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http://dx.doi.org/10.1177/02692163231180655 | DOI Listing |
Curr Opin Psychol
December 2025
Universidad Autónoma Metropolitana-Iztapalapa, Av. Ferrocarril San Rafael Atlixco, Núm. 186, Col. Leyes de Reforma, C.P., 09310, Ciudad de, Mexico. Electronic address:
This paper presents a state-of-the-art review of collective memories of urban spaces, examining them from the perspective of mental maps. It is observed that urban memory reflects the socio-cultural diversity and inherent social inequalities of contemporary metropolises. Memory and cultural heritage play a significant role in urban dynamics.
View Article and Find Full Text PDFPalliat Med
September 2025
School of Nursing, Psychotherapy and Community Health, Faculty of Science and Health, Dublin City University, Glasnevin Campus, Dublin, Ireland.
Background: Emotional and psychosocial support is vital for children with life-limiting or life-threatening conditions and their families. Memory-making interventions, which create lasting memories, are gaining recognition, yet a comprehensive synthesis of their efficacy and scope is lacking.
Aim: To systematically review and synthesize evidence on memory-making interventions for children and young people aged 0-19 years with life-threatening or life-limiting conditions and their families in paediatric palliative and bereavement contexts.
Front Neurol
June 2025
Department of Respiratory Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Background: Neuroblastoma (NB) is a common malignancy in children, and accurate risk stratification and prognostic assessment are essential for personalized treatment. Current tumor assessment methods rely on clinical features and conventional imaging techniques, which have limited predictive accuracy. The aim of this study was to develop a deep learning model based on multiphase enhanced CT images and clinical features to improve the accuracy of risk stratification and prognostic assessment of NB.
View Article and Find Full Text PDFNeural Netw
October 2025
Kummer Institute Center for Artificial Intelligence and Autonomous Systems, Missouri University of Science and Technology, Rolla, 65409, MO, USA.
This article presents DeepART, a gradient-free and one-shot incremental learning technique for the training of deep Hebbian neural networks using the dynamics of Adaptive Resonance Theory (ART) algorithms. In the presented model, layers of a deep neural network are interpreted as modified FuzzyART modules with complement coded inputs and winner-take-all local weight updates with a FuzzyARTMAP head module providing feature-category-label mapping to enable supervised learning. These local weight update rules are derived for fully-connected and convolutional layers.
View Article and Find Full Text PDFFront Psychiatry
May 2025
Department of Clinical and Health Psychology, University of Vienna, Vienna, Austria.
Background: Clown visits are an effective intervention to alleviate patients' stress and anxiety in pediatric hospital settings. However, while children and adolescents in inpatient psychiatric treatment might uniquely benefit from healthcare clowning, little research has addressed the effectiveness of clown visits in this setting.
Method: This pilot study examined the short-term effects of clown visits on psychological (self-reported stress and mood) and physiological (salivary cortisol) outcomes in 29 children and adolescents aged between 7 and 17 years (M = 12.