Changing grizzly bear space use and functional connectivity in response to human disturbance in the southern Canadian Rocky Mountains by Eric C. Palm, Clayton D. Apps, Tal Avgar, Melanie Dickie, Bruce N. McLellan, Joseph M. Northrup, Michael A. Sawaya, Julie W. Turner, Jesse Whittington, Erin L. Landguth, Katherine A. Zeller, Clayton T. Lamb

“…Our study builds upon existing work simulating animal space use from fitted iSSFs by incorporating individual‐level variation into population‐level simulations and by fitting functional responses that help capture broad‐scale variation in behavior and improve model transferability to new areas. Our results provide insights into grizzly bear movement and connectivity in an area of high conservation importance, and our predictive maps can be used to directly inform transboundary management actions and conservation planning.…”
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Multi-scale attention-enhanced deep learning approach for detecting seven trunk pests and diseases in Shanghai’s urban plane trees by Tianyang Song, Guohua Hu, Tianci Yu, Xing Meng, Yanting Zhang, Ruiqing Yang, Benyao Wang, Xia Li

“…Trained on 3,983 annotated samples from Shanghai, the model achieved a 3.8% increase in mean Average Precision at a 50% Intersection over Union threshold (mAP50) and a significant reduction in missed detections compared to the baseline YOLOv8. …”
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Soil Salinity Detection and Mapping by Multi-Temporal Landsat Data: Zaghouan Case Study (Tunisia) by Karem Saad, Amjad Kallel, Fabio Castaldi, Thouraya Sahli Chahed

“…These samples were representative of distinct soil salinity classes, including non-saline, slightly saline, moderately saline, strongly saline, and very strongly saline soils. Soil salinity modeling using Landsat-8 OLI data revealed that the SI-5 index provided the most accurate predictions, with an R² of 0.67 and an RMSE of 0.12 dS/m. …”
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Normative structural connectome constrains spreading transient brain activity in generalized epilepsy by Jie Xia, Siqi Yang, Jiao Li, Yao Meng, Jinpeng Niu, Huafu Chen, Zhiqiang Zhang, Wei Liao

“…The collective abnormality of structurally connected neighbors significantly predicted regional activity abnormality, indicating that white matter network architecture constrains aberrant activity patterns. …”
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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…Therefore, CNN is used as the fault prediction also. The model is implemented using Python programming language and demonstrated its effectiveness on test cases. …”
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The Paradox of Urban Travel Behavior on Public Transport Use: A Bibliometric and Critical Theoretical Review by Kaamah Abdallah Faisal, Kombe Wilbard Jackson, Sakijege Tumpale

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A Three-Level Meta-Frontier Framework with Machine Learning Projections for Carbon Emission Efficiency Analysis: Heterogeneity Decomposition and Policy Implications by Xiaoxia Zhu, Tongyue Feng, Yuhe Shen, Ning Zhang, Xu Guo

“…Methodologically, we introduce two novel projection combinations—“exogenous-exogenous-accumulation (E-E-A) and exogenous-exogenous-consistent (E-E-C)”—to resolve the inconsistency of technology gap ratios (TGRs > 1) in traditional nonradial directional distance function (DDF) models. Reinforcement learning (RL) optimizes dynamic direction vectors, whereas graph neural networks (GNNs) encode spatial interdependencies to constrain the TGR within [0, 1]. …”
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Accounting for transience in the baseline climate state changes the surface climate response attributed to stratospheric aerosol injection by Alistair Duffey, Peter J Irvine

“…However, relative to the hypothetical scenario with lower CO _2 concentrations that would achieve a stabilised climate at the same temperature, SAI produces a 69% larger reduction in global precipitation. Accounting for stabilisation can also meaningfully change the spatial pattern of surface temperature response attributable to SAI. …”
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Impact of modulating surface heat flux through sea ice leads on Arctic sea ice in EC-Earth3 in different climates by T. Tian, R. Davy, L. Ponsoni, S. Yang

“…<p>This sensitivity study examines the impact of modulating surface sensible heat flux over leads – open-water areas within sea ice cover – to approximate finer-scale processes that are often underrepresented in climate models. We aim to assess how this parameterization (referred to as ECE3L) influences the persistent positive bias in Arctic sea ice (concentration and thickness) in the global climate model EC-Earth3 (ECE3). …”
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GOES‐R PM2.5 Evaluation and Bias Correction: A Deep Learning Approach by Alqamah Sayeed, Pawan Gupta, Barron Henderson, Shobha Kondragunta, Hai Zhang, Yang Liu

“…Abstract Estimating surface‐level fine particulate matter from satellite remote sensing can expand the spatial coverage of ground‐based monitors. This approach is particularly effective in assessing rapidly changing air pollution events such as wildland fires that often start far away from centralized ground monitors. …”
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PCES-YOLO: High-Precision PCB Detection via Pre-Convolution Receptive Field Enhancement and Geometry-Perception Feature Fusion by Heqi Yang, Junming Dong, Cancan Wang, Zhida Lian, Hui Chang

“…To address these issues, this paper proposes PCES-YOLO, an enhanced YOLOv11-based model. First, a developed Pre-convolution Receptive Field Enhancement (PRFE) module replaces C3k in the C3k2 module. …”
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Mapping emergent coral reefs: a comparison of pixel‐ and object‐based methods by Amy Stone, Sharyn Hickey, Ben Radford, Mary Wakeford

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Implications of human induced changes on the distribution of important plant species in the northwestern coastal desert of Egypt by Marwa Waseem Halmy, Paul E. Gessler, Selim Z. Heneidy

“…Few studies have conducted spatially explicit modeling of plant species distribution in Egypt. …”
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Clinical-oriented 3D visualization and quantitative analysis of gingival thickness using convolutional neural networks and CBCT by Lan Yang, Lan Yang, ZiCheng Zhu, Yongshan Li, Jieying Huang, Xiaoli Wang, Haoran Zheng, Jiang Chen

“…The 3D model enabled millimeter-precision quantification, supporting multi-angle and multi-level GT assessment that overcame the limitations of traditional 2D measurements.ConclusionThis system represents a methodological advancement from qualitative to spatial quantitative GT assessment. …”
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Bayesian active sound localisation: To what extent do humans perform like an ideal-observer? by Glen McLachlan, Piotr Majdak, Jonas Reijniers, Michael Mihocic, Herbert Peremans

“…The model predictions showed a general agreement with actual human performance. …”
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Orchard variable-rate spraying method integrating GNSS and wind-excited audio-conducted leaf area density by Hangxing Zhao, Hangxing Zhao, Hangxing Zhao, Shenghui Yang, Shenghui Yang, Shenghui Yang, Wenwei Li, Wenwei Li, Han Feng, Han Feng, Shijie Jiang, Shijie Jiang, Weihong Liu, Weihong Liu, Jingbin Li, Yongjun Zheng, Yongjun Zheng, Songchao Zhang

“…A variable-rate spray control model and algorithm were then constructed to regulate spray flow according to the spatial distribution of leaf area density across the orchard.ResultsField experiments demonstrated that the system achieved a mean relative error of only 5.52% in spray flow rate regulation. …”
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On the convective nature of roll waves instability by C. Di Cristo, A. Vacca

“…The study reveals an influence of the disturbance frequency on the perturbation spatial growth rate, which constitutes the theoretical foundation of semiempirical criteria commonly employed for predicting roll waves occurrence.…”
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Study on the Disturbed Mechanical Behavior and Energy Evolution Characteristics of Deep Roof Rock Considering Spatio-Temporal Effects by WANG man, ZHANG Yang, XIE Jing, NIU Zehua, DENG Huchao, YANG Bengao, ZHAO Lijuan, D ING Xiaogang, GAO Mingzhong

“…This model generalizes the disturbance stress path generated by the multi-working face mining of coal seam group in the longitudinal dimension as a cyclic loading and unloading process, the increase of the disturbance stress concentration factor caused by the reduction of the distance between the coal seams is reflected in the stress path as the increase of the peak stress of cyclic loading and unloading. …”
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Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India by Aparnna Ravi, Dhanyalekshmi Pillai, Christoph Gerbig, Stephen Sitch, Sönke Zaehle, Vishnu Thilakan, Chandra Sekhar Jha, Thara Anna Mathew

“…We improve these model predictions by additionally using satellite-based solar-induced chlorophyll fluorescence (SIF), soil temperature , and soil moisture specific to the vegetation classes of the domain. …”
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Arsenic toxicity exacerbates China’s groundwater and health crisis by Xin Liu, Fu-Jun Yue, Wei Wen Wong, Shao-Chong Lin, Tian-Li Guo, Si-Liang Li

“…A random forest analysis identified chemical properties (including oxidation–reduction potential, pH, total manganese ion, total iron ion, total dissolved solids, and sulfate ion) as the most influential drivers, contributing 56% to the model’s explanatory power, followed by geographical factors at 28%, climatic factors at 10%, and human activities at 6%. …”
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