ABSTRACT
In response to the construction process of Healthy China. it is rather important to create a safe, healthy and energy-efficient indoor environment for public buildings. The public building space is often densely populated, with a large flow of people and many types of air pollution, which presents non-uniform dynamic distribution characteristics. This brings great challenges to the control of indoor air safety, especially during the pandemic period of COVID-19. Excessive ventilation may not only cause large energy waste. but also lead to cross-contamination and even a cluster of infection. In this paper, an operation and maintenance (O&M) control system for indoor air safety is developed based on the core concepts and basic methods of human ergonomics. In this system, one of the important human environmental variables is focused for control, i.e.. indoor air pollution level. Especially after the outbreak of COVID-19. droplets and droplet nuclei from respiration are the most significant air pollution categories required for mitigation. Towards the efficient control of air pollution in large public buildings. it should further take into account the interaction of human, equipment and machines (i.e., ventilation_ air purification and disinfection and intelligent control system) and building environment. Firstly, on the basis of the online monitoring of indoor air pollution concentration and personnel flow, the non-uniform dynamic distribution of indoor pollutants and personnel can be obtained by using the non-uniform and low-dimensional rapid prediction models and computer vision processing. Then, the optimal setting results of ventilation parameters (e.g., ventilation modes, supply air rate. etc.) can be outputted by the environmental control decision system. Finally, based on a combination of monitoring sensors, controllers and actuator hardware equipment (at the location of fans or dampers), the intelligent regulation and control of ventilation system can be realized, aimed at minimizing energy consumption and reducing pollutant concentration and exposure level. Meanwhile, the air purification and disinfection system (especially for the disinfection of virus particles) are operated under the condition of the ventilated environment, which can serve as a powerful auxiliary to the maintenance of indoor air safety. The workflow and effect of the O&M control system are demonstrated by an engineering application case of the front hall in the International Convention and Exhibition Center. The results indicate that the non-uniform and low-dimensional rapid prediction model for pollutant concentration is effective for the ventilation control with the average prediction difference of 11.9%. The implementation of the intelligent ventilation system can reduce the risk of human infection to less than 4%. and its energy-saving ratio for the ventilation can be as high as about 45%. Through optimizing the layout strategies of disinfection devices based on the intelligent ventilation control, the space accessibility of negative oxygen ions can be well accepted, to further increase the removal efficiency of air pollution. The calculated value of space disinfection rate is more than 99%, which can further reduce the risk of infection by 1-2 orders of magnitude. This study can provide an important reference for the promotion and upgrading of O&M control system for indoor air safety.
ABSTRACT
Purpose: The purpose of this paper is exploring the effects of segment dynamic and temporal dynamic triggered by the COVID-19 pandemic on classifying service quality attributes, thereby formulating improvement strategies to satisfy customers and respond to threats. Design/methodology/approach: Given the dynamics of the attractive quality theory, this paper designs a framework with four phases by embedding techniques of text mining and deep learning based on evidence from online reviews. Findings: This paper figures out dynamics of service quality attributes for distinct segments and their dynamic proportion along with different stages of the pandemic. Another finding demonstrates segment dynamic and temporal dynamic effects of sentiments toward service quality attributes on customer satisfaction under the impacts of pandemic. Classification results and improvement strategies are derived for varying segments at different pandemic situations. Practical implications: This paper reveals dynamic effects on classifying service quality attributes, which contributes to assisting hospitality practitioners from different segments in improving service quality when facing with the challenges of crisis and potential risks. Originality/value: Given hospitality industry is time- and segment-sensitive, the authors achieve the quantification of dynamics of attractive quality theory and extend it into hospitality marketing and crisis management from the perspective of dynamics with evidence from online reviews. © 2022, Emerald Publishing Limited.
ABSTRACT
Purpose The purpose of this paper is exploring the effects of segment dynamic and temporal dynamic triggered by the COVID-19 pandemic on classifying service quality attributes, thereby formulating improvement strategies to satisfy customers and respond to threats. Design/methodology/approach Given the dynamics of the attractive quality theory, this paper designs a framework with four phases by embedding techniques of text mining and deep learning based on evidence from online reviews. Findings This paper figures out dynamics of service quality attributes for distinct segments and their dynamic proportion along with different stages of the pandemic. Another finding demonstrates segment dynamic and temporal dynamic effects of sentiments toward service quality attributes on customer satisfaction under the impacts of pandemic. Classification results and improvement strategies are derived for varying segments at different pandemic situations. Practical implications This paper reveals dynamic effects on classifying service quality attributes, which contributes to assisting hospitality practitioners from different segments in improving service quality when facing with the challenges of crisis and potential risks. Originality/value Given hospitality industry is time- and segment-sensitive, the authors achieve the quantification of dynamics of attractive quality theory and extend it into hospitality marketing and crisis management from the perspective of dynamics with evidence from online reviews.
ABSTRACT
In response to the construction process of Healthy China. it is rather important to create a safe, healthy and energy-efficient indoor environment for public buildings. The public building space is often densely populated, with a large flow of people and many types of air pollution, which presents non-uniform dynamic distribution characteristics. This brings great challenges to the control of indoor air safety, especially during the pandemic period of COVID-19. Excessive ventilation may not only cause large energy waste. but also lead to cross-contamination and even a cluster of infection. In this paper, an operation and maintenance (O&M) control system for indoor air safety is developed based on the core concepts and basic methods of human ergonomics. In this system, one of the important human environmental variables is focused for control, i.e.. indoor air pollution level. Especially after the outbreak of COVID-19. droplets and droplet nuclei from respiration are the most significant air pollution categories required for mitigation. Towards the efficient control of air pollution in large public buildings. it should further take into account the interaction of human, equipment and machines (i.e., ventilation_ air purification and disinfection and intelligent control system) and building environment. Firstly, on the basis of the online monitoring of indoor air pollution concentration and personnel flow, the non-uniform dynamic distribution of indoor pollutants and personnel can be obtained by using the non-uniform and low-dimensional rapid prediction models and computer vision processing. Then, the optimal setting results of ventilation parameters (e.g., ventilation modes, supply air rate. etc.) can be outputted by the environmental control decision system. Finally, based on a combination of monitoring sensors, controllers and actuator hardware equipment (at the location of fans or dampers), the intelligent regulation and control of ventilation system can be realized, aimed at minimizing energy consumption and reducing pollutant concentration and exposure level. Meanwhile, the air purification and disinfection system (especially for the disinfection of virus particles) are operated under the condition of the ventilated environment, which can serve as a powerful auxiliary to the maintenance of indoor air safety. The workflow and effect of the O&M control system are demonstrated by an engineering application case of the front hall in the International Convention and Exhibition Center. The results indicate that the non-uniform and low-dimensional rapid prediction model for pollutant concentration is effective for the ventilation control with the average prediction difference of 11.9%. The implementation of the intelligent ventilation system can reduce the risk of human infection to less than 4%. and its energy-saving ratio for the ventilation can be as high as about 45%. Through optimizing the layout strategies of disinfection devices based on the intelligent ventilation control, the space accessibility of negative oxygen ions can be well accepted, to further increase the removal efficiency of air pollution. The calculated value of space disinfection rate is more than 99%, which can further reduce the risk of infection by 1-2 orders of magnitude. This study can provide an important reference for the promotion and upgrading of O&M control system for indoor air safety.
ABSTRACT
Coronaviruses are RNA viruses. We should be alerted from the outbreak of the severe acute respiratory syndrome coronavirus (SARS-CoV) in 2003, the discovery of the human coronavirus NL63 (HCoV-NL63) in 2004 and the pneumonia outbreak caused by the novel coronavirus in 2019 (2019-nCoV). Coronaviruses can adhere to mucous membranes of the eye, nose, mouth, respiratory tract and digestive tract through various media, which leads to inflammatory reaction, pulmonary fibrosis, kidney failure and death in severe cases. As an exposed organ, the eye can also be infected. With the progress of molecular technology and the in-depth research of coronaviruses, there have been seven known coronaviruses that can infect humans, among which HCoV-NL63, SARS-CoV and 2019-nCoV can cause eye diseases. This article summarizes and analyzes the latest research results at home and abroad concerning the structural characteristics, transmission routes, ocular pathogenic characteristics and treatment of HCoV-NL63, SARS-CoV and 2019-nCoV, in order to provide reference for clinical diagnosis and treatment. (Chin J Ophthalmol, 2021, 57: 871-875).
Subject(s)
COVID-19 , Coronavirus NL63, Human , Eye Diseases , Humans , SARS-CoV-2ABSTRACT
Traditional Chinese medicine (TCM) network pharmacology and molecular docking technology were applied to explore the mechanism of anti-coronavirus pneumonia (coronavirus disease 2019, COVID-19) of Qingfei Paidu decoction. The Chinese Pharmacopoeia (2015 edition) and Traditional Chinese Medicine Systems Pharmacology (TCMSP), OMIM (Online Mendelian Inheritance in Man), GeneCard, STRING, and others online databases are used for building a series of network, and selecting the core target and analyzing the signal pathway. Finally, we make molecular docking predictions for the important compounds. The results showed that the Qingfei Paidu decoction compound-pneumonia target network contained 292 compounds and 214 corresponding targets, and the core targets involved AKT1 (AKT serine/threonine kinase 1), IL6 (interleukin 6), MAPK8 (mitogen-activated protein kinase 8), MAPK1 (mitogen-activated protein kinase 1), and JUN (jun proto-oncogene). GO (Gene Ontology) function enrichment analysis yielded 858 GO entries, and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment screening yielded 122 related pathways, including hypoxia inducible factor-1 (HIF-1) and Toll-like receptor (TLRs) signaling pamways related to pneumonia, as well as T-cell receptor (TCR) signaling pathway related to lung injury protection. The molecular docking results showed that some core compounds of the Chinese herbal medicine of Qingfei Paidu decoction have a certain degree of affinity for 2019-novel coronavirus (2019-nCoV) main protease (3C-like protease, 3CLpro) and angiotensin-converting enzyme 2 (ACE2). In this paper, we preliminarily explored the potential therapeutic mechanism for Qingfei Paidu decoction to against COVID-19 and predicted the active ingredients. We hope mat me results will help to the further study on me active ingredients and mechanism of Qingfei Paidu decoction to COVID-19.