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Great deviations in building energy consumption simulation are attributed to the simplified settings of occupants' air conditioning (AC) usage schedules. This study was designed to develop a method to quantify the uncertainty and randomness of AC usage behavior and incorporate the model into simulations, in order to improve the prediction performance of AC energy consumption. Based on long-term onsite monitoring of household thermal environments and AC usage patterns, two stochastic models were built using unsupervised cluster and statistical methods. Based on the Monte Carlo method, the AC operation schedule was generated through AC opening duration, setpoints, and other relevant parameters, and was further incorporated into EnergyPlus. The results show that the ideally deterministic AC operation settings from the standard significantly overestimate the cooling energy consumption, where the value based on the fixed mode was 6.35 times higher. The distribution of daily AC energy consumption based on the stochastic modeling was highly consistent with the actual situation, thanks to the accurate prediction of the randomness and dynamics of residents' AC usage patterns. The total cooling energy consumption based on two stochastic models was found to be much closer to the actual values. The work proposes a method of embedding stochastic AC usage models to EnergyPlus 22.1 benefits for an improvement in building energy consumption simulation and the energy efficiency evaluation regarding occupant behavior in the future. [ABSTRACT FROM AUTHOR]

Psoriasis is a genetic chronic disease mediated by the immune system with systemic and cutaneous manifestations that can significantly deteriorate patients' quality of life. Two-three percent of the population worldwide suffer from psoriasis and it imposes a substantial economic burden on patients. The aetiology is mainly related with genes and environmental factors. The pathophysiology of psoriasis is characterized by T cells and dendritic cells, antimicrobial peptides, genetic predispositions, lipoprotein-2, galactosin-3, fractalkine, vaspin, and human neutrophilic peptides, etc. in the progression of psoriasis. For patients with psoriasis, the traditional treatments include corticosteroids, vitamin D 3 analogues, calcineurin inhibitors, methotrexate, cyclosporine, acitretin, phototherapy, and biological agents, etc. Nanodermatology is an emerging, multidisciplinary science that is gaining increasing recognition in the treatment of psoriasis. This review provides a summary of the pathophysiology, epidemiology, clinical diagnosis, and classical pharmacotherapy of psoriasis. The review also summarizes different nanotechnology therapies for effective treatment of psoriasis., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2021 Termedia Sp. z o. o.)