COVID-19 Pandemic and Bond ETF Valuation Discount

The COVID-19 pandemic has had an initial and outsized negative impact on bond exchange-traded funds (ETFs), causing concerns for financial stability. Using a large panel of US bond ETFs, we conduct a comprehensive examination of the impact of the pandemic on ETF valuation discounts. We find the change in COVID-19 deaths to be significantly related to the valuation discounts of government bond ETFs and corporate bond ETFs, with investment-grade corporate bond ETFs showing greater sensitivity. These valuation discounts reversed dramatically after the Federal Reserve announced its intentions to purchase corporate bonds and bond ETFs. Government economic policies to combat the pandemic are also negatively related to the valuation discounts of corporate bond ETFs. These findings are evidence of the efficacy of broad-based liquidity support on restoring financial stability in the bond ETF market at a time of enormously stressed market sentiment and massive pricing dislocations. Copyright 2022 With Intelligence LLC.

Crowd intervention strategies considering indoor respiratory exposure risks

In order to explore impacts of crowd intervention strategies on indoor respiratory exposure risks during major pandemics, a variety of crowd motion scenarios were established in general indoor conditions based on improved pedestrian dynamics model and respiratory infection probability model. Then, multi-agent simulation technology was utilized to simulate impacts of strategies, including protection optimization, pedestrian flow optimization and route optimization, on the exposure risks. The results show that indoor respiratory exposure risks are mainly determined by total pedestrian flow, individuals' stay length, movement route planning and duration of stay in contaminated areas. The carryover effect will be formed due to pedestrians' obedience behavior of social distancing, which will further increase exposure time to contaminated areas. The lower pathogen permeability of masks, and the greater space ventilation are, the lower infection probability the crowd will face. © 2022 China Safety Science Journal. All rights reserved.

Effectiveness and policies analysis of pool testing method for COVID-19

Purpose: This research aims to figure out whether the pool testing method of SARS-CoV-2 for COVID-19 is effective and the optimal sample size is in one bunch. Additionally, since the infection rate was unknown at the beginning, this research aims to propose a multiple sampling approach that enables the pool testing method to be utilized successfully. Design/methodology/approach: The authors verify that the pool testing method of SARS-CoV-2 for COVID-19 is effective under the situation of the shortage of nucleic acid detection kits based on probabilistic modeling. In this method, the testing is performed on several samples of the cases together as a bunch. If the test result of the bunch is negative, then it is shown that none of the cases in the bunch has been infected with the novel coronavirus. On the contrary, if the test result of the bunch is positive, then the samples are tested one by one to confirm which cases are infected. Findings: If the infection rate is extremely low, while the same number of detection kits is used, the expected number of cases that can be tested by the pool testing method is far more than that by the one-by-one testing method. The pool testing method is effective only when the infection rate is less than 0.3078. The higher the infection rate, the smaller the optimal sample size in one bunch. If N samples are tested by the pool testing method, while the sample size in one bunch is G, the number of detection kits required is in the interval (N/G, N). Originality/value: This research proves that the pool testing method is not only suitable for the situation of the shortage of detection kits but also the situation of the overall or sampling detection for a large population. More importantly, it calculates the optimal sample size in one bunch corresponding to different infection rates. Additionally, a multiple sampling approach is proposed. In this approach, the whole testing process is divided into several rounds in which the sample sizes in one bunch are different. The actual infection rate is estimated gradually precisely by sampling inspection in each round. © 2021, Emerald Publishing Limited.

Face Recognition With Masks Based on Spatial Fine-Grained Frequency Domain Broadening

Along with social distancing, wearing masks is an effective method of preventing the transmission of COVID-19 in the ongoing pandemic. However, masks occlude a large number of facial features, preventing facial recognition. The recognition rate of existing methods may be significantly reduced by the presence of masks. In this paper, we propose a method to effectively solve the problem of the lack of facial feature information needed to perform facial recognition on people wearing masks. The proposed approach uses image super-resolution technology to perform image preprocessing along with a deep bilinear module to improve EfficientNet. It also combines feature enhancement with frequency domain broadening, fuses the spatial features and frequency domain features of the unoccluded areas of the face, and classifies the fused features. The features of the unoccluded area are increased to improve the accuracy of recognition of masked faces. The results of a cross-validation show that the proposed approach achieved an accuracy of 98% on the RMFRD dataset, as well as a higher recognition rate and faster speed than previous methods. In addition, we also performed an experimental evaluation in an actual facial recognition system and achieved an accuracy of 99%, which demonstrates the effectiveness and practicability of the proposed method.

Generative Facial Prior and Semantic Guidance for Iterative Face Inpainting

Image inpainting techniques have been greatly improved by relying on structure and texture priors. However, damaged original images or rough predictions cannot provide sufficient texture information and accurate structural priors, leading to a drop in image quality. Moreover, from the perspective of human visual perception, it is important to pay attention to facial symmetry and facial attribute consistency. In this paper, we present a face inpainting system with iteration structure, guided by generative facial priors contained in pretrained GANs and predicted semantic information. Specifically, generative facial priors generated by the GAN inversion techniques introduce sufficient textures and features to assist inpainting;semantic maps are able to provide facial structural information and semantic categories of different pixels for face reconstruction. In particular, we iteratively refine images multiple times, updating semantic maps at each iteration. The Weighted Prior-Guidance Modulation layer (WPGM) is devised for incorporating priors into networks through spatial modulation. We also propose facial feature self-symmetry loss to constrain the symmetry of faces in feature space. Experiments on CelebA-HQ and LaPa datasets demonstrate the superiority of our model for facial detail and attribute consistency. Meanwhile, under the background of COVID-19, it is worth trying recognition via inpainting to deal with recognition challenges brought by mask occlusion. Relevant experiments show that our inpainting model does help to recognition tasks to a certain degree, with higher accuracy.

Gendering National Sacrifices: The Making of New Heroines in China's Counter-COVID-19 TV Series

From February 2020 to the end of 2021, China's state-controlled media focused on creating its "victorious" narrative of combating the COVID-19 pandemic. This article focuses on two high-profile and COVID-19-themed TV series that aim to rewrite the collective memories of the Wuhan lockdown as part of state's affective governance strategies. Using a feminist textual analysis, the article examines the gendered nature of state narratives by dissecting the representation of national heroines of the pandemic. It demonstrates the centrality of heterosexual families and gender performances in romanticizing individual sacrifices and mass suffering. Unlike the socialist-era role models, the personal weakness and emotional flaws of China's new heroines are tactically displayed to enhance emotional authenticity and resonate with contemporary audiences. Yet these state narratives reflect only stereotypical depictions of femininity within a hierarchical gender order in post-reform China, where moralized womanhood is imbued with a sacrificial attitude that serves to discipline China's female citizens.

Head Pose Estimation in Complex Environment Based on Four-branch Feature Selective Extraction and Regional Information Exchange Fusion Network

Under the severe situation of the COVID-19 pandemic, masks cover most of the effective facial features of users, and their head pose changes significantly in a complex environment, which makes the accuracy of head pose estimation in some systems such as safe driving systems and attention detection systems impossible to guarantee. To this end, we propose a powerful four-branch feature selective extraction network (FSEN) structure, in which three branches are used to extract three independent discriminative features of pose angles, and one branch is used to extract composite features corresponding to multiple pose angles. By reducing the dimension of high-dimensional features, our method significantly reduces the amount of computation while improving the estimation accuracy. Our convolution method is an improved spatial channel dynamic convolution (SCDC) that initially enhances the extracted features. Additionally, we embed a regional information exchange network (RIEN) after each convolutional layer in each branch to fully mine the potential semantic correlation between regions from multiple perspectives and learn and fuse this correlation to further enhance feature expression. Finally, we fuse the independent discriminative features of each pose angle and composite features from the three directions of channel, space, and pixel to obtain perfect feature expression for each pose angle, and then obtain the head pose angle. We conducted extensive experiments on the controlled environment datasets and a self-built real complex environment dataset (RCE) and the results showed that our method outperforms state-of-the-art single-modality methods and performs on par with multimodality-based methods. This shows that our network meets the requirements of accurate head-pose estimation in real complex environments such as complex illumination and partial occlusion. Author

Satisfaction and reimbursement of telemedicine in head and neck surgery

Introduction: The COVID-19 pandemic accelerated telemedicine efforts throughout otolaryngology. This study examines the impact of telemedicine visits on surgical yield, financial reimbursement, and patient satisfaction within the head and neck division at a tertiary referral center. Method: This is a retrospective review of new head and neck patients seen via telemedicine between January 2020 and December 2020. Chart review was conducted to identify the reason for the visit and surgical yield. Patient satisfaction was assessed using Press-Ganey surveys. Chi-squared tests were used to compare satisfaction scores, and Wilcoxon rank-sum tests and t tests were used to compare reimbursements. Results: In 2020 the head and neck division saw 1157 new patients in-person and 123 new patients via telemedicine. Telemedicine visits led to 52 (42%) surgeries, and 58 (47%) of patients seen were requesting a second opinion. Financial reimbursement data were available for 42 telemedicine and 202 in-person visits. Average reimbursement for telemedicine visits was 86%. No differences were seen between government and commercial payers in the charges (P = .22) and reimbursements (P = .42) for in-person visits. For the telemedicine visits, charges (P < .01) and reimbursements (P = .03) were significantly less for government payers. Of the telemedicine visits, 91% were rated as 'very good' in patients' likeliness to recommend, compared with 94% of in-person visits (P = .30). Some 91% of telemedicine patients felt that the ability of the care team to explain the condition was 'very good,' compared with 92% of in-person patients (P = .83). For 77% and 78% of patients, a 'very good' rating was given on the ease of contacting and scheduling telemedicine visits, which was not significantly different than the 79% and 83% of patients rating in-person visits (P = .90, P =.55). Conclusion: Definitive decisions about surgical planning can be made effectively by patients and providers in a virtual setting. Patient satisfaction rates are generally high for telemedicine visits and similar to those for in-person visits, but reimbursement for telemedicine visits was notably lower in government payers.

Zoom into the future: Constructing head and neck treatment plans via telemedicine

Introduction: COVID-19 has accelerated the need for virtual visits within health care. We examine whether otolaryngologists can make definitive treatment plans for new head and neck patients through a virtual video platform using existing chart information. Method: An institutional review board exempt retrospective chart review was conducted of new patients presenting for treatment or second opinion via virtual video visits between January 2020 and December 2020 at our tertiary care institution. Treatment plan, visit outcomes, and information available in the chart at time of visit (biopsy, ultrasound, computed tomography [CT], magnetic resonance imaging [MRI], and positron emission tomography [PET]) was collected. Treatment plan was designated as the following: yes, a definitive plan was made or no, an additional in-person visit was required. Outcome measures included whether a follow-up was recommended (eg, clinic visits or surgery) and if a follow-up occurred. Results: A total of 447 head and neck virtual visits were found, 124 of which were video visits for new patients. A treatment plan could be prescribed 88.7% of the time (n = 110). Fourteen patients required additional imaging, biopsy, or consultation with other departments to formulate a plan. A higher proportion of patients with tonsillar neoplasms (42.8%, n = 3) and thyroid nodules (57.1%, n = 4) needed in-person follow-up in comparison with other concerns. Of all patients, 89.5% were instructed to follow up (n = 111), 57.7% of which were for surgery (n = 64), 26.1% for clinic visits (n =29), and 16.2% for miscellaneous other reasons (eg, fine-needle aspiration, radiation therapy, staging workup, consult;n = 18). CT scans were the most commonly available information in the chart for 54% of patients (n = 67), followed by biopsy report (30.6%, n = 38), MRI (27.4%, n = 34), PET (20.9%, n = 26), and ultrasound (18.5%, n = 23). For new patients with parotidspecific concerns (n = 38), a definitive treatment plan could be made for 97.3% (n = 37) and involved surgery 72.2% of the time (n = 26). Conclusion: A high ability exists to make definitive treatment decisions about a new head and neck patient's care through a virtual video visit platform, especially for parotidrelated concerns. This study supports the feasibility of transitioning in-person head and neck visits to virtual.

Are in-person postoperative parotidectomy follow-ups a thing of the past?

Introduction: COVID-19 accelerated the need for virtual visits within health care, and otolaryngology was no exception. We examined whether otolaryngologists are able to perform postoperative care through a virtual visit platform, specifically for patients who underwent parotidectomy. Method: A retrospective case review under institutional review board exemption of patients who underwent parotidectomy and postoperative video visits between September 2019 and December 2020 was conducted. A chart review of all video visits was sorted for “established” patients (ie, previously seen by the department presenting for surveillance, surgery follow-up, or new concern) and narrowed to postoperative parotidectomy follow-up patients. Days between surgery and postoperative follow-up, treatment plan, and postvisit outcomes were reviewed. Treatment plan was designated as follows: yes, a definitive treatment plan was made;no, a provider required additional in-person visits;and, not applicable, no concerns existed. Outcomes measures included whether an inperson follow-up was recommended and if a follow-up occurred. Results: There were 447 head and neck virtual visits found, 302 established visits, and 194 new video visits. There were 96 postoperative parotidectomy patients. Demographics were 28 male and 68 female, with an average age of 54 years. The first video visit occurred, on average, 48 days postop. Of the patients, 8.3% (n = 8) presented with minor complications (eg, eye dryness, seroma, first bite pain) and required a treatment plan. The virtual visit was sufficient for prescribing a plan for 100% of those visits. For the other 91.7% of patients (n = 88), no treatment plan was required, and 26% were instructed to follow up (n = 25), 23 of whom were routine for surveillance and 2 for procedural follow-up. All other patients were instructed to follow up as needed. We noted 11 clinic and 2 surgery (hematoma evacuation, seroma aspiration) follow-ups at the time of review. Conclusion: The results demonstrate the ability to make definitive decisions about a parotidectomy patient's postoperative care through a virtual visit platform. This study supports the feasibility of transitioning in-person parotidectomy postop visits to virtual.

Effectiveness and policies analysis of pool testing method for COVID-19

Purpose: This research aims to figure out whether the pool testing method of SARS-CoV-2 for COVID-19 is effective and the optimal sample size is in one bunch. Additionally, since the infection rate was unknown at the beginning, this research aims to propose a multiple sampling approach that enables the pool testing method to be utilized successfully. Design/methodology/approach: The authors verify that the pool testing method of SARS-CoV-2 for COVID-19 is effective under the situation of the shortage of nucleic acid detection kits based on probabilistic modeling. In this method, the testing is performed on several samples of the cases together as a bunch. If the test result of the bunch is negative, then it is shown that none of the cases in the bunch has been infected with the novel coronavirus. On the contrary, if the test result of the bunch is positive, then the samples are tested one by one to confirm which cases are infected. Findings: If the infection rate is extremely low, while the same number of detection kits is used, the expected number of cases that can be tested by the pool testing method is far more than that by the one-by-one testing method. The pool testing method is effective only when the infection rate is less than 0.3078. The higher the infection rate, the smaller the optimal sample size in one bunch. If N samples are tested by the pool testing method, while the sample size in one bunch is G, the number of detection kits required is in the interval (N/G, N). Originality/value: This research proves that the pool testing method is not only suitable for the situation of the shortage of detection kits but also the situation of the overall or sampling detection for a large population. More importantly, it calculates the optimal sample size in one bunch corresponding to different infection rates. Additionally, a multiple sampling approach is proposed. In this approach, the whole testing process is divided into several rounds in which the sample sizes in one bunch are different. The actual infection rate is estimated gradually precisely by sampling inspection in each round. © 2021, Emerald Publishing Limited.

Analysis of Epidemic Events Based on Event Evolutionary Graph

In this paper, by analyzing the characteristics of the news reports of the COVID-19 epidemic events, we extract the event ancestor pairs from the text, extract the relationship between the events through attention-based bidirectional LSTM, and display them in the form of EEG model, which is conducive to the analysis of the evolution of epidemic events. The method proposed in this paper provides a new idea for the evolution of network events. The constructed event map can clearly show the evolution path of network events, monitor key nodes of network events, assist relevant management departments to formulate corresponding measures, and lead the events forward in a positive way. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.