Rift basins of the late phanerozoic of Africa: regional patterns and conceptual development aspects by V. M. Usova

“…The author proposes a model to correlate the rifting process with the centers of evolution and regeneration of the African superplume and the spread of heated superdeep material from these centers through the channels of granulite belts.   …”
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Eurasian ice sheet formation promoted by weak AMOC following MIS 3 by Lu Niu, Gregor Knorr, Lars Ackermann, Uta Krebs-Kanzow, Gerrit Lohmann

“…Although temporal and spatial evolution of the EIS during the last glacial cycle has not been well-established, strong evidence indicates the existence of nearly ice-free conditions during Marine Isotope Stage 3 (MIS 3). …”
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Clathrin facilitates the morphogenesis of retrovirus particles. by Fengwen Zhang, Trinity Zang, Sam J Wilson, Marc C Johnson, Paul D Bieniasz

“…These data indicate that a number of retroviruses employ clathrin to facilitate the accurate morphogenesis of infectious particles. We propose a model in which clathrin contributes to the spatial organization of Gag and Pol proteins, and thereby regulates proteolytic processing of virion components during particle assembly.…”
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The role of transaction costs for the optimal supply of carbon sequestration from cover crops in Denmark by Luiza M. Karpavicius, Katarina Elofsson, Gregor Levin, Arezoo Taghizadeh-Toosi

“…The purpose of this study is to investigate how transaction costs affect the cost-effective supply of carbon sequestration from cover crops in Denmark. We develop a model of the optimal adoption of cover crops, accounting for farm spatial heterogeneity and potentially nonlinear transaction costs to adoption. …”
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Geodiversity as a Driver of Soil Microbial Community Diversity and Adaptation in a Mediterranean Landscape by Samuel Pelacani, Maria Teresa Ceccherini, Francesco Barbadori, Sandro Moretti, Simone Tommasini

“…Variable importance provided insight into the controlling factor of geomicrobial spatial distribution. The spatial distribution of the predicted Actinobacteria genera generally follows topographic constraints, mostly altitude. …”
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Multi-scenario Dynamic Simulation and Optimization of Urban Ventilation Environment: A Case Study of Taiyuan Metropolitan Area by Junda HUANG, Yuncai WANG

“…Then, a prediction model is constructed based on the random forest algorithm. …”
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Urban-rural inequality in soil heavy metal health risks: Insights from Baoding, China by Lingzhi Luo, Liang Wang, You Li, Hongying Cao, Yanling Guo, Xiaoyong Liao

“…We used random forest models to predict high-resolution soil metal concentration maps, Positive Matrix Factorization for source apportionment, and spatial exposure models to estimate human health risks under multiple exposure pathways. …”
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A method for mapping hunting occurrence using publicly available, geographic variables by Conner R. Burke, M. Nils Peterson, David T. Sawyer, Christopher E. Moorman, Christopher Serenari, Krishna Pacifici

“…We describe one approach to address this challenge using spatially explicit logistic regression models that accurately predict whether each parcel of land in North Carolina, USA, was hunted using free and publicly available geographic predictors. …”
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Spatio-Temporal Coupling and Forecasting of Construction Industry High-Quality Development and Human Settlements Environmental Suitability in Southern China: Evidence from 15 Provi... by Keliang Chen, Bo Chen, Wanqing Chen

“…Using panel data for 15 southern provinces (2013–2022), we applied the entropy method, coupling coordination model, Dagum Gini coefficient, spatial trend surface analysis, gravity model, and grey forecasting to evaluate current conditions and predict future trends. …”
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Optimal Graph Information Fused Graph Attention Network for Traffic Flow Forecasting by Xing Xu, Luchen Fei, Yun Zhao, Xiaoshu Lü

“…Traffic flow forecasting has complex spatial correlation and time dependence. Most current research models are based on a predefined graph structure with a priori knowledge for prediction, which cannot well extract the hidden spatial relationships in traffic data. …”
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Developing a semi-automated technique of surface water quality analysis using GEE and machine learning: A case study for Sundarbans by Sheikh Fahim Faysal Sowrav, Sujit Kumar Debsarma, Mohan Kumar Das, Khan Mohammad Ibtehal, Mahfujur Rahman, Noshin Tabassum Hridita, Atika Afia Broty, Muhammad Sajid Anam Hoque

“…The predictive framework leverages Google Earth Engine (GEE) and AutoML, utilizing deep learning libraries to create dynamic, adaptive models that enhance prediction accuracy. …”
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Quality Assessment of MRI-Radiomics-Based Machine Learning Methods in Classification of Brain Tumors: Systematic Review by Shailesh S. Nayak, Saikiran Pendem, Girish R. Menon, Niranjana Sampathila, Prakashini Koteshwar

“…Machine learning algorithms such as deep learning networks, support vector machines, random forests, and logistic regression were applied to develop predictive models. Conclusions: The present study indicates high accuracies in glioma classification, outperforming traditional imaging methods and inexperienced radiologists in some cases. …”
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Mapping indicator species of segetal flora for result-based payments in arable land using UAV imagery and deep learning by Caterina Barrasso, Robert Krüger, Anette Eltner, Anna F. Cord

“…Additionally, we investigated the potential of spatial co-occurrence and canopy height heterogeneity to predict the presence of species difficult to detect by UAVs. …”
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TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors by Zhonghuang Wang, Zhonghuang Wang, Zhe Zhang, Dongli Zhao, Dongli Zhao, Zhenglin Du, Bixia Tang, Enhui Jin, Hailong Kang, Wenming Zhao, Yuanguang Meng

“…The analysis elucidates the differences between the two immune repertoires in various aspects and constructs an early screening machine learning model for ovarian tumors based on the characteristics of the immune repertoire.ResultThe finding revealed that patients with malignant ovarian tumors exhibited a reduction in balance, richness, and diversity in their immune repertoires compared to those with benign tumors. …”
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Wind Power Forecasting Based on Multi-Graph Neural Networks Considering External Disturbances by Xiaoyin Xu, Zhumei Luo, Menglong Feng

“…Though much progress has been achieved in deep learning approaches, existing methods cannot effectively decompose and model intertwined spatio-temporal dependencies. Current methods typically treat wind power as a unified signal without explicitly separating inherent patterns from external influences, so they have limited prediction accuracy. …”
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Ionospheric Response to the 24–27 February 2023 Solar Flare and Geomagnetic Storms Over the European Region Using a Machine Learning–Based Tomographic Technique by Ting Li, Dunyong Zheng, Changyong He, Fei Ye, Pengfei Yuan, Yibin Yao, Mengguang Liao, Jian Xie

“…We reconstructed the ionospheric electron density (IED) in Europe to analyze the spatial distribution of ionosphere and its temporal evolution during this period. …”
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Construction and Preliminary Validation of the Children's Academic Readiness Test to Enter Primary School in Afghanistan Country by Mohammad Naeem Rasooli, Ahmad Abedi, Mohammad Ashori

“…All the general model evaluation indices, in line with the predetermined desirable values, suggest the adequacy of the factorial model for the components of numerical reasoning, attention and memory, picture completion, quantitative reasoning, retrieval, associative recall, sentence repetition and counting, visual-spatial reasoning, problem-solving (connecting dots game), and visual-motor skills. …”
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Epigenetic-modification associated hnRNPA3 acts as a prognostic biomarker and promotes malignant progression of HCC by Xufan Cai, Weihui Guo, Fang Wu, Weilang Xu, Tao Ding, Yizhe Diao, Lei Wang, Zhenyuan Qian, Guangyuan Song

“…Logistic regression, receiver operating characteristic curve (ROC), Kaplan–Meier analysis, and nomogram modeling were used to evaluate prognostic values of hnRNPA3 in HCC. hnRNPA3 level in cell subtypes in HCC tumor microenvironment was analysed through spatial transcriptomic. …”
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Mitofilin–mtDNA Axis Mediates Chronic Lead Exposure-Induced Synaptic Plasticity Impairment of Hippocampal and Cognitive Deficits by Lihong Su, Jinchao Hou, Boxuan Wang, Yuqi Li, Xiaodong Huo, Tao Wang, Yuankang Zou, Gang Zheng

“…To elucidate the role and mechanism of the Mitofilin–mtDNA axis in hippocampal synaptic plasticity and learning and memory impairment induced by lead exposure, in this study, both in vivo and in vitro models were subjected to chronic lead exposure. The results showed that the spatial learning and memory abilities of lead-exposed mice were significantly reduced. …”
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Digital mapping of soil organic carbon in the hilly and mountainous landscape of Indian Himalayan region employing machine-learning techniques by Justin George Kalambukattu, Suresh Kumar, Bappa Das, Trisha Roy

“…The pixel wise uncertainty in SOC prediction by different models were also spatially mapped by generating the lower (LL) and upper limits (UL) of the 90% prediction interval. …”
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