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In Chinese character processing studies, it is widely accepted that semantic radicals, whether character or non-character ones, can undergo semantic activation. However, there is a notable absence of studies dedicated to understanding the nature and operation of the semantic radicals' semantic information. To address this gap, the present study employed a masked semantic priming paradigm combined with a part-of-speech decision task and a lexical decision task across three experiments. Experiment 1 was designed to examine the semantic autonomy and the semantic attachment of semantic radicals in transparent phonograms. Experiment 2 sought to further investigate the degree of semantic autonomy of semantic radicals in opaque phonograms. Experiment 3 was crafted to further probe into the presence of semantic attachment of semantic radicals in pseudo-characters. Results showed significant priming effects in both transparent and opaque phonogram conditions, with faster reaction times and higher accuracy for semantically related prime-target pairs. However, no such priming effect was observed in the pseudo-character condition, indicating that semantic radicals are not activated in non-lexical contexts. These findings suggest that semantic radicals were semantically activated when embedded in both transparent and opaque phonograms, but not when planted in pseudo-characters. The plausible account put forward is that semantic radicals stand on pars with their composed phonograms in possessing their own semantic information, but the former is semantically strongly attached to the latter, such that it cannot live without the latter's semantic company.
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http://dx.doi.org/10.1186/s40359-025-02855-1 | DOI Listing |
Cancer Imaging
August 2025
Department of Radiology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Cancer Immunology and Biotherapy, Tianjin, Huan-Hu-Xi Road, Ti-Yuan-Bei, He Xi District, Tianjin, China. tjl
Background: Accurate preoperative assessment of occult lymph node metastasis (OLNM) plays a crucial role in informing therapeutic decision-making for lung cancer patients. Computed tomography (CT) is the most widely used imaging modality for preoperative work-up. The aim of this study was to develop and validate a CT-based machine learning model integrating intra-and peri-tumoral features to predict OLNM in lung cancer patients.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
August 2025
In the natural language processing task of clinical named entity recognition (CNER), accurately identifying the boundaries and categories of medical entities is crucial. However, traditional methods struggle to recognize a large number of clinical terms and symbols that have never been encountered before, ultimately limiting the performance of CNER. Besides, there exist some easy-to-confuse Chinese clinical entities that are semantically similar but belong to quite different categories, such as "" (pulmonary nodules, a symptom entity) and "" (pulmonary tuberculosis, a disease entity), which can lead to entity misidentification.
View Article and Find Full Text PDFPLoS One
July 2025
Changsha Institute of Technology, Changsha, China.
In recent years, there has been significant progress in Chinese text sentiment analysis research. However, few studies have investigated the differences between languages, the effectiveness of domain knowledge, and the requirements of downstream tasks. Considering the uniqueness of Chinese text and the practical needs of sentiment analysis, this study aims to address these gaps.
View Article and Find Full Text PDFJ Psychopathol Clin Sci
August 2025
School of Natural Sciences, Macquarie University.
Comments on Fernandes et al. (see record 2026-12254-001). Fernandes et al.
View Article and Find Full Text PDFFront Hum Neurosci
June 2025
School of English Studies, Sichuan International Studies University, Chongqing, China.
Introduction: A majority of Chinese characters are phonograms composed of phonetic and semantic radicals that serve different functions. While radical processing in character recognition has drawn significant interest, there is inconsistency regarding the semantic activation of embedded semantic radicals, and little is known about the duration of such sub-lexical semantic activation.
Methods: Using a priming character decision task and a between-subjects design, this study examined whether semantic radicals embedded in SP phonograms (semantic radicals on the left and phonetic radicals on the right) can be automatically activated and how long such activation persists.