Advancing Early Diagnosis: Predicting Mild Cognitive Impairment Progression in Normal Individuals Using Deep Learning on MRI Features by Abdullah Baktash, Yashar Sarbaz, Saeed Meshgini, Reza Afrouzian

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Sensitivity Analysis of Soil Hydraulic Parameters for Improved Flow Predictions in an Atlantic Forest Watershed Using the MOHID-Land Platform by Dhiego da Silva Sales, Jader Lugon Junior, David de Andrade Costa, Renata Silva Barreto Sales, Ramiro Joaquim Neves, Antonio José da Silva Neto

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A cluster-based local modeling paradigm for high spatiotemporal resolution VPD prediction using multi-source data and machine learning by Mi Wang, Zhuowei Hu, Xiangping Liu, Wenxing Hou

“…The results show that the local modeling significantly enhances prediction accuracy, with the XGBoost model outperforming others across all clusters and maintaining high precision across seasons scales and different land use types. …”
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Skillful seasonal prediction of the boreal summer Pacific–Japan teleconnection pattern by Kan Yi, Chenqi Wang, Yunfei Zhang, Xiang Li, Jian Wang, Renqiang Wen, Mengjiao Du

“…Our findings elucidate that the spatial structure of the PJ pattern simulated by models introduces substantial diversities in prediction skills. …”
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Machine learning-assisted multi-dimensional transcriptomic analysis of cytoskeleton-related molecules and their relationship with prognosis in hepatocellular carcinoma by Yuxuan Li, Mingbo Cao, Xiaorui Su, Gaoyuan Yang, Yupeng Ren, Zhiwei He, Zheng Shi, Ziyi Hu, Guirong Liang, Qi Zhang, Zhicheng Yao, Meihai Deng

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L’action sur les territoires face au défi d’une temporalité ouverte. L’improvisation comme modèle pour l’action aménagiste ? by Lisa Levy

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L’action sur les territoires face au défi d’une temporalité ouverte. L’improvisation comme modèle pour l’action aménagiste ? by Lisa Levy

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Eco-Spatial Modeling of Two Giant Flying Squirrels (Sciuridae: <i>Petaurista</i>): Navigating Climate Resilience and Conservation Roadmap in the Eastern Himalaya and Indo-Burma Bio... by Imon Abedin, Manokaran Kamalakannan, Tanoy Mukherjee, Hilloljyoti Singha, Dhriti Banerjee, Hyun-Woo Kim, Shantanu Kundu

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Predicting species distributions in the open ocean with convolutional neural networks by Morand, Gaétan, Joly, Alexis, Rouyer, Tristan, Lorieul, Titouan, Barde, Julien

“…These findings show the adequacy of deep learning for species distribution modelling in the open ocean. Additionally, this purely correlative model was then analysed with explicability tools to understand which variables had an influence on the model’s predictions. …”
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Relationships between abundances of breeding ducks and attributes of Canadian prairie wetlands by Blake Bartzen, Kevin W. Dufour, Mark T. Bidwell, Michael D. Watmough, Robert G. Clark

“…In regions where duck densities were high, there were more ducks per pond; conversely, there were fewer ducks per pond in regions where pond densities were high, indicating that mechanisms influencing local habitat use were, in part, mediated by processes occurring at larger spatial scales. Although models explained small amounts of variation of duck abundance on a per pond basis, these models explained more variation when results were aggregated to the level of survey segment, indicating reasonable performance of models for estimating duck abundance over specific areas with known pond areas. …”
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Enhancing landslide-scale rainfall threshold predictive modeling for rainfall-induced red-bed soft rock landslide occurrence using a stock-taking approach by Qi Li, Zidan Liu, Ziyu Tao

“…Using a Bayesian modeling framework for predicting the probability occurrence of landslides triggered by a rainfall event above the defined rainfall threshold, we found that high intensity rainfall events play a more important role in triggering R-SRLs than their long duration.…”
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Using Earth observation to support the predictive accuracy of species distribution models in ecological restoration: a case study of Poland beavers (Castor fiber) by H. A. Cheriyanda Raveendra, L. Picco, F. Pirotti, F. Pirotti

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Generation driven understanding of localized 3D scenes with 3D diffusion model by Hao Sun, Junping Qin, Zheng Liu, Xinglong Jia, Kai Yan, Lei Wang, Zhiqiang Liu, Shaofei Gong

“…In addition to accurately predicting the distribution of the noise tensor, the framework significantly enhances the understanding of localized scenes by effectively integrating spatial context information. …”
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Soil Erosion Prediction Using Morgan-Morgan-Finney Model in a GIS Environment in Northern Ethiopia Catchment by Gebreyesus Brhane Tesfahunegn, Lulseged Tamene, Paul L. G. Vlek

“…Even though scientific information on spatial distribution of hydrophysical parameters is critical for understanding erosion processes and designing suitable technologies, little is known in Geographical Information System (GIS) application in developing spatial hydrophysical data inputs and their application in Morgan-Morgan-Finney (MMF) erosion model. …”
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Flexible movement kernel estimation in habitat selection analyses with generalized additive models by Rafael Arce Guillen, Jennifer Pohle, Florian Jeltsch, Manuel Roeleke, Björn Reineking, Natasha Klappstein, Ulrike Schlägel

“…In addition, including a bivariate tensor product in the model leads to a better uncertainty estimation of the model parameters and lower mean‐squared error of the model predictions. …”
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STFGCN: Spatio-Temporal Fusion Graph Convolutional Networks for Subway Traffic Prediction by Xiaoxi Zhang, Zhanwei Tian, Yan Shi, Qingwen Guan, Yan Lu, Yujie Pan

“…Experimental results on the Hangzhou Metro&#x2019;s inbound and outbound passenger flow datasets demonstrate that the STFGCN model exhibits significant superiority over baseline models and shows excellent performance in metro passenger flow prediction. …”
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Estimation and prediction of water conservation in the upper reaches of the Hanjiang River Basin based on InVEST-PLUS model by Pengtao Niu, Zhan Wang, Jing Wang, Yi Cao, Peihao Peng

“…With the gradual prominence of global water shortage and other problems, evaluating and predicting the impact of land use change on regional water conservation function is of great reference significance for carrying out national spatial planning and environmental protection, and realizing land intelligent management. …”
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A Novel Short‐Term Prediction Model for Regional Equatorial Plasma Bubble Irregularities in East and Southeast Asia by Xiukuan Zhao, Guozhu Li, Haiyong Xie, Lianhuan Hu, Wenjie Sun, Yi Li, Guofeng Dai, Jianfei Liu, Yu Li, Baiqi Ning, Michi Nishioka, Septi Perwitasari, Prasert Kenpankho

“…For 60‐min prediction, the STEP model can still achieve reasonable accuracy with an RMSE of 0.110 TECU/min and an R2 of 0.482, showing significant improvement over traditional models. …”
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Predicting the needs of people living with a disability using the two-level logit-skewed exponential power model by Abayomi Ajayi, Olaniyi Olayiwola, Fadeke Apantaku, Idowu Osinuga, Oluwaseun Wale-Orojo

“…Cartograms were used to determine the spatial distribution for the proportion of doctor’s visit and cost using the predicted values. …”
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Spatial targeting of Screening + Eave tubes (SET), a house-based malaria control intervention, in Côte d'Ivoire: A geostatistical modelling study. by Tiago Canelas, Edward Thomsen, Daniel McDermott, Eleanore Sternberg, Matthew B Thomas, Eve Worrall

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