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1.
Tourism Management ; : 104734, 2023.
Article in English | ScienceDirect | ID: covidwho-2211538

ABSTRACT

A comparative vignette-based experimental survey design incorporating various socio-psychological factors, linked to the Theory of Planned Behavior (TPB), the Health Belief Model (HBM) and the risk-attitude DOSPERT scale was carried out to test variations in eight travel-related COVID-19 protective measures on Swiss tourists' travel intentions. Among the tested measures, vaccination passports, surgical masks and quarantining are those that stand out the most, with surgical masks having the greatest acceptance and willingness to adopt while traveling. Quarantining, on the other hand, appears to have a deterrent influence on travel intentions, and vaccination passports have the lowest perceived barriers during travel, but the highest perceived benefits in mitigating the spread of the infection. The discussion of individual differences has specific implications for tourism management against the background of our empirical findings.

2.
New Microbes and New Infections ; : 101090, 2023.
Article in English | ScienceDirect | ID: covidwho-2211188

ABSTRACT

Background During the Corona Pandemic, the use of masks has increased significantly. The lack of control on hygiene protocols and the need to use PPE properly increases the spread of bacterial infection. The purpose of this study was to investigate the degree of contamination and frequency of bacterial species isolated from surgical and N95 masks used by hospital personnel. Methods A total number of 175 masks were collected from staff working in Sina hospital (Hamadan province, Iran) during the first six months of 2022. The bacterial contamination of masks were evaluated and identified using biochemical kits. Antimicrobial susceptibility testing of the isolates were done using Kirby-Bauer methods and MIC were assessed for each isolate against different disinfectants (Sodium hypochlorite 5%, Hydrogen Peroxide 3%, Ethanol 70% and Deconex). Results Of 175 masks, 471 bacterial isolates were detected including 9 species. The most prevalent strain were Coagulase negative Staphylococcus (28%) followed by Acinetobacter (20.8%) and Pseudomonas (13.8%), while, Klebsiealla and Enterococcus were the least frequent species with the rate of 3.8% and 1.2%, respectively. The results of MIC methods indicated that all 471 strains were resistant to ehtanol70% and sensitive to hydrogen peroxide 3%. Furthermore, the mean average of Deconex inhibitory effect is lower than Sodium hypochlorite 5%. Conclusions According to the results of this study, there was a high prevalence of CoNS, Acinetobacter and Pseudomonas in hospital with a high resistance pattern against antibiotics especially Ampicillin and disinfectants.

3.
Journal of Water Process Engineering ; 50, 2022.
Article in English | Web of Science | ID: covidwho-2211024

ABSTRACT

The outbreak of COVID-19 has led to the increase in face mask waste globally. In this study, face mask-derived carbocatalysts doped with nitrogen (N-Mask) were fabricated through one-step pyrolysis of 1:5 w/w mixture of face mask and urea at different temperatures to activate peroxymonosulfate (PMS) for gatifloxacin (GAT) degradation. The N-Mask prepared at 800 degrees C (N-Mask800) exhibited the highest GAT degradation rate with k(app) = 0.093 min(-1) which could be attributed to its high N doping level (17.1 wt%) and highest specific surface area (237.13 m(2) g(-1)). The relationship between k(app), catalyst loading and PMS dosage at various pHs on GAT degradation were successfully established. It was also found that the GAT degradation rate was inhibited in the sequential operating mode compared to the simultaneous operating mode. It was construed that adsorption and catalysis share the same active sites. Deterioration in catalytic performance was observed over successive cycles due to the surface chemistry change during catalysis, and difficulty in catalyst recovery after treatment. Radical scavenger study revealed that both radical and nonradical pathways were involved during GAT degradation, with nonradical pathway playing a dominant role. XPS analysis revealed that pyrrolic N and graphitic N can facilitate PMS activation via radical and nonradical pathways. Based on the LC-MS/MS analysis, the GAT degradation intermediates were identified, and the possible degradation pathways were tentatively proposed. Overall, this study demonstrated that carbocatalyst derived from face mask could be transformed into costeffective and environmentally friendly PMS activator for environmental wastewater treatment applications.

4.
Fuel ; 340:127551, 2023.
Article in English | ScienceDirect | ID: covidwho-2210295

ABSTRACT

Inexpensive iron-based catalysts are the most promising catalysts for microwave-assisted deconstruction of waste plastics. However, the microwave heating efficiency of most of the synthesized iron-based catalysts is very low, in particular, the FeAl catalyst was prepared by microwave combustion method, and its mixture with disposable medical masks (DMMs) was only heated to about 150℃ within 10 min. Here, we introduce the second-phase metals (Co or Ni) into the FeAl catalyst, resulting in the rearrangement of the catalyst structure and electrons to give the catalyst good microwave absorption ability. The mixture of the catalyst and DMMs can be quickly heated to above 900℃ in 10 min, especially after reaching the melting point of plastic, the instantaneous heating rate reaches 350 ℃·min−1. under the unique microwave hot-spot pyrolysis mechanism, DMMs can be rapidly pyrolyzed into carbon nanotubes (19.65 wt%) and gas (77.65 wt%) within 14 min due to the efficient dehydrogenation efficiency and activity of Co. The corresponding H2 yield is up to 38.66 mmolH2·g−1DMMs, and the percentage of CO and H2 in the gas is as high as 90 wt%. This work improves the microwave conversion efficiency of iron-based catalysts by introducing second phase metals, and waste DMMs were efficiently converted into CO, H2 and CNTs, which can also be extended to other polymer or biomass chemical cycles.

5.
Discover Psychology ; 3(1):5, 2023.
Article in English | ProQuest Central | ID: covidwho-2209628

ABSTRACT

Many studies conducted after the COVID-19 pandemic have examined the relationship between changes in social traits, such as attractiveness and wearing face masks. However, most studies examine the effect of wearing face masks at a single time point, and the time effect is not known. Additionally, few studies address wearing sunglasses, another facial occluding item. This study examined the effects of facial occluding (unoccluded face, face masks, sunglasses, or both) on perceived attractiveness, trustworthiness, and familiarity at two time points, September 2020, six months after the start of the COVID-19 pandemic, and April 2022, almost two years later, using Japanese higher and lower attractive faces. Results showed that only lower attractive faces wearing face masks had a time effect on attractiveness and familiarity and no time effect on social traits in higher attractive faces. Perceived all social traits were the highest for unoccluded faces, and faces wearing face masks had the same level of attractiveness and familiarity as unoccluded faces. Perceived trustworthiness was higher for unoccluded faces, faces wearing face masks, sunglasses, and both sunglasses and face masks, respectively. Additionally, faces wearing both sunglasses and face masks had the lowest perceived all social traits. These findings suggest that the positive and time effects of wearing face masks are limited in Japan, suggesting a greater positive impact of unoccluded faces. They also suggest that the negative impact of wearing sunglasses is significant.

6.
Indian Journal of Microbiology. ; 2023.
Article in English | EMBASE | ID: covidwho-2209535

ABSTRACT

Coronavirus has continued to evolve and has thus caused unprecedented challenges for human society. Multiple nations have fully or partially relied on the limited approach against the COVID-19 variants, which includes not wearing face masks, vaccine hesitancy, and political conflicts. For effective pandemic management, all nations still need to adhere to the unlimited approach, which includes wearing face masks, vaccination, and risk-oriented strategies. Despite many people's resistance to these relatively restrictive measures, the society could not only reduce physical impacts but also social impacts of COVID-19 variants in time, in particular without flexibly relying on the unlimited approach. Copyright © 2023, Association of Microbiologists of India.

7.
Acta Universitatis Danubius. Oeconomica ; 18(2), 2022.
Article in English | ProQuest Central | ID: covidwho-2207333

ABSTRACT

In the current international pandemic context, the risks of the underground economy through its most perverse forms, corruption, undeclared work, tax evasion, etc., have been greatly exacerbated by urgently favouring the restriction of freedoms, the infusion of important resources into the economy and not least the interest of Pharma. The turbulent and unprepared international framework has created the premise that in this unfortunate period an activity in the underground economy that influences all its forms, namely corruption, will flourish. According to press reports, the sale of masks, medicines and anti-pandemic health products was a real El Dorado of Romania. Fabulous surcharge purchases made by UNIFARM are known, as well as worldwide, according to a World Bank report, due to the elimination of normal public procurement control filters. The pandemic generated by the SARS-CoV-2 virus, both globally and nationally, has had various influences on the underground economy, some favorable for the public sector but most unfavourable for the private sector.

8.
Journal of Experimental Biology and Agricultural Sciences ; 10(6):1376-1390, 2022.
Article in English | Scopus | ID: covidwho-2217793

ABSTRACT

Due to the SARS-CoV-2 pandemic, it is crucial to study the efficiency of face masks in retaining viruses for the upcoming years. The first objective of this study was to validate a method to elute viruses from polyester and cotton face masks. We observed that deionized water followed by 3% beef glycine (pH 9.5 or pH 7.2) was significantly more efficient (p < 0.05) in eluting the bacteriophage phiX174 virus from polyester (4.73% ± 0.25% to 28.67% ± 1.89%), polyester/cotton (3% ± 0.33%), and cotton (1.7% ± 0.21%) face masks than 3% beef glycine only (pH 9.5 or pH 7.2) as a single eluent (3.4% ± 0.16% to 21.33% ± 0.94% for polyester, 1.91% ± 0.08% for polyester/cotton, and 1.47% ± 0.12% for cotton face masks). Also, deionized water was significantly less efficient as a single eluent for eluting bacteriophage phiX174 from all the studied face mask types. The polyethylene glycol (PEG) precipitation method was substantially more efficient (p < 0.05) as a second step concentration method for the viruses in the eluates than the organic flocculation (OF) method. Higher viral loads were eluted from polyester face masks than cotton ones. We also found varying viral loads in the eluate solutions from different commercial polyester face masks, with the highest percentage seen for the N95 face mask. The second objective was to apply the validated method to study the effect of autoclaving on the different face mask materials. Results of the study did not show any significant differences in the viral loads eluted from the studied face masks before and after one and five autoclaving cycles. Moreover, a scanning electron microscope (SEM) analysis revealed no changes in the yarns, elongation, tensile strength, and contact angle measurements of the polyester or cotton materials after one or five autoclaving cycles. © Production and Hosting by Horizon Publisher India [HPI] (http://www.horizonpublisherindia.in/). All rights reserved.

9.
Iatreia ; 36(1):40-50, 2023.
Article in English | EMBASE | ID: covidwho-2217759

ABSTRACT

Introduction: During the COVID-19 pandemic and the cases of shortages of personal protective equipment (PPE), the utilization of modified snorkel masks has been documented, seeking to provide respiratory and facial pro-tection against SARS-CoV-2 aerosols. However, there is no report of changes in vital signs that can occur with its use, along with the perception of its wear by health personnel. Method(s): A case series was performed. Equipment: Snorkel mask, 3D adapter, and antimicrobial filter. CO2 level, respiratory rate, oximetry, pulse, and blood pressure were monitored for one hour. During the time of use, activities related to patient care were simulated. At the end, the usage characteristics were evaluated through a survey. Result(s): 14 volunteers were included in the study. After one hour of conti-nuous use, the clinical parameters were predominantly normal. 85% of the participants preferred this modified snorkel mask instead of personal protective equipment established for COVID-19 (goggles, N95 mask and visor). Conclusion(s): The adapted snorkel mask could be an alternative to PPE equipment in situations of scarce resources. This is only considered within the framework of its acceptability by a group of health professionals, in addition to the few effects on the vital signs evaluated in this case series. Further objective evaluations of usability and effectiveness are required. Copyright © 2023 Universidad de Antioquia.

10.
Health Scope ; 11(4), 2022.
Article in English | Web of Science | ID: covidwho-2217426

ABSTRACT

Context: At the beginning of the COVID-19 pandemic, the effects of personal protective equipment (PPE) such as face masks, as well as environmental conditions, including temperature and humidity changes, were discussed due to the lack of effective medicine. Methods: The preferred reporting items for systematic reviews and meta-analysis (PRISMA) were implemented to conduct the present systematic review. The articles were selected from papers published by May 2020 in PubMed, Web of Science, Science Direct, Scopus, and Google Scholar databases. This meta-analysis estimated relative risk (RR) and pooled mean depicted as effect size (ES) using the random or fixed effects methods. Results: Ten studies met inclusion criteria, four of which addressed the effect of face masks and six of which dealt with temperature and humidity changes. This eta-analysis study showed that wearing face masks against the COVID-19 virus had a remarkable safety impact with RR (%95 CI) 8.56 (2.10 - 34.90), (I-2 = %0.0 P = 0.999), and the pooled mean changes in temperature and humidity were estimated to be with ES (%95 CI) 9.03 (4.32 - 13.74), (I-2 = %99.7, P = 0.0001) and with ES (%95 CI) 56.82 (46.12 - 67.51), ( I-2 = %99.3, P = 0.0001) during the outbreak of the COVID-19. Conclusions: The findings of this systematic review and meta-analysis illustrate the effectiveness of face masks, in general, in preventing the transmission of the COVID-19 virus. According to the findings, temperature and humidity changes do not increase the outbreak of the COVID-19 virus.

11.
Healthcare ; 11(2):242, 2023.
Article in English | ProQuest Central | ID: covidwho-2215797

ABSTRACT

Healthcare waste (HCW) is generated in different healthcare facilities (HCFs), such as hospitals, laboratories, veterinary clinics, research centres and nursing homes. It has been assessed that the majority of medical waste does not pose a risk to humans. It is estimated that 15% of the total amount of produced HCW is hazardous and can be infectious, toxic or radioactive. Hazardous waste is a special type of waste which, if not properly treated, can pose a risk to human health and to the environment. HCW contains potentially harmful microorganisms that can be spread among healthcare personnel, hospital patients and the general public, causing serious illnesses. Healthcare personnel are the specialists especially exposed to this risk. The most common medical procedure, which pose the highest risk, is injection (i.e, intramuscular, subcutaneous, intravenous, taking blood samples). The World Health Organization (WHO) estimates that around 16 billion injections are administered worldwide each year. However, if safety precautions are not followed, and needles and syringes are not properly disposed of, the risk of sharps injuries increases among medical staff, waste handlers and waste collectors. What is more, sharps injuries increase the risk of human immunodeficiency virus (HIV), hepatitis B and C viruses (HBV/HCV), tuberculosis (TB), diphtheria, malaria, syphilis, brucellosis and other transmissions. Disposing of medical waste in a landfill without segregation and processing will result in the entry of harmful microorganisms, chemicals or pharmaceuticals into soil and groundwater, causing their contamination. Open burning or incinerator malfunctioning will result in the emission of toxic substances, such as dioxins and furans, into the air. In order to reduce the negative impact of medical waste, waste management principles should be formulated. To minimize health risks, it is also important to build awareness among health professionals and the general public through various communication and educational methods. The aim of this paper is to present a general overwiev of medical waste, its categories, the principles of its management and the risks to human health and the environment resulting from inappropriate waste management.

12.
Frontiers in Public Health ; 10:921494, 2022.
Article in English | MEDLINE | ID: covidwho-2215402

ABSTRACT

Background: Many countries have recommended using face masks for the general population in public places to reduce the risk of COVID-19 transmission. This study aimed to assess the effects of socioeconomic status on face mask use among pedestrians during the COVID-19 pandemic.

13.
35th Conference on Graphics, Patterns, and Images, SIBGRAPI 2022 ; : 282-287, 2022.
Article in English | Scopus | ID: covidwho-2213368

ABSTRACT

We present a method for evaluating COVID-19 contamination risk based on social distancing between individuals and face mask usage. Our method employs images captured by surveillance cameras as input to a system that computes a health risk indicator in real time. This system can handle real-world situations, performing detections in large public spaces, such as squares and streets, as well as other potentially crowded areas like restaurants and shopping centers. Our system uses the number of people with and without masks and their proximity to evaluate the risk of COVID-19 contamination. We employed deep neural networks to detect people with and without masks, and we used computer vision to measure the distance between them. Both cases presented challenges, including distinguishing face masks at wildly different distances and positions concerning the camera, occlusions, shape variance, etc. We have built and made public a face mask detection dataset (44,402 faces) with images that include these challenging scenarios and used them to train our deep neural networks. Our best deep neural network architecture achieved 91.41% precision, 82.88% accuracy, and 89.88% recall on face mask detection. © 2022 IEEE.

14.
35th Conference on Graphics, Patterns, and Images, SIBGRAPI 2022 ; : 204-209, 2022.
Article in English | Scopus | ID: covidwho-2213367

ABSTRACT

With the COVID-19 pandemic's emergency, using facial masks and contactless biometric systems became even more relevant to reduce the risk of contamination. Several direct and indirect problems gained relevance with the pandemic. Among them, masked face recognition (MFR) aims to recognize a person even when the person is wearing a face mask. Some state-of-the-art algorithms that work well for unmasked faces have suffered a severe performance drop when receiving masked faces as input. In this sense, the scientific community proposed approaches and competitions related to this topic. In this paper, we introduce a comparative study of four prominent solutions pipelines that use different techniques to tackle the masked face recognition problem, proposed by Huber et al. [1], Neto et al. [2], Boutros et al. [3], and Hsu et al. [4]. The performance evaluation was conducted on a real masked face database (MFR2 [5]), and using synthetic masks in three mainstream databases (LFW, AgeDB30, and CFP-FP). We report results regarding unmasked-masked (U-M) and masked-masked (M-M) face verification performance. The unmasked-unmasked (U-U) scenario was also reported as a baseline to evaluate the drop of the selected models on non-occluded face verification. We further analyze the obtained results, generating a comprehensive comparative study of the selected approaches. © 2022 IEEE.

15.
32nd International Scientific Symposium Metrology and Metrology Assurance, MMA 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2213356

ABSTRACT

Respiratory infections have arisen as a public health concern. The regulation of COVID-19 is based on knowledge of its transmission mechanism. Masks and respirators act as a physical barrier against respiratory droplets that enter through the nose and mouth, as well as droplets spat by sick persons. Textile masks (including 'do-it-yourself'), surgical (medical) masks and respirators are the three basic types of personal protection devices, covering the human face. The purpose of our work is to give a study on the morphological features of masks and respirators, which are widely accessible in Bulgarian shops and pharmacies, revealing their structure and differences between them. The results will be further used for the assessment of heat and mass transfer abilities of the masks/respirators, which are largely preconditioned by the masks' morphology. © 2022 IEEE.

16.
2022 International Symposium on Electronics and Smart Devices, ISESD 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2213343

ABSTRACT

The number of Covid-19 cases has decreased, with vaccines and the implementation of health protocols. Currently, people are starting to carry out face-to-face activities such as in schools, offices, shopping centers or other public places. However, entering the new normal activities, new variants of Covid19 may be formed and spread, therefore people still have to implement and maintain the health protocols, including the use of face mask in the offices or other public places. This study design the smart room system equipped with face mask detection to ensure the implementation of health protocols and air quality smart system to monitor the CO2 levels, temperature, and humidity, as well as disinfecting the room regularly with UV-C. Face Mask Detection system is developed in Raspberry, where the images from camera are processed with machine learning using MobileNetv2 for image classification method with Python libraries TensorFlow and Keras. The implementation results show that face mask detection able to process up to five people in one frame, with a maximum distance of 220cm from the camera. Air quality monitoring system also works well in detecting and classifying air parameters with error reading is under 5% and displaying them on the website application with average delay is about 4 seconds. © 2022 IEEE.

17.
2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022 ; : 99-102, 2022.
Article in English | Scopus | ID: covidwho-2213269

ABSTRACT

During the COVID-19 pandemic, it has been a standard procedure for people all around the world to use Respiratory Protection Masks (RPM) that cover both the nose and the mouth. The Consequences of wearing RPMs, those pertaining to the perception and production of spoken communication, are rapidly becoming more prominent. Nevertheless, the utilization of face masks also causes attenuation in voice signals, and this alteration affects speech-processing technologies such as Automatic Speaker Verification (ASV) and speech-to-text conversion. An intervention by a deep learning-based algorithm is considered vital to remedy the issue of inappropriate exploitation of speaker-based technology. Therefore, in the proposed framework, a speaker identification system has been implemented to examine the effect of masks. First, the speech signals have been captured, pre-processed, and augmented by a variety of data augmentation techniques. Afterward, different 'Mel-Frequency Cepstral Coefficients' (MFCC) features have been extracted to be fed into a 'Long Short-Term Memory' (LSTM) for identifying speakers. The system's overall performance has been assessed using accuracy, precision, recall, and Fl-score, which yields 93%, 93.3%, 92.2%, and 92.8%, respectively. The obtained results are still in a rudimentary phase, and they are subjected to further enhancements in the future by data expansion and exploitation of multiple optimization techniques. © 2022 IEEE.

18.
2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022 ; : 118-121, 2022.
Article in English | Scopus | ID: covidwho-2213267

ABSTRACT

Following the declaration of COVID-19 as a worldwide pandemic, hindering a multitude number of lives, face mask exploitation has become extremely crucial to barricade the emanation of the virus. The masks available in the market are of various sorts and materials and tend to affect the speaker's vocal characteristics. As a result, optimum communication may be hampered. In the proposed framework, a speaker identification model has been employed. Also, the speech corpus has been captured. Then, the spectrograms were obtained and passed through a two-stage pre-processing. The first stage includes the audio samples. In contrast, the second stage has targeted the spectrograms. Afterward, the generated spectrograms were passed into a hybrid Convolutional Neural Network- Long Short-Term Memory (CNN-LSTM) model to perform the classification. Our proposed framework has shown its capability to identify speakers while they are wearing face masks. Moreover, the system has been evaluated on the collected dataset, where it has attained 92.7%, 92.62%, 87.71%, and 88.26% in terms of accuracy, precision, recall, and F1-score, respectively. The acquired findings are still preliminary and will be refined further in the future by data expansion and the employment of numerous optimization approaches. © 2022 IEEE.

19.
13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2213240

ABSTRACT

Face Mask Detection is currently a hot topic that has piqued the interest of researchers all over the world. Today, the entire world is dealing with the COVID-19 pandemic. To control the spread of the Coronavirus the most important task people need to do is use a mask. There is still a lot of research and study being done on COVID-19. Several studies have also shown that wearing a face mask significantly reduces the problem of viral transmission. In addition, a person wearing a face mask perceives a sense of protection. When we are at home, we take care of everything, but when we are in public places such as offices, malls, and colleges, it becomes more difficult to keep people safe. Machine Learning and Data Mining are a collection of technologies that provide effective solutions to complex problems in a variety of fields. We attempted to develop a face mask recognition system using machine learning in order to prevent the spread of the Coronavirus. This is a good system for detecting a face mask in news channel images and videos. It can recognize both Mask and No Mask faces. With the advancement of this system, it will be possible to detect whether or not a person is wearing a face mask. If the person is not wearing a face mask, it will display a message such as "No Mask,"otherwise it will display "Mask Detected." © 2022 IEEE.

20.
2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2022 ; : 598-603, 2022.
Article in English | Scopus | ID: covidwho-2213124

ABSTRACT

People's lives have been severely disrupted recently due to the COVID-19 outbreak's fast worldwide proliferation and transmission. An option for controlling the epidemic is to make individuals wear face masks in public. For such regulation, automatic and effective face detection systems are required. A facial mask recognition model for real-time video-recorded streaming is provided in this research, which categorizes the pictures as (with mask) or (without mask). A dataset from Kaggle was used to develop and assess the model. The suggested system is computationally more precise, efficient and lightweight when compared to other systems like VGG-16, DenseNet-121, and Inception-V3 which helped the developed model meet low end PC system requirements. The collected data set contains exactly 12,000 images and has a 98.1% performance training accuracy and a validation accuracy of 98.2%, which is achieved by using MobileNetV2. © 2022 IEEE.

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