Hyperspectral Reconstruction Method Based on Global Gradient Information and Local Low-Rank Priors by Chipeng Cao, Jie Li, Pan Wang, Weiqiang Jin, Runrun Zou, Chun Qi

“…First, to improve the prior model’s efficiency in utilizing information of different frequencies, we design a gradient sampling strategy and training framework based on decision trees, leveraging changes in the loss function gradient information to enhance the model’s predictive capability for data of varying frequencies. …”
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Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Our proposed model incorporates a single RNN layer, complemented by essential supporting layers, which contributes to a reduction in complexity and a decrease in the number of parameters. …”
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SAR Estimations in a Classroom with Wireless Computers by Norton Escopelli Soares, Giovani Bulla, Claudio E. Fernández-Rodríguez, Alvaro A. A. de Salles

“…Abstract This research provides detailed examination of the peak spatial Specific Absorption Rate (psSAR) in different age students in a classroom with wireless computers. …”
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Evaluation of Near‐Surface Specific Humidity and Air Temperature From Atmospheric Infrared Sounder (AIRS) Over Oceans by Weikang Qian, Yixin Wen, Shang Gao, Zhi Li, Jesse Kisembe, Haotong Jing

“…The Atmospheric Infrared Sounder (AIRS) provides global estimates of near‐surface AT and SH estimates, with continuous improvements in accuracy leading to significant reductions in error rates. However, existing studies have not systematically validated AIRS near‐surface products in both temporal and spatial perspectives, especially over oceans. …”
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Spatio-temporally explicit reconstruction of upper range limit of trees since the LGM over the Tibetan Plateau by Jinfeng Xu, Xiaoyi Wang, Xianyong Cao, Eryuan Liang, Lin Zhang, Xiangjin Shen, Tao Wang

“…This reconstruction was developed by integrating multi-satellite-derived high-resolution map, in situ dendrochronological observation and paleoclimate dataset into a novel climate-driven predictive model. The model accounts for climate change effects, such as growing season temperatures and local climatic stressors, as well as migration time-lags. …”
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Long-term exposure to PM2.5 and cardiorespiratory mortality: an ecological small-area study in five cities in Colombia by Diana Marín, Víctor Herrera, Juan Gabriel Piñeros-Jiménez, Oscar Alberto Rojas-Sánchez, Sonia C. Mangones, Yurley Rojas, Jhon Cáceres, Dayana M. Agudelo-Castañeda, Néstor Y. Rojas, Luis Carlos Belalcazar-Ceron, Jonathan Ochoa-Villegas, María Leonor Montes-Mejía, Veronica Maria Lopera-Velasquez, Sanit María Castillo-Navarro, Alexander Torres-Prieto, Jill Baumgartner, Laura A. Rodríguez-Villamizar

“…Cardiorespiratory mortality spatially clustered in some Colombian cities and was associated with long-term exposure to PM2.5 in urban areas where the LUR models had the highest predictive accuracy. …”
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INNOVATION-ORGANIZATIONAL AND COMMUNICATIVE-ECONOMIC PARADIGM OF MANAGEMENT: A METHODOLOGICAL FOUNDATION FOR SUSTAINABLE DEVELOPMENT IN THE ARCHITECTURE AND CONSTRUCTION SECTOR by Анастасія Михалко, Руслан Кубанов, Дмитро Макатьора

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The Impact of Land Circulation on Common Prosperity in the Digital Economy Context by Cong Xu, Feng Wu, Jingran Lin, Yie-Ru Chiu

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The role of automated surface water distribution systems in energy-saving agriculture: A case study from central Iran’s Arid Plateau by Dorsa Rahparast, Seied Mehdy Hashemy Shahdany, Ronny Berndtsson

“…A hydraulic simulation model and a centralized Model Predictive Control approach were used to analyze the existing system and propose a recovery plan. …”
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Advancing plant biomass measurements: Integrating smartphone‐based 3D scanning techniques for enhanced ecosystem monitoring by Peter Dietrich, Melanie Elias, Peter Dietrich, Stanley Harpole, Christiane Roscher, Jan Bumberger

“…Additionally, results indicate significant effects of plant species richness and fertilization on biomass production and volume estimates, underscoring the potential for high‐resolution temporal and spatial analyses of vegetation dynamics. This method's innovation extends beyond traditional practices with implications for future integration of AI to automate species segmentation, ecological trait extraction and predictive modelling. …”
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An annual 30 m cultivated-pasture dataset of the Tibetan Plateau from 1988 to 2021 by B. Han, J. Bi, S. Tao, T. Yang, Y. Tang, M. Ge, H. Wang, Z. Jin, J. Dong, Z. Nan, J.-S. He, J.-S. He

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The glycolytic characteristics of hepatocellular carcinoma and its interaction with the microenvironment: a comprehensive omics study by Dan Chen, Dandan Lin, Huling Li, Jiandong Yang, Lei Liu, Hanyuan Zhang, Dandan Tang, Kai Wang

“…Through public data integration, 17 glycolysis-related DEGs were identified and 101 predictive models were constructed using machine learning. …”
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How does academic self-efficacy influence learning anxiety and academic burnout in Chinese characters learning among international students in China? by Yang Lin

“…BackgroundThe interplay between learning self-efficacy, anxiety, and burnout has been extensively documented in English as a Second Language (ESL) education. However, Chinese character learning—a uniquely complex task involving visual–spatial processing, stroke order mastery, and radical decomposition—presents distinct cognitive and affective challenges. …”
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Rhetoric of allegorical formation in Maqamat Ayed Al-Qarni by Salih Mala Aziz  ,  Yahya Mahmoud Ahmed

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Toward 6G: Deep GRU and RNN Empowered MVDR and LCMV Adaptive Beamformers for IRS-Aided Wireless Environments by D. L. Sharini, Ravilla Dilli, M. Kanthi, G. D. Goutham Simha

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‘Out of the Tropics’ Sheds Light on Latitudinal Gradients in Clade Ages of Climbers, China by Mingfei Zhao, Hongbo Li, Yuhang Wang, Yuan Jiang, Muyi Kang, Kaixiong Xing

“…A dataset including 2487 climbing species was used to quantify geographical patterns of MFA across China. Spatial regression analyses with information‐theoretical multi‐model selections were performed to estimate the importance of climatic variables. …”
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Improving the estimation precision of the mapping of groundwater salinity by employing the Indicator Kriging Technique by Sandeep Ravish, Baldev Setia, Surinder Deswal, Vishal Puri, Bhupender Singh, Kuldeep Sharma, Ashok Kumar Yadav

“…By using nonlinear and nonparametric techniques with electrical conductivity thresholds, the IKT improved the salinity estimates’ spatial distribution accuracy. IKT was useful for public health, water management, and agricultural planning since it offered a more accurate and probabilistic prediction of high salinity levels. …”
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Assessing particulate matter (PM2.5) concentrations and variability across Maharashtra using satellite data and machine learning techniques by Ganesh Machhindra Kunjir, Suvarna Tikle, Sandipan Das, Masud Karim, Sujit Kumar Roy, Uday Chatterjee

“…In this context, the present study aims to predict PM2.5 concentrations across Maharashtra, India, for the year 2023, employing machine learning models to improve spatial and temporal air quality assessments. …”
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Bayesian approach for localizing cardiac sources in Magnetocardiography using Vectorcardiography based total variational priors by Vikas R. Bhat, Karunakar Kotegar, H. Anitha

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Maritime Traffic Knowledge Discovery via Knowledge Graph Theory by Shibo Li, Jiajun Xu, Xinqiang Chen, Yajie Zhang, Yiwen Zheng, Octavian Postolache

“…Furthermore, the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm is employed to identify suitable docking berths. …”
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