The COVID-19 pandemic has renewed interest in the importance of indoor air quality for health. The spread of respiratory aerosols is the primary mechanism for COVID-19 transmission, making it crucial to understand the role of effective ventilation in managing the risk of disease transmission. The concentration of exhaled carbon dioxide (CO2) in indoor spaces can be used as a proxy measure of ventilation efficiency. Poor indoor air quality has been associated with a range of acute and chronic health problems, including respiratory issues, cardiovascular disease, and cancer. Poor air quality may also impair cognitive performance and productivity. Social and economic inequalities exacerbate the impact of indoor air quality issues, making it crucial to address these problems in an equitable manner. Public libraries have been identified as an effective intermediary for providing education and free air quality monitoring technology to communities, with the ultimate goal of promoting awareness and increasing access to tools to promote accountability for maintaining high indoor air quality standards. The primary objectives of this initiative are to: 1) develop a citizen science toolkit for assessing indoor air quality in public spaces and deploy the toolkit to public libraries in Arizona; and 2) to conduct a program evaluation to determine whether this kit can be effectively deployed through public libraries to promote citizen science efforts and engage community members in promoting healthier indoor air quality, identify areas where improvements can be made, and prepare the program to be scaled to a larger audience.
Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network “mobile” can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.
The relation between flux and fluctuation is fundamental to complex physical systems that support and transport flows. A recently obtained law predicts monotonous enhancement of fluctuation as the average flux is increased, which in principle is valid but only for large systems. For realistic complex systems of small sizes, this law breaks down when both the average flux and fluctuation become large. Here we demonstrate the failure of this law in small systems using real data and model complex networked systems, derive analytically a modified flux-fluctuation law, and validate it through computations of a large number of complex networked systems. Our law is more general in that its predictions agree with numerics and it reduces naturally to the previous law in the limit of large system size, leading to new insights into the flow dynamics in small-size complex systems with significant implications for the statistical and scaling behaviors of small systems, a topic of great recent interest.