Sentiment Analysis of COVID-19 Vaccination in Bangla Language with Code-Mixed Text from Social Media

The vaccination program which helps avert pandemics is facing new hurdles, including the emergence of hazardous new virus strains and public distrust. Analyzing the sentiment expressed in social media interactions related to vaccines may aid the health authority in implementing public safety procedures and guide the government in developing appropriate policies. The purpose of this research is to identify the public sentiments toward the COVID-19 vaccination in Bangladesh from social media comments. Comments posted on social media platforms often mix formal and informal language known as code-mixed text and do not adhere to any particular grammatical standards. In addition, the Bangla language lacks computational models and annotated resources for sentiment analysis. To overcome this, we created CoVaxBD, a Bangla-English code-mixed and sentiment-annotated corpus of Facebook comments. This paper also proposes a model for sentiment analysis based on the multilingual BERT. It achieves a validation accuracy of around 97.3 % and a precision score of approximately 97.4%. © 2022 IEEE.

Did national holidays accelerate COVID-19 diffusion "during the first phase of the” of pandemic in Bangladesh?

Bangladesh registered 20,117,32 confirmed cases of COVID-19 and the death toll crossed the grim milestone of 29,323 across the country as of August 31st, 2022. Despite the enforcement of stringent COVID-19 measures, the country witnessed an accelerated diffusion of coronavirus cases during the national events, inclusive of short festivals, in 2020. The present study aims to examine the association between these national holidays and the COVID-19 trasmission rate in Bangladesh. We employed a mathematical model and calculated the instantaneous reproduction number, Rt, of the 64 districts in Bangladesh to check the dynamics of COVID-19 diffusion. The comprehensive analysis shows a notable escalation of Rt value and thus the enhanced transmission rate in Dhaka and in all industrialized cities during the major events such as, garments reopening and religious holidays in Bangladesh. We further showcase the COVID-19 diffusion explicitly in Dhaka Division at the first phase of the pandemic in Bangladesh. Based on our analysis, a set of measures, including restricted public mobility and the celebration of festivals, alongside improving the public's awareness of the situation, has been recommended to evade the future pandemic risks while running the national festival activities in Bangladesh. © 2023, Intelektual Pustaka Media Utama. All rights reserved.

Outcome of Patients before and after Implementation of RRT in a Tertiary Hospital

Aim and background: Although the evidence for rapid response team (RRT) effectiveness remains uncertain, RRT are implemented across many hospitals in the world. We aimed to determine the impact of RRT on outcomes in our hospital. Materials and methods: Our hospital is a 30-bedded non-COVID-19 tertiary care teaching hospital. We collected prospective observational data after implementation of the RRT (February 1, 2021, to September 30, 2021, RRT Period) for a period of 8 months and compared it with retrospective cohort data for 8 months before implementation (February 1, 2020, to September 30, 2020, control period). We conduct a 12th hourly team round consists of a Critical care physician, Anesthesiologist, Duty RMO, Duty Medical officer, and Nurse Supervisor. All the ward patients in the hospital were charted with a Modified early warning score (MEWS) and RRT enrollment will be done if the score is >5 or a single variable score of 3. If the final MEWS ≥ 7 will be transferred immediately to the ICU. The outcomes monitored were hospital mortality and morbidity. Results: During the Control period (February 2020 to September 2020), we analyzed 5522 hospital admissions and 18951 patient days of which 77 patients were transferred to ICU, and mean age of these patients is 55.17 years. Male patients were 53, average length of stay post ICU transfer 4.27 days, of transferred patients medical are 66 and surgical are 11. Death of ICU transferred patients is 14. Number of code blue and death in the ward during this period is 22 and 21, respectively. During RRT period, we analyzed 6956 hospital admissions and 24072 patient days of which 83 patients were transferred to ICU, and mean age of these patients is patients is 58.12, male patients were 55, average length of stay post ICU transfer 3.6 days of which medical are 53 and surgical are 30. Death in ICU transferred patients is 8. Number of code blue and death in the ward during this period is 25 and 43 respectively. Of 43 ward deaths 18 contribute for DNR. Most common reason for transfer to ICU is respiratory failure, Oncology patients were predominant in both groups. The RRT was activated 83 times (11.9 calls per 1,000 patients and 3.44 calls per 1,000 patient-days). The Code blue rate for Control vs RRT were 1.16 and 1.03 per 1,000 patient days, respectively. The hospital mortality for control vs RRT were 1.84 and 1.78 per 1,000 patient days, respectively. The length of stay for control vs RRT were 0.22 and 0.14 per 1,000 patient days, respectively. The ICU mortality of transferred patients for Control vs RRT were 0.73 and 0.33 per 1,000 patient days, respectively. We found a decrease in the trend in code blue rate and hospital mortality in the ward, length of stay, and mortality in ICU transferred patients in the RRT period compared with the control period. Conclusion: We observed a trend towards decline in mortality and morbidity after implementation of RRT, and continuing for a longer duration may give us robust data.

The role of trade unions in promoting CSR in Bangladesh’s ready-made garments sector: the post-pandemic scenario

Purpose: This study investigates the effectiveness of trade unions in preserving and promoting the rights of the worker, and being their voice in ensuring safe working conditions as part of the firms’ CSR activities. Design/methodology/approach: Data were collected from employees, managers, and owners of ready-made garments firms in Bangladesh. An open-ended survey instrument was used and distributed widely. Analysis of the 200 responses was undertaken using the qualitative narrative technique. Findings: The findings show that, unlike traditional labor-management relations, in Bangladesh managers tend to have a more favorable attitude towards unions than employees do. The strong political links between the factory owners and the unions’ leadership raise questions about whose interest the unions represent. Practical implications: The authors highlight how adopting a CSR agenda can help unions make better representations on behalf of their members. This, in turn, can enhance the workforce’s efficiency and help strengthen the sector to develop processes to help face disruptions like those experienced during the COVID-19 pandemic. Originality/value: The study is unique in addressing the role of unions in promoting CSR activities in emerging economies, where the formal institutional application remains limited. The study’s findings can help explain some of the sector’s challenges. © 2022, Emerald Publishing Limited.

Technology Induction in Education During COVID-19 is Recreation or a Curse?: Integration of Technological and Behavioral Factors from the Students' Perspective

The current study attempts to identify and measure the role of technology induction during the COVID-19 pandemic as either recreation or curse in students' learning. By integrating the technology acceptance model (TAM) and innovation diffusion theory (IDT) the study tries to measure the student's online learning experience as recreation or curse. Data was collected from 387 students through purposive sampling. The findings of the study confirm that introduction of technology in online learning plays a recreational and significant role in student's online learning. However, computer self-efficacy and relative advantage were found to be a curse in online learning during the pandemic. The overall findings of the study imply that the shift of student's learning from traditional to online learning has been through introduction of new technology and innovations, although the diffusion of innovation and technology among Pakistani students has been challenging because of a comparatively lower computer literacy level. The usefulness and ease of online learning have been the strongest predictive and recreational aspects in students' online learning. Institutes and higher education commissions should further invest in enhancing the quality and effectiveness of these factors to improve the overall learning outcome of students through recreational technological induction in education.

Detection of COVID-19 and Pneumonia Using Deep Convolutional Neural Network

COVID-19 has created a panic all around the globe. It is a contagious disoriginated from Wuhan in December 2019 and spread quickly all over the world. The healthcare sector of the world is facing great challenges tackling COVID cases. One of the problems many have witnessed is the misdiagnosis of COVID-19 cases with that of healthy and pneumonia cases. In this article, we propose a deep Convolutional Neural Network (CNN) based approach to detect COVID+ (i.e., patients with COVID-19), pneumonia and normal cases, from the chest X-ray images. COVID-19 detection from chest X-ray is suitable considering all aspects in comparison to Reverse Transcription Polymerase Chain Reaction (RT-PCR) and Computed DenseNet121, DenseNet201 and InceptionResNetV2 have been adopted in this proposed work. They have been trained individually to make particular predictions. Empirical results demonstrate that DenseNet201 provides overall better performance with accuracy, recall, F1-score and precision of 94.75%, 96%, 95% and 95% respectively. After careful comparison with results available in the literature, we have found to develop models with a higher reliability. All the studies were carried out using a publicly available chest X-ray (CXR) image data-set.

CNN Implementation for Detect Cheating in Online Exams During COVID-19 Pandemic: A CVRU Perspective

Here, the use of CNN-based technologies is provided with a new method for the detection of fraud during e-exams. This technology will assist providers in identifying any unknown situation during online tests, which are recommended by the majority of governments worldwide owing to the Covid-19 pandemic. Most colleges and students worldwide are severely impacted by their academic programmers, and the universities' role of testing using conventional approaches is a challenge. Thus, the students undergo several of their classes from various kinds of online third-party apps. The universities cannot, however, rely on these service providers for a long time to perform online examinations. Therefore, this work provides a full set-up of computing applications for students who can use them on their own laptops/personal computers with strict university guidance. © 2021

Impacts of COVID-19 pandemic on livestock industry and food security: A review

COVID-19 is a worldwide pandemic that spread over 192 countries and caused more than 3 million people deaths by 2021. It arises a concern on livestock cultivation, their production, and maintaining the supply chain to sustain the existing economy worldwide. The prediction of potential consequences on livestock production and food security is unexpected. Numerous cases among workers in animal farms and product processing plants are evolved during the panic situation, leading to a negative impact on livestock management, and the distribution of products to human doors simultaneously. One of the significant contributions to the drastic decline in livestock operation is the high cost of animal feed. Social distance also slows down all regular activities in livestock farms, resulting in a considerable upset on outcomes. Not only that shutting down transportation flexibility leads to be a burden for farmers in case of high production costs. In the context of consumers, the sublime price of meat, milk, and eggs has addressed the exacerbating risk to worldwide nutrition security. Hence, the world is experiencing an outbreak challenge in resilient, fair, and flexible animal production systems and ensuring food safety globally.

Nexuses Between Energy Efficiency, Renewable Energy Consumption, Foreign Direct Investment, Energy Consumption, Global Trade, Logistics and Manufacturing Industries of Emerging Economies: In the Era of COVID-19 Pandemic

This study aims to find the nexuses among energy efficiency, renewable energy consumption, foreign direct investment, logistics industry, manufacturing industry and global trade during the COVID-19 pandemic and their impact on global supply chains in exporting nations of the world. The data for this study has been extracted from the World Development Indicators and Statista 2021 for 13 years ranging from 2007-to 2020 for nine top exporting countries. The fixed effect panel estimation technique was implied to examine and analyze the data. The results of our study revealed that highly risky diseases significantly impact supply chain operations globally. Global supply chains, logistics and manufacturing industries significantly influence global trade operations. Our results implicate that the overall international trade and logistics can be enhanced by improving the manufacturing and logistics industries by coping with the risk of pandemic diseases. Moreover, by utilizing cost-effective, renewable and efficient energy resources companies address sustainability issues of global trade and operations. By exerting further attention to the proficiency of the levies approval process, competence and quality of logistics services, and ease of assembling competitively priced shipments, the governments can significantly enhance the export from the logistics industry. Also, increasing manufacturing and agricultural value-added healthier consequences might be acquired in global supply chain operations from the manufacturing industry. Copyright © 2022 Rehman Khan, Hassan, Khan, Khan, Godil and Tanveer.

TELE-BASED VIRTUAL BP MANAGEMENT BY PHARMACIST OR NURSE PRACTITIONER VERSUS OFFICE-BASED PCP LED INTERVENTION IN MANAGEMENT OF SYSTOLIC BP. A SYSTEMATIC REVIEW AND META-ANALYSIS

Background Telemedicine was quickly adopted by health systems throughout the United States during the COVID 19 pandemic crisis suggesting its relative feasibility and implementation. Nevertheless, there is limited data on whether a virtual blood pressure (BP) management approach is better than an office led approach. In this systematic review and meta-analysis of randomized clinical trials (RCTs) we aim to compare the differences in systolic BP (SBP) by NP or Pharmacist virtually as compared with primary care physician (PCP) in office. Methods We searched PubMed, MEDLINE, EMBASE, and Cochrane database for studies from January 2000 till October, 2021 with inclusion criteria of RCTs on pharmacist or NP based virtual (tele) BP management versus PCP based office visit (Usual Care) for BP management. Review manager 5.4 was used for data analysis. We used PRISMA guidelines to report synthesize and report our findings. Results We included nine RCTs which met our inclusion criteria with total of 3234 participants in both groups. There were 1615 participants in the APP tele visit group and 1619 participants in the PCP usual care/office visit group. Our results show that the use of NP/Pharmacist based telemedicine visit for SBP management was associated with statistically significant decrease in SBP compared to PCP based office visit (MD: -8.19, 95% CI -10.17, -6.21, P< 0.001, I2= 75%). In the analysis restricted to duration of follow up for less than 6 months (MD: -8.19, 95% CI: -11.74, -4.65, p<0.001) and 12 months (MD:-8.82, 95% CI: -11.21, -6.43, p=0.08), there is no statistically significant difference (p value=0.77). Both the NP as well as Pharmacist based tele visit to control SBP has shown better outcomes compared to PCP based office visit, NP vs PCP (MD: -8.78, 95% CI: -13.93, -3.64, P<0.001) and Pharmacist vs PCP (MD: -8.32, 95% CI: -10.58,-6.06, P<0.001), respectively. Conclusion Our study showed that tele-based intervention by NP/Pharmacist decreased SBP better than usual care in office by PCP. Virtual BP management should be further explored in these times of COVID-19 despite widespread heterogeneity of results and challenges related to the scope of practice and reimbursement of NP/pharmacists.

Implementation of Encryption Technique for analysis of Image Transmission during COVID-19 Pandemic

The necessity of rapid and appropriate diagnosis is emphasized by the COVID 19 as a serious danger to world health. The interchange of patient data across health centers addresses the growth of the number of patients and minimizes needless trials. The sharing of medical information helps patient care to accelerate;thus the sharing of health data is a need nowadays. Due to the sharing of information online among healthcare professionals, safety remains a key concern. In a diagnostic method during the COVID-19 pandemic, computer tomography (CT) and X-ray photos play an essential role in the transmission of information to organizations. Steganography techniques of encryption and imaging can be used in order to secure transmission of COVID-19 pictures. This work proposes a novel encryption for COVID-19 diagnostic using the image steganography (EIS-SDT) paradigm for safe data transfer. For the breakdown of images, a discrete multiple-level transformer for EIS-SDT employs the technique for optimizing the pixel selection for MANTA RY Foraging. For secrete image encryption, the EIS-SDT approach employs a dual logistic chaotic map. Additional security for the steganography process is ensured by the implementation of the DLCM-based encryption mechanism. The EIS-SDT model is efficiently performed by thorough simulation results analysis, and the results are analyzed using many assessment parameters. The analysis showed that the EIS-SDT model exceeds existing technology considerably. © 2021 IEEE.

Prevalence of Coronavirus Anxiety, Nomophobia, and Social Isolation Among National and Overseas Pakistani Students

The COVID-19 pandemic during initial lockdowns created a problematic situation in which individuals were forced to remain within their homes and were forced to follow social distance restrictions for the well-being of themselves and others. In response, people use social networking sites on mobile phones to gather information about the COVID-19 epidemic. This study aims to investigate the influence of lockdowns on mobile phone usage among university students. Moreover, the harmful effects of COVID-19, such as anxiety, social isolation, and nomophobia among national and international students, are also investigated. The total sample size for this cross-sectional study is 438 individuals. The sample consists of Pakistani students studying at local universities (58.7%) and Pakistani students studying abroad (41.3%). The indigenous data is gathered through convenience sampling. The snowball sampling approach is adopted to acquire data from overseas. The findings show that the excessive use of mobile phones for browsing social networking sites to get information about the pandemic caused COVID-19 anxiety, nomophobia (“no-mobile-phone” phobia), and feelings of social isolation. Our results indicate that the COVID-19 outbreak greatly impacted students' massive mobile phone use and psycho-social well-being, regardless of their geographic location. © 2022. All Rights Reserved.

Exploring the Barriers to Online Learning During the COVID-19 Pandemic. A Case of Pakistani Students from HEIs Higher Education Institutions

The main objective of this study is to explore various barriers preventing students in Pakistani universities from learning online during the COVID-19 pandemic. Applying a qualitative research design, twelve (12) in-depth interviews were conducted with business school students, selected at undergraduate and graduate levels from six (06) universities in Islamabad and Rawalpindi, Pakistan. With thematic analysis, various themes emerged from the interview data. Based on the findings, students who live in rural areas are more affected by online le arning during the COVID-19 pandemic than students in urban areas due to identified barriers and, most importantly, lack of technology infrastructure. The findings of this study will be helpful for policy makers including government and educational community to conduct and deliver smooth online education in the country during the pandemic.

Shrimp farming in southwestern Bangladesh: a case study of economic impacts during COVID-19

Bangladesh is endowed with a long coastline and therefore offers the enormous potential of marine wealth. In the coastal part of Bangladesh, shrimp is one of the most important export-oriented aquacultures due to high-profit return on the same value. Shrimp farming contributes significantly to the livelihoods of rural Bangladeshis in the southwestern region. It is critical to be aware of current culture practices and the measures shrimp farmers take to sustain the trend of exporting shrimp around the world. A random sampling was done of shrimp farmers in the Batiaghata Upazila of Khulna district to learn about the current state of shrimp farming and the challenges they are faced during COVID-19. The recent study reveals that most farmers following semi-intensive monoculture practice, application of organic sources in the shrimp pond, selection of PCR tested hatchery-produced Post Larvae (PL) and maintaining good hygiene practice that delivered considerable production of shrimp in this area. But in addition, with these good production farmers also face some difficulties. Some major shrimp diseases were identified in this study including White Feces Disease (WFD), White Spot Syndrome Virus (WSSV), Eosinophilia-Myalgia Syndrome (EMS), Black Gill Disease and some parasite attacks like Zutharium. Lower market price, flood and mortality are other constraints for shrimp farming. The low market price is the major issue for shrimp farmers nowadays around this pandemic situation. As a result, the government, donor agencies, planners, academics, and non-governmental organizations (NGOs) should come forward during the pandemic periods to assist farmers in resolving challenges and ensuring shrimp export revenues of Bangladesh are sustainable.

Socially Responsible Investing and Sustainable Indices: A Sustainability Agenda

COVID-19 pandemic has brought climate change and socially responsible investing back to the forefront. Sustainable investing, though well-entrenched in developed countries, is slowly gaining traction in emerging markets. Sustainability indices operate as quality indicators and bridge information gap. This study explores the usefulness of three such indices and offers an autoregressive moving average model on Carbonex series for sustainable investments on Bombay Stock Exchange. However, the model fails to align with the long-term goals of socially responsible investing and the investor community needs to engage with regulators, corporations and rating agencies so that these sustainability indices can better serve their information needs and offer a valid measure of sustainable practices. COVID-19 brings with it the opportunity to ideate and envision innovative approaches to support a carbon-free economic agenda and to design eco-friendly infrastructure, planned urban development and transition to clean energy. Take–make–consume–waste attitude is out and the philosophy of preserve–endure–nurture–bequeath will be the new normal. © 2021 Institute of Public Enterprise.

THz sensing of CoViD-19 disinfecting products using photonic crystal fiber

Methanol and Benzene are two volatile impurities that can be adulterate into Ethanol to make hand sanitizes, putting the disinfection practices at risk. In this paper, an optical fiber-based Photonic Crystal Fiber (PCF) sensor is developed to offer low loss and increased sensitivity concurrently in order to detect volatile contaminants combined with Ethanol in an efficient and safe manner. In the PCF, both the core and cladding area, rectangular air holes are utilized, and an absorbing layer, PML, is imposed to investigate a variety of optical characteristics. To quantify the exhibition of the recommended fiber sensor, Finite Element Method (FEM) framework is utilized. The simulation results on the proposed sensor model exhibit very gratifying results on the Relative Sensitivity (RS) as 99.15%, 99.36% and 99.41% confinement loss as 5 × 10−17 dB/cm, 2 × 10−16 dB/cm and 1.17 × 10−17 dB/cm, EML as 0.00065 cm−1, 0.00085 cm−1 and 0.00068 cm−1 for Ethanol, Methanol and Benzene, respectively at 2.2 THz frequency regime. Physical insights into the proposed fiber were also highlighted. The current manufacturing techniques are capable of producing the sensor we proposed. This PCF sensor is applicable to a larger variety of chemical, gas, and bio-sensing applications. © 2021 The Authors

First wave of covid-19 in India using IoT for identification of virus.

Internet of Things (IoT) are evolving rapidly and making it possible for many uses, such as manufacturing, military, education and health, to link different intelligent objects. Coronavirus has recently spread widely around the globe and no effective therapies are currently available. It is also very necessary to avoid infection and to control the symptoms, such as fever and shortness of breath. As Coronavirus is a disease that is circulating very rapidly and the social distancing to deter an outbreak is very significant, it is essential to provide a system that is intelligent enough to monitor the effects of individuals with little direct contact. This document contains an IoT-based and wireless sensor network architecture and simulation of the COVID-19 Monitoring Mechanism (CSMM) for the monitoring of people in their quarantine, particularly the elderly who are living under chronic diseases and immune failure, and are therefore more likely to contract severe diseases. The mechanism relies on patient health data remotely. A doctor or care practitioner may carry out the monitoring process. For starters, where there is high fire or trouble breathing, this can conveniently be used for a detected urgent or irregular situation. The process will then give a warning to the health care provider or practitioner, sending urgent SMS with time and condition to act without any delays to save the patient's life.

Computer aid screening of COVID-19 using X-ray and CT scan images: An inner comparison.

The objective of this study is to conduct a critical analysis to investigate and compare a group of computer aid screening methods of COVID-19 using chest X-ray images and computed tomography (CT) images. The computer aid screening method includes deep feature extraction, transfer learning, and machine learning image classification approach. The deep feature extraction and transfer learning method considered 13 pre-trained CNN models. The machine learning approach includes three sets of handcrafted features and three classifiers. The pre-trained CNN models include AlexNet, GoogleNet, VGG16, VGG19, Densenet201, Resnet18, Resnet50, Resnet101, Inceptionv3, Inceptionresnetv2, Xception, MobileNetv2 and ShuffleNet. The handcrafted features are GLCM, LBP & HOG, and machine learning based classifiers are KNN, SVM & Naive Bayes. In addition, the different paradigms of classifiers are also analyzed. Overall, the comparative analysis is carried out in 65 classification models, i.e., 13 in deep feature extraction, 13 in transfer learning, and 39 in the machine learning approaches. Finally, all classification models perform better when applying to the chest X-ray image set as comparing to the use of CT scan image set. Among 65 classification models, the VGG19 with SVM achieved the highest accuracy of 99.81%when applying to the chest X-ray images. In conclusion, the findings of this analysis study are beneficial for the researchers who are working towards designing computer aid tools for screening COVID-19 infection diseases.