A Meteorology Based Particulate Matter Prediction Model for Megacity Dhaka by Sadia Afrin, Mohammad Maksimul Islam, Tanvir Ahmed

“…Models also exhibit strong predictive power in forecasting PM levels of two other CAMSs in Dhaka. …”
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External validation of risk prediction models for post-stroke mortality in Berlin by Jessica L Rohmann, Tobias Kurth, Heinrich J Audebert, Marco Piccininni, Lukas Reitzle

“…We aimed to assess the performance of two prediction models for post-stroke mortality in Berlin, Germany.Design We used data from the Berlin-SPecific Acute Treatment in Ischaemic or hAemorrhagic stroke with Long-term follow-up (B-SPATIAL) registry.Setting Multicentre stroke registry in Berlin, Germany.Participants Adult patients admitted within 6 hours after symptom onset and with a 10th revision of the International Classification of Diseases discharge diagnosis of ischaemic stroke, haemorrhagic stroke or transient ischaemic attack at one of 15 hospitals with stroke units between 1 January 2016 and 31 January 2021.Primary outcome measures We evaluated calibration (calibration-in-the-large, intercept, slope and plot) and discrimination performance (c-statistic) of Bray et al’s 30-day mortality and Smith et al’s in-hospital mortality prediction models. …”
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Spatial multilevel modelling male partners’ influence on women’s modern contraceptive use: a study in Angola and Zambia by Kabeya Clement Mulamba

“…This paper discusses the application of spatial multilevel modelling, which incorporates two levels of information based on the nature of the data available. …”
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A novel cancer-associated membrane signature predicts prognosis and therapeutic response for lung adenocarcinoma by Biao Tu, Jun Wu, Wei Zhang, Haitao Tang, Tenghui Dai, Bingfeng Xie

“…A distinct LUAD-enriched epithelial cluster (Epi_c0) exhibiting hypoxic and EMT signatures was identified. 35 cancer-specific membrane proteins were defined, several of which, including TSPAN8, BACE2, and COX16, showed strong spatial localization within the tumor regions. LCaMPS, a 9-membrane gene-based prognostic model, stratified patient prognosis and predicted 5- and 10-year survival rates with high accuracy. …”
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Generalizable Storm Surge Risk Modeling by Mahlon Scott, Hsin-Hsiung Huang

“…Inspired by principles of robust statistical modeling, this paper introduces a Bayesian hierarchical model integrated with Gaussian processes to account for spatial random effects. …”
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Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak by Alvin Garcia, Sydney Liu, Xiaodi Du, Max Curie, Azarakhsh Jalalvand, Peter Steiner, Egemen Kolemen

“…This improvement highlights the model’s enhanced predictive accuracy for measured images from the validation set. …”
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Wide-Area Active Frequency Control with Multi-Step-Size MPC by Yan Xie, Shiying Ma, Jiakai Shen, Xiaojun Tang, Jianmiao Ren, Liwen Zheng

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Prediction of Surface Water Temperature and Its Spatial-Temporal Variation Characteristics of 11 Main Lakes in Yunnan–Guizhou Plateau by Shanshan Xu, Kun Yang, Xiaolu Zhou, Jie Zhang, Chenghao Yang, Yi Luo

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Tuberculosis disease burden in China: a spatio-temporal clustering and prediction study by Jingzhe Guo, Ce Liu, Fang Liu, Erkai Zhou, Runxue Ma, Ling Zhang, Bin Luo

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Actual and Predictive Transport Modeling of Fluoride Contamination of the Sfax-Agareb Coastal Aquifer in the Mediterranean Basin by Samira Melki, Amina Mabrouk El Asmi, Mohamadou Ould Baba Sy, Moncef Gueddari

“…This study, using numerical modeling, gives new insights for short- and medium-term prediction of eventual fluoride concentrations in the saturated zone of the Sfax-Agareb aquifer.…”
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An Improved YOLOv5 Model for Lithographic Hotspot Detection by Mu Lin, Wenjing He, Jiale Liu, Fencheng Li, Jun Luo, Yijiang Shen

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A Review of Enhancement Techniques for Cone Beam Computed Tomography Images by Hassn Mazin Al-alaaf, Mohammed Sabah Jarjees

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Predictive modeling of soil profiles for precision agriculture: a case study in safflower cultivation environments by Megha Sharma, Shailendra Goel, Ani A. Elias

“…The robustness, versatility, and predictive ability of two statistical learning models in correctly classifying the soil profile to clusters were tested. …”
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A monthly sub-national Harmonized Food Insecurity Dataset for comprehensive analysis and predictive modeling by Melissande Machefer, Michele Ronco, Anne-Claire Thomas, Michael Assouline, Melanie Rabier, Christina Corbane, Felix Rembold

“…The scientific community can also leverage the HFID to develop data-driven predictive models, enhancing the capacity to forecast and prevent future food crises.…”
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Modeling inter-city population flows: a Deep Radiation model with multisource geographic features by Jingjing Liu, Lei Xu, Le Ma, Chao Wang, Nengcheng Chen

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Establishment of agricultural drought monitoring at different spatial scales in southeastern Europe by Andreja SUŠNIK, Tjaša POGAČAR, Gregor GREGORIČ, Jožef ROŠKAR, Andrej CEGLAR

“…In the study two specific products designed for regional scale are described: preliminary maps of the SPI (Standardized Precipitation Index) and products generated by implementation of numerical weather prediction model. It seems to be a lot of potential in both products for a first overview of key meteorological parameters in the region. …”
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Evaluation of CMIP Earth System Models on Root Biomass Simulation by Ke ZHOU, Youqi SU, Yu ZHANG, Minhong SONG, Tongwen WU, Linfeng YANG, Xizhao WANG, Tianya LI

“…Roots play an important role in the carbon cycle of ecosystems.The Earth System Models （ESMs） of the Coupled Model Intercomparison Project （CMIP） have been widely used to simulate and predict root biomass.In this paper， the spatial distribution， dynamic change， and comparison with observed values of root biomass of 14 ESMs simulated historical experiments were analyzed.The results showed that： （1） The global distribution of multi-year average from 1850 to 2005 of root biomass indicated that 7 ESMs had maximum or minimum values， while the rest ESMs showed that root biomass was higher in the middle and high latitudes of the equator and the northern hemisphere.The root biomass distribution at different latitudes showed that 40°S is also one of the high value areas； （2） The simulation results from 1995 to 2005 are compared with the site observation data （1990 -2010） in different climatic zones by using SS index， the result showed deviations are relatively large but the simulation effect of temperate zone is slightly better than frigid zone and tropical zone.On the global scale， BCC-CSM2-MR is the best simulated ESM； （3） In the Qinghai-Xizang Plateau， ESMs can reasonably simulate the seasonal variation over the years 1850 to 2005 of root biomass， but the relationship between interannual variation of the simulated root biomass and the meteorological factors （temperature， precipitation） by different ESMs is different.In order to conduct more precise and in-depth research and analysis， in addition to improving the model， it is also necessary to improve the collection of observational data.…”
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Spatial and Temporal Changes in Nutrient Source Contribution in a Lowland Catchment Within the Baltic Sea Region Under Climate Change Scenarios by Damian Bojanowski, Paulina Orlińska‐Woźniak, Paweł Wilk, Ewa Jakusik, Ewa Szalińska

“…To track spatial and seasonal changes of total nitrogen and phosphorus for the Wełna River (central Poland), we used climate change data and the SWAT model. …”
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Application of Multi-Scale Geological Modeling Technology in Sweet Spot Prediction of Shale Oil Reservoirs by HU Laidong, HUO Hanyong, GUAN Qianqian, TANG Caixia, TAO Ji, ZHANG Yuxuan

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Impact of Multiscale Heterogeneous Sediments and Boundary Conditions on Dispersivity Spatial Variations by Ziqi Ma, Linlin Qi, Zhenxue Dai, Zhijie Yang, Yue Ma, Dayong Wang, Kenneth C. Carroll, Mohamad Reza Soltanian

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