Advances on the Links Between Turbulent and Submeso‐ to Mesoscales During EUREC4A by E. Gauvrit, M.‐N. Bouin, J.‐M. Delouis, F. Boulanger

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Ring-like Bright Monster Waves in Variable-Coefficient Partially Nonlocal Coupled NLS Equations with Directional Diffraction and External Perturbations in (3+1)D by Emmanuel Yomba

“…Partially nonlocal (PNL) variable-coefficient nonlinear Schrödinger equations (NLSEs) represent a significant area of study in mathematical physics and quantum mechanics, particularly in scenarios where potential and coefficients vary spatially or temporally. The (3+1)-dimensional partially nonlocal (PNL) coupled nonlinear Schrödinger (NLS) model, enriched with different values of two transverse diffraction profiles and subjected to gain or loss phenomena, undergoes dimensional reduction to a (2+1)-dimensional counterpart model, facilitated by a conversion relation. …”
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Deep Ultraviolet Excitation Photoluminescence Characteristics and Correlative Investigation of Al-Rich AlGaN Films on Sapphire by Zhe Chuan Feng, Ming Tian, Xiong Zhang, Manika Tun Nafisa, Yao Liu, Jeffrey Yiin, Benjamin Klein, Ian Ferguson

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Enhancing flood susceptibility mapping in Sana’a, Yemen with random forest and eXtreme gradient boosting algorithms by Yahia Alwathaf, Ahmed M. Al-Areeq, Yousef A. Al-Masnay, Ali R. Al-Aizari, Nabil M. Al-Areeq

“…Both models demonstrated high accuracy in predicting flood-prone areas, with RF achieving an accuracy of 92% and XGBoost slightly outperforming it with an accuracy of 94%. …”
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Pathways to Turbulent Dissipation in a Submarine Canyon by Charlotte Bellerjeau, Matthew H. Alford, Arnaud Le Boyer, Giovanni Dematteis, Alberto Naveira Garabato, Gunnar Voet, Nicole Couto, Bethan L. Wynne‐Cattanach

“…Fluxes from both methods agree within a factor of 3 with dissipation estimates from a finescale parameterization which is often used in climate‐scale ocean models. Coarse graining predicts 68% of energy fluxing to dissipation from frequencies lower than 8cpd, while the weakly nonlinear method predicts 34%. …”
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OTHERWORLDLY LANDSCAPES IN THE HISTORIC TEXT TRUYỀN KỲ MẠN LỤC BY NGUYEN DU by Van Hoa Pham

“…By applying landscape theory and model-setting methods, the paper analyzes and compares the richness and uniqueness of spatial movement types that create otherworldly landscapes as a hallmark of supernatural stories. …”
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Assessing Rainfall Erosivity with Artificial Neural Networks for the Ribeira Valley, Brazil by Reginald B. Silva, Piero Iori, Cecilia Armesto, Hugo N. Bendini

“…Soil loss is one of the main causes of pauperization and alteration of agricultural soil properties. Various empirical models (e.g., USLE) are used to predict soil losses from climate variables which in general have to be derived from spatial interpolation of point measurements. …”
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A novel method for grading urban socio-economic development levels based on NTL data and Landsat data by Xiang Hua, Jiehai Cheng, Yuke Meng, Rongji Luo

“…Experimental results demonstrate that the proposed hybrid model achieves strong performance in predicting urban socio-economic development levels, with an accuracy of 86.2%. …”
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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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Convolution Representation of Traveling Pulses in Reaction-Diffusion Systems by Satoshi Kawaguchi

“…Additionally, we consider the traveling pulses in the kernel-based Turing model. The stability of the spatially homogeneous state and most unstable wave number are examined. …”
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THE NEW “NORMAL”: TRANSFORMATION OF THE STEREOTYPE OF WORK USING ICTS AND THE OPPORTUNITIES FOR MOTIVATION DURING THE COVID-19 PANDEMIC by M. Angelova, S. Raychev

“…Background: The new reality is accelerating the business model transformation at a faster pace than ever before to ensure existential survival in a crisis for which no one was prepared. …”
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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. …”
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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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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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The Effects of Climate Change on Human Behavior and Stress by Mitra Sadat Fathifard, Fateme Javid, Abbas Rahdan

“…All processes and data analysis in GIS environment were assessed using the Inverse Distance Weighting (IDW) statistical model, which predicts the spatial structure of unknown points based on the correlation between measured points. …”
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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. …”
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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. …”
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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. …”
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