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Integrative molecular and physiological insights into the phytotoxic impact of liquid crystal monomer exposure and the protective strategy in plants.
Plant Biotechnol J
January 2025
Key Laboratory of Cultivation and Protection for Non-Wood Forest Trees, Ministry of Education, Central South University of Forestry and Technology, Changsha, China.
Liquid crystal monomers (LCMs), the integral components in the manufacture of digital displays, have engendered environmental concerns due to extensive utilization and intensive emission. Despite their prevalence and ecotoxicity, the LCM impacts on plant growth and agricultural yield remain inadequately understood. In this study, we investigated the specific response mechanisms of tobacco, a pivotal agricultural crop and model plant, to four representative LCMs (2OdF3B, 5CB, 4PiMeOP, 2BzoCP) through integrative molecular and physiological approaches.
View Article and Find Full Text PDFSeasonal Land Use and Land Cover Mapping in South American Agricultural Watersheds Using Multisource Remote Sensing: The Case of Cuenca Laguna Merín, Uruguay.
Sensors (Basel)
January 2025
Departamento de Geografía, Facultad de Ciencias, Universidad de la República, Montevideo 4225, Uruguay.
Recent advancements in Earth Observation sensors, improved accessibility to imagery and the development of corresponding processing tools have significantly empowered researchers to extract insights from Multisource Remote Sensing. This study aims to use these technologies for mapping summer and winter Land Use/Land Cover features in Cuenca de la Laguna Merín, Uruguay, while comparing the performance of Random Forests, Support Vector Machines, and Gradient-Boosting Tree classifiers. The materials include Sentinel-2, Sentinel-1 and Shuttle Radar Topography Mission imagery, Google Earth Engine, training and validation datasets and quoted classifiers.
View Article and Find Full Text PDFEnhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning.
Sensors (Basel)
December 2024
Intelligent Manufacturing Laboratory, Production Engineering Institute, Faculty of Mechanical Engineering, University of Maribor, Smetanova ulica 17, 2000 Maribor, Slovenia.
Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time.
View Article and Find Full Text PDFA Comparative Analysis of Explainable Artificial Intelligence Models for Electric Field Strength Prediction over Eight European Cities.
Sensors (Basel)
December 2024
2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, 12462 Athens, Greece.
The widespread propagation of wireless communication devices, from smartphones and tablets to Internet of Things (IoT) systems, has become an integral part of modern life. However, the expansion of wireless technology has also raised public concern about the potential health risks associated with prolonged exposure to electromagnetic fields. Our objective is to determine the optimal machine learning model for constructing electric field strength maps across urban areas, enhancing the field of environmental monitoring with the aid of sensor-based data collection.
View Article and Find Full Text PDFLipid Profile of Mayr in Adaptation to Natural Conditions in the Cryolithozone.
Int J Mol Sci
December 2024
Institute for Biological Problems of Cryolithozone, Siberian Branch of Russian Academy of Sciences, Division of Federal Research Centre "The Yakut Scientific Centre of the Siberian Branch of the Russian Academy of Sciences", 41 Lenina Av., Yakutsk 677000, Russia.
The prevalence of coniferous trees in the forest landscapes of northeastern Siberia is conditioned by their high frost resistance. The Kajander larch ( Mayr), which can survive under natural conditions (down to -60 °C) in the cryolithozone of Yakutia, is the dominant forest-forming species. We hypothesise that our study using HPTLC-UV/Vis/FLD, TLC-GC/FID, and GC-MS methods of seasonal features of the lipid profile of Kajander larch tissues will bring us closer to understanding the mechanisms of participation of lipid components in the adaptation of this valuable tree species to the cold climate of the cryolithozone.
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