InceptionDTA: Predicting drug-target binding affinity with biological context features and inception networks by Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi

“…In this paper, we introduce InceptionDTA, a novel drug-target binding affinity prediction model that leverages CharVec, an enhanced variant of Prot2Vec, to incorporate both biological context and categorical features into protein sequence encoding. …”
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The manifestation of VIS-NIRS spectroscopy data to predict and mapping soil texture in the Triffa plain (Morocco) by Ayoub Lazaar, Biswajeet Pradhan, Zakariae Naiji, Abdelali Gourfi, Kamal El Hammouti, Karim Andich, Abdelilah Monir

“…However, the maps of predicted and measured soil texture showed an excellent spatial similarity for the sand fraction, a certain difference in the variability of clay fraction, while the maps of silt fraction show a lower difference. …”
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Automated yield prediction in vineyard using RGB images acquired by a UAV prototype platform by Giorgia Orlandi, Alessandro Matese, Alessandro Ulrici, Rosalba Calvini, Andrea Berton, Salvatore Filippo Di Gennaro

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Predicting future corn suitability zones under climate change scenarios in the United States of America by Birhan Getachew Tikuye, Ram Lakhan Ray

“…This study employs the MaxEnt (Maximum Entropy) model to predict spatial changes in corn suitability across the United States under baseline and future climate change scenarios. …”
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A Robust Framework for Bamboo Forest AGB Estimation by Integrating Geostatistical Prediction and Ensemble Learning by Lianjin Fu, Qingtai Shu, Cuifen Xia, Zeyu Li, Hailing He, Zhengying Li, Shaoyang Ma, Chaoguan Qin, Rong Wei, Qin Xiang, Xiao Zhang, Yiran Zhang, Huashi Cai

“…This study first employed Empirical Bayesian Kriging Regression Prediction (EBKRP) to spatialize sparse GEDI and ICESat-2 LiDAR metrics using Sentinel-2 and topographic covariates. …”
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Study on the Evolution and Prediction of Land Use and Landscape Patterns in the Jianmen Shu Road Heritage Area by Chenmingyang Jiang, Xinyu Du, Jun Cai, Hao Li, Qibing Chen

“…In this study, we considered three cities along the Jianmen Shu Road, analyzed the evolution characteristics of land use and landscape patterns from 2012 to 2022, and used the multi-criteria evaluation–cellular automata-Markov (MCE-CA-Markov) model to predict the land use and landscape patterns in 2027. …”
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Spatial transcriptomics and scRNA-seq: decoding tumor complexity and constructing prognostic models in colorectal cancer by Wei Song, Yatao Wang, Min Zhou, Fengqin Guo, Yanliang Liu

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Deep Gaussian process with uncertainty estimation for microsatellite instability and immunotherapy response prediction from histology by Sunho Park, Morgan F. Pettigrew, Yoon Jin Cha, In-Ho Kim, Minji Kim, Imon Banerjee, Isabel Barnfather, Jean R. Clemenceau, Inyeop Jang, Hyunki Kim, Younghoon Kim, Rish K. Pai, Jeong Hwan Park, N. Jewel Samadder, Kyo Young Song, Ji-Youn Sung, Jae-Ho Cheong, Jeonghyun Kang, Sung Hak Lee, Sam C. Wang, Tae Hyun Hwang

“…Finally, MSI-SEER’s tile-level predictions revealed novel insights into the role of spatial distribution of MSI-H regions in the tumor microenvironment and ICI response.…”
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Analysis and prediction of storability and storage quality of pear fruit based on clustering and time series analysis by ZHOU Hui-juan, YE Zheng-wen, LI Rong-hua, WANG Xiao-qing, LUO Jun

“…The change of fruit texture of three pear varieties can be well fitted by exponential equation, and the change of sugar and acid content can be well described by nonlinear equation. The prediction errors of the two prediction models are low. …”
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Assessment and Prediction of Typhoon-Related Direct Economic Loss in Fujian Province Based on LightGBM by Zhang Zhixia, Yang Jian, Chen Sixiao, Lin Sen

“…In real-world applications, the proposed model effectively captured the spatial distribution of losses from Typhoon Meranti, demonstrating its potential for disaster loss prediction. …”
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Global foot-and-mouth disease risk assessment based on multiple spatial analysis and ecological niche model by Qi An, Yiyang Lv, Yuepeng Li, Zhuo Sun, Xiang Gao, Hongbin Wang

“…A multi-algorithm ensemble model considering climatic, geographic, and social factors was developed to predict the suitability area for FMDV, and then risk maps of FMD for each species of livestock were generated in combination with the distribution of livestock. …”
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Neural Network-Based Prediction of Amplification Factors for Nonlinear Soil Behaviour: Insights into Site Proxies by Ahmed Boudghene Stambouli, Lotfi Guizani

“…Finally, it is recommended to further refine this study by including additional soil parameters such as spatial configuration and by adopting more refined soil models.…”
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PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific by Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li

“…Moreover, as observed from the spatial distribution of the anomaly correlation coefficient, the model exhibits higher forecasting accuracy for coastal and marginal sea regions.…”
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Numerical modeling of electromagnetic wave propagation in spatially-varying evaporation duct conditions via 3D parabolic equation method by Hanjie Ji, Hanjie Ji, Lixin Guo, Yan Zhang, Tianhang Nie, Yiwen Wei, Jinpeng Zhang, Qingliang Li, Xiangming Guo, Yusheng Zhang

“…Conventional two-dimensional (2D) models assume homogeneous refractive index distribution along the cross-range dimension in a single propagation plane, limiting their ability to capture the 3D spatial heterogeneities present in real-world scenarios. …”
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Morphodynamic predictions based on Machine Learning. Performance and limits for pocket beaches near the Bilbao port by Manuel Viñes, Agustín Sánchez-Arcilla, Irati Epelde, César Mösso, Javier Franco, Joaquim Sospedra, Aritz Abalia, Pedro Líria, Manel Grifoll, Alberto Ojanguren, Mario Hernáez, Manuel González, Agustín Sánchez-Arcilla

“…Predicting the morphodynamic behaviour of pocket beaches exposed to energetic waves and meso-tidal ranges—particularly under strong seasonal variability and the influence of climate change—requires a robust characterization of coastal morphodynamics across a wide range of temporal and spatial scales. …”
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An Interpretable Implicit-Based Approach for Modeling Local Spatial Effects: A Case Study of Global Gross Primary Productivity Estimation by S. Du, H. Huang, K. Shen, Z. Liu, S. Tang

“…In geographic machine learning tasks, conventional statistical learning methods often struggle to capture spatial heterogeneity, leading to unsatisfactory prediction accuracy and unreliable interpretability. …”
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Predicting present and future habitats using LiDAR to integrate research and monitoring with landscape analyses by David A. MacLean, Thomas Baglole, Maurane Bourgouin, Billie Chiasson, Jiban C. Deb, Maitane Erdozain, Remus J. James, Lauren Negrazis, Louka Tousignant, Phil Wiebe, Greg Adams, Joseph R. Bennett, Erik J.S. Emilson, Nicole J. Fenton, Graham J. Forbes, Michelle A. Gray, Karen A. Kidd, Andrew McCartney, Gaetan Moreau, Kevin B. Porter, Osvaldo Valeria, Lisa A. Venier

“…LiDAR-based enhanced forest inventory provided forest structure variables that improved bird habitat models and spatial predictions of bird habitat, metrics explaining bryophyte composition and richness, and variability in beetle abundance and richness. …”
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Interpretable Transformer Neural Network Prediction of Diverse Environmental Time Series Using Weather Forecasts by Enrique Orozco López, David Kaplan, Anna Linhoss

“…The TNN was tested and its prediction uncertainty quantified for each response variable from one‐to fourteen‐day‐ahead forecasts using past observations and spatially distributed weather forecasts. …”
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Effective rain rate model for analysing overestimated rain fade in short millimetre-wave terrestrial links due to distance factor by Asma Ali Budalal, Ibraheem Shayea, Md. Rafiqul Islam, Jafri Din, Abdulsamad Ebrahim Yahya, Yousef Ibrahim Daradkeh, Marwan Hadri Azmi

“…Thus, an effective rain rate concept and model are proposed to represent rain intensity variations for short paths to eliminate the need for an effective path length that more accurately predicts rain attenuation at path lengths exceeding 1 km. …”
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Spatial clustering analysis combined with ensemble modeling identified potential coastal conservation hotspots of White-eyed gulls in the Red Sea by Mohanad Abdelgadir, Monif AlRashidi, Randa Alharbi, Abdulaziz S. Alatawi

“…In this study, we used a spatial clustering analysis combined with an ensemble modeling approach to predict the coastal distribution and identify potential hotspots for the White-eyed gull. …”
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