Background:The clinical presentation of European patients with mild-to-moderate infection is still unknown.Objective: To study the clinical presentation of Covid-19 in Europe. Methods:Patients with positive diagnosis of Covid-19 were recruited from 18 European hospitals.Epidemiological and clinical data were obtained through a standardized questionnaire. Bayesian analysis was used for analyzing the relationship between outcomes.Results: 1,420 patients completed the study (962 females, 30.7% of health care workers). The mean age of patients was 39.17±12.09 years. The most common symptoms were headache (70.3%), loss of smell (70.2%), nasal obstruction (67.8%), cough (63.2%), asthenia (63.3%), myalgia (62.5%), rhinorrhea (60.1%), gustatory dysfunction (54.2%) and sore throat (52.9%).Fever was reported by on 45.4%. The mean duration of Covid-19 symptoms of mild-to-moderate cured patients was 11.5±5.7 days. The prevalence of symptoms significantly varied according to age and sex. Young patients more frequently had ear, nose, and throat complaints, whereas elderly individuals often presented fever, fatigue and loss of appetite. Loss of smell, headache, nasal obstruction and fatigue were more prevalent in female patients. The loss of smell was a key symptom of mild-to-moderate Covid19 patients and was not associated with nasal obstruction and rhinorrhea. Loss of smell persisted at least 7 days after the disease in 37.5% of cured patients. Conclusion:The clinical presentation of mild-to-moderate Covid-19 substantially varies according to the age and the sex characteristics of patients. Olfactory dysfunction seems to be an important underestimated symptom of mild-to-moderate Covid-19 that needs to be recognized as such by the WHO.

Objective. To investigate prevalence and recovery of olfactory dysfunction (OD) in COVID-19 patients according to the disease severity.Methods. From 22 March to 3 June 2020, 2581 COVID-19 patients were identified from 18 European hospitals. Epidemiological and clinical data were extracted at baseline and within the 2-month post-infection.Results. The prevalence of OD was significantly higher in mild form (85.9%) compared with moderate-to-critical forms (4.5-6.9%; P = 0.001). Of the 1916 patients with OD, 1363 completed the evaluations (71.1%). A total of 328 patients (24.1%) did not subjectively recover olfaction 60 days after the onset of the dysfunction. The mean duration of self-reported OD was 21.6 AE 17.9 days. Objective olfactory evaluations identified hyposmia/anosmia in 54.7% and 36.6% of mild and moderate-tocritical forms, respectively (P = 0.001). At 60 days and 6 months, 15.3% and 4.7% of anosmic/hyposmic patients did not objectively recover olfaction, respectively. The higher baseline severity of objective olfactory evaluations was strongly predictive of persistent OD (P < 0.001). Conclusion.OD is more prevalent in mild COVID-19 forms than in moderate-to-critical forms. OD disappeared in 95% of patients regarding objective olfactory evaluations at 6 months.

Fuzzy Actor-Critic Learning (FACL) and Fuzzy Q-Learning (FQL) are reinforcement learning methods based on Dynamic Programming (DP) principles. In this paper, they are used to tune online the conclusion part of Fuzzy Inference Systems (FIS). The only information available for learning is the system feedback, which describes in terms of reward and punishment the task the fuzzy agent has to realize. At each time step, the agent receives a reinforcement signal according to the last action it has performed in the previous state. The problem involves optimizing not only the direct reinforcement, but also the total amount of reinforcements the agent can receive in the future. To illustrate the use of these two learning methods, we first applied them to a problem that involves finding a fuzzy controller to drive a boat from one bank to another, across a river with a strong nonlinear current. Then, we used the well-known Cart-Pole Balancing and Mountain-Car problems to be able to compare our methods to other reinforcement learning methods and focus on important characteristic aspects of FACL and FQL. We found that the genericity of our methods allows us to learn every kind of reinforcement learning problem (continuous states, discrete/continuous actions, various type of reinforcement functions). The experimental studies also show the superiority of these methods with respect to the other related methods we can find in the literature. Index Terms-DynamicProgramming (DP), fuzzy logic, learning, Markovian Decision Problem (MDP), reinforcement.

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