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Covid-19 has turned the world on its head, causing dramatic alterations in people's lives. The study's major goal is to learn about people's attitudes toward online classes/jobs, their daily routines and Covid measures/precautions they take on a daily basis. All of these conclusions were reached by statistical analysis of original data gathered through a questionnaire and an online survey. The report contains the most comprehensive and small-scale investigation into how people perceive the impact of the COVID-19 issue on many elements of their lives based on daily activities. The results of the investigation were also shown in terms of an individual's eating habits, sleep pattern, physical activity, stress/ anxiety levels, work involvement, social media/ phone usage, and productivity. The information was gathered from a sample of 503 people who completed a structured questionnaire using Google forms utilising a suitable random sampling procedure. The data was analysed and hypotheses were tested using reliable statistical tools such as descriptive statistics, chi-square test, z-test, ANOVA with R programming, and MS-Excel. It was discovered that about half of the people are fairly productive;a small percentage of the population believes they are not productive, and the majority of the populationnever engages in any type of exercise. When people go out, they are cognizant of wearing a mask. The majority of them consume immunity-boosting foods. Most people are least interested in online classes/ related employment due to their health and other issues, and instead prefer to kill their boredom by helping with household tasks. Many people suffer fromstress and anxiety. Many of them are adhering to Covid's safety precautions and lockout rules. This study is unique in that it covers all of the activities that an individual can engage in on a daily basis during the Covid epidemic. © 2023 AIP Publishing LLC.
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This comparative quantitative study aims at investigating whether instructional delivery methods, such as online, hybrid, blended learning and face-to-face delivery methods, had an effect on students' grades when teaching mathematics to English language learners in a higher education Institution in the United Arab Emirates. Final course grades, in GPA format, of 574 students were collected over the course of three academic years. Assumptions of analysis of variance (ANOVA), post hoc tests, effect sizes Cohen's d were examined. The statistically significant difference across four different instructional delivery methods showed effect sizes that grew from medium to large to very large when increasing the amount of online instruction. These findings surpass other studies and suggest a high practical significance. The consequences of COVID19 on instructional delivery methods had a favourable effect on students' grades. Higher education institutions in the UAE may use these findings for future planning, even beyond the pandemic. Recommendations are made for further research to include more variables and other disciplines.
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The speed of spread of Coronavirus Disease 2019 led to global lockdowns and disruptions in the academic sector. The study examined the impact of mobile technology on physics education during lockdowns. Data were collected through an online survey and later evaluated using regression tools, frequency, and an analysis of variance (ANOVA). The findings revealed that the usage of mobile technology had statistically significant effects on physics instructors' and students' academics during the coronavirus lockdown. Most of the participants admitted that the use of mobile technologies such as smartphones, laptops, PDAs, Zoom, mobile apps, etc. were very useful and helpful for continued education amid the pandemic restrictions. Online teaching is very effective during lock-down with smartphones and laptops on different platforms. The paper brings the limelight to the growing power of mobile technology solutions in physics education. © 2018 Tsinghua University Press.
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Adoption of digital payment methods rises during the COVID-19 pandemic. The coronavirus outbreak is affecting how consumers make payments. The majority of customers want to continue using digital payments once the virus has been contained. Global consumers were using them more frequently than they had before the epidemic. The main payment options gaining from this shift are e-Wallets and contactless cards as people use less cash and make more online purchases. Prior to COVID 19, fewer people used digital payment methods worldwide. When Covid-19 spread and physical transactions were on the verge of collapse, digital payments became a reality. This study's primary goals are to evaluate the effectiveness ofonline payment apps used by respondents during Covid 19 and consumer perceptions of the uptake of these methods. Both primary and secondary methods are applied in the process. Structured questionnaires were given to the residents of the Chennai area using the primary data approach. Articles, journals, and various forms of Internet have been utilized in secondary data. The collected data is analysed through Analysis of Variance method. The conclusion of this study shows that people were satisfied that online payment app is more convenient, time saving and easy to adopt. Thoughthere are many barriers in online payment app there were some preventive measures and security. © 2022 IEEE.
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This paper presents the degree of noise pollution in Braila. Braila is a city located in southeastern Romania. For this purpose, sound level measurements were performed in various important locations in this city. The monitoring took place between November 2019 and June 2020. The measurements were performed using a professional digital acoustic sound level meter that can record sound values between 30dB-130dB. The sound level meter works with two frequency filters: "A” and "C”. "A” filter responds in the same way as the human ear to the increase and decrease of sound amplitude along the spectrum. "C” filter is suitable for uniform measurements without amplitude increase or amplitude decrease. "C” filter can measure the sound level for cars and engines. Both filters operate in the 31.3 Hz and 8 kHz range. The series measured with Noise Logger Communication Tool sound level meter in the two frequency domains were represented as a boxplot. In all monitored areas, the average values recorded in A frequency range are significantly lower than those recorded in C frequency range. This is due to the presence in the environment of some sources of noise from road traffic which includes light and high-speed cars. The data distribution is generally asymmetric to the left, with higher scores. After the establishment of the state of emergency caused by the spread of SARS-CoV-2 coronavirus, it is observed that the data distribution becomes asymmetric to the right, predominating the low values of the sound intensity level. Using Anova program we analyzed the similarity between the noise series measured in the A and C frequency range. For this purpose, Pearson coefficients also were calculated. © 2022 International Multidisciplinary Scientific Geoconference. All rights reserved.
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The objective of this research is to analyze the level of satisfaction and effectiveness of pre-professional practices in university students, before and during the pandemic. The analyzed data was collected through surveys applied to 67 students. The data was analyzed with a descriptive approach, using tables to summarize the results, while in the analysis of the difference in means in the effectiveness and satisfaction scales, the ANOVA method was used, obtaining a p- value= 0.1134, the same as indicated that there is no variation in the means of the scales. For the correlation analysis, the Pearson coefficient was calculated, whose value indicated a strong correlation between the satisfaction scale of the place where the practice was carried out and the level of satisfaction (0.637). Finally, a web page model is proposed that is capable of better guiding the choice of the place where the students will carry out the pre-professional practices. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The pandemic caused by Covid-19 at the end of 2019 affected the development of academic activities in educational institutions at all levels. This article focuses its interest on analyzing the academic performance, failure and dropout of the students of the Universidad de las Fuerzas Armadas ESPE, Santo Domingo, before and during the pandemic. The analyzed data was collected from the academic results matrices of the Departamento de Ciencias Exactas of the ordinary academic periods: 201950, 201951, 202050, 202051, 202150 and 202151. The information was analyzed with a descriptive approach, using bar charts, which indicate the evolution of the areas of knowledge in the indicated periods. For the variation of academic performance, the ANOVA method was used, obtaining a p − value = 0.126, which indicated that there is no significant variation between the means of the analyzed data. In addition, it was determined that between academic periods the assumptions of normality and homoscedasty with values p − value > 0.05 are met. In the linear correlation analysis, the Pearson coefficient was calculated, whose value indicated a strong negative correlation between the academic performance and the percentage of failure (values of 0.887, 0.796), while between the academic performance and the percentage of abandonment there was a moderate negative correlation (values of 0.428, 0.636). Finally, models based on linear regression are proposed in the areas of knowledge analyzed, to predict the academic performance of the new academic period 202250. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Our research uses the environmental pillar of ESG as a proxy for environmental corporate social responsibility. We examine the performance of environmentally clustered portfolios by using simple quantitative investment strategies with optimum asset rotation. Post-hoc, sample-split analysis with non-parametric tests is performed. The results suggest that both environmental status and dynamic environmental performance are key characteristics of divergent financial behaviors. We show that environmentally low-rated companies present better financial performance, while environmental leaders are less risky and show more resilience. Assets with a dynamic environmental profile outperform on average in terms of returns and risk. Furthermore, supporting evidence of positive spillovers in high-rated environmental clusters is identified after the Paris Agreement. We evaluate the resilience of the environmental clusters during the COVID-19 crisis and the Russia-Ukraine war effect. © 2023 Elsevier B.V.
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The study aims to determine SARS-CoV-2 RNA in sewage of Cancun wastewater treatment plants, the main touristic destination of Mexico, and to estimate the infected persons during the sampling period. SARS-CoV-2 RNA traces were detected in the inlet of the five plants during almost all the sampling months. However, there is no presence of SARS-CoV-2 RNA traces in the effluent of the five WWTPs during the study period. ANOVA analysis showed differences in the concentrations of RNA traces of SARS-CoV-2 between the sample dates, but no differences were found from one WWTP to another. Estimated infected individuals by Markov chain Monte Carlo simulation are higher (between 77% and 91%) than the cases reported by the health authority. Wastewater monitoring and the estimation of infected individuals are a helpful tool, because estimation provides early warning signs on how broadly SARS-CoV-2 is circulating in the city, and led to the authorities to take measures wisely. PRACTITIONER POINTS: There is no presence of SARS-CoV-2 RNA traces in the effluent of the facilities, suggesting the effectiveness of treatment. Surveillance of viral RNA concentrations at treatment plants revealed presence in the influent of five plants Estimated infected individuals by MCMC simulation are higher than cases reported by health authority Environmental surveillance approach in wastewater influent is helpful to identify the clusters and to take informed decisions.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/epidemiology , Wastewater , RNA, Viral/genetics , Mexico , Caribbean RegionABSTRACT
The most prevalent conditions among ocular surgery and COVID-19 patients are fungal eye infections, which may cause inflammation and dry eye, and may cause ocular morbidity. Amphotericin-B eye drops are commonly used in the treatment of ocular fungal infections. Lactoferrin is an iron-binding glycoprotein with broad-spectrum antimicrobial activity and is used for the treatment of dry eye, conjunctivitis, and ocular inflammation. However, poor aqueous stability and excessive nasolacrimal duct draining impede these agens' efficiency. The aim of this study was to examine the effect of Amphotericin-B, as an antifungal against Candida albicans, Fusarium, and Aspergillus flavus, and Lactoferrin, as an anti-inflammatory and anti-dry eye, when co-loaded in triblock polymers PLGA-PEG-PEI nanoparticles embedded in P188-P407 ophthalmic thermosensitive gel. The nanoparticles were prepared by a double emulsion solvent evaporation method. The optimized formula showed particle size (177.0 ± 0.3 nm), poly-dispersity index (0.011 ± 0.01), zeta-potential (31.9 ± 0.3 mV), and entrapment% (90.9 ± 0.5) with improved ex-vivo pharmacokinetic parameters and ex-vivo trans-corneal penetrability, compared with drug solution. Confocal laser scanning revealed valuable penetration of fluoro-labeled nanoparticles. Irritation tests (Draize Test), Atomic force microscopy, cell culture and animal tests including histopathological analysis revealed superiority of the nanoparticles in reducing signs of inflammation and eradication of fungal infection in rabbits, without causing any damage to rabbit eyeballs. The nanoparticles exhibited favorable pharmacodynamic features with sustained release profile, and is neither cytotoxic nor irritating in-vitro or in-vivo. The developed formulation might provide a new and safe nanotechnology for treating eye problems, like inflammation and fungal infections.
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The performance of microfluidic biosensor of the SARS-Cov-2 was numerically analyzed through finite element method. The calculation results have been validated with comparison with experimental data reported in the literature. The novelty of this study is the use of the Taguchi method in the optimization analysis, and an L8(25) orthogonal table of five critical parameters-Reynolds number (Re), Damköhler number (Da), relative adsorption capacity (σ), equilibrium dissociation constant (KD), and Schmidt number (Sc), with two levels was designed. ANOVA methods are used to obtain the significance of key parameters. The optimal combination of the key parameters is Re = 10-2, Da = 1000, σ = 0.2, KD = 5, and Sc 104 to achieve the minimum response time (0.15). Among the selected key parameters, the relative adsorption capacity (σ) has the highest contribution (42.17%) to the reduction of the response time, while the Schmidt number (Sc) has the lowest contribution (5.19%). The presented simulation results are useful in designing microfluidic biosensors in order to reduce their response time.
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A QR Code is a two-dimensional barcode scanned by a digital device or smartphone that holds data as a sequence of pixels in a square-shaped pattern. QR codes are widely employed in commercial tracking systems, encoding URLs, contact information, map coordinates, and physical and digital documents. Nowadays, several smartphones have built-in QR readers;they are often employed in marketing and advertising campaigns. More recently, QR codes have recreated a critical role in tracing COVID-19 pandemic exposure and slowing the spread of the virus. Web attackers can encode malicious URLs of custom malware or phishing site into a QR code, which could violate or disclose personal or financial information on a smartphone's data when scanned. This study investigates several symmetrical lightweight cryptography (LWC) algorithms to enhance QR code protection. Modern well-defined LWC features (performance and security) are compared and evaluated. The results adopt reliable and safe mechanisms for QR codes' security issues. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The proceedings contain 79 papers presendted at a virtual meeting. The special focus in this conference is on Recent Advances in Mechanical Engineering Research and Development. The topics include: Firmware of Indigenous and Custom-Built Flexible Robots for Indoor Assistance;Automation of AM Via IoT Towards Implementation of e-logistics in Supply Chain for Industry 4.0;Evaluation and Optimization of Process Parameter for Surface Roughness of 3D-Printed PETG Specimens Using Taguchi Method at Constant Printing Temperature;Evaluation of Preventive Activities of COVID-19 Using Multi-criteria Decision Making Method;mechanical Characterization of Concrete with Rice Husk-Based Biochar as Sustainable Cementitious Admixture;Ranking of Barriers for SSCM Implementation in Indian Textile Industries;Framework to Monitor Vehicular GHG Footprint;solution to Real-Time Problem in Shifter Knob Assembly at Automobile Manufacturing Industry;performance of Chemical Route-Synthesized SnO2 Nanoparticles;a Numerical Study to Choose the Best Model for a Bladeless Wind Turbine;Effect of Tissue Properties on the Efficacy of MA on Lungs;effect of Process Parameters and Coolant Application on Cutting Performance of Centrifugal Cast Single Point Cutting Tools;Study and Analysis of Thermal Barrier Application of Lanthanum Oxide Coated SS-304 Steel;recovery of Iron Values from Blast Furnace Gas Cleaning Process Sludge by Medium Intensity Magnetic Separation Method;fatigue Analysis of Rectangular Plate with a Circular Cut-Out;protection of Vital Facilities from the Threat of External Explosion Using D3o Material;investigation on Coefficient of Heat Transfer Through Impact of Engine Vibration;electrical Modulus and Conductivity Study of Styrene-Butadiene Rubber/Barium Hexaferrite Flexible Polymer Dielectrics;preface.
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COVID-19 had caused the whole world to come to a standstill. The current detection methods are time consuming as well as costly. Using Chest X-rays (CXRs) is a solution to this problem, however, manual examination of CXRs is a cumbersome and difficult process needing specialization in the domain. Most of existing methods used for this application involve the usage of pretrained models such as VGG19, ResNet, DenseNet, Xception, and EfficeintNet which were trained on RGB image datasets. X-rays are fundamentally single channel images, hence using RGB trained model is not appropriate since it increases the operations by involving three channels instead of one. A way of using pretrained model for grayscale images is by replicating the one channel image data to three channel which introduces redundancy and another way is by altering the input layer of pretrained model to take in one channel image data, which comprises the weights in the forward layers that were trained on three channel images which weakens the use of pre-trained weights in a transfer learning approach. A novel approach for identification of COVID-19 using CXRs, Contrast Limited Adaptive Histogram Equalization (CLAHE) along with Homomorphic Transformation Filter which is used to process the pixel data in images and extract features from the CXRs is suggested in this paper. These processed images are then provided as input to a VGG inspired deep Convolutional Neural Network (CNN) model which takes one channel image data as input (grayscale images) to categorize CXRs into three class labels, namely, No-Findings, COVID-19, and Pneumonia. Evaluation of the suggested model is done with the help of two publicly available datasets; one to obtain COVID-19 and No-Finding images and the other to obtain Pneumonia CXRs. The dataset comprises 6750 images in total; 2250 images for each class. Results obtained show that the model has achieved 96.56% for multi-class classification and 98.06% accuracy for binary classification using 5-fold stratified cross validation (CV) method. This result is competitive and up to the mark when compared with the performance shown by existing approaches for COVID-19 classification.
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The unexpected emergence of the COVID-19 pandemic has changed how grocery shopping is done. The grocery retail stores need to ensure hygiene, quality, and safety concerns in-store shopping by providing "no-touch" smart packaging solutions for agri-food products. The benefit of smart packaging is to inform consumers about the freshness level of a packaged product without having direct contact. This paper proposes a data-driven decision support system that uses smart packaging as a smart product-service system to manage the sustainable grocery store supply chain during outbreaks to prevent food waste. The proposed model dynamically updates the price of a packaged perishable product depending on freshness level while reducing food waste and the number of rejected customers and maximising profit by increasing the inventory turnover rate of grocery stores. The model was tested on a hypothetical but realistic case study of a single product. The results of this study showed that stock capacities, freshness discount rate, freshness period, and quantity discounts significantly affect the performance of a grocery store supply chain during outbreaks.
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In metallurgical processes, metal sheet cutting is usually a basic technological operation that needs to be performed. All other technological operations follow the procedure of metal sheet cutting, with the final aim of manufacturing a final product. Machines used for that basic metal cutting operation shall be reliable, efficient, fast, and relatively easy to work with. While working with a laser, the authors noticed the inefficiency of cutting with nitrogen. Nitrogen bottles got empty too quickly, which caused additional costs. Inefficient, i.e., excessive nitrogen consumption requires a more frequent supply of nitrogen. During the COVID-19 pandemic, nitrogen was not always available, as suppliers shifted to manufacture oxygen bottles for medical needs. Therefore, the authors engaged in finding solutions to reduce the consumption of nitrogen at cutting. The mentioned problem was studied within the experiment that focused on the optimization of nitrogen use during fiber laser cutting, the procedure, and results of which are described in this paper. Specimens of different cutting parameters were prepared and cut to measure their roughness and burr height. The collected data were used to create a mathematical model with an ANOVA table. The experiment resulted in the determination of optimal cutting parameters achieved by the lowest possible cutting gas pressure.
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INTRODUCTION: Although optimal wellbeing of young adults (YA) is a vital asset for productivity and measurable and sustainable development, there is a dearth of information on the wellbeing status of YA, especially after the COVID-19 lockdown in Ghana. The study has established the post-lockdown wellbeing status of YA in the COVID-19 pandemic epicenters of Ghana. METHODS: The wellbeing status of 1783 (24.49 ± 4.62 year) Ghanaian YA from Kumasi, Accra, and Kasoa (known epicentres of COVID) was assessed in this cross-sectional study. Body mass index (BMI) was calculated, and physical, social, emotional, spiritual and intellectual states were assessed. RESULTS: More females were found to be overweight (315, 17.7%) and obese (160, 9.0%) compared to males. The majority (714; 40.0%) of the young adults were between the ages 25-30 years and overweight, with a mean BMI of 25.46 ± 4.67 kg/m2. Overall, 157 (8.8%) had poor, 755 (42.3%) average, 479 (26.9%) good, while 392 (22.0%) had outstanding wellbeing. Specifically, the average grade was recorded for physical (29.07 ± 6.67), spiritual (29.32 ± 6.80), and intellectual (28.29 ± 6.56), while 'good grade' was obtained for social (32.16 ± 5.13) and emotional (31.54 ± 5.07) dimensions of wellbeing. CONCLUSION: Average Ghanaian YA in the study were overweight (BMI value) and had average wellbeing, which may suggest the risk of cardiovascular diseases. Educational and physical activity interventions with meticulous dietary control and proper understanding of family history, age and genetic factors will help to improve the wellbeing of Ghanaian YA.
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COVID-19 , Overweight , Male , Female , Humans , Young Adult , Adult , Overweight/diagnosis , Overweight/epidemiology , Ghana/epidemiology , COVID-19/epidemiology , Cross-Sectional Studies , Pandemics , Communicable Disease ControlABSTRACT
The novel Covid-19 pandemic has massively caused considerable damages to various industries and sectors in the whole world. As is the case in the rest of the other countries, Moroccan supply chains (SCs) have been seriously disrupted. To adapt to this new condition, Moroccan companies need to quickly adjust their processes through the use of digital technologies. This research seeks to analyse how Moroccan companies responded to the Covid-19 pandemic through the adoption of digital solutions. The present data were collected from 196 companies sampled across different regions in Morocco and analysed using the Chi-square test, the algorithmic K-means method, and the analysis of variance (ANOVA). The findings revealed that the sector has impacted the behavior of the supply chain (SC) in the adoption of technological solutions. Findings also revealed that the companies operating in the first and second sector have mobilized expensive technological tools to overcome the devastating effects of the Covid-19 pandemic. Also, companies with a simple SC have mobilized low-cost digital solutions to maintain their resilience. © 2022 IEEE.
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The Covid-19 pandemic has changed all aspects of life, including the world of education globally. The learning methods provided are adapted to existing conditions (online learning). This condition has an impact on student learning outcomes. Besides, another factor that affects student learning outcomes is the gender of students, which impacts student behavior in learning. This study aims to see the effect of the learning methods provided (online and offline) and gender differences on the learning outcomes obtained and the interaction of the two factors. The research design used is a two-way multivariate analysis of variance, with the dependent variable (study exam score in Bahasa Indonesia, Mathematics, and natural science subjects). The results showed that the learning method and gender significantly affected test results in all subjects. However, there is no interaction between these two factors. © 2022 IEEE.
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A QR Code is a two-dimensional barcode scanned by a digital device or smartphone that holds data as a sequence of pixels in a square-shaped pattern. QR codes are widely employed in commercial tracking systems, encoding URLs, contact information, map coordinates, and physical and digital documents. Nowadays, several smartphones have built-in QR readers;they are often employed in marketing and advertising campaigns. More recently, QR codes have recreated a critical role in tracing COVID-19 pandemic exposure and slowing the spread of the virus. Web attackers can encode malicious URLs of custom malware or phishing site into a QR code, which could violate or disclose personal or financial information on a smartphone’s data when scanned. This study investigates several symmetrical lightweight cryptography (LWC) algorithms to enhance QR code protection. Modern well-defined LWC features (performance and security) are compared and evaluated. The results adopt reliable and safe mechanisms for QR codes’ security issues. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.