Blind Direction-of-Arrival Estimation with Uniform Circular Array in Presence of Mutual Coupling by Song Liu, Lisheng Yang, Shizhong Yang, Qingping Jiang, Haowei Wu

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A Two-Step Reconstruction Framework for Mapping Seamless All-Weather Daily Evapotranspiration Using Thermal Infrared Data by Gengle Zhao, Long Zhao, Lisheng Song, Hua Wu, Qiaoyun Xie, Shaomin Liu, Kejia Xue, Sinuo Tao, Penghai Wu, Lingfeng Zhang

“…ET has conventionally been generated using thermal infrared-based models, cloud contamination of satellite data could prohibit accurate estimates of spatial continuous daily ET. …”
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Landscape Pattern Changes and Ecological Vulnerability Assessment in Mountainous Regions: A Multi-Scale Analysis of Heishui County, Southwest China by Weiqi Gu, Hong Fu, Wen Jin

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Quantitative inversion of integrated hyperspectral and optical remote sensing images to monitor dust distribution in open pit mines by Simin Feng, Jin Zhang

“…The ZY1-02E satellite demonstrates high feasibility and accuracy in AOD inversion, and the results obtained effectively illustrate the spatial distribution of dust pollution. This highlights the potential for aerosol remote sensing inversion using hyperspectral satellite data, providing effective means for regional dust monitoring, and a scientific basis for subsequent development of dust reduction measures.…”
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Classification and spectrum optimization method of grease based on infrared spectrum by Xin Feng, Yanqiu Xia, Peiyuan Xie, Xiaohe Li

“…The results show that this machine learning method can effectively eliminate the interference fringes in the IR spectrum, and complete the feature selection and dimensionality reduction of the high-dimensional spectral data. The 63 kinds of greases exhibit spatial clustering under certain IR spectrum recognition spectral bands, which are linked to characteristic peaks of lubricating greases and improve the recognition accuracy of these greases. …”
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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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An Improved Wavelet Soft-Threshold Function Integrated with SVMD Dual-Parameter Joint Denoising for Ancient Building Deformation Monitoring by Jiaxing Zhao, Houzeng Han, Yang Deng, Youqiang Dong, Jian Wang, Wenjin Chen

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Pooled error variance and covariance estimation of sparse in situ soil moisture sensor measurements in agricultural fields in Flanders by M. G. A. Hendrickx, M. G. A. Hendrickx, J. Vanderborght, J. Vanderborght, P. Janssens, P. Janssens, P. Janssens, S. Bombeke, E. Matthyssen, A. Waverijn, J. Diels, J. Diels

“…These results demonstrate that the common assumption of uncorrelated random errors to determine parameter and model prediction uncertainty is not valid when measurements from sparse in situ soil moisture sensors are used to parameterize soil hydrological models. …”
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Evaluation of Physics‐Based Data Assimilation System Driven by Neutral Density Data From a Single Satellite by Dexin Ren, Jiuhou Lei

“…The data assimilation approach that is based on the self‐consistent upper‐atmosphere model may provide better predictive capability of the coupled thermosphere system. …”
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Multi-modal action recognition via advanced image fusion techniques for cyber-physical systems by Zaiyong Shou, Daoyu Zhu

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Symbiotic relationship and attribution analysis of digitalization in agriculture, rural, and finance: evidence from China by Xiaojuan Yang, Kai Liu, Weiwei Li, Weiwei Li

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The use and integration of airborne laser scanning and satellite time series data in precision forest management for plantations of fast-growing tree species by Gonzalo Gavilan-Acuna, Nicholas C. Coops, Piotr Tompalski, Dominik Roeser, Andrés Varhola

“…Conclusion Despite progresses, challenges remain in refining predictive models, expanding remote sensing applications, and developing tools that translate complex data into field operations. …”
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Analysis of The State of The Tourism Industry in Russia аnd The Direction of Its Development by P. G. Nikolenko, A. M. Terekhov

“…Based on the Box–Jenkins methodology, predictive models were created and medium-term forecasts were calculated for variables characterizing the number of tourist firms and the number of sanatorium-resort organizations and recreation organizations. …”
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Relating natural image statistics to patterns of response covariability in macaque primary visual cortex by Amirhossein Farzmahdi, Adam Kohn, Ruben Coen-Cagli

“…As a result, the model predicts that increasing the size of an image reduces correlations for pairs with overlapping receptive fields and increases correlations for pairs with offset receptive fields. …”
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Estimating Rainfall Erosivity in North Korea Using Automated Machine Learning: Insights into Regional Soil Erosion Risks by Jeongho Han, Seoro Lee

“…Using the optimized model, RE in North Korea was estimated, and the spatial distribution of RE was analyzed using the Kriging interpolation. …”
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Revisiting the distribution and total amount of nitrogen fixation across the Kuroshio by Takuya Sato, Takuhei Shiozaki, Shota Takino, Kiyotaka Hidaka, Tamaha Yamaguchi, Daiki Ito, Daisuke Ambe, Sayaka Sogawa, Takashi Setou, Yugo Shimizu, Taketoshi Kodama, Kazutaka Takahashi

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Optimal control prevents itself from eradicating stochastic disease epidemics. by Rachel Russell, Nik J Cunniffe

“…Using Model Predictive Control, in which the optimisation is performed repeatedly as the system evolves to correct for deviations from the optimal control predictions, improves performance but the level of control calculated at each repeated optimisation is still insufficient. …”
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An Upscaling-Based Strategy to Improve the Ephemeral Gully Mapping Accuracy by Solmaz Fathololoumi, Daniel D. Saurette, Harnoordeep Singh Mann, Naoya Kadota, Hiteshkumar B. Vasava, Mojtaba Naeimi, Prasad Daggupati, Asim Biswas

“…The overall classification error of the upscaling strategy at spatial resolutions of 0.6, 2, 4, 6, 8, and 10 m (Upscaled), as well as that of the direct Sentinel-2 model, were 7.9%, 8.2%, 9.1%, 10.3%, 11.2%, 12.5%, and 14.5%, respectively. …”
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Mapping the Cerrado–Amazon Transition Using PlanetScope–Sentinel Data Fusion and a U-Net Deep Learning Framework by Chuanze Li, Angela Harris, Beatriz Schwantes Marimon, Ben Hur Marimon Junior, Matthew Dennis, Polyanna da Conceição Bispo

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Digital twin-enabled post-disaster damage and recovery monitoring with deep learning: leveraging transfer learning, attention mechanisms, and explainable AI by Umut Lagap, Saman Ghaffarian

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