Improving the energy efficiency of the building sector has become an increasing concern in the world, given the alarming reports of greenhouse gas emissions. The management of building energy systems is considered an essential means for achieving this goal. Predicting indoor temperature constitutes a critical task for the management strategies of these systems. Several approaches have been developed for predicting indoor temperature. Determining the most effective has thus become a necessity. This paper contributes to this objective by comparing the ability of seven machine learning algorithms (ML) and the thermal gray box model to predict the indoor temperature of a closed room. The comparison was conducted on a set of data recorded in a room of the Laboratory of Civil Engineering and geo-Environment (LGCgE) at Lille University. The results showed that the best prediction was obtained with the artificial neural network (ANN) and extra trees regressor (ET) methods, which outperformed the thermal gray box model.

Post-COVID-19 condition is characterized by many symptoms starting from fatigue and dyspnea, while more persistent symptoms can include smell and taste dysfunction, joint pain, palpitations, gastrointestinal (GI) issues, and headaches. 1 The COVID-19 pandemic was proved to affect mental and cognitive health, especially in affecting anxiety and depression among patients. 2 In addition to affecting sleep quality, many studies assessed the prevalence of insomnia during the pandemic, which ranges between 37.6% and 23.8% based on previous studies. 3,4 When it comes to the post-COVID-19 condition, a study conducted by Xu et al. indicates that rates of insomnia were 26.4% among COVID-19 survivors 2 weeks after discharge, 5 although there are not enough data available yet to better describe the association between post COVID-19 and insomnia. Interestingly, at Jordan University Hospital (JUH) in Amman, Jordan, a case of severe insomnia was reported in which insomnia symptoms started after COVID-19 and lasted for 6 months which led the patient to visit JUH. | CASE PRESENTATIONRA is a 41-year-old female patient, a pharmacist, and a mother of four kids. She is a nonsmoker and does not consume any alcohol. RA is allergic to NSAIDs.

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