Leveraging Next‐Generation Satellite Remote Sensing‐Based Snow Data to Improve Seasonal Water Supply Predictions in a Practical Machine Learning‐Driven River Forecast System by Sean W. Fleming, Karl Rittger, Catalina M. Oaida Taglialatela, Indrani Graczyk

“…We test a new space‐based remote sensing product, spatially and temporally complete (STC) MODSCAG fractional snow‐covered area (fSCA), as input for the Natural Resources Conservation Service (NRCS) operational US West‐wide WSF system. fSCA data were considered alongside traditional SNOTEL predictors, in both statistical and AI‐based NRCS operational hydrologic models, throughout the forecast season, in four test watersheds (Walker, Wind, Piedra, and Gila Rivers in California, Wyoming, Colorado, and New Mexico). …”
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A Novel Ionospheric Inversion Model: PINN‐SAMI3 (Physics Informed Neural Network Based on SAMI3) by Jiayu Ma, Haiyang Fu, J. D. Huba, Yaqiu Jin

“…The model incorporates the governing equations of the ionospheric physical model SAMI3 into the neural network to reconstruct the temporal‐spatial distribution of ionospheric plasma parameters. …”
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Spatial and temporal epidemiology of SARS-CoV-2 virus lineages in Teesside, UK, in 2020: effects of socio-economic deprivation, weather, and lockdown on lineage dynamics by Moss, E.D., Rushton, S.P., Baker, P., Bashton, M., Crown, M.R., dos Santos, R.N., Nelson, A., O’Brien, S.J., Richards, Z., Sanderson, R.A., Yew, W.C., Young, G.R., McCann, C.M., Smith, D.L.

“…The relationships between positive tests and covariates varied greatly between lineages, likely due to the strong heterogeneity in their spatial and temporal distributions. Cases during the second wave appeared to be higher in areas that recorded fewer first-wave cases, however, an additional model showed the number of first-wave cases was not predictive of second-wave cases. …”
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Efficient solving of Schrödinger equation using deep convolutional neural network model with an attention mechanism and transfer learning by Ziyi Zhao, Shishun Zhao, Mingjun Zhou, Yujun Yang

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Temporal Forecasting with a Bayesian Spatial Predictor: Application to Ozone by Yiping Dou, Nhu D. Le, James V. Zidek

“…One of these approaches adapts a multivariate method originally designed for spatial prediction. The second is based on a state-space modeling approach originally developed and used in a case study involving one week in Mexico City with ten monitoring sites. …”
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Multi-omics approach reveals the impact of prognosis model-related genes on the tumor microenvironment in medulloblastoma by Dongming Han, Dongming Han, Xuan Chen, Xuan Chen, Xin Jin, Jiankang Li, Dongyang Wang, Dongyang Wang, Ziwei Wang

“…This study aimed to develop a TME-associated risk score(TMErisk) model using RNA sequencing data to predict patient outcomes and elucidate biological mechanisms.MethodsRNA sequencing data from 322 Tiantan and 763 GSE85217 MB samples were analyzed. …”
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<i>Solanum macrocarpon</i> L. Ethanolic Leaf Extract Exhibits Neuroprotective and Anxiolytic Effects in Scopolamine-Induced Amnesic Zebrafish Model by Ion Brinza, Corina Guliev, Ibukun Oluwabukola Oresanya, Hasya Nazli Gok, Ilkay Erdogan Orhan, Lucian Hritcu

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A Global Irradiance Prediction Model Using Convolutional Neural Networks, Wavelet Neural Networks, and Masked Multi-Head Attention Mechanism by Walid Mchara, Lazhar Manai, Mohamed Abdellatif Khalfa, Monia Raissi, Salah Hannechi

“…However, traditional models struggle to capture the complex spatial and temporal dependencies in irradiance data, limiting prediction accuracy under varying weather conditions. …”
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Multispheroidal model of magnetic field of uncertain extended energy-saturated technical object by B. I. Kuznetsov, T. B. Nikitina, I. V. Bovdui, K. V. Chunikhin, V. V. Kolomiets, B. B. Kobylianskyi

“…Coordinates of the geometric location and magnitudes of spatial extended spheroidal harmonics of spheroidal sources of multispheroidal model of magnetic field calculated as magnetostatics geometric inverse problems solution in the form of nonlinear minimax optimization problem based on near field measurements for prediction far extended technical objects magnetic field magnitude. …”
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Short-term displacement prediction for newly established monitoring slopes based on transfer learning by Yuan Tian, Yang-landuo Deng, Ming-zhi Zhang, Xiao Pang, Rui-ping Ma, Jian-xue Zhang

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Integrated multi-omics analysis reveals the functional and prognostic significance of lactylation-related gene PRDX1 in breast cancer by Qinqing Wu, Qinqing Wu, Heng Cao, Jiangdong Jin, Dongxu Ma, Yixiao Niu, Yixiao Niu, Yanping Yu, Yanping Yu, Xiang Wang, Yiqin Xia

“…The prognostic model constructed based on the gene expression profile of PRDX1-positive monocytes demonstrated high accuracy in predicting patient survival in both the training and validation cohorts. …”
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Predicting changes in maximum temperatures in the mid-future period in Sistan and Baluchestan under SSP scenarios by abdolreza kashki, ghorban jafari

“…IDW interpolation in GIS was used to map spatial temperature changes. Paired-sample t-tests evaluated differences between baseline and mid-future periods.Finding: The CanESM5 model performed best in predicting temperature changes. …”
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MaxEnt Modeling of Future Habitat Shifts of <i>Itea yunnanensis</i> in China Under Climate Change Scenarios by Jinxin Zhang, Xiaoju Li, Suhang Li, Qiong Yang, Yuan Li, Yangzhou Xiang, Bin Yao

“…The optimized model (RM = 3.0, FC = QHPT) significantly reduced overfitting risk (ΔAICc = 0) and achieved high prediction accuracy (AUC = 0.968). …”
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Rapid Simulation of Floods by Considering the Spatial and Temporal Characteristics of Inundation by Rukai Wang, Jijian Lian, Ximin Yuan, Fuchang Tian, Kuang Li, Zhanyou Liu

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Ruxolitinib-dependent reduction of seizure load and duration is accompanied by spatial memory improvement in the rat pilocarpine model of temporal lobe epilepsy by Andrew Carrel, Eleonora Napoli, Kathryn Hixson, Jessica Carlsen, Yasmin Cruz Del Angel, Dana Strode, Nicolas Busquet, Vijay Kumar, Michael F. Wempe, Shelley J. Russek, Amy R. Brooks-Kayal

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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…As such, the study proposes a combined prediction model. This model integrates data decomposition, dimensionality reduction, deep learning, and optimization techniques.MethodsThe model uses the variational mode decomposition (VMD) method to break down the ship’s roll motion data into components at different scales. …”
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The Historical Evolution and Significance of Multiple Sequence Alignment in Molecular Structure and Function Prediction by Chenyue Zhang, Qinxin Wang, Yiyang Li, Anqi Teng, Gang Hu, Qiqige Wuyun, Wei Zheng

“…Multiple sequence alignment (MSA) has evolved into a fundamental tool in the biological sciences, playing a pivotal role in predicting molecular structures and functions. With broad applications in protein and nucleic acid modeling, MSAs continue to underpin advancements across a range of disciplines. …”
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Machine Learning-Enhanced 3D GIS Urban Noise Mapping with Multi-Modal Factors by Jianping Pan, Yuzhe He, Wei Ma, Shengwang An, Lu Li, Dan Huang, Dunxin Jia

“…Most existing noise prediction models fail to fully account for three-dimensional (3D) spatial information and a wide range of environmental factors. …”
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A data-driven reduced-order model for fast prediction of resonant acoustic flow under vertical vibration based on secondary decomposition by Yuqi Gao, Ning Ma, Shifu Zhu, Pengchao Zhang, Hongxing Liu, Zhongyuan Xie

“…Accurate dimensionality reduction models are crucial for constructing real-time computational digital twin systems for process equipment. …”
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Advancements in Technologies and Methodologies of Machine Learning in Landslide Susceptibility Research: Current Trends and Future Directions by Zongyue Lu, Genyuan Liu, Zhihong Song, Kang Sun, Ming Li, Yansi Chen, Xidong Zhao, Wei Zhang

“…This paper provides a comprehensive overview of the diverse challenges encountered by machine learning models in landslide susceptibility assessment, encompassing aspects such as model selection, the formulation of evaluation index systems, model interpretability, and spatial heterogeneity. …”
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