Healthsaving technologies of supporting micronutrients functions of eye-sidht at students with myopia by E. Yu. Egorova, A. T. Bykov, O. A. Gromova, I. Yu. Torshin, N. N. Slushalova, N. V. Khvatova

“…This paper presents the results two centers randomized trial of the effectiveness of the usage of vitamin-mineraL complex "Focus Forte" in the group of 120 young patients at the age of (1619 years, students of fuLL-time education in Ivanovo and Krasnodar) in the context of integrated therapy for 2 months. …”
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Integration of geospatial techniques and machine learning in land parcel prediction by Nekkanti Haripavan, Subhashish Dey, Chimakurthi Harika Mani Chandana

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Forest aboveground biomass retrieval integrating ICESat-2, Landsat-8, and environmental factors by Sunjie Ma, Jisheng Xia, Chun Wang, Zhifang Zhao, Fuyan Zou, Maolin Zhang, Guize Luan, Ci Li, Xi Tu, Letian Li

“…The synergistic integration of optical imSagery and LiDAR data provides a comprehensive spatial framework for the precise estimation of aboveground biomass (AGB). …”
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Spectral Efficiency of Wireless Relay Network in Frequency Non-Selective Channel by E. A. Mavrychev, E. N. Pribludova, S. B. Sidorov

“…As a result a task of powers and phases optimization in the relay nodes (i.e. the complex weighted coefficients optimization) becomes actual. …”
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Modelling multi-layer fine fuel loads in temperate eucalypt forests using airborne LiDAR and inventory data by Trung H. Nguyen, Simon Jones, Karin J Reinke, Mariela Soto-Berelov

“…Future research should explore the scalability of this method by integrating satellite-derived data to extend FFL mapping at broader spatial scales.…”
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Importance of Spectral Information, Seasonality, and Topography on Land Cover Classification of Tropical Land Cover Mapping by Chansopheaktra Sovann, Stefan Olin, Ali Mansourian, Sakada Sakhoeun, Sovann Prey, Sothea Kok, Torbern Tagesson

“…Accurate land cover (LC) mapping is vital to monitor these changes, but mapping tropical forests is challenging due to complex spatial patterns, spectral similarities, and frequent cloud cover. …”
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Designing green and safe micro mobility routes: An advanced geo-analytic decision system based approach to sustainable urban infrastructure by Ömer Kaya

“…Micro-mobility solutions have gained significant attention as a sustainable alternative, yet their integration into urban transport networks remains a complex task. To this end, this study introduces a geo-analytic decision-making framework for optimizing micro-mobility route planning. …”
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Downscaled‐GRACE Data Reveal Anthropogenic and Climate‐Induced Water Storage Decline Across the Indus Basin by Arfan Arshad, Ali Mirchi, Saleh Taghvaeian, Amir AghaKouchak

“…The downscaled data at 1 km2 resolution illustrate the spatial heterogeneity of TWS and GWS depletion within each sub‐region. …”
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Remote Sensing Drought Monitoring and Assessment in Southwestern China based on Machine Learning by Hejia JIA, Xiehui LI, Lei WANG, Yuting XUE, Huiquan LIN

“…Due to the complexity of drought and the diversity of influencing factors， the accurate monitoring of drought still faces many problems， especially the increasing frequency and aggravation of drought in Southwestern China， and the formation and disaster causing process have certain particularity.However， the traditional drought monitoring methods cannot meet the requirements of regional drought monitoring， so more scientific monitoring methods and means are needed.Since machine learning can comprehensively consider a variety of disaster causing factors to establish a comprehensive drought monitoring model， it undoubtedly provides a new technical means for drought monitoring.Therefore， this paper used multi-source remote sensing data from 2010 -2019 and meteorological station data from 1980-2019 to first construct a random forest monitoring model to reconstruct and supplement the surface temperature in Southwestern China， and then constructed XGBoost monitoring model to monitor， evaluate and validate the drought in Southwestern China.The results showed that： （1） The correlation coefficients between the training set and test set of the random forest model and the actual surface temperature of the stations exceeded 0.9， which reached a significant correlation.The spatial distribution of LST reconstruction values was similar to that of remote sensing monitoring values， and the values were close to the observed values of meteorological stations.（2） The correlation coefficients between the monitoring values of XGBoost model training set and test set and the SPEI calculated values at the stations were more than 0.86， with significant correlation.The overall consistency rate of drought grade between the monitored value and the calculated SPEI values exceeded 85%.（3） The overall consistent rate between the monitored values of the XGBoost model and the MCI values was above 67.88%， which was more consistent.The consistent rate of all months exceeded 58%， with the highest consistent rate of 75.07% in September and the lowest consistent rate of 58.26% in February.（4） The drought in each season monitored by the model was basically consistent with the actual drought， which could better reflect the spatial distribution and drought in Southwestern China.…”
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Unveiling migraine subtype heterogeneity and risk loci: integrated genome-wide association study and single-cell transcriptomics discovery by Shuxu Wei, Yan Quan, Xinyi Li, Suiqin Zhong, Ling Xiao, Chao Yang, Ronghuai Shen, Xiaojia Lu, Lingbin He, Youti Zhang, Xianxi Huang

“…Tissue-enriched specificity was validated via genetically informed spatial mapping of cells for complex traits (gsMap), a novel algorithm integrating sc-ST and GWAS data to map subtype-associated cellular architectures at single-cell resolution across embryonic tissues. …”
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Comparative analysis of Sentinel-2 and PlanetScope imagery for chlorophyll-a prediction using machine learning models by Eden T. Wasehun, Leila Hashemi Beni, Courtney A. Di Vittorio, Christopher M. Zarzar, Kyana R.L. Young

“…The application of high spatial resolution remote sensing technology enables the detailed capture of information from water bodies for water quality assessment. …”
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Construction of multifunctional composite networks and resilience evaluation under multiple attack scenarios: A case study of the Yangtze river delta by Jianshen Qu, Hao Wang, ZiWei Zhang, Zhili Xu, Yuexia Han, Bin Dong

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Downscaling of Urban Land Surface Temperatures Using Geospatial Machine Learning with Landsat 8/9 and Sentinel-2 Imagery by Ratovoson Robert Andriambololonaharisoamalala, Petra Helmholz, Dimitri Bulatov, Ivana Ivanova, Yongze Song, Susannah Soon, Eriita Jones

“…However, current satellite thermal infrared (TIR) sensors have a low spatial resolution, making it difficult to accurately capture the complex thermal variations within urban areas. …”
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Leveraging Satellite Data for Predicting PM10 Concentration with Machine Learning Models: A Study in the Plains of North Bengal, India by Ayan Das, Manoranjan Sahu

“…Remote sensing offers an effective solution, providing real-time observations with high spatial and temporal resolution. This study aimed to estimate PM10 concentrations in Siliguri City, West Bengal, from 2019 to 2022, using Aerosol Optical Depth (AOD) at a 10 × 10 km spatial resolution. …”
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An ensemble machine learning bioavailable strontium isoscape for Eastern Canada by Mael Le Corre, Felipe Dargent, Vaughan Grimes, Joshua Wright, Steeve D. Côté, Megan S. Reich, Jean-Noël Candau, Marrissa Miller, Brent Holmes, Clement P. Bataille, Kate Britton

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Estimating canopy height in tropical forests: Integrating airborne LiDAR and multi-spectral optical data with machine learning by Brianna J. Pickstone, Hugh A. Graham, Andrew M. Cunliffe

“…We suggest using RF due to its ease in model building, computational time, and efficient feature selection for predicting canopy height. The S2 data at 10 m spatial resolution combined with RF were most appropriate, yielding an R2 of 0.68, RMSE of 3.52 m, and MAE of 2.63 m. …”
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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…Firstly, training samples in classification algorithms are typically selected through pixel-based random sampling or manual regional sampling. <b>This approach struggles with accurately modeling complex patterns in high-resolution images and often results in redundant samples.…”
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Uncovering mangrove range limits using very high resolution satellite imagery to detect fine‐scale mangrove and saltmarsh habitats in dynamic coastal ecotones by Cheryl L. Doughty, Kyle C. Cavanaugh, Samantha Chapman, Lola Fatoyinbo

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Artificial intelligence and machine learning to enhance critical mineral deposit discovery by Rhys S. Davies, McLean Trott, Jaakko Georgi, Alexander Farrar

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Trafficking in cancer: from gene deregulation to altered organelles and emerging biophysical properties by Julie Patat, Kristine Schauer, Kristine Schauer, Hugo Lachuer

“…Several proteins of the intracellular trafficking machinery are deregulated in diseases, particularly cancer. This complex and deadly disease stays a heavy burden for society, despite years of intense research activity. …”
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