Innovative Perspectives on Ecological Assessment in the Agro-Pastoral Ecotone of Inner Mongolia: An Integrated Evaluation and Forecast of Landscape and Ecological Risks and Drivers by Jiaru Wu, Peng Han, Jiwu Zhai, Qing Zhang

“…Future ecological risks from 2025 to 2040 were predicted using the multi-criteria evaluation-cellular automata-Markov model. …”
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Masked pre-training of transformers for histology image analysis by Shuai Jiang, Liesbeth Hondelink, Arief A. Suriawinata, Saeed Hassanpour

“…In digital pathology, whole-slide images (WSIs) are widely used for applications such as cancer diagnosis and prognosis prediction. Vision transformer (ViT) models have recently emerged as a promising method for encoding large regions of WSIs while preserving spatial relationships among patches. …”
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A sub-meter resolution urban surface albedo dataset for 34 U.S. cities based on deep learning by Shengao Yi, Xiaojiang Li, Yixuan Liu, Xinyu Dong, Wei Tu

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Re-identification assistance and multi-stage association for pedestrian multi-object tracking by Ye Li, Li Zhan, Lei Wu, Hongkun Liu, Jianli Min, Xinzhong Wang

“…Currently, most methods mainly use the Kalman filter to model the motion and predict the position of the pedestrian in the next frame. …”
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The Value of Learning about Natural History in Biodiversity Markets. by Douglas J Bruggeman

“…I use an individually-based, spatially-explicit population model for the Red-cockaded Woodpecker (Picoides borealis) to predict spatial- and temporal- influences of landscape change on species occurrence and genetic diversity. …”
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Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What’s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

“…As a result, the efficient allocation of public security resources based on spatio-temporal crime prediction models has become a critical concern for urban management. …”
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Computational exploration of structural hypotheses for an additional sequence in a mammalian mitochondrial protein. by Aymen S Yassin, Rajendra K Agrawal, Nilesh K Banavali

“…<h4>Conclusions</h4>By hypothesizing that the insert sequence occupies the IF1 binding site, continuous IF2(mt) models that occupy both the IF2 and IF1 binding sites can be predicted computationally. …”
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Evaluation of Landslide Risk Using the WoE and IV Methods: A Case Study in the Zipaquirá–Pacho Road Corridor by Sandra Velazco, Álvaro Rodríguez, Martín Riascos, Fernando Nieto, Dayana Granados

“…Of these, 70% were used to build the models, while the remaining 30% were reserved for validation, ensuring spatial representativeness. …”
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FROM PIXELS TO DIAGNOSIS: A DEEP LEARNING FRAMEWORK FOR HISTOPATHOLOGICAL IMAGE ANALYSIS IN CANINE TESTICULAR PATHOLOGY

“…We fine-tuned the model on a proprietary dataset of testicular tissue sections, annotated by two pathologists. …”
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Le rôle des facteurs locaux sur les effets des changements climatiques au Quaternaire supérieur sur les environnements naturel du Néguev septentrional by Aaron Yair

“…However; existing global models are not yet capable of predicting accurately the evolution of regional climates and their possible impact on the environment. …”
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Simulation of urban development in the City of Rome: Framework, methodology, and problem solving by Simone Di Zio, Armando Montanari, Barbara Staniscia

“…In Italy’s case, the implementation of the UrbanSIM model involved the territory of Rome, including the municipalities of Rome and Fiumicino. …”
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Comparison of Deep and Machine Learning Approaches for Quebec Tree Species Classification Using a Combination of Multispectral and LiDAR Data by Omid Reisi Gahrouei, Jean-François Côté, Philippe Bournival, Philippe Giguère, Martin Béland

“…The results indicated that Dense Convolution Network (DenseNet) achieved the best overall accuracy of 78%, outperforming machine learning methods by 5%. In addition, the models’ performance was independently assessed using permanent and temporary ground sample plots, acknowledging the superiority of DenseNet in terms of overall accuracy (73%) in predicting the dominant species. …”
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Mapping the global distribution of livestock. by Timothy P Robinson, G R William Wint, Giulia Conchedda, Thomas P Van Boeckel, Valentina Ercoli, Elisa Palamara, Giuseppina Cinardi, Laura D'Aietti, Simon I Hay, Marius Gilbert

“…The Gridded Livestock of the World (GLW) database, produced in 2007, provided modelled livestock densities of the world, adjusted to match official (FAOSTAT) national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 5×5 km at the equator). …”
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The Combination Application of FY-4 Satellite Products on Typhoon Saola Forecast on the Sea by Chun Yang, Bingying Shi, Jinzhong Min

“…Effective comprehensive application of satellite products will inevitably improve numerical weather prediction. FengYun-4 (FY-4) series satellites can provide not only radiance data but also retrieval data with high temporal and spatial resolutions. …”
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Treatment-prognostication-adjustment a new therapeutic idea by analyzing T cell immune checkpoint in tumor microenvironment by algorithm: A bibliometric analysis by Shiwei Ma, Xin Wu, Zhongguang Wu, Qiangqiang Zhao

“…In the past three years, survival analysis, immune cell infiltration, and prediction model have been used. It can be seen that the focus in this field has shifted from tumor cell behavior and directly related molecules to prognosis prediction and non-tumor cells in the microenvironment. …”
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Range dynamics of Anopheles mosquitoes in Africa suggest a significant increase in the malaria transmission risk by Peixiao Nie, Chunyan He, Jianmeng Feng

“…Through a unified scheme, we developed 21 species distribution models to predict the range dynamics of 21 major An. species in Africa under future scenarios and also examined their overall range dynamic patterns mainly through suitability overlap index and range overlap index. …”
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Estimating the impact of interventions against COVID-19: From lockdown to vaccination. by James Thompson, Stephen Wattam

“…Our model predicts far fewer cases and deaths than the equivalent equation-based SEIR model. …”
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Digital mapping of soil organic carbon stocks in the forest lands of Dominican Republic by Efraín Duarte, Erick Zagal, Juan A. Barrera, Francis Dube, Fabio Casco, Alexander J. Hernández

“…Model A reported the lowest prediction error and uncertainty with an R2 of 0.83, an RMSE of 35.02 Mg C ha−1. …”
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Multivariate and long-term time series analysis to assess the effect of nitrogen management policy on groundwater quality in Wallonia, BE by E. Verstraeten, A. Alonso, L. Collier, M. Vanclooster

“…</p> <p>Importantly, the findings are not fully conclusive due to the limited predictive power of the regression models. This highlights the multifaceted nature of groundwater nitrate contamination and the challenges in defining input variables that accurately capture the drivers. …”
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Normalization Strategies in Multi-Center Radiomics Abdominal MRI: Systematic Review and Meta-Analyses by Jovana Panic, Arianna Defeudis, Gabriella Balestra, Valentina Giannini, Samanta Rosati

“…The main challenge is represented by the great and unavoidable image variability which is usually addressed using different pre-processing techniques including spatial, intensity and feature normalization. The purpose of this study is to systematically summarize normalization methods and to evaluate their correlation with the radiomics model performances through meta-analyses. …”
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