ABSTRACT
Autonomous search is an ongoing cycle of sensing, statistical estimation, and motion control with the objective to find and localise targets in a designated search area. Traditionally, the theoretical framework for autonomous search combines sequential Bayesian estimation with information theoretic motion control. This paper formulates autonomous search in the framework of possibility theory. Although the possibilistic formulation is slightly more involved than the traditional method, it provides a means for quantitative modelling and reasoning in the presence of epistemic uncertainty. This feature is demonstrated in the paper in the context of partially known probability of detection, expressed as an interval value. The paper presents an elegant Bayes-like solution to sequential estimation, with the reward function for motion control defined to take into account the epistemic uncertainty. The advantages of the proposed search algorithm are demonstrated by numerical simulations.
ABSTRACT
OBJECTIVES: Fatigue is a common comorbidity in patients with axial spondyloarthritis (axSpA), often reported also by those in clinical remission or with moderate disease activity. The aim of this study is to assess the prevalence of fatigue in patients with axSPA, and to investigate possible non-disease-related determinants, with a special focus on depression. METHODS: Patients with axSpA were assessed using the Chalder's Fatigue Questionnaire (CFQ) for fatigue, and the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) for depression. Ankylosing Spondylitis Disease Activity Score (ASDAS), Bath Ankylosing Spondylitis Functional Index (BASFI) and Health Assessment Questionnaire (HAQ) were also used to assess disease activities and disability. Univariate and multivariate linear regressions were performed to identify possible predictors of fatigue. RESULTS: Out of 119 patients, 53 (44.5%) had fatigue. Patients with fatigue had higher HADS-D, ASDAS, BASFI, HAQ scores. HADS-D was predictive of CFQ score in univariate and multivariate regressions for total CFQ, and for mental and physical subscales. The correlation between HADS-D and CFQ total score was statistically significant also when taking into consideration only patients in clinical remission and with moderate disease activity. Depressed patients had higher CFQ score compared to non-depressed ones, and did not show any difference in CFQ scores when stratified for disease activity or systemic inflammation. CONCLUSIONS: The study found correlation between fatigue and disease activity and depression in patients with axSpA. These findings suggest that depression could represent the major determinant of fatigue in patients with axSpA, independently of clinical activity.