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1.
World J Gastroenterol ; 28(48):6811-26, 2022.
Article in English | PubMed Central | ID: covidwho-2201059

ABSTRACT

The global coronavirus disease 2019 (COVID-19) has become one of the biggest threats to the world since 2019. The respiratory and gastrointestinal tracts are the main targets for severe acute respiratory syndrome coronavirus 2 infection for they highly express angiotensin-converting enzyme-2 and transmembrane protease serine 2. In patients suffering from COVID-19, gastrointestinal symptoms have ranged from 12% to 61%. Anorexia, nausea and/or vomiting, diarrhea, and abdominal pain are considered to be the main gastrointestinal symptoms of COVID-19. It has been reported that the direct damage of intestinal mucosal epithelial cells, malnutrition, and intestinal flora disorders are involved in COVID-19. However, the underlying mechanisms remain unclear. Thus, in this study, we reviewed and discussed the correlated mechanisms that cause gastrointestinal symptoms in order to help to develop the treatment strategy and build an appropriate guideline for medical workers.

2.
Frontiers in public health ; 10:1091484, 2022.
Article in English | EMBASE | ID: covidwho-2199568

ABSTRACT

Aim: To evaluate the impact of a telemedicine medication management service in patients with hypertension. Method(s): Participants were allocated to either a telemedicine service (N = 173) or usual care (UC) (N = 179). The primary outcome was blood pressure (BP) reduction from baseline to the 6-month follow-up visit, the proportion of the target BP achievement, overall adherence to prescribed medication as well as a composite of non-fatal stroke, non-fatal myocardial infarction and cardiovascular death. Result(s): At 6 months, BP was controlled in 89.6% (n = 155) of intervention patients and 78.8% (n = 141) of UC patients (OR = 1.14, 95% CI = 1.04-1.25, P = 0.006), giving a mean difference of -6.0 (-13.0 to -2.5 mmHg) and -2.0 mmHg (-4.0 to -0.1 mmHg) in SBP and DBP, respectively. 17.9% (n = 31) of the patients in the intervention group were non-adherent with medications, compared with 29.1% (n = 52) in the UC group (P = 0.014). The composite clinical endpoints were reached by 2.9% in the intervention group and 4.5% in the control group with no significant differences (OR = 1.566, 95% CI = 0.528-4.646). Conclusion(s): Telemedicine medication management for hypertension management had led to better BP control and medication adherence improvement than UC during COVID-19 epidemic, resulting in a reduction of overall adverse cardiovascular events occurrence. Copyright © 2022 Li, Hu, Yao, Zuo, Wang, Li and Lv.

3.
Front Psychiatry ; 13, 2022.
Article in English | PubMed Central | ID: covidwho-2199414

ABSTRACT

Depression symptoms significantly impact college students' mental health, particularly during the "closed management” period during the spread of COVID-19. Exploring the mechanism that affects college students' depression symptoms can help alleviate the impact of closed management policies on individual mental health and improve their mental health level. The onset of the COVID-19 pandemic resulted in the normalization of epidemic prevention and control in China and the implementation of the dynamic zero-COVID policy. This study used the Five-Factor Mindfulness Questionnaire—Short Form, Psychological Resilience Scale, and Beck Depression Scale to investigate the mindfulness, psychological resilience, and depression symptoms of 1,062 students under closed management conditions at Northwest Normal University. The mindfulness, psychological resilience, and depression status of students in closed management were investigated using an online questionnaire survey. Eight hundred and ten college students (Mage = 20.43, SD = 1.67, range = 17-30) were selected to test the model using the structural equation model and bootstrap method. The results showed that the gender differences in mindfulness and psychological resilience were not significant. Gender differences in depression symptoms were significant, and depression symptoms in men were significantly higher than in women. Grade differences in resilience, mindfulness, and depression levels were not significant. Thus, psychological resilience is negatively associated with depressive symptoms. Psychological resilience plays a mediating role between mindfulness and depressive symptoms. This study provides reference and inspiration for improving college students' mental health under epidemic prevention and control circumstances.

4.
Frontiers in Psychology ; 13, 2022.
Article in English | Web of Science | ID: covidwho-2199202

ABSTRACT

COVID-19, as a crucial public health crisis, has affected our lives in nearly every aspect. Besides its major health threats, COVID-19 brings severe secondary impacts, one of which is the rise of social stigma. Although numerous studies have examined the antecedents and outcomes of COVID-19-related stigma, we still lack a systematic understanding of who is being stigmatized during the COVID-19 pandemic, what exacerbates COVID-19-related stigma, and what impacts COVID-19-related stigma has on victims. Therefore, this review aims to provide a systematic overview of COVID-19-related stigma. With 93 papers conducted with 126,371 individuals in more than 150 countries and territories spanning five continents, we identify three targets that have received the most research: Chinese/Asian people, (suspected) patients and survivors, and healthcare workers. Furthermore, we find that for each stigma target, characteristics of the stigmatized, stigmatizer, and context contribute to COVID-19-related stigma and that this stigma negatively influences victims' health and non-health outcomes. We call for future research to provide a more integrative, balanced, and rigorous picture of COVID-19-related stigma via conducting research on neglected topics (e.g., contextual factors that contribute to stigma toward HCWs) and stigma interventions and using a longitudinal design. In practice, we urge governments and institutions (e.g., ministries of public health, hospitals) to pay close attention to stigma issues and to promote safe and inclusive societies.

5.
Frontiers in Medicine ; 9, 2022.
Article in English | Web of Science | ID: covidwho-2198986

ABSTRACT

BackgroundHigh-flow nasal oxygenation (HFNO) has been suggested as an alternative oxygenation method during procedural sedation. This randomized, non-inferiority trial evaluated the safety and efficacy of HFNO compared with laryngeal mask airway (LMA) in pediatric ambulatory oral surgery under deep sedation. MethodsIn total, 120 children aged 2-7 years (weight: 10-30 kg) were equally assigned into two groups, namely, HFNO with propofol total intravenous anesthesia infusion (HFNO-IV) or LMA with propofol total intravenous anesthesia infusion (LMA-IV). The primary objective was to monitor carbon dioxide (CO2) accumulation during perioperative surgery. Secondary objectives included monitoring transcutaneous oxygen saturation, grade exposure to the surgical field, perioperative adverse events, or other events. The predefined non-inferiority margin was 7 mmHg. During the COVID-19 pandemic, a novel WeChat applet was implemented to gather follow-up data after discharge. ResultsNon-inferiority could be declared for HFNO relative to LMA (mean difference in transcutaneous CO2 (TcCO2) = -1.4 mmHg, 95% CI: -2.9, 0.1 mmHg;P > 0.05). The pre-surgical TcCO2 of the HFNO-IV group (45.4 +/- 4.5 mmHg) was similar to that of the LMA-IV group (44.0 +/- 3.5 mmHg), within the clinically acceptable normal range. All the children maintained SpO(2) levels of >97%. The surgical field exposure score of the HFNO group was significantly better than that of the LMA group. There was no significant difference between the two groups regarding risk or adverse events. ConclusionHFNO was not inferior to LMA for maintaining oxygenation and ventilation in patients undergoing pediatric ambulatory oral surgery under deep sedation under strict isolation from the oral cavity to the upper airway.

6.
Ieee Transactions on Emerging Topics in Computational Intelligence ; 2022.
Article in English | Web of Science | ID: covidwho-2192093

ABSTRACT

Recently under the condition of reducing nucleic acid testing for COVID-19 in large population, the computer-aided diagnosis with the chest computed tomography (CT) image has become increasingly important in differential diagnosis of community-acquired pneumonia (CAP) and COVID-19. In prac-tice, there usually exist a mass of unlabeled CT images, especially in regions without adequate medical resources, and the existing diagnosis methods cannot take advantage of the useful information among them. Therefore, it is practical and urgent need to develop a computer-aided diagnosis model that can effectively exploit both labeled and unlabeled samples. To this end, in this paper, we pro -pose a semi-supervised multi-view fusion method for the diagnosis of COVID-19. It explores both the discriminative features from labeled samples and the structure information from unlabeled samples and fuses multi-view features extracted from CT images, including image feature, statistical feature, and lesions specific feature, for improving the diagnostic performance. Specifically, in the proposed model, we utilize semi-supervised learning technique with pairwise constraint regularization to learn the model with both labeled samples and unlabeled samples. Simultaneously, we employ low-rank multi-view constraint to capture latent comple-mentary information among different features from CT images. Experimental results show that the proposed method outperforms the state-of-the-art methods in differential diagnosis of CAP vs. COVID-19.

7.
2022 International Conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2022 ; : 271-275, 2022.
Article in English | Scopus | ID: covidwho-2192020

ABSTRACT

Computer-Aided Diagnosis (CAD) is applied in the medical analysis of X-ray images widely. Due to the COVID-19 pandemic, the speed of COVID-19 detection is slow, and the workforce is scarce. Therefore, we have an idea to use CAD to diagnose COVID-19 and effectively respond to the pandemic. Recent studies show that convolutional neural network (CNN) is an appropriate technique for medical image classification. However, CNN is more suitable for datasets with many images, such as ImageNet. Medical image classification relies on doctors to label medical images, so obtaining large-scale medical image data sets is a time-consuming, costly, and unrealistic task. The method of data augmentation for a limited medical dataset can be used to increase the number of images. However, this technology will produce many repeated images, which will easily lead to the overfitting problem of CNN. In the case of a limited number of radiological images, transfer learning is a practical and effective method which can help us overcome the overfitting problem of ordinary CNN by transferring the pre-Trained models on large datasets to our tasks. The proposed model is DenseNet based deep transfer learning model (TLDeNet) to identify the patients into three classes: COVID-19, Normal or Pneumonia. We then analyzed and assessed the performance of our model on COVID-19 X-ray testing images by performing extensive experiments. It is finally demonstrated that the proposed model is superior to other deep transfer learning models according to comparative analyses. The Grad-Cam method is finally applied to interpret the convolutional neural network, revealing that our proposed model focuses on the similar region of the X-ray images as doctors. © 2022 IEEE.

8.
IEEE Sensors Journal ; : 1-1, 2022.
Article in English | Scopus | ID: covidwho-2192001

ABSTRACT

Wireless sensor networks (WSNs) are composed of a large number of spatially distributed sensor nodes to monitor and transmit information from the environment. However, the batteries used by these sensor nodes have limited energy and can not be charged or replaced due to the harsh deployment environment. This energy limitation will seriously affect the lifetime of the network. Therefore, the purpose of this research is to reduce energy consumption and balance the load of sensor nodes by clustering routing protocols, so as to prolong the lifetime of the network. Firstly, the coronavirus herd immune optimizer is improved and used to optimize the network clustering. Secondly, the cluster heads are selected according to the energy and location factors in the clusters, and a reasonable cluster head replacement mechanism is designed to avoid the extra communication energy consumption caused by the frequent replacement of cluster heads. Finally, a multi-hop routing mechanism between the cluster heads and the base station is constructed by Q-learning. Simulation results show that the proposed work can improve the structure of clusters, enhance the load balance of nodes, reduce network energy consumption and prolong the network lifetime. The appearance time of the first energy-depleted node is delayed by 25.8%, 85.9% and 162.2% compared with IGWO, ACA-LEACH and DEAL in the monitoring area of 300m ×300m, respectively. In addition, the proposed protocol shows better adaptability in varying dynamic conditions. IEEE

9.
Waste Management ; 157:159-167, 2022.
Article in English | MEDLINE | ID: covidwho-2184363

ABSTRACT

The demand for polypropylene (PP) melt-blown materials has dramatically increased due to the COVID-19 pandemic. It has caused serious environmental problems because of the lack of effective treatment for the waste PP melt-blown materials. In this study, we propose a green and sustainable recycling method to create PP sponges from waste PP melt-blown material for oil spill cleaning by freeze-drying and thermal treatment techniques. The recycling method is simple and without secondary pollution to the environment. The developed recycling method successfully transforms 2D laminar dispersed PP microfibers into elastic sponges with a 3D porous structure, providing the material with good mechanical properties and promotes its potential application in the field of oil spill cleaning. The morphology structure, thermal properties, mechanical properties, and oil absorption properties are tested and characterized. The PP sponges with a three-dimensional porous network structure show an exceedingly low density of >0.014 g/cm3, a high porosity of <98.77 %, and a high water contact angle range of 130.4-139.9degree. Moreover, the PP sponges own a good absorption capacity of <47.61 g/g for different oil and solvents. In particular, the compressive modulus of the PP sponges is 33.59-201.21 kPa, which is higher than that of most other fiber-based porous materials, indicating that the PP sponges have better durability under the same force. The excellent comprehensive performance of the PP sponges demonstrates the method developed in this study has large application potential in the field of the recycle of waste PP melt-blown materials.

10.
Journal of Virus Eradication ; 8(4):100308, 2022.
Article in English | MEDLINE | ID: covidwho-2181183

ABSTRACT

Background: A community COVID-19 outbreak caused by the B.1.1.7 SARS-CoV-2 variant occurred in Taiwan in May 2021. High-risk populations such as people living with HIV (PLWH) were recommended to receive two doses of COVID-19 vaccines. While SARS-CoV-2 vaccines have demonstrated promising results in general population, real-world information on the serological responses remains limited among PLWH.

11.
Journal of Hospitality and Tourism Management ; 54:56-64, 2023.
Article in English | Web of Science | ID: covidwho-2180589

ABSTRACT

To promote tourism recovery in the post-COVID-19 pandemic era, it is critical to understand the psychological factors that either boost or suppress travel demands. However, little is known about the underlying psychological mechanism that affects compensatory travel intention. Therefore, by scrutinizing the roles that autonomous self -motivation, sensation seeking, and perceived susceptibility to COVID-19 play, this study conducted two scenario -based experiments (N = 223 + 200) to explore the psychological mechanism and boundary conditions behind the influence of boredom on compensatory travel intention. The findings reveal that people are more likely to generate compensatory travel intention when there is a higher level of boredom during the COVID-19 pandemic due to their desire for sensation seeking. This effect is magnified when people adopt autonomous self-motivating strategies. However, for people with high (vs. low) perceived susceptibility to COVID-19, a high level of boredom evokes lower compensatory travel intention through sensation seeking.

12.
7th China National Conference on Big Data and Social Computing, BDSC 2022 ; 1640 CCIS:23-39, 2022.
Article in English | Scopus | ID: covidwho-2173950

ABSTRACT

University is one of the most likely environments for the cluster infection due to the long-time close contact in house and frequent communication. It is critical to understand the transmission risk of COVID-19 under various scenario, especially during public health emergency. Taking the Tsinghua university's anniversary as a representative case, a set of prevention and control strategies are established and investigated. In the case study, an alumni group coming from out of campus is investigated whose activities and routes are designed based on the previous anniversary schedule. The social closeness indicator is introduced into the Wells-Riley model to consider the factor of contact frequency. Based on the anniversary scenario, this study predicts the number of the infected people in each exposure indoor location (including classroom, dining hall, meeting room and so on) and evaluates the effects of different intervention measures on reducing infection risk using the modified Wells-Riley model, such as ventilation, social distancing and wearing mask. The results demonstrate that when applying the intervention measure individually, increasing ventilation rate is found to be the most effective, whereas the efficiency of increased ventilation on reducing infection cases decreases with the increase of the ventilation rate. To better prevent COVID-19 transmission, the combined intervention measures are necessary to be taken, which show the similar effectiveness on the reduction of infected cases under different initial infector proportion. The results provide the insights into the infection risk on university campus when dealing with public health emergency and can guide university to formulate effective operational strategies to control the spread of COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

13.
Journal of Medical Virology ; 06:06, 2023.
Article in English | MEDLINE | ID: covidwho-2173234

ABSTRACT

Global COVID-19 pandemics highlight the need of developing vaccines with universal and durable protection against emerging SARS-CoV-2 variants. Here we developed an extended-release vaccine delivery system (GP-diABZI-RBD), consisting the original SARS-CoV-2 WA1 strain receptor-binding domain (RBD) as the antigen and diABZI STING agonist in conjunction with yeast beta-glucan particles (GP-diABZI) as the platform. GP-diABZI-RBD could activate STING pathway and inhibit SARS-CoV-2 replication. Compared to diABZI-RBD, intraperitoneal injection of GP-diABZI-RBD elicited robust cellular and humoral immune responses in mice. Using SARS-CoV-2 GFP/DELTAN transcription and replication-competent virus-like particle system (trVLP), we demonstrated that GP-diABZI-RBD-prototype vaccine exhibited the strongest and durable humoral immune responses and antiviral protection;whereas GP-diABZI-RBD-Omicron displayed minimum neutralization responses against trVLP. By using pseudotype virus (PsVs) neutralization assay, we found that GP-diABZI-RBD-Prototype, GP-diABZI-RBD-Delta, and GP-diABZI-RBD-Gamma immunized mice sera could efficiently neutralize Delta and Gamma PsVs, but had weak protection against Omicron PsVs. In contrast, GP-diABZI-RBD-Omicron immunized mice sera displayed the strongest neutralization response to Omicron PsVs. Taken Together, the results suggest that GP-diABZI can serve as a promising vaccine delivery system for enhancing durable humoral and cellular immunity against broad SARS-CoV-2 variants. Our study provides important scientific basis for developing SARS-COV-2 VOC-specific vaccines. This article is protected by copyright. All rights reserved.

15.
Reviews in Cardiovascular Medicine ; 23(11) (no pagination), 2022.
Article in English | EMBASE | ID: covidwho-2156131

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) pandemic has severely affected healthcare systems around the world. This study aimed to investigate the perceptions of cardiologists regarding how the COVID-19 pandemic has affected the clinical practice patterns for acute coronary syndrome (ACS). Method(s): A multicenter clinician survey was sent to 300 cardiologists working in 22 provinces in China. The survey collected demographic information and inquired about their perceptions of how the COVID-19 pandemic has affected ACS clinical practice patterns. Result(s): The survey was completed by 211 (70.3%) cardiologists, 82.5% of whom were employed in tertiary hospitals, and 52.1% reported more than 10 years of clinical cardiology practice. Most respondents observed a reduction in ACS inpatients and outpatients in their hospitals during the pandemic. Only 29.9% of the respondents had access to a dedicated catheter room for the treatment of COVID-19-positive ACS patients. Most respondents stated that the COVID-19 pandemic had varying degrees of effect on the treatment of acute ST-segment elevation myocardial infarction (STEMI), acute non-ST-segment elevation myocardial infarction (NSTEMI), and unstable angina. Compared with the assumed non-pandemic period, in the designed clinical questions, the selection of coronary interventional therapy for STEMI, NSTEMI, and unstable angina during the COVID-19 pandemic was significantly decreased (all p < 0.05), and the selection of pharmacotherapy was increased (all p < 0.05). The selection of fibrinolytic therapy for STEMI during the pandemic was higher than in the assumed non-pandemic period (p < 0.05). Conclusion(s): The COVID-19 pandemic has profoundly affected ACS clinical practice patterns. The use of invasive therapies significantly decreased during the pandemic period, whereas pharmacotherapy was more often prescribed by the cardiologists. Copyright: © 2022 The Author(s).

16.
Frontiers in Public Health ; 10:1050034, 2022.
Article in English | MEDLINE | ID: covidwho-2163194

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), infects humans through a strong interaction between the viral spike protein (S-protein) and angiotensin converting enzyme 2 (ACE2) receptors on the cell surface. The infection of host lung cells by SARS-CoV-2 leads to clinical symptoms in patients. However, ACE2 expression is not restricted to the lungs;altered receptors have been found in the nasal and oral mucosa, vessel, brain, pancreas, gastrointestinal tract, kidney, and heart. The future of COVID-19 is uncertain, however, new viral variants are likely to emerge. The SARS-CoV-2 Omicron variant has a total of 50 gene mutations compared with the original virus;15 of which occur in the receptor binding domain (RBD). The RBD of the viral S-protein binds to the human ACE2 receptor for viral entry. Mutations of the ACE2-RBD interface enhance tight binding by increasing hydrogen bond interactions and expanding the accessible surface area. Extracorporeal membrane oxygenation, hyperbaric oxygen, and aggressive dialysis for the treatment of COVID-19 have shown various degrees of clinical success. The use of decoy receptors based on the ACE2 receptor as a broadly potent neutralizer of SARS-CoV-2 variants has potential as a therapeutic mechanism. Drugs such as 3E8 could block binding of the S1-subunit to ACE2 and restrict the infection of ACE2-expressing cells by a variety of coronaviruses. Here, we discuss the development of ACE2-targeted strategies for the treatment and prevention of COVID-19.

17.
BMC Public Health ; 22(1):2339, 2022.
Article in English | MEDLINE | ID: covidwho-2162338

ABSTRACT

BACKGROUND: The spread of unvetted scientific information about COVID-19 presents a significant challenge to public health, adding to the urgency for increased understanding of COVID-19 information-seeking preferences that will allow for the delivery of evidence-based health communication. This study examined factors associated with COVID-19 information-seeking behavior.

18.
Chinese Journal of Microbiology and Immunology (China) ; 42(2):141-147, 2022.
Article in Chinese | EMBASE | ID: covidwho-1928711

ABSTRACT

Objective To investigate the changes in epidemiological characteristics of common respiratory pathogens in children in Beijing during COVID-19 epidemic.Methods A total of 9 728 serum samples were collected from cases of acute respiratory infections in Beijing Children′s Hospital from January 2020 to December 2020.Indirect immunofluorescence antibody test was performed to detect IgM antibodies against eight common respiratory pathogens and the test results were statistically analyzed.The eight common respiratory pathogens were influenza virus A (FluA), influenza virus B (FluB), respiratory syncytial virus (RSV), adenovirus (ADV), parainfluenza virus (PIV), Mycoplasma pneumoniae (Mp), Chlamydia pneumoniae (Cp) and Legionella pneumophila (Lp).Results The detection rate of respiratory pathogens in 9 728 cases was 41.71% (4 058/9 728) and respiratory viruses (FluA, FluB, RSV, ADV and PIV) accounted for 46.18% (2 343/5 074) of all detected pathogens.Mp, FluB and FluA accounted for 84.73% (4 299/5 074)of all detected pathogens, and the detection rates were 24.27% (2 361/9 728), 11.49% (1 118/9 728) and 8.43% (820/9 728), respectively.There were 846 cases positive for two kinds of pathogens, and the most common co-infection was Mp and FluB.The detection rates in male and female were 37.56% (2 089/5 562) and 47.26% (1 969/4 166), respectively.There were significant differences in the total detection rate and the positive rates of PIV and Mp between different sexes (P<0.05).The detection rate in school-age children (6-12 years old) was the highest (52.26%, 1 535/2 937).The detection rates of respiratory pathogens in different months ranged from 30.12% (203/674) to 49.81% (268/538) with higher rates in autumn and winter [42.45% (1 304/3 072) and 43.29% (1 618/3 738)].The detection rates of FluA and FluB were higher in summer [11.46% (195/1 701)] and winter [14.63% (547/3738)], respectively.Most of RSV infection occurred in summer [1.35% (23/1 701)], and Mp could be detected all year round, especially in winter and spring [27.21% (1 017/3 738) and 25.64% (312/1 217)].The detection rate of respiratory pathogens in outpatient group was higher than that in inpatient group [46.48% (1 583/3 406) vs 39.15% (2 475/6 322)].The detection rate in severe cases was 26.10% (71/272).The detection rates of total pathogens, FluB and Mp were higher in outpatients than in inpatients and the differences were statistically significant (P<0.05).The detection rates of FluA, PIV and ADV were higher in inpatients than in outpatients and the differences were statistically significant (P < 0.05).The detection rates of total pathogens, FluB and Mp in mild cases were significantly higher than those in severe cases and the differences were statistically significant (P<0.05).The detection rate of RSV in severe cases was significantly higher than that in mild cases and the difference was statistically significant (P<0.05).Conclusions The protective measures taken during the period of regular prevention and control of COVID-19 epidemic could better prevent the spread of respiratory viruses, having a certain impact on the population susceptible to respiratory pathogens and typical seasonal patterns, but had little effect on the prevention and control of Mp.New protective measures needed to be studied to prevent Mp infection in children during epidemical season.

19.
Frontiers in Physics ; 10:15, 2022.
Article in English | English Web of Science | ID: covidwho-1883946

ABSTRACT

Coronavirus disease 2019 (COVID-19) has exposed the public safety issues. Obtaining inter-individual contact and transmission in the underground spaces is an important issue for simulating and mitigating the spread of the pandemic. Taking the underground shopping streets as an example, this study aimed to verify commercial facilities' influence on the spatiotemporal distribution of inter-individual contact in the underground space. Based on actual surveillance data, machine learning techniques are adopted to obtain utilizers' dynamics in underground pedestrian system and shops. Firstly, an entropy maximization approach is adopted to estimate pedestrians' origin-destination (OD) information. Commercial utilization behaviors at different shops are modeled based on utilizers' entering frequency and staying duration, which are obtained by re-identifying individuals' disappearances and appearances at storefronts. Based on observed results, a simulation method is proposed to estimate utilizers' spatiotemporal contact by recreating their space-time paths in the underground system. Inter-individual contact events and exposure duration are obtained in view of their space-time vectors in passages and shops. A social contact network is established to describe the contact relations between all individuals in the whole system. The exposure duration and weighted clustering coefficients were defined as indicators to measure the contact degree of individual and the social contact network. The simulation results show that the individual and contact graph indicators are similar across time, while the spatial distribution of inter-individual contact within shops and passages are time-varying. Through simulation experiments, the study verified the effects of self-protection and commercial type adjustment measures.

20.
2021 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1874292

ABSTRACT

Practical and efficient face alignment has been highly required and widely focused in recent years, especially under the trend of edge computation and real-Time operation. And it is a critical need to deal with masked faces in the context of COVID-19 epidemic. In this paper, we propose a novel cascaded facial landmark detector towards efficient masked face alignment, which we call QCN (Quantized Cascaded Network). QCN consists of three stages: Alignment, estimation and refinement. The alignment stage help to pre-Align the faces to alleviate extreme poses. And the next two stages localize facial landmarks in a coarse-To-fine manner. Thanks to the Network Architecture Search and Quantization techniques, the networks of QCN are designed as efficient as possible. Specifically, QCN occupies 1.75 Mb storage and runs in 84.18 MFLOPs only. Despite costs little computations, the proposed method yields 62.62% AUC (@0.08) on test set of JD-landmark-mask, which achieves 2nd place in the Grand Challenge of 106-point Facial Landmark Localization in ICME2021. © 2021 IEEE.

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