The model could be used in the study of the interaction between respiratory and cardiovascular systems in pathophysiological conditions.Fuzzy set theory and a series of theories derived from it have been widely used to deal with uncertain phenomena in multi-criterion decision-making problems. However, few methods except the Z-number considered the reliability of information. In this paper, we propose a multi-criterion decision-making method based on the Dempster-Shafer (DS) theory and generalized Z-numbers. To do so, inspired by the concept of hesitant fuzzy linguistic term set, we extend the Z-number to a generalized form which is more in line with human expression habits. Afterwards, we make a bridge between the knowledge of Z-numbers and the DS evidence theory to integrate Z-valuations. The identification framework in the DS theory is used to describe the generalized Z-numbers to avoid ambiguity. Then, the knowledge of Z-numbers is used to derive the basic probability assignment of evidence and the synthetic rules in the DS theory are used to integrate evaluations. An illustrative example of medicine selection for the patients with mild symptoms of the COVID-19 is provided to show the effectiveness of the proposed method.Laboratory-acquired infections (LAIs) are defined as infections of laboratory staff by exposure to pathogenic microorganisms during an experimental procedure. For a biosafety level-3 (BSL-3) laboratory with a high potential of exposure, reducing risks and threats relevant to LAIs has become a critical concern, especially after the recent outbreak of Novel Coronavirus causing COVID-19 in Wuhan, China. This study aimed to investigate the spatial-temporal characteristics of bioaerosol dispersion and deposition of two kinds of bioaerosols (Serratia marcescens and phage ΦX174). A combination of laboratory experiment and numerical simulation was adopted to explore bioaerosol removal.  https://www.selleckchem.com/products/bgb-8035.html  Three-dimensional concentration iso-surface mapping in conjunction with flow field analysis was employed to elucidate bioaerosol migration and deposition behavior. The total deposition number and unit area deposition ratio were calculated for different surfaces. The results indicate that bioaerosol concentration remains stable for up to 400 s after release, and that almost 70% of all bioaerosol particles become deposited on the surfaces of walls and equipment. Vortex flow regions and high-concentration regions were determined, and the most severely contaminated surfaces and locations were identified. Our results could provide the scientific basis for controlling the time interval between different experiments and also provide guidelines for a laboratory disinfection routine. Furthermore, future work regarding laboratory layout optimization and high efficiency air distribution for bioaerosol removal in a BSL-3 laboratory should be emphasized.In this paper, we examine how conservation-planning and local regeneration in historic urban cores have been re-shaped under austerity conditions and how local planners and local government more generally have negotiated or navigated this emerging austerity terrain. We seek to contribute to wider debates on 'austerity urbanism', by examining the impacts of austerity on local planning and how planning officials have attempted to moderate austerity largely imposed by central government (entrenched roll-back neoliberalism) but often through the further roll-out of neoliberalism in local growth strategies. Drawing on the experience of three Irish urban centres, we examine efforts to 'sell' the historic city. Both nationally and within the three case study areas, a common overarching theme was evident in the initial post-crisis response to urban development an emphasis on utilising heritage as a potential economic regeneration pathway. However, while drawing on intangible heritage and heritage narratives for place-branding, the actual protection of tangible built heritage assets was undermined through a greater emphasis on 'flexible' planning responses to managing heritage, which seek to minimise barriers to development.Growing concern about major threats, including climate change, environmental disasters, and other hazards, is matched with the increased interest and appeal of the concept of urban resilience. Much scholarly attention has focused on how to define urban resilience, in addition to raising questions about its applicability and usefulness. But those debates typically overlook questions of implementation. Implementation is important not only for how cities respond to threats but also because it can influence how urban resilience is perceived, discussed, and understood. The policy literature suggests that implementation is rarely straightforward and has ideological and normative perspectives embedded within it. Building on this literature, this paper argues that urban resilience implementation raises its own conceptual questions for both theory and practice. Further, implementing urban resilience entails its own unique challenges, such as extensive coordination, maintaining adaptability, divergent time horizons, and diverse outcomes. The paper also introduces the idea of resilience resistance as a new challenge for urban resilience. Resistance refers to the condition in which governance systems inherently develop barriers to change, flexibility, and adaptability through implementation. Several aspects of resistance are highlighted, including fatigue, complacency, and overconfidence. However, the implementation process can also have unintended positive effects on a city's capacity to prepare for and respond to shocks.This study presents an in-depth investigation on the transmission of the novel coronavirus (COVID-19) from the urban perspective. It focuses on the "aftermath" of the outbreak and the spread of the infection among cities. Especially, this study provides insights of the fundamentals of the factors that may affect the spread of the infection in cities, where the marginal effects of some most influential factors to the virus transmission are estimated. It reveals that the distance to epicenter is a very strong influential factor, and is negatively linked with the spread of COVID-19. In addition, subway, wastewater and residential garbage are positively connected with the virus transmission. Moreover, both urban area and population density are negatively associated with the spread of COVID-19 at the early stage of the epidemic. Furthermore, this study also provides high precision estimation of the number of COVID-19 infection in Wuhan city, which is the epicenter of the outbreak in China. Based on the real-world data of cities outside Wuhan on March 2, 2020, the estimated number is 56,944.