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Air-borne pollutants in particulate matter (PM) form, produced either physically during industrial processes or certain biological routes, have posed a great threat to human health. Particularly during the current COVID-19 pandemic, effective filtration of the virus is an urgent matter worldwide. In this review, we first introduce some fundamentals about PM, including its source and classification, filtration mechanisms, and evaluation parameters. Advanced filtration materials and their functions are then summarized, among which polymers and MOFs are discussed in detail together with their antibacterial performance. The discussion on the application is divided into end-of-pipe treatment and source control. Finally, we conclude this review with our prospective view on future research in this area. (c) 2022 Institute of Process Engineering, Chinese Academy of Sciences. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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Background: Although COVID-19 vaccines have been developed, the number of people willing to receive the vaccine has not yet reached the level for herd immunity. Using the health belief model with governmental information support, this study examined private self-consciousness in combination with other factors that influence the intention to receive the COVID-19 vaccine. Materials and methods: The perceived susceptibility to and perceived seriousness of COVID-19, perceived benefits of and perceived barriers to the COVID-19 vaccine, governmental information support, private self-consciousness, and the intention to receive the vaccine were examined in 523 adults. The data were analyzed with partial least squares regression. Results: The results indicate that private self-consciousness reduces the effect of perceived susceptibility on the intention to receive the vaccine and the negative effect of the perceived barriers to receiving it on intention. Conclusion: The information provided by the public health department should focus on perceived seriousness and perceived benefits because they are not affected by private self-consciousness.
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Air transportation is eminent for its fast speed and low cargo damage rate among other ways. However, it is greatly limited by emergent factors like bad weather and current COVID-19 epidemic, where irregular flights may occur. Confronted with the negative impact caused by irregular flight, it is vital to rearrange the preceding schedule to reduce the cost. To solve this problem, first, we established a multi-objective model considering cost and crew satisfaction simultaneously. Secondly, due to the complexity of irregular flight recovery problem, we proposed a tabu-based multi-objective particle swarm optimization introducing the idea of tabu search. Thirdly, we devised an encoding scheme focusing on the characteristic of the problem. Finally, we verified the superiority of the tabu-based multi-objective particle swarm optimization through the comparison against MOPSO by the experiment based on real-world data. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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COVID-19 has led to immense impacts on the hospitality sector, putting millions of jobs at risk. The uncertainty has resulted in significant psychological effects on service staff. Developing on micro-level interpersonal interactions between line managers and service staff, this article aims to propose a bottom-up approach to alleviate service staff's anxiety and enhance their work resilience during and after the pandemic. The proposed conceptual framework synthesised the personal uncertainty constructs, self-determination theory (SDT) and leader-member exchange (LMX) to address the psychological issues that emerged from a prolonged ambiguous and unsettled period. The framework proposes that interpersonal exchanges at the micro-level can strengthen service staff's intrinsic motivation and resilience. This article offers new insights into crisis management research and practice in the hospitality sector by developing a people-centred approach. At the micro-level, this framework offers a holistic strategy, including a flat team structure, uncertainty-embracing organisational environment, transparent decision-making process and sympathetic behaviours from leaders to facilitate service staff to develop greater coping mechanisms for the unknown future. Furthermore, this framework provides organisations preliminary guidelines to establish a longitudinal preventive strategy to strengthen employees' work resilience. © The Author(s) 2022.
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During the COVID-19 pandemic, online meetings became common for daily teamwork in the home office. To understand the opportunities and challenges of meeting in virtual reality (VR) compared to videoconferences, we conducted the weekly team meetings of our human-computer interaction research lab on five off-the-shelf online meeting platforms over 4 months. After each of the 12 meetings, we asked the participants (N = 32) to share their experiences, resulting in 200 completed online questionnaires. We evaluated the ratings of the overall meeting experience and conducted an exploratory factor analysis of the quantitative data to compare VR meetings and video calls in terms of meeting involvement and co-presence. In addition, a thematic analysis of the qualitative data revealed genuine insights covering five themes: spatial aspects, meeting atmosphere, expression of emotions, meeting productivity, and user needs. We reflect on our findings gained under authentic working conditions, derive lessons learned for running successful team meetings in VR supporting different kinds of meeting formats, and discuss the team's long-term platform choice. Copyright © 2023 Bonfert, Reinschluessel, Putze, Lai, Alexandrovsky, Malaka and Döring.
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The COVID-19 global pandemic outbreak has presented higher education institutions with the impediment of transforming to a new curriculum, pedagogy, and educational management. Inevitable transformation in higher education triggered by COVID-19 is still ongoing, albeit most countries are now at the endemic stage. However, transformation should not just be about simply changing instructional delivery. The COVID-19 pandemic is a unique opportunity for educators and policymakers to rethink education systems and reimagine what is important, necessary, and desirable for future generations. Hence, this study focuses on identifying strategies for higher education institutions to deal with unknown uncertainties during and after the pandemic. Expert Opinion Method was conducted involving five professors who are senior management in their respective universities and have been directly involved in formulating strategies and policies during the pandemic. Four major dimensions were developed from the findings: (1) Resilience and Change Management, (2) Digital Transformation and Online Learning, (3) Curriculum Change, and (4) Sustainability. Flexibility is also the most common issue discussed by experts. Based on thematic analysis, post COVID-19 strategic framework for higher education institution sustainability is proposed. In addition, this study can be a roadmap for educators, policymakers, and all relevant stakeholders to prepare for future disruptions in the education sector.
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The Covid-19 pandemic has caused large scale of people in danger of infection and death during early outbreak period. Precise screening of the new coronal virus through PCR (Polymerase Chain Reaction) testing on the nasal or oral sample becomes very critical for epidemic control. This study proposes the idea of using a robotic remote manipulation platform for oral and nasal specimen collection operated by medical staffs. The oral cavity image was captured by a compact camera and then displayed on the human machine interface for the medical staffs to confirm the target region for sample collection. The wiping action of the robot was accomplished with a force control with force sensing the contact force between the cotton swab and soft tissue. A prototype of the swabbing robot has been implemented to verify the feasibility and safety of the remote robot-assisted specimen collection. © 2022 IEEE.
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It is evident that increasing the intensive-care-unit (ICU) capacity and giving priority to admitting and treating patients will reduce the number of COVID-19 deaths, but the quantitative assessment of these measures has remained inadequate. We develop a comprehensive, non-Markovian state transition model, which is validated through the accurate prediction of the daily death toll for two epicenters: Wuhan, China and Lombardy, Italy. The model enables prediction of COVID-19 deaths in various scenarios. For example, if appropriate treatment priorities had been used, the death toll in Wuhan and Lombardy would have been reduced by about 10% and 7%, respectively. The strategy depends on the epidemic scale and is more effective in countries with a younger population structure. Analyses of data from China, South Korea, Italy, and Spain suggest that countries with less per capita ICU medical resources should implement this strategy in the early stage of the pandemic to reduce mortalities. We emphasize that the results of this paper should be interpreted purely from a scientific and a quantitative-analysis point of view. No ethical implications are intended and meaningful. © 2022 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.
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As Corona Virus Disease (COVID-19) pandemic strikes the world, retail industry has been severely impacted by staff shortage and high risk of virus outbreak. However, most of existing smart retail solutions is associated with high deployment and maintenance cost that are infeasible for small retail stores. As an effort to mitigate the issue, a computer vision-powered smart cashierless checkout system is proposed based on You Only Look Once (YOLO) v5 and MobileNet V3 for product recognition along with 3-stage image synthesis framework that includes crop and paste algorithm, GAN-based shadow synthesis and light variation algorithm. By using 3000 images generated from the framework, proposed model was trained and optimized with TensorRT. Experimental result shows that the lightweight model can be deployed on affordable edge devices like Jetson Nano while achieving high Mean Average Precision (mAP) of 98.2%, Checkout Accuracy (cAcc) of 89.17% with only 0.142s of inference time. © 2022, Success Culture Press. All rights reserved.
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BACKGROUND: Asthma can manifest in a variety of clinical phenotypes like cough variant asthma, chest tightness variant asthma (CTVA), and masked asthma. Patients with CTVA usually have a singular or primary complaint of chest tightness, which is often overlooked or misdiagnosed due to the lack of characteristic asthma symptoms. We hereby report a case of CTVA managed by omalizumab. CASE REPORT: A 15-year-old female patient reported to us with repeated coughing persisting for 3 weeks. Initial treatment with standard asthma drugs had minimal effect. Later during the disease, chest tightness became the primary symptom, and she was managed with steroids, ß2 receptor agonists, and leukotriene receptor agonists but without complete relief. Based on clinical signs and symptoms, the response to baseline drugs, and results of bronchial provocation test, the diagnosis was revised to CTVA, and the patient was started on Omalizumab in addition to baseline drugs, which significantly improved her condition. CONCLUSIONS: CTVA is difficult to diagnose due to its insidious symptoms and poor characteristics. Improper treatment can lead to uncontrolled disease, negative psychological issues, and reduced quality of life. Comprehensive assessment of children's airway inflammation level, lung function, bronchial provocation test, and responsiveness to drug therapy should be performed for accurate diagnosis. Omalizumab in combination with standard drugs can significantly improve the outcomes of CTVA.
Subject(s)
Anti-Asthmatic Agents , Asthma , Anti-Asthmatic Agents/therapeutic use , Asthma/diagnosis , Asthma/drug therapy , Bronchial Provocation Tests , Cough , Female , Humans , Omalizumab/therapeutic use , Quality of LifeABSTRACT
Air pollution has become an essential issue in environmental protection. The Air Quality Index (AQI) is often used to determine the severity of air pollution. When the AQI reaches the red level, the proportion of asthma patients seeking medical treatment will increase by 30% more than usual. If the AQI can be predicted in advance, the benefits of early warning can be achieved. In recent years, a scholar has proposed an alpha-Sutte indicator which shows its excellence in time series prediction. However, the calculation of alpha-Sutte indicators uses a fixed weight. Thus, a beta-Sutte indicator, using a dynamic weight with a high computation cost, has appeared. However, the computational complexity and sliding window required of the beta-Sutte indicator are still high compared to the alpha-Sutte indicator. In this study, a modified gamma-Sutte indicator, using a dynamic weight with a lower computational cost than the beta-Sutte indicator, is proposed. In order to prove that the proposed gamma-Sutte indicator has good generalization ability and is transferable, this study uses data from different regions and periods to predict the AQI. The results showed that the prediction accuracy of the gamma-Sutte indicator proposed was better than other methods.
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Purpose: COVID-19 has led to 4 million deaths worldwide since 2019. COVID-19 patients with cancers likely express biomarker changes in circulation. While many biomarker studies focused on COVID-19 diagnosis and prognosis, the panel of biomarkers used in SARS-CoV-2 infected cancer patients for COVID-19 severity and prognosis are largely unclear. Therefore, this systematic review aims to determine what biomarkers have been measured in cancer patients with COVID-19 and their prognostic utility. Methods: A systematic literature review in PubMed, Embase, and Scopus was performed on June 16th, 2021. The search keywords coronavirus, neoplasm, biomarkers, and disease progression were used to filter out 17 eligible studies, which were then carefully evaluated. Results: A total of 4,168 patients from 17 eligible articles were included in this study. Sixteen types of cancer and 60 biomarkers were identified. The majority of changed biomarkers in the cancer patients with COVID-19 compared to the healthy group and non-cancer patients with COVID-19 were biochemical and inflammatory markers. The up-regulated markers, including CRP, D-dimer, ferritin, IL-2R, IL-6, LDH, and PCT, were identified in eligible studies. Albumin and hemoglobin were significantly down-regulated in cancer patients with COVID-19. Additionally, we observed that the SARS-CoV-2 infected cancer patients with lower levels of CRP, ferritin, and LDH successfully survived from antiviral drug and immunotherapy for COVID-19 treatments. Conclusion: Several important clinical biomarkers, such as CRP, ferritin, and LDH, may serve as the prognostic markers to predict the outcomes following COVID-19 treatment and monitor the deterioration of COVID-19 in cancer patients.
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As with the rapid development of air transportation and potential uncertainties caused by abnormal weather and other emergencies, such as Covid-19, irregular flights may occur. Under this situation, how to reduce the negative impact on airlines, especially how to rearrange the crew for each aircraft, becomes an important problem. To solve this problem, firstly, we established the model by minimizing the cost of crew recovery with time-space constraints. Secondly, in view of the fact that crew recovery belongs to an NP-hard problem, we proposed an improved particle swarm optimization (PSO) with mutation and crossover mechanisms to avoid prematurity and local optima. Thirdly, we designed an encoding scheme based on the characteristics of the problem. Finally, to verify the effectiveness of the improved PSO, the variant and the original PSO are used for comparison. And the experimental results show that the performance of the improved PSO algorithm is significantly better than the comparison algorithms in the irregular flight recovery problem covered in this paper. © 2022, Springer Nature Switzerland AG.
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This article reports on research exploring how religious involvement and commitment are related to post-pandemic well-being among Chinese university students. The Religious Commitment Inventory-10, the Religious Involvement Scale, and the Post-Pandemic Well-Being Scale were administered to 1739 university students selected from 119 comprehensive universities. Results showed that religious involvement and religious commitment significantly and positively predicted post-pandemic well-being beyond demographic variables. The significance of religious education and the limitations and contributions of this research are also discussed.
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Background: For a period of time, the outbreak of the COVID-19 outbreak in many urban villages in our country had caused concern. The dense and complex population structure of urban villages, with their inter-regional mobility, posed a challenge to the prevention and control of the epidemic. Objective: Urban village areasare more prone to regional outbreaks of infectious diseases because of their spatial environment, demographic characteristics, cross-regional mobility and the characteristics of residents' medical treatment behavior. The purpose of this study was tounderstand the characteristics of the COVID-19 epidemic situation in urban villages and the current situation and difficulties of primary care institutions in carrying out COVID-19 epidemic prevention and control measures, in order to provide references for primary care institutions to deal with normalized prevention and control, social dynamic clearing work and future infectious disease prevention and control. Methods: By using public opinion analysis, literature retrieval, online interviews with epidemic prevention and control personnel and experts in urban village, the epidemic situation, prevention and control status of urban village were summarized, and the existing weak links and important loopholes were analyzed. Results: Based on the relevant information, a total of six points of concern were extracted: (1) The number of mapping and screening objects was large, which was the focus and difficulty of epidemic prevention and control work in urban villages.(2) There was not strict closed-loop management lead to virus carriers who were not timely controlled, which caused a risk of spreading the epidemic.(3) The prevention and control of nosocomial infection in primary care institutions was not in place.(4)There were loopholes in the inspection of close contacts in the principle of territorial management;close contacts who did not live and work in the same administrative area but only screened in their living places, which may lead to the spread of the epidemic in workplaces where secondary close contacts may be at risk of infection were not screened in a timely manner.(5) Overload had become the norm, highlighting the large gap in primary health care manpower.(6) During the normalization of epidemic prevention and control, residents were paralyzed and careless, and the phenomenon of not wearing masks in public places and crowd gathering was common. Health education still needs to be strengthened and emphasized that residents were the first responsible for their own health. Conclusion: Primary care providers played an important role in the prevention and control of COVID-19 in urban village by undertaking community management, outpatient treatment, public health services, health education, vaccination, quarantine hotel stationing, joint prevention and control, etc. It was recommended that additional fever sentinel clinics be set up for early detection and isolation to avoid further spread of the epidemic, rental houses be requisitioned to meet the demand for isolated medical observation, primary care institutions be strengthened for hospitalization and prevention, green relief channels be opened to protect special groups from medical treatment, volunteers be organized to reinforce primary care institutions, and health education emphasized that residents were the first to be responsible for maintaining their own health and raised personal awareness of the risk of COVID-19 prevention and control. Copyright © 2022 by the Chinese General Practice.
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The COVID pandemic has highlighted the need for universities to be innovative and inclusive in their response to changing circumstances and to develop high quality courses in a completely online environment. In Semester 1, 2020, the team redeveloped a large undergraduate English and Chinese translation course at an Australian university in flipped mode while shifting the course to fully online delivery. The authors found that although student attitudes towards online flipped learning were initially mixed, levels of student engagement were similar to previous semesters. By the second semester of implementation, student evaluations of the course were significantly higher than in pre-flipped, pre-online semesters. This experience demonstrates that it is possible to develop a flipped university translation course that is interactive and engaging and challenges students academically. With appropriate scaffolding and the judicious use of technology, flipped learning offers a very positive learning experience and can be a key element of effective course design in fully online mode. © 2021, IGI Global.
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In view of the COVID-19 pandemic and its highly infectious characteristic, traditional artificial diagnosis based on medical imaging, though capable of detecting pulmonary lesion in human body, is found of lower efficiency. Therefore, it is particularly urgent that we design a set of accurate and automatic pneumonia diagnosis methods with aid of artificial intelligence technology, so that pneumonia in patients can be diagnosed and treated early. This study first introduces DenseNet to the Convolutional Neural Network (CNN) structure to improve sharing of characteristic information of lung image in convolutional layers and thus obtain more accurate image features. Secondly, characteristics of pneumonia disease are discriminated rapidly using the Graphic Attention Network (GAT). The authors adopt the X-ray dataset in Radiological Society of North America (RSNA) Pneumonia Detection Challenge released by Kaggle to train and verify the network. According to experimental results, the accuracy of COVID-19 diagnosis and F-Score both reach 98%. The method provides CT doctors with an end-to-end deep learning technology for pneumonia diagnosis. © 2021 IEEE.
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SARS-CoV-2 exploits the host cellular machinery for virus replication leading to the acute syndrome of coronavirus disease 2019 (COVID-19). Growing evidence suggests SARS-CoV-2 also exacerbates many chronic diseases, including cancers. As mutations on the spike protein (S) emerged as dominant variants that reduce vaccine efficacy, little is known about the relation between SARS-CoV-2 virus variants and cancers. Compared to the SARS-CoV-2 wild-type, the Gamma variant contains two additional NXT/S glycosylation motifs on the S protein. The hyperglycosylated S of Gamma variant is more stable, resulting in more significant epithelial-mesenchymal transition (EMT) potential. SARS-CoV-2 infection promoted NF-κB signaling activation and p65 nuclear translocation, inducing Snail expression. Pharmacologic inhibition of NF-κB activity by nature food compound, I3C suppressed viral replication and Gamma variant-mediated breast cancer metastasis, indicating that NF-κB inhibition can reduce chronic disease in COVID-19 patients. Our study revealed that the Gamma variant of SARS-CoV-2 activates NF-κB and, in turn, triggers the pro-survival function for cancer progression.