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The accuracy of metacognitive judgments is rarely incentivized in experiments; hence, it depends on the participants' willingness to invest cognitive resources and respond truthfully. According to arguments promoted in economic research that performance cannot reach its full potential without proper motivation, metacognitive abilities might therefore have been underestimated. In two experiments (N = 128 and N = 129), we explored the impact of incentives on the accuracy of judgments of learning (JOLs), memory performance, and cue use in free recall of word lists.

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Designing advanced materials that effectively mitigate the poor cycle life of battery-type electrodes with high specific capacities is crucial for next-generation energy storage systems. Herein, graphene oxide-ceria (GO-CeO) nanocomposite synthesized via a facile wet chemical route is explored as cathode for high-performance supercapacitors. The morphological analysis suggests fine ceria (CeO) nanoparticles dispersed over ultrathin graphene oxide (GO) sheets while structural studies reveal face-centered cubic phase of CeO in the nanocomposite.

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Northern bobwhite quail (Colinus virginianus) are an important game bird that generates substantial revenue for rural communities and is also an important grassland conservation species. Unfortunately, Northern bobwhite populations have been declining across their range for over 50 years. In the southwest bobwhite range, parasites are suspected to contribute substantially to the decline.

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Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features.

BMC Public Health

January 2025

Department of Health and Intelligent Engineering, College of Health Management, China Medical University, 110122, Shenyang, Liaoning Province, China.

Background: Depressive symptoms in adolescents can significantly affect their daily lives and pose risks to their future development. These symptoms may be linked to various factors experienced during both childhood and adolescence. Machine learning (ML) has attracted substantial attention in the field of adolescent depression; however, studies establishing prediction models have primarily considered childhood or adolescent features separately, resulting in a lack of analyses that incorporate factors from both stages.

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Objective: This study aimed to assess the effectiveness of conventional magnetic resonance imaging (MRI) combined with three-dimensional (3D) ultrasound for the preoperative prediction of nonperfused volume ratio (NPVR) in uterine fibroids after high-intensity focused ultrasound (HIFU) ablation.

Materials And Methods: In total, 178 patients who had undergone HIFU ablation therapy for uterine fibroids between July 2021 and August 2023 were enrolled. Baseline clinical, MRI, and 3D ultrasound parameters collected before and after HIFU ablation were analyzed.

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