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. …”
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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. …”
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Potential of EnMAP Hyperspectral Imagery for Regional-Scale Soil Organic Matter Mapping by Yassine Bouslihim, Abdelkrim Bouasria

“…While these results are promising, this study identified limitations in the ability of PLSR to extrapolate predictions beyond the sampled areas, suggesting the need to explore non-linear modeling approaches. …”
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Assessment of Normalized Difference Vegetation Index based vegetation dynamics for monitoring rice growth and yield forecasting in the Mahaweli H region of Sri Lanka by Ganewatte Visal P., Abannikov Victor N., De Seram Osanda L., Wijayaratne Bimasha S., Vichare Aniket S.

“…In the regions of Talawa, Meegalewa, and Galnewa, negative correlation coefficients were recorded. Yield forecasting models developed for the subregions with positive correlations demonstrated high accuracy, confirming the potential of Normalized Difference Vegetation Index as a reliable indicator for rice yield prediction. …”
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Transformer-Based Student Engagement Recognition Using Few-Shot Learning by Wejdan Alarefah, Salma Kammoun Jarraya, Nihal Abuzinadah

“…In this research, we propose an innovative FSL model that employs a prototypical network with the vision transformer (ViT) model pre-trained on a face recognition dataset (e.g., MS1MV2) for spatial feature extraction, followed by an LSTM layer for temporal feature extraction. …”
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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. …”
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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. …”
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Forecast of oil and gas reservoirs of the Sea of Okhotsk based on interpretation processing of seismic material by А. К. Shatyrov

“…Solving problems of forecasting hydrocarbon deposits through the development of a structural and technological scheme for prospecting and evaluation of a geological and geophysical model to identify images of oil and gas deposits.Materials and methods. …”
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The Analysis of Downscaling Results of Weather Parameters for Iran Future by Maryam Bayatvarkeshi, rojin fasihi

“…The purpose of this research is to predict the weather parameters changes under different scenario of LARS- WG downscaling model over the country in future. 2-Materials and Methods In this study, the effect of climate change on temperature, solar radiation and precipitation, as the most important parameters of country in future years, were evaluated. …”
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Carbon dioxide pipelines are disproportionally located in marginalized communities in the United States by Julia A. Davis, Nafiseh Salehi, Liqing Li, Majid Shafiee-Jood

“…Using census-tract demographic data and pipeline spatial data, we applied LASSO regression to identify key demographic variables and incorporated them into binary logistic regression models to uncover if the locations of, and disadvantages associated with, carbon dioxide pipelines are equally distributed among different demographics. …”
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MPAR-RCNN: a multi-task network for multiple person detection with attribute recognition by S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, Jayashree Shetty, Praveen Gurunath Bharathi

“…This study introduces an innovative MTL framework designed to incorporate Multi-Person Attribute Recognition (MPAR) within a single-model architecture. Named MPAR-RCNN, this framework unifies object detection and attribute recognition tasks through a spatially aware, shared backbone, facilitating efficient and accurate multi-label prediction. …”
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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. …”
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Developing an ensemble machine learning framework for enhanced climate projections using CMIP6 data in the Middle East by Younes Khosravi, Taha B.M.J. Ouarda, Saeid Homayouni

“…The results indicate that Stacking-EML not only significantly improves prediction accuracy compared to individual models and traditional CMIP6 outputs but also enhances climate projections by integrating multiple ML models, offering more reliable, regionally refined forecasts. …”
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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. …”
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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. …”
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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

“…The resulting complete set can then be used to define treatment burdens for presumed malaria at any level of spatial and temporal aggregation. Validation of the model has shown that these burdens are quantified to an acceptable level of accuracy at the district, provincial, and national scale.…”
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Research on an Ecological Sensitivity Evaluation of Mountain-Type National Parks Under Multi-Modal Optimization: A Case Study of Shennongjia, China by Xingyu Zhou, Huan Huang, Shi Dai, Duanya Zheng, Jie Zhao

“…The results demonstrate that the refined data structure enhances terrain coupling accuracy by transitioning from “Vegetation Type—Runoff Coefficient” to “Vegetation Density—Runoff Coefficient” conversions, with the optimized model exhibiting superior sensitivity in spatial element identification. …”
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Sestrin2 alleviates cognitive impairment via inhibiting hippocampus ferroptosis in cigarette smoke-induced chronic obstructive pulmonary disease by Da-Wei Zhang, Ming-Ming Yang, Meng-Xi Zhou, Yuan-Yuan Wei, Lei Hu, Mei Hong, Ting-Ting Chen, Xiao-Min Wang, Yi-Chuan Ding, Chuan-Sheng Wei, Fang Li, Wen Chen, Jia-Ying Kang, Jing-Jing Ye, Guang-He Fei

“…Long-term CS exposure caused hippocampus impairment, leading to spatial and working memory impairments in COPD model mice. …”
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Seasonal Early Warning of Impacts of Harmful Algal Blooms on Farmed Shellfish in Coastal Waters of Scotland by O. Stoner, T. Economou, A. R. Brown

“…Through a comprehensive yearly prediction experiment, we demonstrate considerable skill in predicting the impact of unseen HAB seasons at a regional level.…”
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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. …”
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