The present study examined the role of attentional demand on infants' perseverative behavior in a noncommunicative looking version of an A-not-B task. The research aimed at clarifying age-related improvements in the attention process that presumably underlies the development of cognitive control. In a between-subjects design, forty 10-month-olds and forty 12-month-olds were assigned to either a distractor or a no-distractor condition as a means of testing the role of attentional load. The authors used an eye tracker to record infants' looking behavior while they anticipated the reappearance of the target of interest as well as continuously throughout the task. The data demonstrated that 10-month-olds show more perseverative looking than do 12-month-olds and that increased attentional demand leads to more perseverative looking. Correct anticipation, however, was not affected by age or distraction. The results also failed to show that 12-month-olds are better than 10-month-olds at handling the increased attentional demand introduced in the distractor condition, in that the effect of the distractor was not larger for the younger infants. Our results are in line with the theoretical view of cognitive control as dependent on a limited attentional resource, which can explain perseverative behaviors in different tasks and at different ages.
Background: This study examines the relationship between unmet healthcare needs and employment status, with a focus on how this relationship was influenced by the Spanish economic recession of 2008-2012.
Methods: Data were obtained from the Spanish National Health Survey for 2006 and 2011-2012. The outcome variable was the presence of unmet healthcare needs, describing its reasons.
Key Laboratory of Organic Integrated Circuits, Ministry of Education & Tianjin Key Laboratory of Molecular Optoelectronic Sciences, Department of Chemistry, School of Science, Tianjin University, Tianjin 300072, China.
Organic semiconductor single crystals (OSSCs), which possess the inherent merits of long-range order, low defect density, high mobility, structural tunability and good flexibility, have garnered significant attention in the organic optoelectronic community. Past decades have witnessed the explosive growth of OSSCs. Despite numerous conceptual demonstrations, OSSCs remain in the early stages of implementation for applications that require high integration and multifunctionality.
Background: Internet searches offer an indicator of public attention and possible demand for certain things. Studying the spatiotemporal characteristics of the public's concern for vaccination can determine the spatiotemporal distribution of demand for vaccines in China, and capture the changes in the health awareness of the Chinese population, thus informing future vaccination strategies.
Methods: Based on the collection of Baidu search indices for vaccination-related keywords in 363 cities in China, This paper seeks to explore the spatiotemporal changes and regional differences in public attention toward vaccination in China by using the seasonal index, seasonal concentration index, Herfindahl index, Moran index, and Dagum Gini coefficient.
Background: With the clinical integration of sugammadex, a selective relaxant-binding agent, the approach to reversing neuromuscular blockade is revolutionized. Despite its efficacy, sugammadex's adverse reactions range from mild symptoms to severe cases, including anaphylaxis and coagulopathy. Assessing the nature of these reactions using the Food and Drug Administration's Adverse Event Reporting System (FAERS) database is vital for safe anesthetic practice.
Objective: To evaluate the service quality of integrated health and social care institutions for older adults in residential settings in China, addressing a critical gap in the theoretical and empirical understanding of service quality assurance in this rapidly expanding sector.
Methods: This study employs three machine learning algorithms-Backpropagation Neural Networks (BPNN), Feedforward Neural Networks (FNN), and Support Vector Machines (SVM)-to train and validate an evaluative item system. Comparative indices such as Mean Squared Error, Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and predictive performance metrics were employed to assess the models.
