Numerical Simulation of Storm Surge-Induced Water Level Rise in the Bohai Sea with Adjoint Data Assimilation by Liqun Jiao, Youqi Wang, Dong Jiang, Qingrong Liu, Jing Gao, Xianqing Lv

“…Based on in situ water level measurements from five tide gauge stations, the model simulated the spatial distributions of water levels under different wind stress drag coefficients (<i>C_D</i>) schemes driven by reanalysis wind fields and interpolated wind fields. …”
Get full text

TourismNeuro xLSTM: neuro-inspired xLSTM for rural tourism planning and innovation by Jing Jiang, You Li, You Li

“…Our model integrates an extended Long Short-Term Memory (xLSTM) framework with spatial and temporal attention mechanisms and a memory module, enabling it to capture both short-term fluctuations and long-term trends in tourism data. …”
Get full text

Neutrino Follow-Up Analysis of GRB 221009A with KM3NeT by Palacios González Juan

“…Despite no neutrinos have been detected so far in coincidence with these violent phenomena, numerous models predict neutrino emissions by different mechanisms. …”
Get full text

Human attention-guided visual perception is governed by rhythmic oscillations and aperiodic timescales. by Isabel Raposo, Ian C Fiebelkorn, Jack J Lin, Josef Parvizi, Sabine Kastner, Robert T Knight, Assaf Breska, Randolph F Helfrich

“…Our results extend the rhythmic sampling framework of attention by demonstrating that aperiodic neural timescales predict behavior in a spatially-, context-, and demand-dependent manner. …”
Get full text

Tooth segmentation in panoramic dental radiographs using deep convolution neural network -Insights from subjective analysis by Suvarna Bhat, Gajanan K. Birajdar, Mukesh D. Patil

“…Also, a subjective analysis of the model’s predicted mask output from the practitioners is carried out. …”
Get full text

X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

“…The model predictions are explained using the XAI techniques. …”
Get full text

AI Painting Effect Evaluation of Artistic Improvement with Cross-Entropy and Attention by Yihuan Tian, Shiwen Lai, Zuling Cheng, Tao Yu

“…Among other things, the probabilistic calibration network adjusts the model output so that its predicted probabilities are closer to the probability that the sample truly belongs to the classification. …”
Get full text

Determinants of variation in home range of wild pigs by Peter E. Schlichting, Sarah R. Fritts, John J. Mayer, Philip S. Gipson, C. Brad Dabbert

“…We used mixed‐effects linear‐regression models to assess how allometric effects of body size and environmental variables (temp, elevation, latitude, and rainfall) could be used to predict home range size at a local scale. …”
Get full text

What Helps to Detect What? Explainable AI and Multisensor Fusion for Semantic Segmentation of Simultaneous Crop and Land Cover Land Use Delineation by Saman Ebrahimi, Saurav Kumar

“…Interclass-Grad-CAM provides insights into interactions between land cover classes, revealing complex spatial arrangements, while Spectral-Grad-CAM quantifies the contributions of individual spectral bands to model predictions, optimizing spectral data use. …”
Get full text

Ultradense Dark Matter Halos with Poisson Noise from Stellar-mass Primordial Black Holes by Saeed Fakhry, Javad T. Firouzjaee

“…Conversely, at higher values of n , the predicted UDMH distributions align more closely with single-component models dominated by stellar-mass PBHs. …”
Get full text

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. …”
Get full text

Advanced Deep Learning Algorithms for Energy Optimization of Smart Cities by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Adrianna Piszcz

“…Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) facilitate detailed analysis of spatial and temporal data to better predict energy usage. …”
Get full text

Airborne sound insulation performance of lightweight double leaf walls with different stud types by Hequn Min, Bo Wang, Ting Qu

“…To support performance-based design workflows, this paper presents an analytical model based on sound transmission path decoupling, enabling architects to quickly predict the STL of commonly used lightweight double leaf wall types, including wooden, steel, and acoustical stud constructions. …”
Get full text

Advancing resilient power systems through hierarchical restoration with renewable resources by Mohannad Alhazmi, Peijin Li

“…At the upper level, Graph Neural Networks (GNNs) are used to predict fault locations and optimize network topology by analyzing the spatial and topological features of the grid. …”
Get full text

Numerical Solution of Binary Liquid-Phase Adsorption onto Porocel Clay Using Linear, Freundlich and Langmuir Isotherms by Olaosebikan A. Olafadehan, Alfred A. Susu

“…A computational scheme for the solution of the model equations is presented. The scheme is based on orthogonal collocation for spatial discretization of the resulting set of coupled hyperbolic and parabolic partial differential equations for the macro-and micro-system, respectively. …”
Get full text

Improving imperfect data from health management information systems in Africa using space-time geostatistics. by Peter W Gething, Abdisalan M Noor, Priscilla W Gikandi, Esther A A Ogara, Simon I Hay, Mark S Nixon, Robert W Snow, Peter M Atkinson

“…<h4>Methods and findings</h4>This study has taken the example of presumed malaria in outpatients within the largely incomplete Kenyan HMIS database and has defined a geostatistical modelling framework that can predict values for all data that are missing through space and time. …”
Get full text

PKA regulation of neuronal function requires the dissociation of catalytic subunits from regulatory subunits by Weihong Xiong, Maozhen Qin, Haining Zhong

“…However, the spatiotemporal dynamics of endogenous PKA upon activation remain debated. The classical model predicts that PKA catalytic subunits dissociate from regulatory subunits in the presence of cAMP, whereas a second model proposes that catalytic subunits remain associated with regulatory subunits following physiological activation. …”
Get full text

GAN-based solar radiation forecast optimization for satellite communication networks by Chao Chen, Xin Liu, Shizhong Zhao, Muhammad Bilal

“…In such scenarios, predictions often exhibit spatial texture degradation and distortions in radiation intensity. …”
Get full text

The potential spatiotemporal distribution patterns of Avena nuda and Avena sativa from global perspective provide new insights for the cultivation of commonly cultivated oats by Huanhuan Lu, Yuying Zheng, Ting Zhao, Liuban Tang, Fan Zhang, Wengang Xie

“…This study comprehensively collected the geographic distribution and environmental data of A. nuda and A. sativa from global regions, the ensembled niche and Marxan model were used to predict the potential spatiotemporal distribution and planting pattern of commonly cultivated oats, and further explore the environmental factors that affected the spatial distribution and genetic diversity pattern. …”
Get full text

Application of a GA-BP Neural Network in Accurately Characterizing the Diffusion Range of Groundwater Pollutants by Jiayun JI, Xiao XIAO, Pinlu YANG, Yang LIU, Yahong ZHOU

“…To overcome this, two neural network models—GA-BP and standard BP—were applied to predict Mn2+ concentrations at unsampled locations. …”
Get full text