48 research outputs found

    The Co-Regulation of Emotions Between Mothers and their Children with Autism

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    Thirty-four toddlers with autism and their mothers participated in an early intervention targeting joint engagement. Across the 24 intervention sessions, any significant distress episode in the child was coded for emotion regulation outcomes including child negativity, child emotion self-regulation, and mother emotion co-regulation. Results revealed that emotion regulation strategies by both mother and child were employed during distress episodes. An effect of intervention was found such that children decreased their expression of negativity across the intervention and mothers increased their emotional and motivational scaffolding. The results of this study indicate a positive effect of an intervention targeting joint engagement on emotion co-regulation outcomes

    Analysis of the impact of sex and age on the variation in the prevalence of antinuclear autoantibodies in Polish population: a nationwide observational, cross-sectional study

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    The detection of antinuclear autoantibody (ANA) is dependent on many factors and varies between the populations. The aim of the study was first to assess the prevalence of ANA in the Polish adult population depending on age, sex and the cutoff threshold used for the results obtained. Second, we estimated the occurrence of individual types of ANA-staining patterns. We tested 1731 patient samples using commercially available IIFA using two cutoff thresholds of 1:100 and 1:160. We found ANA in 260 participants (15.0%), but the percentage of positive results strongly depended on the cutoff level. For a cutoff threshold 1:100, the positive population was 19.5% and for the 1:160 cutoff threshold, it was 11.7%. The most prevalent ANA-staining pattern was AC-2 Dense Fine speckled (50%), followed by AC-21 Reticular/AMA (14.38%) ANA more common in women (72%); 64% of ANA-positive patients were over 50 years of age. ANA prevalence in the Polish population is at a level observed in other highly developed countries and is more prevalent in women and elderly individuals. To reduce the number of positive results released, we suggest that Polish laboratories should set 1:160 as the cutoff threshold

    Machine-Learning-Based Digital Twins for Transient Vehicle Cycles and Their Potential for Predicting Fuel Consumption

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    Transient car emission tests generate huge amount of test data, but their results are usually evaluated only using their “accumulated” cycle values according to the homologation limits. In this work, two machine learning models were developed and applied to a truck RDE test and two light-duty vehicle chassis emission tests. Different from the conventional approach, the engine parameters and fuel consumption were acquired from the Engine Control Unit, not from the test measurement equipment. Instantaneous engine values were used as input in machine-learning-based digital twins. This novel approach allows for much less costly vehicle tests and optimizations. The paper’s novel approach and developed digital twins model were able to predict both instantaneous and accumulated fuel consumption with good accuracy, and also for tests cycles different to the one used to train the model
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