A mineral-strength conversion model based on LIBS technology and rapid batch testing and application of uniaxial compressive strength by Qinghe ZHANG, Xiaorui WANG, Chuanbing WANG, Weiguo LI, Fengqiang GONG, Xinsheng ZHANG, Jingguo LI

Get full text

Pulsed Focused Nonlinear Acoustic Fields from Clinically Relevant Therapeutic Sources in Layered Media: Experimental Data and Numerical Prediction Results by Tamara KUJAWSKA

“…The comparison of the experimental results with those simulated numerically has shown that the model based on the TAWE approach predicts well both the spatial-peak and spatial-spectral pressure variations in the pulsed focused nonlinear beams produced by the transducer used in water for all excitation levels complying with the condition corresponding to weak or moderate source-pressure levels. …”
Get full text

Climate-Driven Invasion Risks of Japanese Beetle (<i>Popillia japonica</i> Newman) in Europe Predicted Through Species Distribution Modelling by Giuseppe Pulighe, Flavio Lupia, Valentina Manente

Get full text

Shared and distinct neural signatures of feature and spatial attention by Anmin Yang, Jinhua Tian, Wenbo Wang, Liqin Zhou, Ke Zhou

“…The debate on whether feature attention (FA) and spatial attention (SA) share a common neural mechanism remains unresolved. …”
Get full text

Reconstructed hyperspectral imaging for in-situ nutrient prediction in pine needles by Yuanhang Li, Yuanhang Li, Jun Du, Jun Du, Chuangjie Zeng, Chuangjie Zeng, Yongshan Wu, Yongshan Wu, Junxian Chen, Junxian Chen, Teng Long, Teng Long, Yongbing Long, Yongbing Long, Yubin Lan, Yubin Lan, Xiaoliang Che, Tianyi Liu, Jing Zhao, Jing Zhao

“…However, its high cost and complexity hinder practical field applications.MethodsTo overcome these limitations, we propose a deep-learning-based method to reconstruct hyperspectral images from RGB inputs for in situ needle nutrient prediction. The model reconstructs hyperspectral images with a spectral range of 400–1000 nm (3.4 nm resolution) and spatial resolution of 768×768. …”
Get full text

Digital Mapping of Soil Equivalent Calcium Carbonate Using Landsat 8 Satellite Images and Environmental Data by Machine Learning Models in Badr Watershed, Kurdistan Province by M. Zarinibahador

“…The present study aimed to digitally map calcium carbonate equivalent using auxiliary environmental variables, Landsat 8 satellite images, and predictive models and to present the best models in the Badr watershed in the south of Qorveh district. …”
Get full text

Toward a Multi‐Representational Approach to Prediction and Understanding, in Support of Discovery in Hydrology by Luis A. De la Fuente, Hoshin V. Gupta, Laura E. Condon

“…Specifically, we test a lumped water‐balance model (GR4J), a data‐based dynamical systems model (LSTM), and a data‐based regression tree model (Random Forest). …”
Get full text

Multi-Task Trajectory Prediction Using a Vehicle-Lane Disentangled Conditional Variational Autoencoder by Haoyang Chen, Na Li, Hangguan Shan, Eryun Liu, Zhiyu Xiang

“…Trajectory prediction under multimodal information is critical for autonomous driving, necessitating the integration of dynamic vehicle states and static high-definition (HD) maps to model complex agent–scene interactions effectively. …”
Get full text

Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan by Ahmed Emara, Sameh A. Kantoush, Mohamed Saber, Tetsuya Sumi, Vahid Nourani, Emad Mabrouk

“…Results indicate that the XGBoost model effectively predicts 2D spatial abrasions in SBTs, achieving an overall accuracy of 0.864, exceeding 0.9 in some sections. …”
Get full text

Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl by Heba Bedair, Heba Bedair, Yehia Hazzazi, Asmaa Abo Hatab, Marwa Waseem A. Halmy, Mohammed A. Dakhil, Mohammed A. Dakhil, Mubaraka S. Alghariani, Mubaraka S. Alghariani, Mari Sumayli, A. El-Shabasy, Mohamed M. El-Khalafy

“…Furthermore, our models predicted that the distribution range of C. cornigera would drop by more than 25% during the next few decades. …”
Get full text

Predicting Multi-Scenario Land Use Changes and Soil Erosion in the Huaihe River Basin Based on Coupled PLUS-CSLE Model by GUO Weiling, XU Liuyang, JIA Jiang, GAO Chang, XIA Xiaolin, WANG Bangwen, ZHANG Jingyu, CHEN Lei, CHEN Yingjian

“…[Methods] Based on the PLUS model and the Chinese Soil Loss Equation (CSLE), the land use patterns in the Huaihe River Basin under three scenarios—natural development, ecological protection, and rapid development—for the year 2030 were simulated, and the future soil erosion patterns in the basin under these three scenarios were predicted. …”
Get full text

A flexible framework for local-level estimation of the effective reproductive number in geographic regions with sparse data by Md Sakhawat Hossain, Ravi Goyal, Natasha K. Martin, Victor DeGruttola, Mohammad Mihrab Chowdhury, Christopher McMahan, Lior Rennert

“…Methods To overcome this challenge, we propose a two-step approach that incorporates existing $$\:{R}_{t}$$ estimation procedures (EpiEstim, EpiFilter, EpiNow2) using data from geographic regions with sufficient data (step 1), into a covariate-adjusted Bayesian Integrated Nested Laplace Approximation (INLA) spatial model to predict $$\:{R}_{t}$$ in regions with sparse or missing data (step 2). …”
Get full text

Learning Dynamic Spatial-Temporal Dependence in Traffic Forecasting by Chaoyu Ren, Yuezhu Li

“…We also replaced the linear layer in the Gated Recurrent unit with a dynamic graph convolution operation to jointly model spatial-temporal correlation. Finally, we propose a temporal fusion layer with multi-scale features to model accurate temporal semantic information from contextual environment with different window sizes, to further obtain accurate prediction results. …”
Get full text

Developing Transferable Fourier Transform Mid-Infrared Spectroscopy Predictive Models for Buffalo Milk: A Spatio-Temporal Application Strategy Analysis Across Dairy Farms by Han Jiang, Peipei Wen, Yikai Fan, Yi Zhang, Chunfang Li, Chu Chu, Haitong Wang, Yue Zheng, Chendong Yang, Guie Jiang, Jianming Li, Junqing Ni, Shujun Zhang

“…Moreover, when using the two application strategies that predicted contemporaneous samples as the model, and adding 30–70% of the samples from the predicted farm, the model application effect can be improved before the robust model has been fully developed.…”
Get full text

A Model for Predicting Short-Term Operating Speeds of Compact Passenger Vehicles on Interchange Ramps Within Urban Expressway Networks by Tingyu Liu, Lanfang Zhang, Genze Li, Yating Wu, Zhenyu Zhao

“…Three models are established: a short-term operating speed model based on a generalized linear model (GLM), a GLM incorporating for spatial correlation (GLMS), and a deep neural network model considering spatial correlation (DNNS). …”
Get full text

A novel telomere-associated genes signature for the prediction of prognosis and treatment responsiveness of hepatocellular carcinoma by Kuo Kang, Hui Nie, Weilu Kuang, Xuanxuan Li, Yangying Zhou

“…Conclusion In this study, we developed a novel prognostic model comprising 18 TRGs for HCC, which exhibited remarkable accuracy in predicting HCC patients’ prognosis. …”
Get full text

Aggregated Housing Price Predictions with No Information About Structural Attributes—Hedonic Models: Linear Regression and a Machine Learning Approach by Joanna Jaroszewicz, Hubert Horynek

Get full text

Spatial navigation entropy suggests allocentric dysfunction in PPPD by Felipe Faúndez, Camilo Arévalo-Romero, Karen Villarroel, Claudio Lavín, Kevin Alarcón, Kevin Alarcón, Gustavo Vial, Francisco Artus, Pablo Billeke, Paul H. Delano, Paul H. Delano, Paul H. Delano, Hayo A. Breinbauer, Hayo A. Breinbauer

“…VR intolerance was highest in PPPD patients, followed by vestibular controls, with healthy volunteers showing the lowest discomfort.DiscussionOur findings suggest that PPPD involves deficits in allocentric spatial navigation, likely due to predictive coding errors and impaired internal model updating, rather than sensory input dysfunction. …”
Get full text

A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

“…TCNs can capture long-range temporal dependencies well, while the GCN model has complex spatial relationships and enhanced the features for making yield predictions. …”
Get full text

Development of a Weighted Average Ensemble Model for Predicting Officially Assessed Land Prices Using Grid Map Data and SHAP by Surin Im, Kangmin Kim, Geunhee Lee, Hoi-Jeong Lim

“…This study proposes a weighted average ensemble model to predict the Officially Assessed Land Price in Sejong City, South Korea, using 500m <inline-formula> <tex-math notation="LaTeX">$\times 500$ </tex-math></inline-formula>m grid-based spatial data. …”
Get full text