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1.
6th International Conference on Transportation Information and Safety, ICTIS 2021 ; : 240-244, 2021.
Article in English | Scopus | ID: covidwho-1948788

ABSTRACT

The major ports along the coast of China that undertake container transportation are all facing problems in collection and dispatching to a certain extent. In particular, due to the recent impact of the COVID-19 epidemic, truck drivers have difficulty moving across regions, and there was once a phenomenon of no containers being transported by vehicles. This paper sorted out the basic situation of container port collection and dispatching methods all over the world. Taking Shenzhen Port as an example, this paper focused on the analysis of the structural characteristics of container transportation and the impact on the rear urban traffic and atmospheric environment. Then it proposed a intermodal transportation network and established the 'Port Shuttle Hub System' model, which would closely link the port with the railway and inland port, and integrate the transportation organization mode, which greatly improves the efficiency of port containers' transportation. © 2021 IEEE.

2.
Industrial Management and Data Systems ; 2022.
Article in English | Scopus | ID: covidwho-1909117

ABSTRACT

Purpose: Under uncertain circumstances, digital technologies are taken as digital transformation enablers and driving forces to integrate with medical, healthcare and emergency management research for effective epidemic prevention and control. This study aims to adapt complex systems in emergency management. Thus, a digital transformation-driven and systematic circulation framework is proposed in this study that can utilize the advantages of digital technologies to generate innovative and systematic governance. Design/methodology/approach: Aiming at adapting complex systems in emergency management, a systematic circulation framework based on the interpretive research is proposed in this study that can utilize the advantages of digital technologies to generate innovative and systematic governance. The framework consists of four phases: (1) analysis of emergency management stages, (2) risk identification in the emergency management stages, (3) digital-enabled response model design for emergency management, and (4) strategy generation for digital emergency governance. A case study in China was illustrated in this study. Findings: This paper examines the role those digital technologies can play in responding to pandemics and outlines a framework based on four phases of digital technologies for pandemic responses. After the phase-by-phase analysis, a digital technology-enabled emergency management framework, titled “Expected digital-enabled emergency management framework (EDEM framework)” was adapted and proposed. Moreover, the social risks of emergency management phases are identified. Then, three strategies for emergency governance and digital governance from the three perspectives, namely “Strengthening weaknesses for emergency response,” “Enhancing integration for collaborative governance,” and “Engaging foundations for emergency management” that the government can adopt them in the future, fight for public health emergency events. Originality/value: The novel digital transformation-driven systematic circulation framework for public health risk response and governance was proposed. Meanwhile, an “Expected digital-enabled emergency management framework (EDEM model)” was also proposed to achieve a more effective empirical response for public health risk response and governance and contribute to studies about the government facing the COVID-19 pandemic effectively. © 2022, Emerald Publishing Limited.

3.
Environmental Science: Atmospheres ; 1(5):208-213, 2021.
Article in English | Scopus | ID: covidwho-1900673

ABSTRACT

The immense reduction in aerosol levels during the COVID-19 pandemic provides an opportunity to reveal how atmospheric chemistry is regulating our climate, among which the effect of aerosols on climate is a phenomenon of great interest but still in hot debate. The Intergovernmental Panel on Climate Change (IPCC) has continually identified the effect of aerosols on climate to have the largest uncertainty among the factors contributing to global climate change. Several studies indicate an inverse relationship between aerosol presence in the atmosphere and the diurnal surface air temperature range (DTR). Herein, we test this relationship by analyzing the DTR values from in situ weather station records for periods before and during the COVID-19 epidemic in Chinawhere aerosol levels have substantially reduced, compared with the climatological mean levels for a 19 year period.Our analyses find that DTRs fromFebruary to June during the COVID-19 pandemic are greater than 3 standard deviations above the climatological mean DTR. This anomaly has never occurred before in the 21st century and is at least in part associated with the observed reduction in aerosols. © 2021 The Author(s).

4.
Chinese Journal of Biologicals ; 34(6):699-703, 2021.
Article in Chinese | EMBASE | ID: covidwho-1894085

ABSTRACT

Objective To explore the application and safety of apheresis technology in collection of Coronavirus Disease 2019 (COVID-19) convalescent plasma (CP), and to analyze the quality characteristics of the plasma. Methods The general data of COVID-19 convalescent plasma (CP) donors, including gender, age, date of discharge or release from medical isolation, were collected based on informed consent. After physical examination, the CP was collected by apheresis technology with plasma separator, inactivated with methylene blue, and determined for severe acute respiratory symptom Coronavirus 2 (SARS-CoV-2) nucleic acid and specific antibody (RBD-IgG) against SARS-CoV-2. Results The collection process went well, and no serious adverse events related to plasma collection were reported during or after the collection. The average age of COVID-19 CP donors was 38 years (n = 933). The distributions of blood groups A, B, AB and 0 in RhD (+) COVID-19 CP were 33. 4%, 29. 2%, 10% and 27. 2% respectively. The plasma donation date was 18 d from the discharge date in average. All the test results of SARS-CoV-2 nucleic acid in CP were negative, while the proportion of plasma samples at SARS-CoV-2 antibody titer of more than 1: 160 was 92. 60%. Conclusion Apheresis technology was safe and reliable. The COVID-19 CP contained high titer antibody. Large-scale collection and preparation of inactivated plasma against SARS-CoV-2 played an important role in the treatment of COVID-19.

5.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-338229

ABSTRACT

The Omicron BA.2 variant has become a dominant infective strain worldwide. Receptor binding studies reveal that the Omicron BA.2 spike trimer have 11-fold and 2-fold higher potency to human ACE2 than the spike trimer from the wildtype (WT) and Omicron BA.1 strains. The structure of the BA.2 spike trimer complexed with human ACE2 reveals that all three receptor-binding domains (RBDs) in the spike trimer are in open conformation, ready for ACE2 binding, thus providing a basis for the increased infectivity of the BA.2 strain. JMB2002, a therapeutic antibody that was shown to have efficient inhibition of Omicron BA.1, also shows potent neutralization activities against Omicron BA.2. In addition, both BA.1 and BA.2 spike trimers are able to bind to mouse ACE2 with high potency. In contrast, the WT spike trimer binds well to cat ACE2 but not to mouse ACE2. The structures of both BA.1 and BA.2 spike trimer bound to mouse ACE2 reveal the basis for their high affinity interactions. Together, these results suggest a possible evolution pathway for Omicron BA.1 and BA.2 variants from human-cat-mouse-human circle, which could have important implications in establishing an effective strategy in combating viral infection.

6.
13th IEEE Global Engineering Education Conference, EDUCON 2022 ; 2022-March:652-655, 2022.
Article in English | Scopus | ID: covidwho-1874219

ABSTRACT

This article proposes a method to remotely control the robot in the laboratory through the Kinect camera to solve the impact of the Covid-19 epidemic on the laboratory teaching experience which allows users to remotely control robots through their own body movements to understand the principles of robots. It is used to solve the problem of fewer students willing to participate in robot remote education. In this study, the Azure Kinect DK camera was used to collect the motion posture of the upper limbs of the human body. The Kinect camera calculates the frames of human arm joints' motion. The control system calculates the direction of motion of each joint of the human body based on the quaternion by mapping the heterogeneous human joints with the robot joints. Make the posture of the human arm swing correspond to the posture of the robot's movement. Thus, the robot in the laboratory can be driven remotely through Azure Kinect DK. By using the method described in this article, students use the camera's motion capture system to remotely manipulate the robot to grab some simple objects. Through the method described in this research, students can carry out some simple operations on the robots in the laboratory from remote. So it is convenient for students to understand the basic principles of robots and achieve the purpose of better remote experimental teaching. At the same time, students can get practical application of motor servo control, ergonomics, physical simulation engine, digital twin system, etc. © 2022 IEEE.

7.
25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022 ; : 101-106, 2022.
Article in English | Scopus | ID: covidwho-1874158

ABSTRACT

Affected by the COVID-19, the global manufacturing industry has been greatly impacted. In order to adapt to the current new normal of economy, the multi-value chain collaborative operation mode of power manufacturing industry has come into being. In order to deeply study the influencing factors of multi-value chain collaborative operation efficiency in power manufacturing industry, this paper constructs an influencing factors system in terms of management level, technology level and policy level, combines fuzzy interpretative structural model (FISM) with analytic network process (ANP) to develop an analysis model from both qualitative and quantitative perspectives. Accordingly, it is suggested that: power manufacturing enterprises should promote the construction of R&D-production-sales-logistics-services multi-chain collaboration;promote the construction of data space to realize the sharing of data and information;accelerate the development of digital operation mode under Industry 4.0;and build third-party platform to efficiently integrate upstream and downstream resources. © 2022 IEEE.

8.
Land Use Policy ; 118:12, 2022.
Article in English | Web of Science | ID: covidwho-1867469

ABSTRACT

The outbreak of Coronavirus disease 2019 (COVID-19) led to the widespread stagnation of urban activities, resulting in a significant reduction in industrial pollution and traffic pollution. This affected how urban form influences air quality. This study reconsiders the influence of urban form on air quality in five urban agglomerations in China during the pandemic period. The random forest algorithm was used to quantitate the urban form-air quality relationship. The urban form was described by urban size, shape, fragmentation, compactness, and sprawl. Air quality was evaluated by the Air Quality Index (AQI) and the concentration of six pollutants (CO, O-3, NO2, PM2.5, PM10, SO2). The results showed that urban fragmentation is the most important factor affecting air quality and the concentration of the six pollutants. Additionally, the relationship between urban form and air quality varies in different urban agglomerations. By analyzing the extremely important indicators affecting air pollution, the urban form-air quality relationship in Beijing-Tianjin-Hebei is rather complex. In the Chengdu Chongqing and the Pearl River Delta, urban sprawl and urban compactness are extremely important indicators for some air pollutants, respectively. Furthermore, urban shape ranks first for some air pollutants both in the Triangle of Central China and the Yangtze River Delta. Based on the robustness test, the performance of the random forest model is better than that of the multiple linear regression (MLR) model and the extreme gradient boosting (XGBoost) model.

9.
31st ACM World Wide Web Conference, WWW 2022 ; : 3623-3631, 2022.
Article in English | Scopus | ID: covidwho-1861669

ABSTRACT

This paper focuses on a critical problem of explainable multimodal COVID-19 misinformation detection where the goal is to accurately detect misleading information in multimodal COVID-19 news articles and provide the reason or evidence that can explain the detection results. Our work is motivated by the lack of judicious study of the association between different modalities (e.g., text and image) of the COVID-19 news content in current solutions. In this paper, we present a generative approach to detect multimodal COVID-19 misinformation by investigating the cross-modal association between the visual and textual content that is deeply embedded in the multimodal news content. Two critical challenges exist in developing our solution: 1) how to accurately assess the consistency between the visual and textual content of a multimodal COVID-19 news article? 2) How to effectively retrieve useful information from the unreliable user comments to explain the misinformation detection results? To address the above challenges, we develop a duo-generative explainable misinformation detection (DGExplain) framework that explicitly explores the cross-modal association between the news content in different modalities and effectively exploits user comments to detect and explain misinformation in multimodal COVID-19 news articles. We evaluate DGExplain on two real-world multimodal COVID-19 news datasets. Evaluation results demonstrate that DGExplain significantly outperforms state-of-the-art baselines in terms of the accuracy of multimodal COVID-19 misinformation detection and the explainability of detection explanations. © 2022 ACM.

10.
35th AAAI Conference on Artificial Intelligence, AAAI 2021 ; 17B:15424-15430, 2021.
Article in English | Scopus | ID: covidwho-1857854

ABSTRACT

An accurate and efficient forecasting system is imperative to the prevention of emerging infectious diseases such as COVID-19 in public health. This system requires accurate transient modeling, lower computation cost, and fewer observation data. To tackle these three challenges, we propose a novel deep learning approach using black-box knowledge distillation for both accurate and efficient transmission dynamics prediction in a practical manner. First, we leverage mixture models to develop an accurate, comprehensive, yet impractical simulation system. Next, we use simulated observation sequences to query the simulation system to retrieve simulated projection sequences as knowledge. Then, with the obtained query data, sequence mixup is proposed to improve query efficiency, increase knowledge diversity, and boost distillation model accuracy. Finally, we train a student deep neural network with the retrieved and mixed observation-projection sequences for practical use. The case study on COVID-19 justifies that our approach accurately projects infections with much lower computation cost when observation data are limited. Copyright © 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved

11.
Journal of the American College of Cardiology ; 79(9):1842-1842, 2022.
Article in English | Web of Science | ID: covidwho-1848894
12.
J Eur Acad Dermatol Venereol ; 2022 May 10.
Article in English | MEDLINE | ID: covidwho-1832146

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, wearing PPE can induce skin damage such as erythema, pruritus, erosion, and ulceration among others. Although the skin microbiome is considered important for skin health, the change of the skin microbiome after wearing PPE remains unknown. OBJECTIVE: The present study aimed to characterize the diversity and structure of bacterial and fungal flora on skin surfaces of healthcare workers wearing personal protective equipment (PPE) during the COVID-19 pandemic using metagenomic next-generation sequencing (mNGS). METHODS: A total of 10 Chinese volunteers were recruited and the microbiome of their face, hand, and back were analysed before and after wearing PPE. Moreover, VISIA was used to analyse skin features. RESULTS: Results of alpha bacterial diversity showed that there was statistically significant decrease in alpha diversity indice in the skin samples from face, hand, and three sites after wearing PPE as compared with the indice in the skin samples before wearing PPE. Further, the results of evaluated alpha fungal diversity show that there was a statistically significant decrease in alpha diversity indices in the skin samples from hand after wearing PPE as compared with the indices in the skin samples before wearing PPE (P < 0.05). Results of the current study found that the main bacteria on the face, hand, and back skin samples before wearing the PPE were Propionibacterium spp. (34.04%), Corynebacterium spp. (13.12%), and Staphylococcus spp. (38.07%). The main bacteria found on the skin samples after wearing the PPE were Staphylococcus spp. (31.23%), Xanthomonas spp. (26.21%), and Cutibacterium spp. (42.59%). The fungal community composition was similar in three skin sites before and after wearing PPE. CONCLUSION: It was evident that wearing PPE may affect the skin microbiota, especially bacteria. Therefore, it was evident that the symbiotic microbiota may reflect the skin health of medical workers during the COVID-19 pandemic.

13.
Aims Mathematics ; 7(6):10495-10512, 2022.
Article in English | Web of Science | ID: covidwho-1810392

ABSTRACT

Under the background that Covid-19 is spreading across the world, the lifestyle of people has to confront a series of changes and challenges. This also presents new problems and requirements to automation facilities. For example, nowadays masks have almost become necessities for people in public places. However, most access control systems (ACS) cannot recognize people wearing masks and authenticate their identities to deal with increasingly serious epidemic pressure. Consequently, many public entries have turned to an attendant mode that brings low efficiency, infection potential, and high possibility of negligence. In this paper, a new security classification framework based on face recognition is proposed. This framework uses mask detection algorithm and face authentication algorithm with anti-spoofing function. In order to evaluate the performance of the framework, this paper employs the Chinese Academy of Science Institute of Automation-Face Anti-spoofing Datasets (CASIA-FASD) and Reply-Attack datasets as benchmarks. Performance evaluation indicates that the Half Total Error Rate (HTER) is 9.7%, the Equal Error Rate (EER) is 5.5%. The average process time of a single frame is 0.12 seconds. The results demonstrate that this framework has a high anti-spoofing capability and can be employed on the embedded system to complete the mask detection and face authentication task in real-time.

14.
Environmental Science-Nano ; : 11, 2022.
Article in English | Web of Science | ID: covidwho-1778647

ABSTRACT

Hydrogen peroxide (H2O2) solution and its aerosols are common disinfectants, especially for urgent reuse of personal protective equipment during the COVID-19 pandemic. Highly sensitive and selective evaluation of the H2O2 concentration is key to customizing the sufficient disinfection process and avoiding disinfection overuse. Amperometric electrochemical detection is an effective means but poses challenges originated from the precarious state of H2O2. Here, an atomic Co-N-x-C site anchored neuronal-like carbon modified amperometric sensor (denoted as the CoSA-N/C@rGO sensor) is designed, which exhibits a broad detection range (from 250 nM to 50 mM), superior sensitivity (743.3 mu A mM(-1) cm(-2), the best among carbon-based amperometric sensors), strong selectivity (no response to interferents), powerful reliability (only 2.86% decay for one week) and fast response (just 5 s) for residual H2O2 detection. We validated the accuracy and practicability of the CoSA-N/C@rGO sensor in the actual H2O2 disinfection process of personal protective equipment. Further characterization verifies that the electrocatalytic activity and selective reduction of H2O2 is determined by the atomically dispersed Co-N-x-C sites and the high oxygen content of CoSA-N/C@rGO, where the response time and reliability of H2O2 detection is determined by the neuronal-like structure with high nitrogen content. Our findings pave the way for developing a sensor with superior sensitivity, selectivity and stability, rendering promising applications such as medical care and environmental treatment.

15.
29th International Conference on Computers in Education (ICCE) ; : 487-493, 2021.
Article in English | Web of Science | ID: covidwho-1777075

ABSTRACT

Educators worldwide are facing challenges to continue providing quality learning design remotely, digitally and in virtual settings. Although teaching and learning activities are almost relatively easy to be translated to online platforms, education is missing active learning and social presence, both of which can promote effective learning. When digital education ensues, mobile technologies are widely optimized for learning. The Malaysian Communications and Multimedia Commission report shows that smartphones have become the most popular devices to access the Internet, reaching a near saturation usage level at 98.7% in 2020, due to the pandemic. In the aftermath of the COVID-19 pandemic, more education institutions will continue to conduct virtual lessons, and the trend is set to grow exponentially. The XploreRAFE+ mock-up mobile apps was developed with the aim of gamifying learning and foster active learning, framed by the Interest-Driven Creator Theory. In general, people who play games may experience positive activating emotions. Positive activating emotions such as enjoyment and pride are found to be positively correlated with cognitive regulations (Yeo & Frederiks, 2011). This is what XploreRAFE+ aims for its users to achieve - able to internalize the knowledge through game play and therefore, enhance their cognition. As such, this apps was designed to allow instructors who do not have the technological know-how of gamification and Augmented Reality (AR), to be able to embrace both for their learning design. Rather than spending time and effort laboriously on designing a gamified lesson with virtual contents, instructors are now able to save their time and create a gamified lesson by plugging in their content into this apps, choosing AR overlays, selecting game mechanics and eliciting students' learning feedback through ePortfolio. XploreRAFE+ would be able to add value by adding in the affective aspects, virtual extended reality elements, supporting social presence and intimacy, and immediacy of feedback. This study invites further research on the apps' evaluation after its development is fully completed.

16.
Mbio ; 13(1):18, 2022.
Article in English | Web of Science | ID: covidwho-1766600

ABSTRACT

The dynamics of SARS-CoV-2 infection in COVID-19 patients are highly variable, with a subset of patients demonstrating prolonged virus shedding, which poses a significant challenge for disease management and transmission control. In this study, the long-term dynamics of SARS-CoV-2 infection were investigated using a human well-differentiated nasal epithelial cell (NEC) model of infection. NECs were observed to release SARS-CoV-2 virus onto the apical surface for up to 28 days post-infection (dpi), further corroborated by viral antigen staining. Single-cell transcriptome sequencing (sc-seq) was utilized to explore the host response from infected NECs after short-term (3-dpi) and long-term (28-dpi) infection. We identified a unique population of cells harboring high viral loads present at both 3 and 28 dpi, characterized by expression of cell stress-related genes DDIT3 and ATF3 and enriched for genes involved in tumor necrosis factor alpha (TNF-alpha) signaling and apoptosis. Remarkably, this sc-seq analysis revealed an antiviral gene signature within all NEC cell types even at 28 dpi. We demonstrate increased replication of basal cells, absence of widespread cell death within the epithelial monolayer, and the ability of SARS-CoV-2 to replicate despite a continuous interferon response as factors likely contributing to SARS-CoV-2 persistence. This study provides a model system for development of therapeutics aimed at improving viral clearance in immunocompromised patients and implies a crucial role for immune cells in mediating viral clearance from infected epithelia. IMPORTANCE Increasing medical attention has been drawn to the persistence of symptoms (long-COVID syndrome) or live virus shedding from subsets of COVID-19 patients weeks to months after the initial onset of symptoms. In vitro approaches to model viral or symptom persistence are needed to fully dissect the complex and likely varied mechanisms underlying these clinical observations. We show that in vitro differentiated human NECs are persistently infected with SARS-CoV-2 for up to 28 dpi. This viral replication occurred despite the presence of an antiviral gene signature across all NEC cell types even at 28 dpi. This indicates that epithelial cell intrinsic antiviral responses are insufficient for the clearance of SARS-CoV-Z implying an essential role for tissue-resident and infiltrating immune cells for eventual viral clearance from infected airway tissue in COVID-19 patients.

17.
Journal of Virology ; 96(1):11, 2022.
Article in English | Web of Science | ID: covidwho-1756184

ABSTRACT

Over the past 20 years, the severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and SARS-CoV-2 emerged, causing severe human respiratory diseases throughout the globe. Developing broad-spectrum drugs would be invaluable in responding to new, emerging coronaviruses and to address unmet urgent clinical needs. Main protease (Mpro;also known as 3CL(pro)) has a major role in the coronavirus life cycle and is one of the most important targets for anti-coronavirus agents. We show that a natural product, noncovalent inhibitor, shikonin, is a pan-main protease inhibitor of SARS-CoV-2, SARS-CoV, MERS-CoV, human coronavirus (HCoV)-HKU1, HCoV-NL63, and HCoV-229E with micromolar half maximal inhibitory concentration (IC50) values. Structures of the main protease of different coronavirus genus, SARS-CoV from the betacoronavirus genus and HCoV-NL63 from the alphacoronavirus genus, were determined by X-ray crystallography and revealed that the inhibitor interacts with key active site residues in a unique mode. The structure of the main protease inhibitor complex presents an opportunity to discover a novel series of broad-spectrum inhibitors. These data provide substantial evidence that shikonin and its derivatives may be effective against most coronaviruses as well as emerging coronaviruses of the future. Given the importance of the main protease for coronavirus therapeutic indication, insights from these studies should accelerate the development and design of safer and more effective antiviral agents. IMPORTANCE The current pandemic has created an urgent need for broad-spectrum inhibitors of SARS-CoV-2. The main protease is relatively conservative compared to the spike protein and, thus, is one of the most promising targets in developing anticoronavirus agents. We solved the crystal structures of the main protease of SARSCoV and HCoV-NL63 that bound to shikonin. The structures provide important insights, have broad implications for understanding the structural basis underlying enzyme activity, and can facilitate rational design of broad-spectrum anti-coronavirus ligands as new therapeutic agents.

18.
Annals of Emergency Medicine ; 78(4):S49-S50, 2021.
Article in English | EMBASE | ID: covidwho-1748272

ABSTRACT

Study Objective: A vast majority of patients with serious illness present to emergency departments (EDs) in their last year of life with unmet palliative needs. ED-requested palliative care (PC) consults have been shown to reduce hospital length-of-stay and costs. As integrated care delivery models evolve, many health systems are considering how to best deploy PC resources and protocols to the ED to facilitate earlier engagement. Our objective was to demonstrate the financial and operational viability of embedding a palliative consultant in the ED. Methods: This single-site hospital with 42,000 annual ED visits featured a mature PC team, with historically high ICU/ward but minimal ED engagement. Institutional alignment was acquired from key stakeholders (ED, PC, ICU, hospitalists, administration) to fund a new ED-embedded PC consult service. A single PC physician or nurse practitioner was co-located in the ED fishbowl between the hours of 11am-7pm daily, initially weekdays and expanded to weekends after 10 weeks. ED consults were both proactively identified by PC and actively requested by ED clinicians. Clinical and financial data from 08/2020-04/2021 were tracked through the electronic health record, Palliative Care Quality Network registry, and McKesson Horizon Performance Manager. Results: Over 8.5 months, the ED-embedded PC service saw 565 consults. Of these, 46% had a code status change, 8% admitted to a lower level of care, 9% avoided hospitalization, and 13% newly referred to hospice. ED consult volume was consistent month-over-month. ED length-of-stay did not appreciably lengthen. None of these cases were related to COVID-19. Importantly, this additional consult team did not cannibalize inpatient consult volume from usual practice. Compared to inpatient PC consults, median hospital length-of-stay decreased from 10.8 days to 3.3 days (p<0.001). Likewise, median direct costs per hospitalization decreased from $17,726 to $4,617, a 75% reduction or $13,019 per hospitalization (p<0.001). Annualized direct cost avoidance will be $6.5M. Subsequently, the ED provider group volunteered to include ED-palliative consults as a performance metric in their compensation model. Conclusions: ED-embedded palliative consultants are a high cost but even higher-reward intervention. For this hospital, return on investment will exceed 15x. True impact is likely even greater given analyses were not compared against all-comers, and did not account for future deferral of ED revisits and healthcare utilization from earlier introduction into outpatient palliative and hospice services. ED-palliative partnerships significantly advance the quadruple aim and position the ED to lead change in healthcare systems which increasingly prioritize value-based care.

19.
2021 IEEE International Conference on Big Data, Big Data 2021 ; : 899-908, 2021.
Article in English | Scopus | ID: covidwho-1730897

ABSTRACT

This paper studies an emerging and important problem of identifying misleading COVID-19 short videos where the misleading content is jointly expressed in the visual, audio, and textual content of videos. Existing solutions for misleading video detection mainly focus on the authenticity of videos or audios against AI algorithms (e.g., deepfake) or video manipulation, and are insufficient to address our problem where most videos are user-generated and intentionally edited. Two critical challenges exist in solving our problem: i) how to effectively extract information from the distractive and manipulated visual content in TikTok videos? ii) How to efficiently aggregate heterogeneous information across different modalities in short videos? To address the above challenges, we develop TikTec, a multimodal misinformation detection framework that explicitly exploits the captions to accurately capture the key information from the distractive video content, and effectively learns the composed misinformation that is jointly conveyed by the visual and audio content. We evaluate TikTec on a real-world COVID- 19 video dataset collected from TikTok. Evaluation results show that TikTec achieves significant performance gains compared to state-of-the-art baselines in accurately detecting misleading COVID-19 short videos. © 2021 IEEE.

20.
2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 ; : 2587-2594, 2021.
Article in English | Scopus | ID: covidwho-1722868

ABSTRACT

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a worldwide pandemic (COVID-19). Drug repurposing studies, including drugs such as dexamethasone (DEX), chloroquine (CQ), and telmisartan (TLS), have been performed in COVID-19 clinical trials. DEX and CQ have been demonstrated in vitro to bind angiotensin-converting enzyme 2 (ACE2), a cellular entry receptor utilized by SARS-CoV-2. However, how DEX/CQ bind to ACE2 and their mechanisms of action are still unknown. We demonstrated that DEX, CQ, and TLS disrupt the interactions between SARS-CoV-2 spike protein and human ACE2 via binding to an allosteric site close to the viral spike protein binding region at the peptidase domain of ACE2, causing a conformational change of the ACE2. We defined four conformational states of ACE2 based on the two helices distances. Our molecular dynamics simulations suggested that binding to the viral spike protein shifted ACE2 conformation populations away from 'Open' conformation. Such conformation population shift is further enhanced by the Delta variant. The binding of the drugs to ACE2 rescues this conformation population shift allosterically to keep ACE2 in 'Open' conformation mostly. Our findings provide a potential insight that modulating the conformation of ACE2 may prevent SARS-CoV-2 invasion due to unfavored poses for spike protein binding. © 2021 IEEE.

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