UAE e-learning sentiment analysis framework

This research project predicts and infers real-time insights on public mental health relevant to education during and after the COVID-19 pandemic by modeling, deploying, and testing an end-to-end spatiotemporal sentiment analysis framework. Moreover, the project aims to analyze the sentiments and emotions of the public;from Twitter, toward the current context of the e-learning process factored by aspects and emotions. The framework consists of four predictive models based on statistical analysis and machine learning to analyze the UAE education-related Twitter dataset. The first analytics is spatiotemporal analytics, which describes an event at a specific time and specific location. Spatiotemporal analytics is used as the base for the remaining three analytics: Aspect-based Sentiment Analysis, sentiment analysis, and emotion analysis. Aspectbased Sentiment Analysis considers the words/terms related to relevant aspects and then identify the sentiment associated with them. Sentiment Analysis is used to extract the sentiment in a specific text. Emotion Analysis identifies the type of emotion felt by users in their tweets. All the analytics will be visualized into a responsive website that provides a prompt understanding of the public opinions and their feedback towards the e-learning process. As a result, a group of recommendations is generated based on the analytics' resulting emotion to enhance the mental health. © 2021 Association for Computing Machinery.

Dynamic Masking: A Proposal of Burden-Based Metrics for Masking in K-12 Schools During the COVID-19 Pandemic.

BACKGROUND: Ongoing masking of K-12 children has not been universally accepted despite recommendation from public health authorities. In states without universal mask mandates for schools, district administrators are forced to make masking decisions under significant local political pressures. There is a call for endpoints to masking to allow communities to tailor mitigation while keeping schools safe, focusing on harm reduction. METHODS: We reviewed existing measures for the safe opening of schools and designed a stepwise, accessible approach to the removal of masks in the K-12 setting. RESULTS: Focusing first on the assessment of school impact due to COVID-19 disease and then considering the context of existing community transmission levels allows for a metrics-based approach to masking that is flexible and practical, enabling school officials to adapt quickly to the pandemic landscape in their communities, independent of political pressures. CONCLUSIONS: While this proposal is preliminary, a dynamic metric system for masking may encourage those communities who wish to minimize masking to adopt masks during highest risk periods, protecting against SARS-CoV-2 transmission in schools and allowing for more holistic harm reduction. This approach may serve to guide districts during times of uncertainty when central guidance short of universal masking is lacking.

SARS-CoV-2 Incidence and Transmission in 48 K-12 Virginia Public Schools During Community Surge.

Among 20 681 students and 4282 staff, the in-school transmission of SARS-CoV-2 appeared low during highest community spread and at 3- to 6-foot distancing. Nine of 820 school cases (1.1%) resulted in spread, with only one student-to-staff transmission. A school epidemiologist and mitigation audit teams were useful.

Coronavirus Disease 2019 in a Patient With a Systemic Autoinflammatory Syndrome due to an NLRC4 Inflammasomopathy.

The effect of autoinflammatory diseases on severe acute respiratory syndrome coronavirus 2 infection remains unknown. We report a case of coronavirus disease 2019 (COVID-19) in a patient with autoinflammation with infantile enterocolitis with inflammatory flares due to a mutation in the inflammasome component NLRC4. This case highlights the role of immunosuppression in patients with autoinflammation with COVID-19.

Limited variation between SARS-CoV-2-infected individuals in domain specificity and relative potency of the antibody response against the spike glycoprotein (preprint)

The spike protein of SARS-CoV-2 is arranged as a trimer on the virus surface, composed of three S1 and three S2 subunits. Infected and vaccinated individuals generate antibodies against spike, which can neutralize the virus. Most antibodies target the receptor-binding domain (RBD) and N-terminal domain (NTD) of S1; however, antibodies against other regions of spike have also been isolated. The variation between infected individuals in domain specificity of the antibodies and in their relative neutralization efficacy is still poorly characterized. To this end, we tested serum and plasma samples from 85 COVID-19 convalescent subjects using 7 immunoassays that employ different domains, subunits and oligomeric forms of spike to capture the antibodies. Samples were also tested for their neutralization of pseudovirus containing SARS-CoV-2 spike and of replication-competent SARS-CoV-2. We observed strong correlations between the levels of NTD- and RBD-specific antibodies, with a fixed ratio of each type to all anti-spike antibodies. The relative potency of the response (defined as the measured neutralization efficacy relative to the total level of spike-targeting antibodies) also exhibited limited variation between subjects, and was not associated with the overall amount of anti-spike antibodies produced. Accordingly, the ability of immunoassays that use RBD, NTD and different forms of S1 or S1/S2 as capture antigens to estimate the neutralizing efficacy of convalescent samples was largely similar. These studies suggest that host-to-host variation in the polyclonal response elicited against SARS-CoV-2 spike is primarily limited to the quantity of antibodies generated rather than their domain specificity or relative neutralization potency. IMPORTANCEInfection by SARS-CoV-2 elicits antibodies against various domains of the spike protein, including the RBD, NTD and S2. Different infected individuals generate vastly different amounts of anti-spike antibodies. By contrast, as we show here, there is a remarkable similarity in the properties of the antibodies produced. Different individuals generate the same proportions of antibodies against each domain of the spike protein. Furthermore, the relationship between the amount of anti-spike antibodies produced and their neutralization efficacy of SARS-CoV-2 is highly conserved. Therefore, the observed variation in the neutralizing activity of the antibody response in COVID-19 convalescent subjects is caused by differences in the amounts of antibodies rather than their recognition properties or relative antiviral activity. These findings suggest that COVID-19 vaccine strategies that focus on enhancing the overall level of the antibodies will likely elicit a more uniformly efficacious protective response.

COVID-19 Transmission during Transportation of 1st to 12th Grade Students: Experience of an Independent School in Virginia.

BACKGROUND: In-school transmission of COVID-19 among K-12 students is low when mitigation layers are used, but the risk of acquiring COVID-19 during school bus transportation is not well defined. Given the operational limitations of many school districts, more data is needed to determine what mitigation is required to keep COVID-19 transmission low during bus transport. METHODS: An independent school in Virginia monitored 1154 students in grades 1 to 12 with asymptomatic PCR testing every 2 weeks from August 24, 2020 to March 19, 2021, during the highest community transmission. Fifteen buses served 462 students while operating at near capacity of 2 students in every seat, using a physical distancing minimum of 2.5 ft, universal masking, and simple ventilation techniques. RESULTS: A total of 39 individuals were present on buses during their COVID-19 infectious period, which resulted in the quarantine of 52 students. Universal testing and contact tracing revealed no transmission linked to bus transportation. CONCLUSIONS: This study demonstrates a model for the safe operation of school buses while near capacity. COVID-19 transmission can be low during student transport when employing mitigation including simple ventilation, and universal masking, at minimal physical distances and during the highest community transmission.

Helmet Modification to PPE With 3D Printing During the COVID-19 Pandemic at Duke University Medical Center: A Novel Technique.

Care for patients during COVID-19 poses challenges that require the protection of staff with recommendations that health care workers wear at minimum, an N95 mask or equivalent while performing an aerosol-generating procedure with a face shield. The United States faces shortages of personal protective equipment (PPE), and surgeons who use loupes and headlights have difficulty using these in conjunction with face shields. Most arthroplasty surgeons use surgical helmet systems, but in the current pandemic, many hospitals have delayed elective arthroplasty surgeries and the helmet systems are going unused. As a result, the authors have begun retrofitting these arthroplasty helmets to serve as PPE. The purpose of this article is to outline the conception, design, donning technique, and safety testing of these arthroplasty helmets being repurposed as PPE.