Reciprocal regulation between rural settlement expansion and human-elephant conflict in China’s wild elephant range by Beibei Xu, Xin Zhang, Jiejing Zhang, Hui Fan

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Enhancing Visual Place Recognition With Hybrid Attention Mechanisms in MixVPR by Jun Hu, Jiwei Nie, Zuotao Ning, Chaolu Feng, Luyang Wang, Jingyao Li, Shuai Cheng

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Systematic protection and restoration of water bodies in collapse areas based on surface runoff regulation by Shaogang LEI, Yufan XU, Mian ZHANG, Dongxing CHEN, Xia HUA, Dong GUO

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Detecting Sensitive Spectral Bands and Vegetation Indices for Potato Yield Using Handheld Spectroradiometer Data by Diego Gomez, Pablo Salvador, Juan Fernando Rodrigo, Jorge Gil

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Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny by ZHANG Guanghua, LI Congfa, LI Gangying, LU Weidang

“…In addition, the ConvMixer layer is integrated into the prediction head; the depthwise and pointwise convolutions in ConvMixer capture the spatial and channel relationships in the feature information, improving the processing capability for small targets. …”
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Urbanization and its Impact on Land Use and Land Cover in Al Buraimi City, Oman Using Remote Sensing and GIS by Ansari Tauseef Ahmad Ahmad, Singh Chandan Kumar, Albawwab Wael

“…The city’s rapid growth in population burdening its infrastructure, traffic, municipal, education and public health capacity. This paper investigates the transformation of Land Use (LU) / Land Cover (LC) change from 2003 to 2023 in relation to population growth, employing both spatial and non-spatial methods to analyze the urban sprawl. …”
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LiDAR-Based Road Cracking Detection: Machine Learning Comparison, Intensity Normalization, and Open-Source WebGIS for Infrastructure Maintenance by Nicole Pascucci, Donatella Dominici, Ayman Habib

“…The optimized BE layer, enriched with intensity and color information, enabled crack detection through Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Random Forest (RF) classification, with and without intensity normalization. …”
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Multi-task advanced convolutional neural network for robust lymphoblastic leukemia diagnosis, classification, and segmentation by Sercan Yalcin, Zuhal Cetin Yalcin, Muhammed Yildirim, Bilal Alatas

“…The proposed framework achieved an accuracy of 0.978, precision of 0.979, recall of 0.967, F1-score of 0.973, specificity of 0.991, Cohen’s kappa of 0.979, and negative predictive value (NPV) of 0.990. These metrics significantly outperform baseline models, highlighting the MTA-CNN’s ability to accurately identify and classify ALL cases. …”
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Push Factors of Population Migration in Russian Regions in Terms of Age Structure by Evgeniya Mikhailovna Moiseeva

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An Improved U-Net-Based Framework for Estimating River Surface Flow Velocity by 周继威, 安国成, 王根一

“…Existing deep learning models face challenges in generalization due to limited training samples and data heterogeneity across complex river environments. …”
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Community Structure, Assembly and Interactions of <i>Nitrospira</i> Nitrite-Oxidizing Bacteria in Sediments of the Eastern China Marginal Seas by Hao Dong, Hui He, Min Wang

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Flood inundation and damage assessment of the degraded Semliki River plains using SAR data, Google Earth Engine, and GIS techniques by Andrew Mulabbi, John Calvin Esagu, Gertrude Akello, Remigio Turyahabwe

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Identification of traditional flood control facilities concealed in the riparian forest: a case study of the Echi River, central Japan by Takuro Ogura, Kazuyuki Shimamoto, Toshiaki Mizuno, Daisuke Katayama, Hiroyuki Yamauchi, Tsuyoshi Hattanji

“…A high-definition digital terrain model (DTM) was developed to detect convex landforms consistent with Saruo. …”
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Pharmacological potential of 3,5-dimethyl-4-(3-(5-nitrofuran-2-yl)allylidenamino)-1-alkyl-1,2,4-triazolium bromides by A. S. Hotsulia, O. I. Panasenko, T. S. Brytanova

“…A molecular docking method that uses a variety of computational algorithms to predict and analyze interactions, including determining the presence of possible binding sites, estimating binding energies, and the spatial arrangement of molecules. …”
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Heterogeneous Mantle Metasomatism Controlled by Continental Subduction: Evidence From Post‐Collisional Mafic Rocks in the North Qaidam Orogen by Xiangyu Gao, Shengyao Yu, Yu Qi, Lintao Wang, Chuanzhi Li, Xiaocong Jiang, Xingzhou Jiang, Yang Yu

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Public health perspectives on green efficiency through smart cities, artificial intelligence for healthcare and low carbon building materials by Jingjing Sun, Xin Guan, Siqi Yuan, Yalin Guo, Yepei Tan, Yajuan Gao

“…Additionally, the effective use of advanced technologies like convolutional neural networks (CNN) in predicting and promoting low-carbon solutions in construction is gaining attention.MethodsThis study employs a dual approach: (1) A survey of 200 respondents was conducted to gauge public perceptions and attitudes toward smart cities, AI in medicine, and low-carbon building materials. (2) A CNN model was developed and implemented to predict the performance of low-carbon building materials. …”
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Development and Training Strategy of Badminton Action Recognition System Under the Background of Artificial Intelligence by Hongjun Ma, Fan Zhang, Ni Liang

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Influence of Black Carbon on Photovoltaic and Wind Energy Potential Under the Shared Socioeconomic Pathways by Zhenming Ji, Guanying Chen

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Wildlife students as community scientists provide statewide detection data to help non‐invasively monitor Oklahoma bobcats by Nathan J. Proudman, Michelle L. Haynie, Victoria L. Jackson, Jerrod Davis, W. Sue Fairbanks

“…Abstract Community science projects are ideal for collecting species data at large spatial scales and can connect the public with the management and conservation of native wildlife. …”
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Analysing LULC transformations using remote sensing data: insights from a multilayer perceptron neural network approach by Khadim Hussain, Kaleem Mehmood, Sun Yujun, Tariq Badshah, Shoaib Ahmad Anees, Fahad Shahzad, Nooruddin, Jamshid Ali, Muhammad Bilal

“…The study highlights the effectiveness of the MLP-NN model in accurately predicting changes in LULC. The model’s exceptional accuracy and proficiency make it a powerful tool for future LULC forecasts. …”
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