This study extends the findings of Gaustad, Kelly, Payne, and Lylak (2002), which showed that deaf college students and hearing middle school students appeared to have approximately the same morphological knowledge and word segmentation skills. Because the average grade level reading abilities for the two groups of students were also similar, those research findings suggested that deaf students' morphological development was progressing as might be expected relative to reading level. This study further examined the specific relationship between morphologically based word identification skills and reading achievement levels, as well as differences in the error patterns of deaf and hearing readers. Comparison of performance between pairs of deaf college students and hearing middle school students matched for reading achievement level shows significant superiority of younger hearing participants for skills relating especially to the meaning of derivational morphemes and roots, and the segmentation of words containing multiple types of morphemes. Group subtest comparisons and item analysis comparisons of specific morpheme knowledge and word segmentation show clear differences in the morphographic skills of hearing middle school readers over deaf college students, even though they were matched and appear to read at the same grade levels, as measured by standardized tests.
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Asia Pac J Ophthalmol (Phila)
January 2025
Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China. Electronic address:
Myopia stands as a prevalent ocular condition with global implications, impacting individuals at various life stages. In school-age children and adolescents, uncorrected myopia impedes reading and academic performance. Among middle-aged and elderly populations, myopia poses severe risks such as macular degeneration, macular holes and retinal detachment, leading to irreversible visual impairment.
View Article and Find Full Text PDFBMC Public Health
January 2025
School of Exercise and Health, Shanghai University of Sport, Shanghai City, China.
Background: Past cross-sectional studies have reported a positive association between moderate-to-vigorous physical activity (MVPA) and academic achievement in children and adolescents. Despite this, the influence of variations in MVPA over time on academic achievement remains yet to be definitively understood. Therefore, this study aims to track the patterns of MVPA and examine how they are associated with academic achievement over a three-year period among Chinese primary school students.
View Article and Find Full Text PDFNat Mater
January 2025
Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.
Machine learning algorithms have proven to be effective for essential quantum computation tasks such as quantum error correction and quantum control. Efficient hardware implementation of these algorithms at cryogenic temperatures is essential. Here we utilize magnetic topological insulators as memristors (termed magnetic topological memristors) and introduce a cryogenic in-memory computing scheme based on the coexistence of a chiral edge state and a topological surface state.
View Article and Find Full Text PDFTelemed J E Health
January 2025
Department of Clinical Sciences, Dermatology and Venereology, Lund Skin Cancer Research Group, Lund University, Lund, Sweden.
Teledermoscopy (TDS) emerges as an efficient tool for diagnosing skin lesions. In Sweden, double reading is the standard of care, but risk factors for misdiagnosis or mismanagement using single reader evaluations (SRE) are not well-studied. This study aimed to assess the accuracy of SRE compared with the gold standard in TDS.
View Article and Find Full Text PDFbioRxiv
January 2025
Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, 92093.
Deep learning sequence models trained on personalized genomics can improve variant effect prediction, however, applications of these models are limited by computational requirements for storing and reading large datasets. We address this with GenVarLoader, which stores personalized genomic data in new memory-mapped formats with optimal data locality to achieve ~1,000x faster throughput and ~2,000x better compression compared to existing alternatives.
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