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With the diversification of Internet uses, online content type has become richer. Alongside organic results, search engine results pages now provide tools to improve information searching and learning. The People also ask (PAA) box is intended to reduce users' cognitive costs by offering easily accessible information. Nevertheless, there has been scant research on how users actually process it, compared with more traditional content type (i.e., organic results and online documents). The present eye-tracking study explored this question by considering the search context (complex lookup task vs. exploratory task) and users' prior domain knowledge (high vs. low). Main results show that users fixated the PAA box and online documents more to achieve exploratory goals, and fixated organic results more to achieve lookup goals. Users with low knowledge process PAA content at an early stage in their search contrary to their counterparts with high knowledge. Given these results, information system developers should diversify PAA content according to search context and users' prior domain knowledge.
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http://dx.doi.org/10.1016/j.apergo.2024.104367 | DOI Listing |
J Safety Res
September 2025
Massachusetts Institute of Technology (institution) Center for Transportation and Logistics, Agelab (department), Cambridge, Massachusetts, USA.
Introduction: Partial automation is still evolving. There is need to understand how behavior changes over time as drivers develop familiarity with the technology. In Reagan et al.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
September 2025
The tumor microenvironment is a dynamic eco system where cellular interactions drive cancer progression. However, inferring cell-cell communication from non-spatial scRNA-seq data remains challenging due to incomplete li gand-receptor databases and noisy cell type annotations. H ere, we propose scGraphDap, a graph neural network frame work that integrates functional state pseudo-labels and graph structure learning to improve both cell type annotation an d CCC inference.
View Article and Find Full Text PDFProc Mach Learn Res
November 2024
Pretraining plays a pivotal role in acquiring generalized knowledge from large-scale data, achieving remarkable successes as evidenced by large models in CV and NLP. However, progress in the graph domain remains limited due to fundamental challenges represented by feature heterogeneity and structural heterogeneity. Recent efforts have been made to address feature heterogeneity via Large Language Models (LLMs) on text-attributed graphs (TAGs) by generating fixed-length text representations as node features.
View Article and Find Full Text PDFMed Phys
September 2025
School of Computer, Electronics and Information, Guangxi University, Nanning, China.
Background: Deformable medical image registration is a critical task in medical imaging-assisted diagnosis and treatment. In recent years, medical image registration methods based on deep learning have made significant success by leveraging prior knowledge, and the registration accuracy and computational efficiency have been greatly improved. Models based on Transformers have achieved better performance than convolutional neural network methods (ConvNet) in image registration.
View Article and Find Full Text PDFTurk J Pediatr
September 2025
West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Background: The α-actinin-4 (ACTN4) gene encodes an actin-binding protein, which plays a crucial role in maintaining the structure and function of podocytes. Previous studies have confirmed that ACTN4 mutations can lead to focal segmental glomerulosclerosis-1 (FSGS1), a rare disease primarily manifesting in adolescence or adulthood, characterized by mild to moderate proteinuria, with some cases progressing slowly to end-stage renal disease.
Case Presentation: We report a 12.