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  • Open Access

    ARTICLE

    New Findings on the Volatilome of Persea americana Miller

    Elizabeth Martinez1, Ana K. Escalera-Ordaz1, Francisco J. Espinosa-García2, Yolanda M. García-Rodríguez2, Rafael Ariza-Flores3, Javier Ponce-Saavedra4, Patricio Apáez-Barrios5, Héctor Guillén-Andrade1,*

    Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 4155-4171, 2025, DOI:10.32604/phyton.2025.073438 - 29 December 2025

    Abstract Volatile organic compounds (VOCs) play an important role in plant survival and adaptation. They contribute to defense against pests and pathogens, tolerance to abiotic stress, and the mediation of essential ecological interactions such as pollination and attraction of dispersal agents. The complex mixture of VOCs produced by an organism, known as volatilome, varies across species, populations, and individuals, making VOCs a major factor in crop diversification and adaptation. In this context, characterizing the volatilome of crop genotypes can provide insight into their ecological associations and potential relationships with agronomic traits. In this study, the volatilome… More >

  • Open Access

    ARTICLE

    Probabilistic Rock Slope Stability Assessment of Heterogeneous Pyroclastic Slopes Considering Collapse Using Monte Carlo Methodology

    Miguel A. Millán1,*, Rubén A. Galindo2, Fausto Molina-Gómez1

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2923-2941, 2025, DOI:10.32604/cmes.2025.069356 - 30 September 2025

    Abstract Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes, resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns. This complexity poses significant challenges for slope stability analysis, requiring the development of specialized techniques to address these issues. This research presents a numerical methodology that incorporates spatial variability, nonlinear material characterization, and probabilistic analysis using a Monte Carlo framework to address this issue. The heterogeneous structure is represented by randomly assigning different lithotypes across the slope, while maintaining predefined global proportions. This contrasts with the more common approach… More >

  • Open Access

    ARTICLE

    Spatiotemporal Variability of Atmospheric Pollutants in Syria: A Multi-Year Assessment Using Sentinel-5P Data

    Almustafa Abd Elkader Ayek1, Bilel Zerouali2,*, Ankur Srivastava3, Mohannad Ali Loho4,5, Nadjem Bailek6,7, Celso Augusto Guimarães Santos8,9

    Revue Internationale de Géomatique, Vol.34, pp. 669-689, 2025, DOI:10.32604/rig.2025.067137 - 19 August 2025

    Abstract This study investigates the spatial and temporal dynamics of key air pollutants—nitrogen dioxide (NO2), carbon monoxide (CO), methane (CH4), formaldehyde (HCHO), and the ultraviolet aerosol index (UVAI)—over the period 2019–2024. Utilizing high-resolution remote sensing data from the Sentinel-5 Precursor satellite and its TROPOspheric Monitoring Instrument (TROPOMI) processed via Google Earth Engine (GEE), pollutant concentrations were analyzed, with spatial visualizations produced using ArcGIS Pro. The results reveal that urban and industrial hotspots—notably in Damascus, Aleppo, Homs, and Hama—exhibit elevated NO2 and CO levels, strongly correlated with population density, traffic, and industrial emissions. Temporal trends indicate significant pollutant fluctuations More > Graphic Abstract

    Spatiotemporal Variability of Atmospheric Pollutants in Syria: A Multi-Year Assessment Using Sentinel-5P Data

  • Open Access

    ARTICLE

    Trends in Rainfall-Temperature Projections in Upper Bernam River Basin Using CMIP6 Scenarios in Malaysia

    Muazu Dantala Zakari1,2,*, Md. Rowshon Kamal1,*, Norulhuda Mohamed Ramli1, Balqis Mohamed Rehan3, Mohd Syazwan Faisal Bin Mohd4

    Revue Internationale de Géomatique, Vol.34, pp. 487-511, 2025, DOI:10.32604/rig.2025.065835 - 29 July 2025

    Abstract Understanding trends in rainfall and temperature projections is critical for assessing climate change impacts, managing water resources, mitigating disaster risks, and guiding sustainable agricultural and infrastructure planning. This study investigates projected changes in temperature and rainfall in the Upper Bernam River Basin (UBRB), Malaysia, using ten Global Climate Models (GCMs) from CMIP6 across four scenarios (SSP126, SSP245, SSP370, and SSP585). Downscaling was conducted with the Climate-Smart Decision Support System (CSDSS) for the baseline period (1985–2014) and for future periods: 2020s, 2040s, 2060s, and 2080s. Results indicate a consistent warming trend, with maximum temperatures projected to… More >

  • Open Access

    ARTICLE

    A GIS Based Earthquake Hazard Pattern Identification Implementing the Local Site-Specific Parameters and the Historical Seismicity

    Harsh Kumar1, Shilpa Suman2, Abhishek Rawat2,*, Rajat Subhra Chatterjee3, Dheeraj Kumar4, B. S. Chaudhary5

    Revue Internationale de Géomatique, Vol.34, pp. 351-362, 2025, DOI:10.32604/rig.2025.064031 - 30 June 2025

    Abstract The unconsolidated soils of the Indo-Gangetic Plains (IGP) contribute significantly to the amplification of seismic damage during earthquakes. Site-specific effects play a critical role in intensifying ground motion and shaping the spatial distribution of seismic hazards. This study aims to investigate the spatial variability of seismic hazards using geophysical and geological parameters such as lithology, shear wave velocity, soil texture, basement depth, and proximity to fault lines. Training data were derived from common hazard points identified in earthquake catalogues. Several machine learning (ML) models, including Logistic Regression (LR), K-Nearest Neighbors, Random Forest, and Decision Tree, More >

  • Open Access

    ARTICLE

    Spatial Variability Assessment on Staple Crop Yields in Hisar District of Haryana, India Using GIS and Remote Sensing

    Sanghati Banerjee1, Om Pal2, Tauseef Ahmad3, Shruti Kanga4, Suraj Kumar Singh1,*, Bhartendu Sajan1

    Revue Internationale de Géomatique, Vol.34, pp. 71-88, 2025, DOI:10.32604/rig.2025.057963 - 24 February 2025

    Abstract Agriculture is a primary activity in many countries, with wheat being a major cereal crop in India. Accurate pre-harvest forecasts of crop acreage and production are critical for policymakers to address supply-demand dynamics, pricing, and trade. This study focuses on estimating wheat acreage and yield in Barwala block, Hisar district, Haryana, for the 2019–2020 Rabi season using remote sensing techniques. Multi-temporal satellite data capturing phenological stages of wheat (Seedling to Ripening) were processed using supervised classification with a maximum likelihood classifier in ERDAS Imagine. Wheat crop acreage was determined by overlaying ground truth points on… More >

  • Open Access

    ARTICLE

    Assessment of Salinity Tolerance and Ecotypic Variability in Vicia narbonensis L.: Morphological, Physiological, and Biochemical Responses

    Hocine Bougrine1,2, Salah Hadjout1,*, Mohamed Zouidi1, Abdeldjalil Belkendil1, Amer Zeghmar1, Chaouki Boulekdam1, Walid Ouaret3, Walid Soufan4, Fathi Abdellatif Belhouadjeb5, Amar Mebarkia2

    Phyton-International Journal of Experimental Botany, Vol.94, No.1, pp. 251-267, 2025, DOI:10.32604/phyton.2025.060096 - 24 January 2025

    Abstract Salinity stress is a major challenge for global agriculture, particularly in arid and semi-arid regions, limiting plant productivity due to water and soil salinity. These conditions particularly affect countries along the southern Mediterranean rim, including Algeria, which primarily focuses on pastoral and forage practices. This study investigates salinity tolerance and ecotypic variability in Vicia narbonensis L., a fodder legume species recognized for its potential to reclaim marginal soils. Morphological, physiological, and biochemical responses were assessed in three ecotypes (eco2, eco9, and eco10) exposed to different salinity levels (low, moderate, and severe). The study was conducted using… More >

  • Open Access

    ARTICLE

    Pressure Classification Analysis on CNN-Transformer-LSTM Hybrid Model

    Peng Xia1, Wu Zeng2,*, Yin Ni1, Ye Jin3

    Journal on Artificial Intelligence, Vol.6, pp. 361-377, 2024, DOI:10.32604/jai.2024.059114 - 13 December 2024

    Abstract Stress is defined as a subjective reflection of an internal psychological state of tension or arousal, manifesting as an interpretive, emotional, and defensive coping process within the body. Prolonged and sustained stress can significantly increase the risk of psychological and physiological disorders. Heart rate variability (HRV) is a key biomarker for assessing autonomic cardiac function, typically increasing during relaxation and decreasing under stress. Although measuring stress through physiological parameters like HRV is a common approach, achieving ultra-high accuracy based on HRV measurements remains a challenging task. In this study, the role of HRV features as… More >

  • Open Access

    ARTICLE

    Network Structure and Variability of Recurrence Fear in Early-Stage Non-Small Cell Lung Cancer: A Symptom Network Analysis

    Lu Liu#, Zhuoheng Lv#, Yousheng Mao, Yan Liu*, Man Liu*

    Psycho-Oncologie, Vol.18, No.4, pp. 317-328, 2024, DOI:10.32604/po.2024.053678 - 04 December 2024

    Abstract Background: Lung cancer, one of the most prevalent and deadly malignancies worldwide, not only poses a significant physical burden but also a profound psychological challenge to patients. Among these psychological challenges, the fear of recurrence stands out as a particularly distressing issue. This fear, often rooted in the patients’ past experiences with the disease and its treatment, can significantly impact their quality of life, mental health, and even compliance with follow-up care. Moreover, this fear can be exacerbated by the lack of understanding and support from healthcare professionals and family members, further isolating patients and… More >

  • Open Access

    ARTICLE

    Continual Reinforcement Learning for Intelligent Agricultural Management under Climate Changes

    Zhaoan Wang1, Kishlay Jha2, Shaoping Xiao1,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1319-1336, 2024, DOI:10.32604/cmc.2024.055809 - 15 October 2024

    Abstract Climate change poses significant challenges to agricultural management, particularly in adapting to extreme weather conditions that impact agricultural production. Existing works with traditional Reinforcement Learning (RL) methods often falter under such extreme conditions. To address this challenge, our study introduces a novel approach by integrating Continual Learning (CL) with RL to form Continual Reinforcement Learning (CRL), enhancing the adaptability of agricultural management strategies. Leveraging the Gym-DSSAT simulation environment, our research enables RL agents to learn optimal fertilization strategies based on variable weather conditions. By incorporating CL algorithms, such as Elastic Weight Consolidation (EWC), with established… More >

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