RESUMEN
Physics II is an undergraduate course on basic electromagnetism that I teach for engineers, and it includes topics from optics as a natural application. Among the many challenges of conducting video lectures during the local restrictions of the SARS-CoV-2 epidemic was finding demonstration material. In this article, I describe how these restrictions led me to develop my home version of Michelson's experiment as an alternative to Young's, and how I was able to highlight the circumstances in which both experiments turn out to be two particular cases of the same underlying idea. [ FROM AUTHOR]
RESUMEN
In a vicious cycle, the rise of global temperatures increases demand for cooler indoor temperatures, while increased use of air conditioning leads to warmer outdoor temperatures. Most modern indoor-climate control systems aim to maintain thermal neutrality i.e., a near-constant indoor temperature, over entire spaces, if not also over time. This consumes significant resources while causing thermal discomfort for some indoor occupants. In an online study, this work explored user perceptions towards dynamic indoor temperatures, which can lead to significant resource conservation. The study included two conditions, early versus late exposure to a range-based thermostat, to assess its user acceptance, in the context of study participants' 1) summer temperatures, 2) general temperature preferences and habits, 3) temperature-unit preference, and 4) extra-thermal factors. Due to local COVID-19 restrictions on in-person research, initial results will report on users' behavioral intention. © 2022 Elsevier B.V.. All rights reserved.
RESUMEN
A knowledge-based cybernetic framework model representing the dynamics of SARS-CoV-2 inside the human body has been studied analytically and in silico to explore the pathophysiologic regulations. The following modeling methodology was developed as a platform to introduce a predictive tool supporting a therapeutic approach to Covid-19 disease. A time-dependent nonlinear system of ordinary differential equations model was constructed involving type-I cells, type-II cells, SARS-CoV-2 virus, inflammatory mediators, interleukins along with host pulmonary gas exchange rate, thermostat control, and mean pressure difference. This formalism introduced about 17 unknown parameters. Estimating these unknown parameters requires a mathematical association with the in vivo sparse data and the dynamic sensitivities of the model. The cybernetic model can simulate a dynamic response to the reduced pulmonary alveolar gas exchange rate, thermostat control, and mean pressure difference under a very critical condition based on equilibrium (steady state) values of the inflammatory mediators and system parameters. In silico analysis of the current cybernetical approach with system dynamical modeling can provide an intellectual framework to help experimentalists identify more active therapeutic approaches.