Advanced flow cytometry for biomedical applications.

Flow cytometry (FC) is a versatile tool with excellent capabilities to detect and measure multiple characteristics of a population of cells or particles. Notable advancements in in vivo photoacoustic FC, coherent Raman FC, microfluidic FC, and so on, have been achieved in the last two decades, which endows FC with new functions and expands its applications in basic research and clinical practice. Advanced FC broadens the tools available to researchers to conduct research involving cancer detection, microbiology (COVID-19, HIV, bacteria, etc.), and nucleic acid analysis. This review presents an overall picture of advanced flow cytometers and provides not only a clear understanding of their mechanisms but also new insights into their practical applications. We identify the latest trends in this area and aim to raise awareness of advanced techniques of FC. We hope this review expands the applications of FC and accelerates its clinical translation.

Mathematical Modelling of Lockdown Policy for COVID-19.

In this paper, we extend the classic SIR model to find an optimal lockdown policy to balance between the economy and people's health during the outbreak of COVID-19. In our model, we intend to solve a two phases optimisation problem: policymakers control the lockdown rate to maximise the overall welfare of the society; people in different health statuses take different decisions on their working hours and consumption to maximise their utility. We develop a novel method to estimate parameters for the model through various additional sources of data. We use the Cournot equilibrium to model people's behaviour. The analysis of simulation results provides scientific suggestions for policymakers to make critical decisions on when to start the lockdown and how strong it should be during the whole period of the outbreak.

Optimal lockdown policy for vaccination during COVID-19 pandemic.

As the COVID-19 spreads across the world, many nations impose lockdown measures at the early stage of the pandemic to prevent the spread of the disease. Controversy surrounds the lockdown as it is a choice between economic freedom and public health. The ultimate solution to a pandemic is to vaccinate a massive population to achieve herd immunity. However, the whole vaccination programme is a long and complicated process. The virus and the vaccine will coexist for quite a long time. How to gradually ease the lockdown based on vaccination progress is an important question, as both economic and epidemiological issues are involved. In this paper, we extend the classic SIR model to find optimal decision to balance between economy and public health in the process of vaccination rollout. The model provides an approach of vaccine value estimation. Our results provide scientific suggestion for policymakers to make important decisions on how to gradually relax the strength for the lockdown over the entire vaccination cycle.

How the COVID-19 Outbreak Affected Organizational Citizenship Behavior in Emergency Construction Megaprojects: Case Study from Two Emergency Hospital Projects in Wuhan, China

The rapid construction of emergency hospitals in areas with a severe COVID-19 outbreak was one of the effective ways to contain and fight the pandemic. However, such rapid construction megaprojects need more than a formal management system to drive the organizational citizenship behavior (OCB) of participants in order to compensate for the lack of formal rules and regulations. Two emergency hospitals especially built for COVID-19 are taken as case studies in this paper to establish a mechanism model and examine the impact of the perceived strength of the COVID-19 event on the emergency megaproject citizenship behavior (EMCB) based on affective events theory (AET). Data from 340 project participants in the two hospitals were collected and tested using structural equation modeling. The results demonstrate that first, the positive affect induced by the COVID-19 event is the direct antecedent that promotes EMCB. Participants' cognition of event criticality and event novelty was seen to have a positive driving effect on the positive affect. However, their cognition of event urgency and event disruption only triggers negative affect. Second, the positive affect induced by the COVID-19 event was seen to have a strong positive and direct promoting effect on the six dimensions of EMCB. Contrary to expectations, the negative affect induced by the COVID-19 event does not significantly influence the six dimensions of EMCB. This study provides empirical suggestions for project managers on how to motivate EMCB through public emergency management to help achieve project objectives. [ABSTRACT FROM AUTHOR] Copyright of Journal of Management in Engineering is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An evaluation of mathematical models for the outbreak of COVID-19.

Mathematical modelling performs a vital part in estimating and controlling the recent outbreak of coronavirus disease 2019 (COVID-19). In this epidemic, most countries impose severe intervention measures to contain the spread of COVID-19. The policymakers are forced to make difficult decisions to leverage between health and economic development. How and when to make clinical and public health decisions in an epidemic situation is a challenging question. The most appropriate solution is based on scientific evidence, which is mainly dependent on data and models. So one of the most critical problems during this crisis is whether we can develop reliable epidemiological models to forecast the evolution of the virus and estimate the effectiveness of various intervention measures and their impacts on the economy. There are numerous types of mathematical model for epidemiological diseases. In this paper, we present some critical reviews on mathematical models for the outbreak of COVID-19. Some elementary models are presented as an initial formulation for an epidemic. We give some basic concepts, notations, and foundation for epidemiological modelling. More related works are also introduced and evaluated by considering epidemiological features such as disease tendency, latent effects, susceptibility, basic reproduction numbers, asymptomatic infections, herd immunity, and impact of the interventions.