The effects of spatial selective attention upon ERPs associated with the processing of word stimuli were investigated. While subjects maintained central eye fixation, ERPs were recorded to words presented to the left and right visual fields. In each of 6 runs, subjects focussed attention to alternate fields to perform a category-detection task. Pairs of semantically related and repeated words were embedded in the word lists presented to the attended and unattended visual fields. Consistent with prior studies, the P1-N1 visual ERP was larger when elicited by words in attended spatial locations. A large negative slow wave identified as N400 was elicited by attended, but not unattended, words. For attended words, N400 was smaller for semantically primed or repeated words. We concluded that spatial selective attention can modulate the degree to which words are processed, and that the cognitive processes associated with N400 are not automatic.
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http://dx.doi.org/10.1016/0168-5597(93)90005-a | DOI Listing |
J Colloid Interface Sci
January 2025
College of Materials Science and Engineering, Beijing University of Technology, Beijing 100124, China. Electronic address:
Rational regulation of interface structure in photocatalysts is a promising strategy to improve the photocatalytic performance of carbon dioxide (CO) reduction. However, it remains a challenge to modulate the interface structure of multi-component heterojunctions. Herein, a strategy integrating heterojunction with facet engineering is developed to modulate the interface structure of metal-organic frameworks (MOF)-based heterojunctions.
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January 2025
Satellite Application Division, Korea Aerospace Research Institute (KARI), Daejeon 34133, Republic of Korea.
For change detection in synthetic aperture radar (SAR) imagery, amplitude change detection (ACD) and coherent change detection (CCD) are widely employed. However, time-series SAR data often contain noise and variability introduced by system and environmental factors, requiring mitigation. Additionally, the stability of SAR signals is preserved when calibration accounts for temporal and environmental variations.
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January 2025
Department of Environmental Remote Sensing and Geoinformatics, Trier University, Universitätsring 15, 54296 Trier, Germany.
Assessing vines' vigour is essential for vineyard management and automatization of viticulture machines, including shaking adjustments of berry harvesters during grape harvest or leaf pruning applications. To address these problems, based on a standardized growth class assessment, labeled ground truth data of precisely located grapevines were predicted with specifically selected Machine Learning (ML) classifiers (Random Forest Classifier (RFC), Support Vector Machines (SVM)), utilizing multispectral UAV (Unmanned Aerial Vehicle) sensor data. The input features for ML model training comprise spectral, structural, and texture feature types generated from multispectral orthomosaics (spectral features), Digital Terrain and Surface Models (DTM/DSM- structural features), and Gray-Level Co-occurrence Matrix (GLCM) calculations (texture features).
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January 2025
Skin Sensing Research Group, School of Health Sciences, Faculty of Environmental and Life Sciences, University of Southampton, Southampton SO17 1HE, UK.
Measuring interface pressure is currently used in a variety of settings, e.g., automotive or clinical, to evaluate pressure distribution at support surface interfaces.
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January 2025
Forest Biometrics and Remote Sensing Laboratory (Silva Lab), School of Forest, Fisheries, and Geomatics Sciences, University of Florida, P.O. Box 110410, Gainesville, FL 32611, USA.
Developing the capacity to monitor species diversity worldwide is of great importance in halting biodiversity loss. To this end, remote sensing plays a unique role. In this study, we evaluate the potential of Global Ecosystem Dynamics Investigation (GEDI) data, combined with conventional satellite optical imagery and climate reanalysis data, to predict in situ alpha diversity (Species richness, Simpson index, and Shannon index) among tree species.
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