimate dataset in a climate-driven predictive model to reconstruct the spatio-temporal upper range limit of trees at 100-year intervals since the Last Glacial Maximum. …”
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Simulation of Suitable Distribution and Differentiation in Local Environments of <i>Cercospora arachidicola</i> in China by Ying Lin, Xue Pei, Chunhao Liang

“…This study aimed to develop a predictive model, optimized using the Biomod tuning function, to assess the future risk and spatial distribution of ELS under various climate change scenarios. …”
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Revealing the Spatiotemporal Changes in Land Use and Landscape Patterns and Their Effects on Ecosystem Services: A Case Study in the Western Sichuan Urban Agglomeration, China by Jing Wang, Peihao Peng, Tao Liu, Juan Wang, Shiqi Zhang, Pengtao Niu

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Integrating GIS-based AHP and groundwater quality assessment to delineate groundwater potential zones in the Rontu Watershed, West Nusa Tenggara, Indonesia by Pascalia Vinca Alvando, Dede Rohmat, Faizal Immaddudin Wira Rohmat, Dasapta Erwin Irawan, Abdullah Husna, Wendi Harjupa, Fauzan Ikhlas Wira Rohmat, Mutiara Indah Nur Rohman

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Quantifying the Impact of Rainfall on Taxi Hailing and Operation by Jian Sun, He Dong, Guoyang Qin, Ye Tian

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Low-cost water level measurement technologies for assessing the impact of climate change and storm surges in coastal areas, suitable for citizen science initiatives by Juan Francisco Martinez-Osuna, Juan Francisco Martinez-Osuna, Viviana Piermattei, Giovanni Coppini, Marco Marcelli, Marco Marcelli

“…These variables provide critical context for interpreting hydrological and oceanographic measurements, enhancing the accuracy of predictive models, and contributing to the development of more robust Early Warning Systems. …”
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Rear-End Crash Risk Analysis considering Drivers’ Visual Perception and Traffic Flow Uncertainty: A Hierarchical Hybrid Bayesian Network Approach by Naikan Ding, Linsheng Lu, Nisha Jiao

“…Results show that (1) the BN model with flow-level data outperformed the BN model without flow-level data and could predict 85.3% of the cases of crash risk decrease, with a false alarm rate of 21.4%; (2) the hierarchical hybrid BN models showed plausible spatial transferability in predicting crash risk variation; and (3) the incorporation of specific flow-level variables and data greatly benefited the successful identification of rear-end crash risk variations. …”
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Spaceborne remote sensing effectively maps species richness across taxonomic groups in a mountain landscape by Cornelius Senf, Lisa Geres, Tobias Richter, Kristin Braziunas, Felix Glasmann, Rupert Seidl, Sebastian Seibold

“…Our results showed that a combination of EnMAP/Sentinel-1/2 performed as well or even better than airborne LiDAR data for predicting species richness, but predictive accuracies of individual spaceborne models were substantially lower. …”
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Improving kidney segmentation in pathological images: a multiscale approach to resolve fragmentation and incomplete boundaries by Muhammad Wajeeh Us Sima, Chengliang Wang, Muhammad Arshad, Jamshed Ali Shaikh, Reem Ibrahim Alkanhel, Dina S. M. Hassan, Ammar Muthanna

“…We evaluated InFeNet on two datasets, where it outperformed state-of-the-art models, demonstrating superior accuracy and predictive performance. …”
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HSF-DETR: Hyper Scale Fusion Detection Transformer for Multi-Perspective UAV Object Detection by Yi Mao, Haowei Zhang, Rui Li, Feng Zhu, Rui Sun, Pingping Ji

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Mapping forest-agroforest frontiers in the Peruvian Amazon with deep learning and PlanetScope satellite data by Wanting Yang, Daniel Ortiz-Gonzalo, Xiaoye Tong, Dimitri Gominski, Rasmus Fensholt

“…Traditional mapping methods are hindered not only by spectral similarity between agroforests and forests, but also by the spatial heterogeneity of forest-agroforest frontiers and the high data demand at large scales is an additional challenge. …”
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Enhancing 3D A* path planning of intelligent bridge crane based on energy efficiency criteria by Heng YANG, Yue LI, Min LIU, Qing DONG

“…Finally, considering the spatial arrangement and operation of the bridge crane in a factory building as an example, environment modeling is conducted on the MATLAB platform, the virtual obstacle is built at the same scale, the operation scheme of the bridge crane lifting the weight at different heights is conducted, and the multi-scheme path planning is conducted before and after the improvement of the algorithm. …”
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Simulated Directional Wave Spectra of the Wind Sea and Swell under Typhoon Mangkhut by Yu Yan, Mengxi Hu, Yugen Ni, Chunhua Qiu

“…A third-generation wave model is driven by the synthetic wind field combined with the revised Holland wind and surface wind product from the National Centers for Environmental Prediction (NCEP). …”
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The Samples and Binary Fractions of Red Supergiants in M31 and M33 by the HST Observations by Min Dai, Shu Wang, Biwei Jiang, Ying Li

“…These results are in good agreement with predictions from the Binary Population and Spectral Synthesis binary evolution model.…”
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Assessment of Normalized Difference Vegetation Index based vegetation dynamics for monitoring rice growth and yield forecasting in the Mahaweli H region of Sri Lanka by Ganewatte Visal P., Abannikov Victor N., De Seram Osanda L., Wijayaratne Bimasha S., Vichare Aniket S.

“…In the regions of Talawa, Meegalewa, and Galnewa, negative correlation coefficients were recorded. Yield forecasting models developed for the subregions with positive correlations demonstrated high accuracy, confirming the potential of Normalized Difference Vegetation Index as a reliable indicator for rice yield prediction. …”
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Forecast of oil and gas reservoirs of the Sea of Okhotsk based on interpretation processing of seismic material by А. К. Shatyrov

“…Forecasting of oil and gas prospects in the Okhotsk Sea in areas where there is no deep drilling can be carried out using the following technologies: detailing the structural and tectonic structure of hydrocarbon traps; multi-feature prediction of hydrocarbon deposits; decomposition of the dispersion of the wave field; low-frequency resonance of seismic emission geodynamic noise; selection of oil and gas-containing objects.…”
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The Effect of Construction Workers’ Work Resilience on Their Leisure Sports Participation: The Mediating Role of Safety and Health Awareness by Yujie Zhang, Shushan Deng, Sen Chen, Zhenning Yao, Yuyang Hou, Qian Huang, Zijian Liu

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A Hybrid Deep Learning Approach for Bearing Fault Diagnosis Using Continuous Wavelet Transform and Attention-Enhanced Spatiotemporal Feature Extraction by Muhammad Farooq Siddique, Faisal Saleem, Muhammad Umar, Cheol Hong Kim, Jong-Myon Kim

“…The model is initially trained on a controlled laboratory bearing dataset and further validated on real and artificial subsets of the Paderborn bearing dataset, demonstrating strong generalization across diverse fault conditions. t-SNE visualizations confirm clear separability between fault categories, supporting the model’s capability for precise and reliable feature learning and strong potential for real-time predictive maintenance in complex industrial environments.…”
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Simulation of the African ITCZ during austral summer seasons and ENSO phases: application of an RCM derived from stretched grid ESM by Teke S. Ramotubei, Teke S. Ramotubei, Willem A. Landman, Mohau J. Mateyisi, Shingirai S. Nangombe, Asmerom F. Beraki, Asmerom F. Beraki

“…IntroductionClimate predictability across timescales in a changing climate presents a unique opportunity and challenges for state-of-the-art climate models. …”
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