Increased thermal suitability elevates the risk of dengue transmission across the mid hills of Nepal. by Bipin Kumar Acharya, Laxman Khanal, Meghnath Dhimal

“…In this study, we utilized Moderate Resolution Imaging Spectroradiometer (MODIS) satellite land surface temperature (LST) data (MOD11A2) and a temperature-dependent mechanistic model (R0) to predict the monthly suitability for dengue transmission in Nepal from 2001 to 2020 for both mosquito vectors, Aedes aegypti and Ae. albopictus. …”
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Contribution of relative humidity on aerosol optical depth role in influencing the regionalization pattern of precipitation over West Africa by Ayomide Victor Arowolo, Ayodeji Festus Ologun, Precious Ebiendele, Ayodeji Oluleye

“…Understanding the complex interactions between aerosol optical depth (AOD), relative humidity, and precipitation is essential for improving climate and weather prediction models, particularly in regions like West Africa, which are vulnerable to climate variability. …”
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Flood Hazard Assessment Using Weather Radar Data in Athens, Greece by Apollon Bournas, Evangelos Baltas

“…The GFFG system improves upon the traditional flash flood guidance (FFG) concept by better integrating the weather radar dataset’s spatial and temporal flexibility, leading to increased resolution results. …”
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Color polymorphic carnivores have faster speciation rates by Moritz M. Heuer, Klaus Fischer, Laura Tensen

“…Therefore, other selective forces than spatial niche segregation, such as predator-prey coevolution, may contribute to color polymorphism in wild carnivores.…”
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OSMlanduse a dataset of European Union land use at 10 m resolution derived from OpenStreetMap and Sentinel-2 by Michael Schultz, Hao Li, Zhaoyan Wu, Daniel Wiell, Michael Auer, Zipf Alexander

“…These labels served as training data for a classification model, predicting land use in remaining areas. Country-specific deep learning convolutional neural networks and Sentinel-2 feature space composites of 2020 at 10 m resolution were employed. …”
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A novel dual-branch network for comprehensive spatiotemporal information integration for EEG-based epileptic seizure detection. by Xiaobing Deng

“…Deep learning EEG-based detection methods have made significant progress, but still face challenges such as the underutilization of spatial relationships, inter-individual physiological variability, and sequence intricacies. …”
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Geography is a stronger predictor of diversification of monogenean parasites (Platyhelminthes) than host relatedness in characin fishes of Middle America. by Fernando Alda, Edgar F Mendoza-Franco, William Hanson-Regan, Ruth G Reina, Eldredge Bermingham, MarkE Torchin

“…At this taxonomical scale, host-switching is mediated by the geographical proximity of potential hosts, underscoring the importance of spatial factors in parasite evolution.…”
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RGB-D Image Saliency Detection Based on Multi-branch Backbone Supervised Network by WANG Wei-bing, ZHANG Xiao-zhuo, DENG Qiang

“…Each fusion group is supervised by the upper level fusion result and truth map, and finally the predicted saliency map is obtained iteratively. Experiments on four representative data sets show that compared with the current advanced RGB-D image saliency detection model. …”
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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. …”
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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. …”
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Plausible Vehicle Trajectory Augmentation With Hybrid Machine Learning by Junyeop Park, Hyeonsoo Jang, Byeongju Kang, Yunhyoung Hwang

“…To address this issue, this paper proposes a novel data augmentation technique, integrating Chebyshev polynomial fitting with Hierarchical Density-Based Spatial Clustering of Applications with Noise clustering and Gaussian mixture models to generate robust training data. …”
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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. …”
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Modern deep neural networks for Direct Normal Irradiance forecasting: A classification approach by Muhammad Saud Ul Hassan, Kashif Liaqat, Laura Schaefer, Alexander J. Zolan

“…Existing DNI forecasting models use meteorological factors, which are both challenging to estimate numerically over short prediction windows and expensive to model through data at a sufficiently high spatial and temporal resolution. …”
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Computational image and molecular analysis reveal unique prognostic features of immune architecture in African Versus European American women with endometrial cancer by Sepideh Azarianpour, Sirvan Khalighi, Arpit Aggarwal, Vidya Sankar Viswanathan, Pingfu Fu, Stefanie Avril, Anant Madabhushi

“…Our study findings suggest the need for population-specific risk prediction models for women with endometrial cancer.…”
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Canopy Randomness, Scale, and Stem Size Effects on the Interfacial Transfer Process in Vegetated Flows by Chien‐Yung Tseng, Rafael O. Tinoco

“…The study provides critical insight into water quality management in vegetated channels with improved dissolved oxygen predictions considering vegetation layout as part of the interfacial transfer model.…”
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Boltzmann energy-based image analysis demonstrates that extracellular domain size differences explain protein segregation at immune synapses. by Nigel J Burroughs, Karsten Köhler, Vladimir Miloserdov, Michael L Dustin, P Anton van der Merwe, Daniel M Davis

“…Here, we address this challenge, developing a new methodology for analysing and quantifying image data and its integration with biophysical models. Specifically we fit a binding kinetics model to 2 colour fluorescence data for cytoskeleton independent synapses (2 and 3D) and test whether the observed inverse correlation between fluorophores conforms to size dependent exclusion, and further, whether patterned states are predicted when model parameters are estimated on individual synapses. …”
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A Feature Integration Network for Multi-Channel Speech Enhancement by Xiao Zeng, Xue Zhang, Mingjiang Wang

“…To further enhance the feature integration, we fuse the outputs of these branches using a spatial attention module. The model is trained to predict the complex ratio mask (CRM), thereby improving the quality of the enhanced signal. …”
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A novel deep learning approach to field-road semantic segmentation by Bei Wang, Wenze Wang

“…This study presents a deep learning framework that implements a novel semantic segmentation model designed to segment field-road trajectories, addressing the marked differences in spatial characteristics. …”
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Data-Efficient Sowing Position Estimation for Agricultural Robots Combining Image Analysis and Expert Knowledge by Shuntaro Aotake, Takuya Otani, Masatoshi Funabashi, Atsuo Takanishi

“…The model’s predictions were comparable to those of intermediate-to-advanced practitioners across diverse field conditions. …”
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Earth's future climate and its variability simulated at 9 km global resolution by J.-Y. Moon, J.-Y. Moon, J. Streffing, J. Streffing, J. Streffing, S.-S. Lee, S.-S. Lee, T. Semmler, T. Semmler, M. Andrés-Martínez, M. Andrés-Martínez, J. Chen, E.-B. Cho, E.-B. Cho, J.-E. Chu, C. L. E. Franzke, C. L. E. Franzke, J. P. Gärtner, R. Ghosh, J. Hegewald, J. Hegewald, S. Hong, D.-W. Kim, D.-W. Kim, N. Koldunov, J.-Y. Lee, J.-Y. Lee, Z. Lin, C. Liu, S. N. Loza, W. Park, W. Park, W. Roh, W. Roh, D. V. Sein, D. V. Sein, D. V. Sein, S. Sharma, S. Sharma, D. Sidorenko, J.-H. Son, J.-H. Son, J.-H. Son, M. F. Stuecker, Q. Wang, G. Yi, G. Yi, M. Zapponini, T. Jung, T. Jung, A. Timmermann, A. Timmermann

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