This paper provides an overview of the features of caregiver input that facilitate language learning across early childhood. We discuss three dimensions of input quality: interactive, linguistic, and conceptual. All three types of input features have been shown to predict children's language learning, though perhaps through somewhat different mechanisms. We argue that input best designed to promote language learning is interactionally supportive, linguistically adapted, and conceptually challenging for the child's age/level. Furthermore, input features interact across dimensions to promote learning. Some but not all qualities of input vary based on parent socioeconomic status, language, or culture, and contexts such as book-reading or pretend play generate uniquely facilitative input features. The review confirms that we know a great deal about the role of input quality in promoting children's development, but that there is much more to learn. Future research should examine input features across the boundaries of the dimensions distinguished here.
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http://dx.doi.org/10.1017/S0305000919000655 | DOI Listing |
Biomech Model Mechanobiol
January 2025
Department of Mechanical Engineering, University of Utah, Salt Lake City, UT, 84112, USA.
When infants are admitted to the hospital with skull fractures, providers must distinguish between cases of accidental and abusive head trauma. Limited information about the incident is available in such cases, and witness statements are not always reliable. In this study, we introduce a novel, data-driven approach to predict fall parameters that lead to skull fractures in infants in order to aid in determinations of abusive head trauma.
View Article and Find Full Text PDFMicrosc Res Tech
January 2025
AIDA Lab. College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh, Saudi Arabia.
The development of deep learning algorithms has transformed medical image analysis, especially in brain tumor recognition. This research introduces a robust automatic microbrain tumor identification method utilizing the VGG16 deep learning model. Microscopy magnetic resonance imaging (MMRI) scans extract detailed features, providing multi-modal insights.
View Article and Find Full Text PDFSci Rep
January 2025
Computer Science Department, Faculty of Computers and Information, South Valley University, Qena, 83523, Egypt.
Adversarial attacks were commonly considered in computer vision (CV), but their effect on network security apps rests in the field of open investigation. As IoT, AI, and 5G endure to unite and understand the potential of Industry 4.0, security events and incidents on IoT systems have been enlarged.
View Article and Find Full Text PDFSci Rep
January 2025
NASA Ames Research Center, Moffett Field, Mountain View, USA.
Spaceflight has several detrimental effects on human and rodent health. For example, liver dysfunction is a common phenotype observed in space-flown rodents, and this dysfunction is partially reflected in transcriptomic changes. Studies linking transcriptomics with liver dysfunction rely on tools which exploit correlation, but these tools make no attempt to disambiguate true correlations from spurious ones.
View Article and Find Full Text PDFNat Commun
January 2025
Center for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, The University of Illinois Chicago, 851 South Morgan Street, Chicago, IL, 60607, USA.
The bottleneck in enhanced sampling lies in finding collective variables that effectively accelerate protein conformational changes; true reaction coordinates that accurately predict the committor are the well-recognized optimal choice. However, identifying them requires unbiased natural reactive trajectories, which, paradoxically, require effective enhanced sampling. Using the generalized work functional method, we uncover that true reaction coordinates control both conformational changes and energy relaxation, enabling us to compute them from energy relaxation simulations.
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