ABSTRACT
Dhaka, the capital of Bangladesh, is one of the most congested megacities in the world today. It's predominantly road-based transportation systems have been failing to meet the dwellers mobility needs. Furthermore, the road congestion results in a significant GDP loss every year. The government has been undertaken (and continuing to undertake) numerous transportation systems and services improvement projects such as Metro Rail, BRT, flyovers and U-loop projects along major corridors. Furthermore, being a sustainable (environmentally friendly) mode, a Water-Taxi (WT) service was introduced in the Hatirjheel lake in December 2016 that currently serves major residential, educational, and business/commercial destinations including Rampura/Badda, Badda-Gulshan-1 link road, and Tejgoan/Kawran-Bazar areas through multiple routes. Previous studies reported that the demand for HatirJheel WT service outperforms its service capacity despite noted service weaknesses. This study assesses the WT service characteristics [i.e., WT station characteristics including their surrounding areas and adjacent bus stops, frequency/headway, travel (waiting and running) time, vessel capacity and ridership level as well as access (pre-trip) and egress (post-trip) modes of the riders]. Field data were collected and questionnaire-based surveys were conducted in late 2019 and early 2020 (just before the COVID-19 lockdown). The survey data reveals that a large percentage of WT riders are exchange (transfer) passengers from buses and para-transits. It is also found that WT operates on irregular headways causing long waiting times for riders. The physical separation between bus stops and WT stations, accessing issues (i.e., walking time and safe crossing of roads) with the WT stations as well as long waiting time at stations significantly deteriorate the WT service performance. Taking into consideration of the existing issues and challenges that may jeopardize the implementation of the proposed improvements, a SWOT analysis is also performed. This study recommends that schedule based reliable WT service with a desirable frequency and posted time-table should be introduced to minimize the waiting times at stations. The future study should focus on developing a model for analyzing the effectiveness of WT and bus system integration (i.e., physical and service - schedule and fare - integration between buses and WTs). If desired, WT and bus system integration would improve the service performance of both modes while attracting additional riders and ultimately supporting sustainable development (i.e., alleviating congestion on local roadways and improving air quality etc.). © 2023 Author(s).
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This study examines how the relationship between oil and stock market return of BRICS behaves at different investment horizons. Using data ranging from 2006 to 2020, the wavelet and MGARCH-DCC found that the stock markets' return of Russia, Brazil, and South Africa are comparatively more correlated with oil price return across the investment horizons and more volatile particularly during the Covid-19 period. However, the stock markets' return of China and India is less correlated with oil price return and less volatile. It is also revealed that oil price return leads the BRICS' stock markets' return and both are positively correlated.
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This paper examines the efficiency and asymmetric multifractal features of NFTs, DeFi, cryptocurrencies, and traditional assets using Asymmetric Multifractal Cross-Correlations Analysis covering the period from November 2017 to February 2022. Considering the full sample with a significant variation among asset classes, the study reveals DeFi-DigiByte is the most efficient while the cryptocurrency-Tether is the least efficient. However, S&P 500 showed high efficiency before COVID-19, and DeFi-Enjin Coin advanced as the most efficient asset during COVID-19. The volatility dynamics of NFTs, DeFi, and cryptocurrencies follow strong nonlinear cross-correlations, but evidence of weaker nonlinearity exists in traditional assets. Additionally, the sensitivity to smaller events in bull markets is high for NFTs and DeFi. The findings have significant implications for portfolio diversification when an investor's portfolio set includes traditional assets and cryptocurrency and relatively new blockchain-based assets like NFTs and DeFi. © 2023 The Authors
ABSTRACT
Newly recognized pandemic infectious disease COVID-19 (Corona-virus disease) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This viral infection causes hypercoagulability and inflammation leading to increased incidence of both arterial and venous thrombotic events (VTEs). Therefore, patients infected with this novel virus seem to be at higher risk of thrombotic events (TEs) resulting in thromboembolic diseases, especially stroke and pulmonary embolism, or even cerebral venous sinus thrombosis (CVST). We report a case of 42-year-old female, presented with features of venous thrombotic events (extensive dural venous sinus thrombosis) and was subsequently found to have COVID-19 positive by reverse transcriptase-polymerase chain reaction (RT-PCR) test. The case report indicates CVST might be an unusual manifestation of COVID-19. Cerebral venous sinus thrombosis even presents as an initial symptom of COVID-19 without significant respiratory symptoms. Early diagnosis and treatment with thrombolytic agent in case of SARS-CoV-2 infection result in reduced morbidity and mortality. We recommend further studies to establish SARS-CoV-2 virus (the COVID-19 disease) as a known risk factor for CVST. © 2020 The author (s).
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Video consultation (VC) use as a method of patient-healthcare interaction has expanded significantly across the National Health Service since the start of the COVID-19 pandemic. Emerging evidence suggests that VC used as an alternative to face-to-face (F2F) consultations offers several advantages such as safety of interaction and convenience (Johns G, Khalil S, Ogonovsky M et al. Taming the chaos: NHS professionals' perspective of using video consulting during COVID-19 in Wales. BMJ Open Qual 2021;10: e001318). A pilot programme of VC use in a dermatology department began in March 2021 using the Attend Anywhere electronic platform. The aim was to explore patient satisfaction of VC within the dermatology outpatient clinic setting for preselected inflammatory skin disorders in a teaching hospital. Data were collected prospectively for a period of 8 months. An automated questionnaire appeared at the end of the VC, prompting patients to provide feedback. The completed forms were collected and analysed by Technology Enabled Care (TEC) Cymru, a national service sponsored by the Welsh Government. Following communication with the research and evaluation lead, the data were shared with the authors. The questionnaire collected information on the type of appointment patients were attending, demographics, VC quality, whether patients had used VC before and/or would use it again in the future, if they had experienced any difficulties, and finally if they found the consultation beneficial. A total of 83 VCs were carried out and 48 patients completed the questionnaire (58% response rate). Participants were 72% female and ages ranged from 13-17 to > 80 years, with only 8.5% being > 65 years old. The majority of participants (72%) ranked the VC quality as excellent and in 69% of cases patients felt that it negated the need for a F2F consultation. All participants would use VC again, with only 8% preferring a F2F consultation. The vast majority of participants reported no technological issues, with audio being the highest ranked challenge of the VC (22%). Overall, the 'patient benefit' questions showed the majority of participants found VC advantageous vs. a F2F consultation and this included saving time overall (69%), in particular with travel and parking (84%), taking time off work (66%), improving access to care (69%), reducing the risk of infection (71%), reducing anxiety (60%) and improving family involvement during the consultation (55%). This study was limited by a small sample size and the questionnaire being designed for all healthcare settings and not specifically for dermatology. However, the results show a clear message of overall patient satisfaction when using VC with only limited technological challenges. VC is an innovative method of patient-healthcare interaction that if used in the correct setting can provide a preferable choice for communication between selected patients and dermatology staff.
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Purpose: Grounded in dynamic capability view, this research develops a decision support model, which enables determining consistent and sufficient configurations of resilience strategies to mitigate vaccine operations and distributions (O&D) challenges and thus improve O&D performance (i.e. O&DP). Design/methodology/approach: Through qualitative in-depth interviews, the authors first identified challenges and resilience strategies related to vaccine O&D. Next, using the quality function deployment technique, three quantitative case studies were performed to determine the most important challenges and resilience strategies. Finally, utilising fuzzy set qualitative comparative analysis, the authors determine sufficient conditions of challenges and strategies leading to improve vaccine O&DP. Findings: The findings reveal that strategies alone are not effective instead a combination of strategies and nullification of challenges is needed to enhance vaccine O&DP. Further, the findings revealed that not only the presence of challenges, but also the lack of strategies reduces the vaccine O&DP. Practical implications: The authors' findings will assist the health service decision-makers for strategizing an effective and efficient vaccination program by selecting the right combination of challenges and resilience strategies. Originality/value: The authors' study develops a novel decision support model and offers significant learning for the future vaccine O&DP. © 2023, Emerald Publishing Limited.
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We investigate the return and volatility spillovers among NFTs, REITs, and other major financial assets from January 2019 to November 2022, using connectedness approaches. The findings indicate that total return and volatility connectedness increased during the COVID-19 and the Russia–Ukraine war. REITs partially maintained their historical independence from shocks from other assets, while NFTs emerged as the new portfolio diversifiers. Findings suggest that investors can use REITs or a combination of NFTs, OIL, GOLD, and REITs with other assets to hedge against volatile assets during periods of financial turmoil. These findings have significant implications for heterogeneous market participants aiming to identify optimal portfolio diversifiers. © 2023 Investment Analysts Society of South Africa.
ABSTRACT
Introduction: Novel corona virus (SARS-Coronavirus-2: SARS-CoV-2) which emerged in Wuhan, China, has spread to multiple countries rapidly. Little information is known about nosocomial infections by SARS-CoV-2 in the initial period. As it spreads across the globe, physicians face the challenges of a contagious pandemic including patient isolation and diagnosis. Case Report: We report a case of concurrent meningoencephalitis and COVID-19 infection in a one-year old Bangladeshi patient who was brought a tertiary hospital in Dhaka, Bangladesh due to fever, convulsion and neck stiffness accompanied by unconsciousness later. Computed tomography (CT) SCAN of brain showed excessive encephalopathic change in both cerebral hemispheres with moderate communicating hydrocephalus, suggesting meningoencephalitis. During his hospitalization, he became infected with SARS-CoV-2 which was confirmed by real time polymerase chain reaction (RT-PCR. Conclusion: SARS-CoV-2 can be rapidly transmitted patient-to patient regardless of whether they have symptoms or not. Each hospital must differentiate patients with known or suspected COVID 19 infection from patients with a low probability COVID-19 infection in order to limit direct or indirect transmission. © 2020 The author (s). Published by Zagazig University.
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This study examines asymmetric efficiency and connectedness among halal tourism stocks, green stocks, cryptocurrency, gold, and oil using data covering the period from 2018M12–2022M09. Employing asymmetric multifractal detrended cross-correlation analysis, this study finds gold to be the most efficient asset and halal tourism stocks to be more efficient than green stocks. The asymmetric connectedness approach identifies green stocks as net transmitters of return shocks in all market conditions and halal tourism stocks (oil) as net receivers of return shocks in normal and upward (downward) market conditions. The connectedness among the assets increases during major economic events such as COVID-19 and the Russia–Ukraine war. Portfolio analysis suggests that the minimum connectedness portfolio outperforms all the other methods and shows halal tourism and green stocks offer significant hedging effectiveness. Our findings have significant implications for investors and policymakers seeking to diversify portfolios, manage risks, and regulate information in periods of financial turmoil and asymmetric market conditions. © 2023 Elsevier Ltd
ABSTRACT
In the domain of Marine Education and Training (MET), simulators have been utilized for the purpose of training seafarers in the norms for avoiding collisions or for developing the skill of ship manoeuvrability, and even the operation of machinery in the engine room, as well as for conducting research on the subject matter of ship structure, specialized vessel operation, working principle of equipment, and shipboard safety training. These tools are even more important when facing disruptive events such as the COVID-19 pandemic. In MET institutions, full-mission bridge and engine room simulators have been utilized for teaching seafarers for more than a decade. A Systematic Literature Review (SLR) was conducted to identify immersive and non-immersive simulator applications produced over the previous ten years to improve seafarers' experiential teaching and learning, in the maritime domain. We retrieved 27 articles using the four stages of PRISMA paradigm: Identification, Screening, Eligibility, and Inclusion. The selected papers were read and analyzed according to the training type, the area of training, and the technologies used. The utilization of immersive and non-immersive simulators in the context of the MET domain has been identified and mapped. A few research studies (9 out of 27) compared immersive and non-immersive simulator-based training with conventional training. The quality and efficacy of immersive and non-immersive simulator training at MET institutions have been studied. A model from the learner's perspective is essential and recommended for future research to assess efficiency and efficacy.
ABSTRACT
Coronavirus disease 2019 (COVID-19) has been diagnosed automatically using Machine Learning algorithms over chest X-ray (CXR) images. However, most of the earlier studies used Deep Learning models over scarce datasets bearing the risk of overfitting. Additionally, previous studies have revealed the fact that deep networks are not reliable for classification since their decisions may originate from irrelevant areas on the CXRs. Therefore, in this study, we propose Operational Segmentation Network (OSegNet) that performs detection by segmenting COVID-19 pneumonia for a reliable diagnosis. To address the data scarcity encountered in training and especially in evaluation, this study extends the largest COVID-19 CXR dataset: QaTa-COV19 with 121, 378 CXRs including 9258 COVID-19 samples with their corresponding ground-truth segmentation masks that are publicly shared with the research community. Consequently, OSegNet has achieved a detection performance with the highest accuracy of 99.65% among the state-of-the-art deep models with 98.09% precision. © 2022 IEEE.
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PurposeThis study aims to contribute by expanding the existing literature on Sukuk return and volatility and exploring the implications of the Sukuk-exchange rate interactions. Design/methodology/approachThis study examines the dynamic interactions of Sukuk with exchange rate in 15 countries, employing the Wavelet approach that considers both time and investment horizons. FindingsThe results reveal significant evolving coherence of Sukuk return and volatility with the underlying exchange rate. The relationship is more potent than what this study witnesses in their counterpart bond market. For Sukuk returns, the coherence is negative, whereas it is positive for volatility. Notably, the coherence is strong in the medium to long term and intensifies during extreme economic episodes, especially during the COVID-19 pandemic. These findings are further validated by comparing firm-level matched data for Sukuk and conventional bond. Originality/valueTo the best of the authors' knowledge, this is the first study that reports the dynamic relationship of Sukuk return and volatility with the underlying exchange rate in 15 countries. Collectively, this study unites valuable insights for faith-based active Islamic investors and cross-border portfolio managers.
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PurposeFake news on social media about COVID-19 pandemic and its associated issues (e.g. lockdown) caused public panic that lead to supply chain (SC) disruptions, which eventually affect firm performance. The purpose of this study is to understand how social media fake news effects firm performance, and how to mitigate such effects.Design/methodology/approachGrounded on dynamic capability view (DCV), this study suggests that social media fake news effects firm performance via SC disruption (SCD) and SC resilience (SCR). Moreover, the relation between SCD and SCR is contingent upon SC learning (SCL) - a moderated mediation effect. To validate this complex model, the authors suggest effectiveness of using partial least squares structural equation modeling (PLS-SEM). Using an online survey, the results support the authors' hypotheses.FindingsThe results suggest that social media fake news does not affect firm performance directly. However, the authors' serial mediation test confirms that SCD and SCR sequentially mediate the relationship between social media fake news and firm performance. In addition, a moderated serial mediation test confirms that a higher level of SCL strengthens the SCD-SCR relationship.Research limitations/implicationsThis work offers a new theoretical and managerial perspective to understand the effect of fake news on firm performance, in the context of crises, e.g. COVID-19. In addition, this study offers the advancement of PLS as more robust for real-world applications and more advantageous when models are complex.Originality/valuePrior studies in the SC and marketing domain suggest different effects of social media fake news on consumer behavior (e.g. panic buying) and SCD, respectively. This current study is a unique effort that investigates the ultimate effect of fake news on firm performance with complex causal relationships via SCD, SCR and SCL.
ABSTRACT
In the domain of Marine Education and Training (MET), simulators have been utilized for the purpose of training seafarers in the norms for avoiding collisions or for developing the skill of ship manoeuvrability, and even the operation of machinery in the engine room, as well as for conducting research on the subject matter of ship structure, specialized vessel operation, working principle of equipment, and shipboard safety training. These tools are even more important when facing disruptive events such as the COVID-19 pandemic. In MET institutions, full-mission bridge and engine room simulators have been utilized for teaching seafarers for more than a decade. A Systematic Literature Review (SLR) was conducted to identify immersive and non-immersive simulator applications produced over the previous ten years to improve seafarers' experiential teaching and learning, in the maritime domain. We retrieved 27 articles using the four stages of PRISMA paradigm: Identification, Screening, Eligibility, and Inclusion. The selected papers were read and analyzed according to the training type, the area of training, and the technologies used. The utilization of immersive and non-immersive simulators in the context of the MET domain has been identified and mapped. A few research studies (9 out of 27) compared immersive and non-immersive simulator-based training with conventional training. The quality and efficacy of immersive and non-immersive simulator training at MET institutions have been studied. A model from the learner's perspective is essential and recommended for future research to assess efficiency and efficacy.
ABSTRACT
The COVID-19 pandemic has presented serious challenges to emergency departments (EDs). EDs play an important role in responding to pandemics, as they make the first substantial strides to recuperate patients and protect them from infectious diseases, as shown in experiences of earlier infectious disease surge events (e.g., SARS-CoV, H1N1, Ebola, etc.). However, there is limited evidence on how facility design can support EDs’ response to pandemics. This chapter aims to provide a systematic literature review (SLR) of EDs’ challenges and responses to pandemics, with a primary focus on facility design strategies. After screening 2489 studies covering the literature from March 2000 to March 2021, 20 articles were reviewed to extract ED design strategies. Key findings include (a) negative-pressure rooms and (b) split flow and cohort isolation that can create various zones for patients with different risk and acuity levels are the most addressed approaches for infection control and accommodating surge capacity. Convertibility and flexibility concept (e.g., reconfiguration of spaces, temporary separation within spaces, reversible air pressure, flexible use of spaces within and adjacent to ED) is key to addressing the unique challenges of the evolving nature of pandemic outbreaks. This chapter provides a summary of existing design strategies for EDs to respond to pandemics. Multiple design strategies need to be combined to minimize the disease transmission in EDs during pandemics and provide surge capacity for the overflow of patients. Detailed design principles were synthesized based on the SLR and translated to a design prototype that aims to address the needs during various stages of pandemics. © 2023 selection and editorial matter, AnnaMarie Bliss and Dak Kopec;individual chapters, the contributors.
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Seroprevalence studies of COVID-19 are used to assess the degree of undetected transmission in the community and different groups such as health care workers (HCWs) are deemed vulnerable due to their workplace hazards. The present study estimated the seroprevalence and quantified the titer of anti-SARS-CoV-2 antibody (IgG) and its association with different factors. This cross-sectional study observed HCWs, in indoor and outdoor patients (non-COVID-19) and garment workers in the Chattogram metropolitan area (CMA, N = 748) from six hospitals and two garment factories. Qualitative and quantitative ELISA were used to identify and quantify antibodies (IgG) in the serum samples. Descriptive, univariable, and multivariable statistical analysis were performed. Overall seroprevalence and among HCWs, in indoor and outdoor patients, and garment workers were 66.99% (95% CI: 63.40-70.40%), 68.99% (95% CI: 63.8-73.7%), 81.37% (95% CI: 74.7-86.7%), and 50.56% (95% CI: 43.5-57.5%), respectively. Seroprevalence and mean titer was 44.47% (95% CI: 38.6-50.4%) and 53.71 DU/mL in the non-vaccinated population, respectively, while it was higher in the population who received a first dose (61.66%, 95% CI: 54.8-68.0%, 159.08 DU/mL) and both doses (100%, 95% CI: 98.4-100%, 255.46 DU/mL). This study emphasizes the role of vaccine in antibody production; the second dose of vaccine significantly increased the seroprevalence and titer and both were low in natural infection.
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This study examines whether the expansion of Australia’s international education sector has been highly dependent on students from China supported by competitive supply chain management. In 2019, Australia’s earnings from international education were A$40.3 billion, of which 30% was contributed by Chinese education visitors. However, researchers and observers have been alluding to the risks of over-reliance on the Chinese market in recent years. Further, the COVID-19 outbreak since early 2020 has severely disrupted the supply chains of the international education sector because Australia imposed travel bans for all international visitors. The econometric results of the study suggest that Chinese students contributed significantly to the education exports and economic growth of Australia. Policy recommendations emphasise on the diversification of the education market and effective supply chain management to recover from the financial hardship experienced by the sector caused by the COVID-19 pandemic along with the recent geopolitical tension between Australia and China. Copyright © 2022 Inderscience Enterprises Ltd.
ABSTRACT
The growth of social data on the internet has accelerated during the last two decades. As a result, researchers can access data and information for various academic and commercial purposes. The novel coronavirus disease (COVID-19) is a current pandemic that has sparked widespread concern worldwide. Spreading misleading information on social media platforms like Twitter, on the other hand, is exacerbating the disease's concern. This research aims to examine tweets and develop a model that can detect public sentiment from social media posts;consequently, necessary precautions can be taken to preserve adequate validity of information for the general public. We believe that various social media platforms have a significant impact on creating public awareness about the disease's importance and encouraging preventive measures among community members. For this study, we applied the Bidirectional Encoder Representations from Transformers (BERT) model, a new deep-learning technique for text analysis and performance with exceptional multi-class accuracy. We also compared it with six shallow machine learning models. © 2022 IEEE.
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Online animal transaction has become a popular growing technique in the COVID-19 pandemic situation in Bangladesh. The purpose of the study is to evaluate the function of physical, socio-religious, and marketing challenges that accelerated online animal selling in the pandemic situation. Using stratified random sampling in randomized block design, a response to a survey questionnaire has been collected from 200 respondents in Chattogram, Bangladesh via E-mail to know their opinion. The Structure Equation Model (SEM) shows that the Personal challenge factor, Market challenge factor, and Price challenge factor have a significant effect on the performance of online satisfaction animal transactions in the COVID-19 situation. But Social–Religious challenge factor has no significant effect on the performance of online satisfaction animal transactions. It is further observed that the online selling experience group shows high satisfaction than the online buying experience group. There is no significant difference in the performance of online satisfaction for all types of online animal transactions. It is also observed that the online bKash/Rocket/Nagad payment methods have significantly higher satisfaction of performance than cash on delivery and online banking payment method for the animal transaction. The Performance of the online satisfaction factor has a positive significant effect on creating online opportunities in the COVID-19 situation. The result will be used to develop the planning and utilization strategy for smooth and high-quality online animal transactions for ensuring sound health in the future © 2022. Shahnur Azad Chowdhury, Shahabuddin, Mohammad Shyfur Rahman Chowdhury, Mohammad Nazmul Hoq, Mustafa Manir Chowdhury, Shahidul Islam and Farah Israt Tania. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license
ABSTRACT
K-means algorithm is one of the well-known unsupervised machine learning algorithms. The algorithm typically finds out distinct non-overlapping clusters in which each point is assigned to a group. The minimum squared distance technique distributes each point to the nearest clusters or subgroups. One of the K-means algorithm’s main concerns is to find out the initial optimal centroids of clusters. It is the most challenging task to determine the optimum position of the initial clusters’ centroids at the very first iteration. This paper proposes an approach to find the optimal initial centroids efficiently to reduce the number of iterations and execution time. To analyze the effectiveness of our proposed method, we have utilized different real-world datasets to conduct experiments. We have first analyzed COVID-19 and patient datasets to show our proposed method’s efficiency. A synthetic dataset of 10M instances with 8 dimensions is also used to estimate the performance of the proposed algorithm. Experimental results show that our proposed method outperforms traditional kmeans++ and random centroids initialization methods regarding the computation time and the number of iterations. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.