Mechanism of the impacts of older adults social participation on their health.

Purpose: Against the background of population aging challenges in China, focusing on health, security, and social participation as core elements of positive aging, this study aims to formulate strategies for promoting the health of the older adults and reveal the pathways and trends of social participation in promoting health.

Method: The study analyzed 1,015 randomly selected older adults individuals living at home in Beijing using household survey questionnaires. Drawing on group dynamics theory and structural equation modeling, the study proposed hypotheses regarding the relationships between social participation, group cohesion, and health status.

Deep Collocative Learning for Immunofixation Electrophoresis Image Analysis.

Immunofixation Electrophoresis (IFE) analysis is of great importance to the diagnosis of Multiple Myeloma, which is among the top-9 cancer killers in the United States, but has rarely been studied in the context of deep learning. Two possible reasons are: 1) the recognition of IFE patterns is dependent on the co-location of bands that forms a binary relation, different from the unary relation (visual features to label) that deep learning is good at modeling; 2) deep classification models may perform with high accuracy for IFE recognition but is not able to provide firm evidence (where the co-location patterns are) for its predictions, rendering difficulty for technicians to validate the results. We propose to address these issues with collocative learning, in which a collocative tensor has been constructed to transform the binary relations into unary relations that are compatible with conventional deep networks, and a location-label-free method that utilizes the Grad-CAM saliency map for evidence backtracking has been proposed for accurate localization.