Bio-inspired relevant interaction modelling in cognitive crowd management

Cognitive algorithms, integrated in intelligent systems, represent an important innovation in designing interactive smart environments. More in details, Cognitive Systems have important applications in anomaly detection and management in advanced video surveillance. These algorithms mainly address the problem of modelling interactions and behaviours among the main entities in a scene. A bio-inspired structure is here proposed, which is able to encode and synthesize signals, not only for the description of single entities behaviours, but also for modelling cause–effect relationships between user actions and changes in environment configurations. Such models are stored within a memory (Autobiographical Memory) during a learning phase. Here the system operates an effective knowledge transfer from a human operator towards an automatic systems called Cognitive Surveillance Node (CSN), which is part of a complex cognitive JDL-based and bio-inspired architecture. After such a knowledge-transfer phase, learned representations can be used, at different levels, either to support human decisions, by detecting anomalous interaction models and thus compensating for human shortcomings, or, in an automatic decision scenario, to identify anomalous patterns and choose the best strategy to preserve stability of the entire system. Results are presented in a video surveillance scenario , where the CSN can observe two interacting entities consisting in a simulated crowd and a human operator. These can interact within a visual 3D simulator, where crowd behaviour is modelled by means of Social Forces. The way anomalies are detected and consequently handled is demonstrated, on synthetic and also on real video sequences, in both the user-support and automatic modes

Dietary Patterns in Portuguese Children and Adolescent Population: The UPPER Project

Considering the nature, extent, and purpose of food processing, this study aims to identify dietary patterns (DPs) and their associations with sociodemographic factors and diet quality in Portuguese children and adolescents. Cross-sectional data were obtained from the National Food, Nutrition and Physical Activity Survey (20152016) of the Portuguese population. Dietary intake was obtained from two non-consecutive days and food items were classified according to the NOVA system. The proportion (in grams) of foods in the total daily diet was considered to identify DPs by latent class analysis, with age and sex as concomitant variables. Associations of DPs with sociodemographic characteristics were assessed using multinomial logistic regression. Linear regressions adjusted by sociodemographic characteristics tested associations of DPs with diet quality. DPs identified were: Unhealthy (higher sugar-sweetened beverages, industrial breads, and sausages intake), Traditional (higher vegetables, fish, olive oil, breads, ultra-processed yogurts, and sausages intake), and Dairy (higher intake of milk, yogurt, and milk-based beverages). Unhealthy was associated with older ages and lower intake of dietary fibre and vitamins and the highest free sugars and ultra-processed foods (UPF), although all DPs presented significant consumption of UPF. These findings should be considered for the design of food-based interventions and school-feeding policies in Portugal.</jats:p

Distinct synovial tissue macrophage subsets regulate inflammation and remission in rheumatoid arthritis.

Immune-regulatory mechanisms of drug-free remission in rheumatoid arthritis (RA) are unknown. We hypothesized that synovial tissue macrophages (STM), which persist in remission, contribute to joint homeostasis. We used single-cell transcriptomics to profile 32,000 STMs and identified phenotypic changes in patients with early/active RA, treatment-refractory/active RA and RA in sustained remission. Each clinical state was characterized by different frequencies of nine discrete phenotypic clusters within four distinct STM subpopulations with diverse homeostatic, regulatory and inflammatory functions. This cellular atlas, combined with deep-phenotypic, spatial and functional analyses of synovial biopsy fluorescent activated cell sorted STMs, revealed two STM subpopulations (MerTKTREM2 and MerTKLYVE1) with unique remission transcriptomic signatures enriched in negative regulators of inflammation. These STMs were potent producers of inflammation-resolving lipid mediators and induced the repair response of synovial fibroblasts in vitro. A low proportion of MerTK STMs in remission was associated with increased risk of disease flare after treatment cessation. Therapeutic modulation of MerTK STM subpopulations could therefore be a potential treatment strategy for RA