Evaluation of a Video Generation Method Linking Dance and Scenes

Owing to the impact of COVID-19, the venues for dancers to perform have shifted from the stage to the media. In this study, we focus on the creation of dance videos that allow audiences to feel a sense of excitement without disturbing their awareness of the dance subject and propose a video generation method that links the dance and the scene by utilizing a sound detection method and an object detection algorithm. The generated video was evaluated using the Semantic Differential method, and it was confirmed that the proposed method could transform the original video into an uplifting video without any sense of discomfort. © 2023 SPIE.

Embracing DDMT Teaching Model and Design Thinking for Organization Development

The multi-generational workforce presents challenges for organizations, as the needs and expectations of employees vary greatly between different age groups. To address this, organizations need to adapt their development and learning principles to better suit the changing workforce. The DDMT Teaching Model of Tsing Hua STEAM School, which integrates design thinking methodology, aims to address this challenge. DDMT stands for Discover, Define, Model & Modeling, and Transfer. The main aim of this study is to identify the organization development practices (OD) and gaps through interdisciplinary models such as DDMT and design thinking. In collaboration with a healthcare nursing home service provider, a proof of concept using the DDMT-DT model was conducted to understand the challenges in employment and retention of support employees between nursing homes under the healthcare organization. The paper highlights the rapid change in human experiences and mindsets in the work culture and the need for a design curriculum that is more relevant to the current and future workforce. The DDMT-DT approach can help organizations address these challenges by providing a framework for HR personnel to design training curricula that are more effective in addressing the issues of hiring and employee retention. By applying the DDMT-DT model, HR personnel can better understand the needs and motivations of the workforce and design training programs that are more relevant to their needs. The proof-of-concept research pilot project conducted with the healthcare nursing home service provider demonstrated the effectiveness of the DDMT-DT model in addressing the issues of hiring and employee retention. The project provides a valuable case study for other organizations looking to implement the DDMT-DT model in their HR practices. Overall, the paper highlights the importance of adapting HR practices to better suit the changing workforce. The DDMT-DT model provides a useful framework for organizations looking to improve their HR practices and better address the needs of their workforce.

Non-Hodgkin's lymphoma complicated with human coronavirus HKU1 pneumonia: A case report and literature review.

Objective: To analyze the clinical manifestations, diagnostic methods and treatment process of the patients with non-Hodgkin's lymphoma complicated with human coronavirus(HCoV)-HKU1 pneumonia and improve the clinical medical staff's awareness of the disease, and to reduce the occurrence of clinical adverse events. Method(s): The clinical data of a patient with non-Hodgkin's lymphoma complicated with HCoV-HKU1 pneumonia with hot flashes and night sweats, dry cough and dry throat as the main clinical features who were hospitalized in the hospital in January 2021 were analyzed, and the relevant literatures were reviewed and the clinical manifestations and diagnosis of HCoV-HKU1 were analyzed. Result(s): The female patient was admitted to the hospital due to diagnosed non-Hodgkin's lymphoma for more than 2 months. The physical examination results showed Karnofsky score was 90 points;there was no palpable enlargement of systemic superfical lymph nodes;mild tenderness in the right lower abdomen, no rebound tenderness, and slightly thicker breath sounds in both lungs were found, and a few moist rales were heard in both lower lungs. The chest CT results showed diffuse exudative foci in both lungs, and the number of white blood cells in the urine analysis was 158 muL-1;next generation sequencing technique(NGS) was used the detect the bronchoalveolar lavage fluid, and HCoV-HKU1 pneumonia was diagnosed. At admission, the patient had symptoms such as dull pain in the right lower abdomen, nighttime cough, and night sweats;antiviral treatment with oseltamivir was ineffective. After treatment with Compound Sulfamethoxazole Tablets and Lianhua Qingwen Granules, the respiratory symptoms of the patient disappeared. The re-examination chest CT results showed the exudation was absorbed. Conclusion(s): The clinical symptoms of the patients with non-Hodgkin's lymphoma complicated with HCoV-HKU1 pneumonia are non-specific. When the diffuse shadow changes in the lungs are found in clinic, and the new coronavirus nucleic acid test is negative, attention should still be paid to the possibility of other HCoV infections. The NGS can efficiently screen the infectious pathogens, which is beneficial to guide the diagnosis and treatment of pulmonary infectious diseases more accurately.Copyright © 2023 Jilin University Press. All rights reserved.

Ensuring self-sustainability in decentralized communities through solar cookers combined with food dryers

In the background of the COVID 2019 pandemic, the importance of developing realistic and efficient decentralized energy solutions is one of the essential requirements. This paper presents the performance of a small-scale solar box cooker cum dryer (SBCD) for decentralized communities and domestic scale applications. The drying process in SBCD uses a simple and effective method for moisture removal. It enables de-moisturization of the cooker interior, allowing efficient use of SBCD for the simultaneous dual-mode operation of cooking and drying. Cooker Opto-thermal Ratio (COR) as a thermal performance parameter and glycerin as a test load enable cooking process analysis. COR-based objective parameters (OPs) realistically comment on the cooker performance in the dual-mode operation. Drying kinetic studies describe the drying performance of the device. The levelized cost of cooking meals (LCCM) allows understating of the economics of SBCD. The mean value of COR for the cooker is 0.104 ± 0.0028 (m2·°C)/W with a percentage standard deviation of 2.69%. The experimental values of OPs, reference cooking time, and maximum achievable load temperature varies between 74 and 86 min and 103–111 °C, respectively. Thus, SBCD cooks in approximately 80–90 min and dries ∼ 100 g of food products simultaneously with 70–80 % moisture removal. The LCCM for SBCD is $ 0.0174 per meal. Thus, SBCD depicts a realistic solution for ensuring self-sustainability in decentralized communities.

Marginal Cost of Energy Volatility in the Brazilian Interconnected Power System

From 2018 to 2022, on average, 70% of the Brazilian effective electric generation was produced by hydropower, 10% by wind power, and 20% by thermal power plants. Over the last five years, Brazil suffered from a series of severe droughts. As a result, hydropower generation was reduced, but demand growth was also declined as results of the COVID-19 pandemic and economic recession. From 2012 to 2022, the Brazilian reservoir system operated with, on average, only 40% of the active storage, but storage recovered to normal levels in the first three months of 2022. Despite large capacity of storage reservoirs, high volatility of the marginal cost of energy was observed in recent years. In this paper, we used two optimization models, NEWAVE and HIDROTERM for our study. These two models were previously developed for mid-range planning of the operation of the Brazilian interconnected power system. We used these two models to optimize the operation and compared the results with observed operational records for the period of 2018-2022. NEWAVE is a stochastic dual dynamic programming model which aggregates the system into four subsystems and 12 equivalent reservoirs. HIDROTERM is a nonlinear programming model that considers each of the 167 individual hydropower plants of the system. The main purposes of the comparison are to assess cooperation opportunities with the use of both models and better understand the impacts of increasing uncertainties, seasonality of inflows and winds, demand forecasts, decisions about storage in reservoirs, and thermal production on energy prices. © World Environmental and Water Resources Congress 2023.All rights reserved

A Review on Solar Energy Policy and Current Status: Top 5 Countries and Kazakhstan

The article describes the world's experience in developing the solar industry. It discusses the mechanisms of state support for developing renewable energy sources in the cases of five countries that are the most successful in this area—China, the United States, Japan, India, and Germany. Furthermore, it contains a brief review of state policy in producing electricity by renewable energy facilities in Kazakhstan. This paper uses statistical information from the International Renewable Energy Agency (IRENA), the International Energy Agency (IEA), British Petroleum (BP), and the Renewable Energy Network (REN21), and peer-reviewed sources. The research methodology includes analytical research and evaluation methods to examine the current state of solar energy policy, its motivators and incentives, as well as the prospects for its development in Kazakhstan and in the world. Research shows that solar energy has a huge development potential worldwide and is sure to take its place in gross electricity production. This paper focuses on the selected economic policies of the top five countries and Kazakhstan, in what may be considered a specific research limitation. Future research suggestions for the expansion of Renewable Energy (RE) in Kazakhstan could include analysing the impact of introducing dedicated policies and incentives for solar systems and exploring the benefits and challenges of implementing large RE zones with government–business collaboration.

Combating the COVID-19 Crisis within the European Union: A Critical Assessment of the ‘Next Generation EU' in the Context of the Budgetary Balance

The paper contains a critical analysis of the new system of own resources of the European Union, established to address the consequences of the COVID-19 crisis. Analysis is mainly from the perspective of the balanced budget rule. Under Council Decision 2020/2053 of 14 December 2020, the Commission is to be, inter alia, empowered to borrow an unprecedentedly huge amount of funds on capital markets on behalf of the EU. This means that, for the first time in history, common budgetary commitments on the part of the EU will be on such a scale that repayment will be spread over many years and will be charged to future generations of EU citizens (known as the ‘Next Generation EU' programme). The research aims to compare these innovations with the long-term financial policy of the EU, as a result of the provisions of the Treaty on the Functioning of the European Union and the Fiscal Compact. It also elaborates on the limits of societal debt issued by their representatives who form public authorities. © 2023 The Author(s).

Housing in Portugal and the COVID-19 Pandemic

The adoption of important housing-related measures in Portugal occurred in 2018/2019, before the period in which the SARS-COV-2 pandemic began to manifest itself. Although these measures intended to anticipate and regulate several dimensions of the right to housing, they were not fully prepared, or were not in a state of concreteness, such as to allow a timely reaction to Covid-19 related changes. The purpose of this paper is to analyze the intersection between the new demands brought about by the pandemic and the distinct legal responses that had an impact on the housing market in Portugal.

Trip generation models for Tikrit city

Urban transportation planning has become a matter of urgency in small cities and, in particular, the need to develop planning models for Tikrit city has become pressing. Questionnaire forms and household interviews were used among families in the city, with 22% asked to complete a full interview, 68% offered paper questionnaires to be retrieved on completion, and the rest contacted electronically due to the restrictions of the COVID-19 pandemic. The data from the 4,150 questionnaires collected showed that the characteristics of the community are compatible with those found in other studies and official statistics, with the community of Tikrit being youthful society, with an average of 88.3% of residents not exceeding 60 years of age. After statistical checks were performed on the obtained data, trip generation models were developed using various methods of cross-classification to match vehicle ownership with both income and family size. Using the developed models, the total number of trips by purpose across four sectors were extracted. A comparison of the results across models showed significant difference between the methods, suggesting that the family size variable should be adopted for such modelling as an easily obtainable and relevant variable. © 2023 AIP Publishing LLC.

HLA-B evolutionary divergence is associated with poor outcomes after SARS-CoV-2 infection

Objectives Human leukocyte antigens (HLA) are highly diverse transmembrane proteins that present viral peptides to T cells and launch pathogen-specific immune responses. We aim to investigate the correlation between HLA evolutionary divergence (HED), a surrogate for the capacity to present different peptides, and the outcomes of SARS-CoV-2 infection in a cohort from the St. Louis Metropolitan area. Methods We enrolled adult patients with SARS-CoV-2 infection confirmed by RT-PCR who were hospitalized at two tertiary hospitals in St. Louis between March and July 2020. Genomic DNA was extracted from peripheral blood and genotyped by next-generation sequencing (NGS). HLA alleles were assigned based on key-exon sequences (G group) and limited to the 2-field resolution. HED was calculated by Grantham distance, which considers the difference in composition, polarity, and molecular volume between each pair of amino acids from maternal and paternal HLA. The HED score was obtained for HLA class I (HLA-A, -B, and -C) genotypes using the HLAdivR package in R. Clinical data were collected retrospectively from electronic medical records. A poor outcome was defined as an admission to the intensive care unit (ICU), a need for mechanical ventilation, or death. A favorable outcome was defined as the absence of the above poor outcomes. Results A total of 234 patients were enrolled in this study, 96 being females (41%). The median age and BMI were 66 years old and 28.30 kg/m2, respectively. African Americans comprised 71.4% of the cohort. Only 19 patients (8.1%) presented with no comorbidity;the rest had one or more comorbidities, with cardiovascular diseases being the most common. A total of 137 (58.5%) patients had poor outcomes from SARS-CoV-2 infection, while 97 (41.5%) patients had a favorable outcome. We detected a significant association between higher HLA-B HED and favorable outcomes, with each 1-point increase in HLA-B HED associated with 8% increased probability for the composite endpoint (OR 1.08, 95% CI=1.01-1.16, P = 0.04). The HED scores calculated for HLA-A or HLA-C were not significantly different between patients with favorable or poor outcomes. In a multivariate logistic regression analysis, increased HLA-B HED score, younger age, and no comorbidity were independently associated with favorable outcomes (P = 0.02, P = 0.01, and P = 0.05, respectively). Conclusion Our study shows a significant correlation between lower HLA-B HED scores and poor outcomes after SARS-CoV-2 infection. This finding suggests that maximizing the presentation of diverse SARS-CoV-2 peptides by HLA-B alleles may improve the clearance of SARS-CoV-2. Further studies are warranted to understand the functional and mechanistic implications of this finding.

Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation

The spread of online misinformation threatens public health, democracy, and the broader society. While professional fact-checkers form the first line of defense by fact-checking popular false claims, they do not engage directly in conversations with misinformation spreaders. On the other hand, non-expert ordinary users act as eyes-on-the-ground who proactively counter misinformation - recent research has shown that 96% counter-misinformation responses are made by ordinary users. However, research also found that 2/3 times, these responses are rude and lack evidence. This work seeks to create a counter-misinformation response generation model to empower users to effectively correct misinformation. This objective is challenging due to the absence of datasets containing ground-truth of ideal counter-misinformation responses, and the lack of models that can generate responses backed by communication theories. In this work, we create two novel datasets of misinformation and counter-misinformation response pairs from in-the-wild social media and crowdsourcing from college-educated students. We annotate the collected data to distinguish poor from ideal responses that are factual, polite, and refute misinformation. We propose MisinfoCorrect, a reinforcement learning-based framework that learns to generate counter-misinformation responses for an input misinformation post. The model rewards the generator to increase the politeness, factuality, and refutation attitude while retaining text fluency and relevancy. Quantitative and qualitative evaluation shows that our model outperforms several baselines by generating high-quality counter-responses. This work illustrates the promise of generative text models for social good - here, to help create a safe and reliable information ecosystem. The code and data is accessible on https://github.com/claws-lab/MisinfoCorrect. © 2023 Owner/Author.

A Study on Establishing Thermal Output Conditions of Radiant Ceiling Heating Panels for Improving Thermal Comfort of Perimeter Zone in Buildings

Amid concerns over airflow-induced transmission of the COVID-19 virus in buildings frequented by large numbers of people, such as offices, the necessity for radiant ceiling heating panels has increased. This is due to the concern that the airflows emitted from the convection heating systems installed near the ceiling or windows for winter heating may be a major cause of COVID-19 transmission. In this study, we aim to evaluate thermal comfort under various indoor and outdoor environmental conditions of a building and present the thermal output conditions of the radiant ceiling heating panel that can replace the convection heating system while ensuring comfort in the perimeter zone and handling the heating load. As a result, we were able to present, in a chart format, the thermal output conditions that can secure thermal comfort by analyzing the indoor airflow distribution depending on the surface temperature of the radiant ceiling heating panel, the interior surface temperature of the window, and the influence of internal heat generation. Moreover, through derived empirical formulas, we were able to determine the heating conditions of the panel that can secure the necessary heat dissipation while minimizing discomfort, such as downdrafts, even for indoor and outdoor conditions that were not evaluated in this study.

Modeling the epidemic trend of middle eastern respiratory syndrome coronavirus with optimal control

Since the outbreak of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2012 in the Middle East, we have proposed a deterministic theoretical model to understand its transmission between individuals and MERS-CoV reservoirs such as camels. We aim to calculate the basic reproduction number (R0) of the model to examine its airborne transmission. By applying stability theory, we can analyze and visualize the local and global features of the model to determine its stability. We also study the sensitivity of R0 to determine the impact of each parameter on the transmission of the disease. Our model is designed with optimal control in mind to minimize the number of infected individuals while keeping intervention costs low. The model includes time -dependent control variables such as supportive care, the use of surgical masks, government campaigns promoting the importance of masks, and treatment. To support our analytical work, we present numerical simulation results for the proposed model.

Enhancing Employer Attractiveness: The Impact of COVID-19 on Generation Z

This paper investigates how employer attractiveness has been affected by developments in the attitudes, values, and goals of Generation Z (born between 1995-2010) due to the COVID-19 pandemic. Research shows the challenging environment for employers who are increasingly facing a 'war for talent' and the need to focus on generational needs and expectations. Work concepts in many cases have been adapted to Generation Y, but a revision of strategies is needed for the newest generation on the labour market. The insurance industry has long struggled to attract young talent and along with retail, logistics, tourism, and banking has been ranked the lowest in employer attractiveness by Generation Z. This is corroborated by the fact that larger corporations are also often perceived as unattractive by young people. While many industries have struggled with the consequences and challenges of the pandemic, the insurance sector can be seen as having mastered the crisis comparatively well. This paper questions whether the relative job security offered by the insurance sector, can be increasingly influential in post pandemic job choices. Since Generation Z was already described as securityoriented before the pandemic, this is expected to have increased as a result of COVID-19 and be reflected in their career and employer choices. The perspectives of Generation Z and employers from the German insurance industry are compared through survey and interview data. The young cohort suspects a worsening of their situation particularly in job offerings and security. At the same time, the insurance industry positions itself well in exactly these areas. Furthermore, the aspirations and expectations of Generation Z towards the professional world coincide strongly with the offerings of insurers as employers. However, the respondents see the sector's image as a deterrent. Although this paper focuses on the insurance industry, strategic recommendations given on how the sector can position itself, are relevant for other sectors facing the challenge of attracting Generation Z employees. © 2022 Authors. All rights reserved.

Meteorological-Data-Based Modeling for PV Performance Optimization

Developing a sustainable and reliable photovoltaic (PV) energy system requires a comprehensive analysis of solar profiles and an accurate prediction of solar energy performance at the study site. Installing the PV modules with optimal tilt and azimuth angles has a significant impact on the total irradiance delivered to the PV modules. This paper proposes a comprehensive optimization model to integrate total irradiance models with the PV temperature model to find the optimal year-round installation parameters of PV modules. A novel integration between installation parameters and the annual average solar energy is presented, to produce the maximum energy output. The results suggest an increase in energy yields of 4% compared to the conventional scheme, where tilt angle is equal to the latitude and the PV modules are facing south. This paper uses a real-time dataset for the NEOM region in Saudi Arabia to validate the superiority of the proposed model compared to the conventional scheme, but it can be implemented as a scheme wherever real-time data are available.

Abnormality detection and intelligent severity assessment of human chest computed tomography scans using deep learning: a case study on SARS-COV-2 assessment.

Different respiratory infections cause abnormal symptoms in lung parenchyma that show in chest computed tomography. Since December 2019, the SARS-COV-2 virus, which is the causative agent of COVID-19, has invaded the world causing high numbers of infections and deaths. The infection with SARS-COV-2 virus shows an abnormality in lung parenchyma that can be effectively detected using Computed Tomography (CT) imaging. In this paper, a novel computer aided framework (COV-CAF) is proposed for classifying the severity degree of the infection from 3D Chest Volumes. COV-CAF fuses traditional and deep learning approaches. The proposed COV-CAF consists of two phases: the preparatory phase and the feature analysis and classification phase. The preparatory phase handles 3D-CT volumes and presents an effective cut choice strategy for choosing informative CT slices. The feature analysis and classification phase incorporate fuzzy clustering for automatic Region of Interest (RoI) segmentation and feature fusion. In feature fusion, automatic features are extracted from a newly introduced Convolution Neural Network (Norm-VGG16) and are fused with spatial hand-crafted features extracted from segmented RoI. Experiments are conducted on MosMedData: Chest CT Scans with COVID-19 Related Findings with COVID-19 severity classes and SARS-COV-2 CT-Scan benchmark datasets. The proposed COV-CAF achieved remarkable results on both datasets. On MosMedData dataset, it achieved an overall accuracy of 97.76% and average sensitivity of 96.73%, while on SARS-COV-2 CT-Scan dataset it achieves an overall accuracy and sensitivity 97.59% and 98.41% respectively.

A Survey on Handover and Mobility Management in 5G HetNets: Current State, Challenges, and Future Directions.

Fifth-generation (5G) networks offer high-speed data transmission with low latency, increased base station volume, improved quality of service (QoS), and massive multiple-input-multiple-output (M-MIMO) channels compared to 4G long-term evolution (LTE) networks. However, the COVID-19 pandemic has disrupted the achievement of mobility and handover (HO) in 5G networks due to significant changes in intelligent devices and high-definition (HD) multimedia applications. Consequently, the current cellular network faces challenges in propagating high-capacity data with improved speed, QoS, latency, and efficient HO and mobility management. This comprehensive survey paper specifically focuses on HO and mobility management issues within 5G heterogeneous networks (HetNets). The paper thoroughly examines the existing literature and investigates key performance indicators (KPIs) and solutions for HO and mobility-related challenges while considering applied standards. Additionally, it evaluates the performance of current models in addressing HO and mobility management issues, taking into account factors such as energy efficiency, reliability, latency, and scalability. Finally, this paper identifies significant challenges associated with HO and mobility management in existing research models and provides detailed evaluations of their solutions along with recommendations for future research.

Reprogramming viral immune evasion for a rational design of next-generation vaccines for RNA viruses.

Type I interferons (IFNs-α/ß) are antiviral cytokines that constitute the innate immunity of hosts to fight against viral infections. Recent studies, however, have revealed the pleiotropic functions of IFNs, in addition to their antiviral activities, for the priming of activation and maturation of adaptive immunity. In turn, many viruses have developed various strategies to counteract the IFN response and to evade the host immune system for their benefits. The inefficient innate immunity and delayed adaptive response fail to clear of invading viruses and negatively affect the efficacy of vaccines. A better understanding of evasion strategies will provide opportunities to revert the viral IFN antagonism. Furthermore, IFN antagonism-deficient viruses can be generated by reverse genetics technology. Such viruses can potentially serve as next-generation vaccines that can induce effective and broad-spectrum responses for both innate and adaptive immunities for various pathogens. This review describes the recent advances in developing IFN antagonism-deficient viruses, their immune evasion and attenuated phenotypes in natural host animal species, and future potential as veterinary vaccines.

A Promising Needle-Free Pyro-Drive Jet Injector for Augmentation of Immunity by Intradermal Injection as a Physical Adjuvant.

Current worldwide mRNA vaccination against SARS-CoV-2 by intramuscular injection using a needled syringe has greatly protected numerous people from COVID-19. An intramuscular injection is generally well tolerated, safer and easier to perform on a large scale, whereas the skin has the benefit of the presence of numerous immune cells, such as professional antigen-presenting dendritic cells. Therefore, intradermal injection is considered superior to intramuscular injection for the induction of protective immunity, but more proficiency is required for the injection. To improve these issues, several different types of more versatile jet injectors have been developed to deliver DNAs, proteins or drugs by high jet velocity through the skin without a needle. Among them, a new needle-free pyro-drive jet injector has a unique characteristic that utilizes gunpower as a mechanical driving force, in particular, bi-phasic pyrotechnics to provoke high jet velocity and consequently the wide dispersion of the injected DNA solution in the skin. A significant amount of evidence has revealed that it is highly effective as a vaccinating tool to induce potent protective cellular and humoral immunity against cancers and infectious diseases. This is presumably explained by the fact that shear stress generated by the high jet velocity facilitates the uptake of DNA in the cells and, consequently, its protein expression. The shear stress also possibly elicits danger signals which, together with the plasmid DNA, subsequently induces the activation of innate immunity including dendritic cell maturation, leading to the establishment of adaptive immunity. This review summarizes the recent advances in needle-free jet injectors to augment the cellular and humoral immunity by intradermal injection and the possible mechanism of action.

A Negative-Pressure Face-Mounted System Reduces Aerosol Spread during Endonasal Endoscopic Surgery.

Purpose Due to the potential risk of COVID-19 transmission during endonasal surgery, we studied methods to reduce droplet and aerosol generation during these procedures. Methods Droplet spread was assessed using ultraviolet light and a camera that detected fluorescence in the operative field and surgeon's personal protective equipment. Density of aerosols sized <10 µm was measured using a photometric particle counter. We designed a face-mounted negative-pressure mask placed on the patients' face during endoscopic endonasal surgery. Sixteen patients were recruited between October 2020 and March 2021 and randomly assigned to the mask and no-mask groups. We compared droplet spread and aerosols generated in both groups, with copious irrigation and continuous suction during drilling forming the mainstay of surgical technique in all cases. Results Droplet contamination due to direct spillage of fluorescein from the syringe was noted in two patients. Aerosol density rose during sphenoid drilling in both groups, with no significant difference when continuous suction and irrigation were employed (1.27 times vs. 1.07 times the baseline, p = 0 .248 ). Aerosol density rose significantly when suction and irrigation were interrupted in the no-mask group (44.9 times vs. 1.2 times, p = 0 .028) , which was not seen when the mask was used. Conclusion Aerosol generation increases during drilling in endonasal procedures and is a concern during this pandemic. The use of a rigid suction close to the drill along with copious irrigation is effective in reducing aerosol spread. The use of a negative pressure mask provides additional safety when inadvertent blockage of suction and inadequate irrigation occur.