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Background: The human–animal bond is crucial for the proper development of animal-assisted therapy (AAT) sessions. However, in specific cases such as in AAT focused on psychiatric patients who are admitted to acute units, there is only a short period of time available to establish this bond. Objectives: To assess the degree of HAB generated after two AAT sessions in adolescents admitted to acute psychiatry units. Methods: A prospective multicenter cohort study aimed at adolescents aged 13 to 17 years admitted to the acute child and adolescent psychiatry unit of three hospitals. Intervention: Two weekly 1 h group sessions of AAT with therapy dogs. Main outcome: The Center for the Study of Animal Wellness Pet Bonding Scale Survey (CSAWPB). Results: One hundred and fourteen adolescents participated. A positive perception of the dog was generated, achieving a good level of bonding and attachment. Conclusions: The results obtained make it possible to affirm that a short period of time is enough to establish a good HAB between patients and therapy dogs. This study aims to contribute to the study of non-pharmacological interventions as a complement to pharmacological treatments in adolescents with mental health disorders.

Urban air quality mapping has been widely applied in urban planning, air pollution control and personal air pollution exposure assessment. Urban air quality maps are traditionally derived using measurements from fixed monitoring stations. Due to high cost, these stations are generally sparsely deployed in a few representative locations, leading to a highly generalized air quality map. In addition, urban air quality varies rapidly over short distances (2 by 100 m and 1 h resolution for fine-grained air quality mapping. The CLADF model exploits deep forest to construct a local model for each cluster consisting of nearest neighbor measurements in contextual feature space, and considers traffic flow as an important contextual feature. Extensive validation experiments were conducted using mobile NO2 measurements collected by 17 postal vans equipped with low-cost sensors operating in Antwerp, Belgium. The experimental results demonstrate that the CLADF model achieves the lowest RMSE as well as advances in accuracy and correlation, compared with various benchmark models, including random forest, deep forest, extreme gradient boosting and support vector regression.