Search results for: pandemic response

Authors: Lisa C. Wan

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To address customers’ safety concerns, more and more hospitality companies are using service robots to provide contactless services. For many companies, the switch from human employees to service robots to lower the contagion risk during and after the pandemic may be permanent. The market size for hospitality service robots is estimated to reach US$3,083 million by 2030, registering a CAGR of 25.5% from 2021 to 2030. While service robots may effectively reduce interpersonal contacts and health risk, it also eliminates the social interactions desired by customers. A recent survey revealed that more than 60% of Americans feel lonely during the pandemic. People who are traveling can also feel isolated when they are at a hotel far away from home. It is therefore important for the hospitality companies to understand whether and how social robots can remedy deprived social connection not only due to a pandemic but also for a trip away from home in the post-pandemic future. This study complements extant hospitality literature regarding service robots by examining how service robots can forge social connections with customers. The service robots we are concerned with are those that can interact and communicate with humans; we broadly refer to them as social robots. We define a social robot as one that is equipped with interaction capabilities – it can either be one that directly interacts with the consumer or one through which the consumer can interact with other humans. Drawing on the theories of mind perception, we propose that service robots can foster social connectedness and increase the perception of social competence of the robot, but these effects will vary across cultures. By applying theories of mind perception and cultural dimension to the hospitality setting, this study shows that service robots that are equipped with social connection function will receive a more favorable evaluation from the consumers and enhance their intention to visit a hotel. The more favorable reaction to social robots is stronger for collectivists (i.e., Asians) than individualists (i.e., Westerners). To our knowledge, this is among the first studies to investigate the impact of culture on consumer reactions to social robots in the hospitality and tourism context. Moreover, this research extends the literature by examining whether people imbue non-human entities (i.e., telepresence social robots) with social competence. Because social robots that foster social connection with humans are still rare in hospitality and tourism, this aspect is an underexplored research area. Our study is the first to propose that, just like their human counterparts that possess relevant social skills, social robots’ interaction capabilities (e.g., telepresence robots) are used to infer social competence. More studies will be conducted to examine consumer reactions to humanoid (vs. non-humanoid) robot in the hospitality settings to generalize our research findings.

Keywords: service robots, COVID-19, social connection, cultures

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Authors: Nina Øystad-Larsen, Miran Cemalovic, Amir M. Kaynia

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The nonlinear static and dynamic analysis procedures presented in EN 1998-1 for the structural response of a RC wall-frame building are assessed. The structure is designed according to the guidelines for high ductility (DCH) in 1998-1. The finite element packages SeismoStruct and OpenSees are utilized and evaluated. The structural response remains nearly in the elastic range even though the building was designed for high ductility. The overstrength is a result of oversized and heavily reinforced members, with emphasis on the lower storey walls. Nonlinear response history analysis in the software packages give virtually identical results for displacements.

Keywords: behaviour factor, dual system, OpenSEES, overstrength, seismostruct

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Authors: Masoud Swalehe, Semra Günay

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Developed countries are losing many lives to non-communicable diseases as compared to their developing counterparts. The effects of these diseases are mostly sudden and manifest at a very short time prior to death or a dangerous attack and this has consolidated the significance of emergency medical system (EMS) as one of the vital areas of healthcare service delivery. The primary objective of this research is to reduce ambulance response times (RT) of Eskişehir province EMS since a number of studies have established a relationship between ambulance response times and survival chances of patients especially out of hospital cardiac arrest (OHCA) victims. It has been found out that patients who receive out of hospital medical attention in few (4) minutes after cardiac arrest because of low ambulance response times stand higher chances of survival than their counterparts who take longer times (more than 12 minutes) to receive out of hospital medical care because of higher ambulance response times. The study will make use of geographic information systems (GIS) technology to dynamically reallocate ambulance resources according to demand and time so as to reduce ambulance response times. Geospatial-time distribution of ambulance calls (demand) will be used as a basis for optimal ambulance deployment using system status management (SSM) strategy to achieve much demand coverage with the same number of ambulance resources to cause response time reduction. Drive-time polygons will be used to come up with time specific facility coverage areas and suggesting additional facility candidate sites where ambulance resources can be moved to serve higher demands making use of network analysis techniques. Emergency Ambulance calls’ data from 1st January 2014 to 31st December 2014 obtained from Eskişehir province health directorate will be used in this study. This study will focus on the reduction of ambulance response times which is a key Emergency Medical Services performance indicator.

Keywords: emergency medical services, system status management, ambulance response times, geographic information system, geospatial-time distribution, out of hospital cardiac arrest

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Authors: Nino Damenia

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E-commerce opens a new horizon for business development, which is why the presence of e-commerce is a necessary condition for the formation, growth, and development of the country's economy. Worldwide, e-commerce turnover is growing at a high rate every year, as the electronic environment provides great opportunities for product promotion. E-commerce in Georgia is developing at a fast pace, but it is still a relatively young direction in the country's economy. Movement restrictions and other public health measures caused by the COVID-19 pandemic have reduced economic activity in most economic sectors and countries, significantly affecting production, distribution, and consumption. The pandemic has accelerated digital transformation. Digital solutions enable people and businesses to continue part of their economic and social activities remotely. This has also led to the growth of e-commerce. According to the data of the National Statistics Service of Georgia, the share of online trade is higher in cities (27.4%) than in rural areas (9.1%). The COVID-19 pandemic has forced local businesses to expand their digital offerings. The size of the local market increased 3.2 times in 2020 to 138 million GEL. And in 2018-2020, the share of local e-commerce increased from 11% to 23%. In Georgia, the state is actively engaged in the promotion of activities based on information technologies. Many measures have been taken for this purpose, but compared to other countries, this process is slow in Georgia. The purpose of the study is to determine development prospects for the economy of Georgia based on the analysis of electronic commerce. Research was conducted around the issues using Georgian and foreign scientists' articles, works, reports of international organizations, collections of scientific conferences, and scientific electronic databases. The empirical base of the research is the data and annual reports of the National Statistical Service of Georgia, internet resources of world statistical materials, and others. While working on the article, a questionnaire was developed, based on which an electronic survey of certain types of respondents was conducted. The conducted research was related to determining how intensively Georgian citizens use online shopping, including which age category uses electronic commerce, for what purposes, and how satisfied they are. Various theoretical and methodological research tools, as well as analysis, synthesis, comparison, and other types of methods, are used to achieve the set goal in the research process. The research results and recommendations will contribute to the development of e-commerce in Georgia and economic growth based on it.

Keywords: e-commerce, information technology, pandemic, digital transformation

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Authors: Gholam Reza Parvizi, Ali Reza Kargar, Amir Arani

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In the present days, learning and teaching researchers have emphasized the role which teachers, tutors, and trainers’ constraint knowledge treat in resizing and trimming what they perform in educational atmosphere. Regarding English language as subject to teaching, although the prominence of instructor’s knowledge about grammar has also been stressed, but the lack of empirical insights into the relationship between teacher’ self-monitoring and self-response of grammar knowledge have been observed. With particular attention to the grammar this article indicates and discusses information obtained self- feedback and conversing teachers of a kind who backwash the issue. The result of the study indicates that enabling teachers to progress and maintain a logical and realistic awareness of their knowledge about grammar have to be prominent goal for teachers’ education and development programs.

Keywords: grammar knowledge, self-monitoring, self-response, teaching grammar, language teaching program

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Authors: Anthony J. Kondracki, Bonzo Reddick, Jennifer L. Barkin

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Background: Many pregnancies in the United States are affected each year with the most common sexually transmitted infections (STIs), including Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Treponema pallidum (TP, syphilis), and the rate of congenital syphilis has reached a 20-year high. We sought to estimate the prevalence of CT, NG, and TP in pregnancy and the risk of preterm birth (PTB) (<37 weeks gestation) and low birthweight (LBW) (<2500g) deliveries according to utilization of prenatal care (PNC) during the COVID-19 pandemic. Methods: This study was based on the 2020 National Center for Health Statistics (NCHS) Natality File restricted to singleton births (N=3,512,858). We estimated the prevalence of CT, NG, TP, PTBand LBW across timing and the number of prenatal care (PNC) visits attended. In multivariable logistic regression models, adjusted odds ratios of PTB and LBW were assessed according to STIs and PNC status. E-values, based on effect size estimates and the lower bound of the 95% confidence intervals (CIs) of the association, examined the potential impact of unmeasured confounding. Results: CT (1.8%) was most prevalent in pregnancy, followed by NG (0.3%) and TP (0.1%). The strongest predictors of PTB and LBW were maternal NG (12.2% and 12.1%, respectively), late initiation/no PNC (8.5% and 7.6%, respectively), and ≤10 prenatal visits (13.1% and 10.3%, respectively). The odds of PTB and LBW were 2.5- to 3-fold greater for each STI in women who received ≤10 compared to >10 prenatal visits. E-values demonstrated the minimum strength of potential unmeasured confounding necessary to explain away observed associations. Conclusions: Timely initiation and receipt of recommended number of prenatal visits benefits screening and treatment of all women for STIs, including NG to substantially reduce infant morbidity and mortality related to PTB and LBW among infants born during the COVID-19 pandemic.

Keywords: COVID-19 pandemic, sexually transmitted infections, preterm birth, low birthweight, prenatal care

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Authors: Murat Colak, Berkay Cakir Saridogan

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Since the dawn of modern corporations, almost every single employee has been working in the same loop, which contains three basic steps: going to work, providing the needs for the work, and getting back home. Only a small amount of people were able to break that standard and live outside the box. As the 2019 pandemic hit the Earth and most companies shut down their physical offices, that loop had to change for everyone. This means that the old management styles had to be significantly re-arranged to the "work from home" type of business methods. The methods include online conferences and meetings, time and task tracking using algorithms, globalization of the work, and, most importantly, remote working. After the global epidemic started, even the tech giants were concerned. Now, it can be seen those technology companies have an incredible step-up in their shares compared to the other companies because they know how to manage such situations even better than every other industry. This study aims to take the old traditional management styles in big companies and compare them with the post-covid methods (2019-2022). As a result of this comparison made using the annual reports and shared statistics, this study aims to explain why the winners of this crisis are the technology companies.

Keywords: Covid-19, technology companies, business models, remote work

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Authors: Marion Francisco

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The study sought to investigate the psychological capital and work engagement of employees as predictors of employee performance in the technology industry in Makati City. It made used of a descriptive correlational method of research and utilized standardized tests, such as Psychological Capital Scale, Utrech Work Engagement Scale, and Employee Performance Scale. A convenience sampling technique was used to gather data samples from 100 populations with the help of Roscoe concept approach. The study revealed that both psychological capital and work engagement have a significant relationship with employee performance. Psychological capital and work engagement can predict employee performance of the respondents. With the results given, the study suggests: (1) to focus on maintaining a high level of psychological capital and work engagement, on achieving a very high level of psychological capital and work engagement, and on improving the low level of psychological capital or work engagement mostly during this COVID-19 pandemic using the proposed employee performance management plan and (2) to create a proposed employee performance management plan as necessary to tailor fit on employees needs to enhance their performance that will help meet company and client’s needs.

Keywords: employee performance, performance management, psychological capital, technology industry, work engagement

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Authors: Luojie Tang

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The article takes the "7.20 Heavy Rainstorm in Zhengzhou" as a starting point, collects relevant disaster data, reproduces the entire process of the disaster, and identifies the main problems exposed by the city in responding to super-standard rain and flood disasters. Based on the review of resilience theory, the article proposes a shift in thinking about the response to super-standard rain and flood disasters from the perspective of resilience, clarifies the differences in the emphasis on resilience at different stages of disasters, and preliminarily constructs a response system for super-standard rain and flood disasters based on the guidance of resilience theory. Finally, combined with the highlighted problems in the 7.20 Heavy Rainstorm in Zhengzhou, the article proposes targeted response strategies from three perspectives: institutional management, technological support, and infrastructure, under the perspective of resilience.

Keywords: resilient city, exceedance-based stormwater management, disaster risk reduction, megalopolis

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Authors: Ahmed Guerine, Ali El Hafidi, Bruno Martin, Philippe Leclaire

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In this paper, we propose a method for the dynamic response of multi-storey structures with uncertain-but-bounded parameters. The effectiveness of the proposed method is demonstrated by a numerical example of three-storey structures. This equation is integrated numerically using Newmark’s method. The numerical results are obtained by the proposed method. The simulation accounting the interval analysis method results are compared with a probabilistic approach results. The interval analysis method provides a mean curve that is between an upper and lower bound obtained from the probabilistic approach.

Keywords: multi-storey structure, dynamic response, interval analysis method, random parameters

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Authors: Hee-Jung Seo, Yunjung Lee, Areum Han, Heeyoung Park, Se-Hyuk Park

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The purpose of this study was to analyze the relationship between happiness and depression among people with disabilities and to analyze the social phenomenon of leisure activities among them to promote physical and leisure activities for people with disabilities. The research methods included analyzing differences in happiness according to depression classification. A total of 281 people with disabilities were analyzed using SPSS WIN Ver. 29.0. In addition, the SumTrend platform was used to analyze terms related to 'leisure activities for the disabled.' The findings can be summarized into two main points: First, there were significant differences in happiness according to depression classification. Second, there were 20 mentions before COVID-19, 34 mentions after COVID-19, and currently 43 mentions, with high positive rates observed in each period. Based on these results, the following conclusions were drawn: First, measures for people with disabilities include strengthening online resources and services, social distancing response policies, improving accessibility, and providing support and financial assistance. Second, measures for non-disabled individuals emphasize the need for education and information provision, promoting dialogue and interaction, ensuring accessibility, and promoting inclusive cultural awareness and attitude change.

Keywords: leisure activities, individuals with disabilities, COVID-19 pandemic, depression

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Authors: Mohamed Noureldin, Jinkoo Kim

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The sensitivity of the seismic response parameters to the uncertain modeling variables of pile-founded fixed steel jacket platforms are investigated using tornado diagram, first-order second-moment, and static pushover analysis techniques. The effects of both aleatory and epistemic uncertainty on seismic response parameters have been investigated for an existing offshore platform. The sources of uncertainty considered in the present study are categorized into three different categories: the uncertainties associated with the soil-pile modeling parameters in clay soil, the platform jacket structure modeling parameters, and the uncertainties related to ground motion excitations. It has been found that the variability in parameters such as yield strength or pile bearing capacity has almost no effect on the seismic response parameters considered, whereas the global structural response is highly affected by the ground motion uncertainty. Also, some uncertainty in soil-pile property such as soil-pile friction capacity has a significant impact on the response parameters and should be carefully modeled. Based on the results, it is highlighted that which uncertain parameters should be considered carefully and which can be assumed with reasonable engineering judgment during the early structural design stage of fixed steel jacket platforms.

Keywords: fixed jacket offshore platform, pile-soil structure interaction, sensitivity analysis

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Authors: Mohsin Shahab, Shagufta Rehmat, Faisal F. Khan

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Background: The global COVID-19 pandemic has generated health problems worldwide. Health care workers are the front-line warriors against the pandemic. The aim of this study was to find out the prevalence of COVID-19 (7th May 2021 to 3rd August 2021) amongst Health Care Workers (HCWs) and to assess the complications associated with it and its effects on their quality of life. Material and Method: The study was conducted in healthcare facilities which serve as pandemic hospitals in district Swat. A total of 140 healthcare workers, who were employed in the COVID-19 health care facilities, including the department of Pulmonology, Intensive Care Unit (ICU), and COVID-19 wards. Participants were tested for COVIID-19 using RT PCR test. A Case Report Form (CRF) for conditions during and post COVID-19 was filled to assess the complications and quality of life of health care workers. Results: A total of 140 Health Care Workers were studied, out of which 40% were doctors, 22% nursing staff, 17% paramedic staff, 9% cleaning staff, lab technologist 6%, 2% operation theater staff, administration staff, and pharmacist. The respondents were also investigated for pre-existing illness prior to SARS-CoV-2 infection, hypertension was the most prevalent, followed by chronic heart diseases and neurological disorders. Fever was the most common symptom, recorded 76.42% in the participants, while 55.71% of participants had dry cough, 55% had a sore throat, following by chest pain 43.56%. Reinfection rate was 10%, with chest pain being recorded in 85.71%. Post disease complication analysis showed that 47.14% of the participants were diagnosed with a new diagnosis after the COVID-19 recovery. Pulmonological diseases were recorded the most as a new diagnosis in, followed by gastrointestinal and psychological problems. Conclusions: The results of the study illustrates how COVID-19 has affected the overall health and quality of life of HCWs in District Swat of Khyber Pakhtunkhwa, Pakistan.

Keywords: SARS-CoV-2, COVID-19, HCW's, symptoms, questionnaire, post COVID-19

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Authors: Arfat Bait Jamil

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This study investigates how the compliment response of thanking is performed by Omani and Australian, lecturers and students, in higher educational settings. Semi-structured interviews and observation records were used to collect data. Thanking responses were aggregated from interviews with Omani lecturers and students in Oman, and from Australian lecturers and students in Australia, wherein they were asked to imagine themselves being complimented on five different compliment topics. After the interviews, they used observation record to note down real-life examples of compliment exchanges, along with their opinions. The findings show that thanking is not a simple compliment response. Depending on the context in which the compliment is delivered, thanking does not always suggest positive thoughts or feelings and compliment approval.

Keywords: Australia, compliment responses, Oman, thanking

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Authors: Saidia Houari

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The current coronavirus pandemic (COVID-19) is a special and unusual reality. It can affect people physically, but also psychologically. Indeed, in such a context, many people will experience reactions of stress, anxiety and depression, and Sports is known to be a great in improving the effectiveness of the nervous system and mental health. Professor Ango Frubuze“many studies proved that sports play an important role in fighting psychological tension and some other psychological problems, such as depression and sleep difficulties, but on condition of practicing them properly,choosing the kind that generates comfort and happiness for man “ .The sports university professor in the German city of Cologne added that the effort exerted during the exercise works on restoring balance to the stress hormones like cortisol.The case report provides an insight into the COVID-19 current situation and represents a picture of the current state of mental health and an overview of novel coronavirus (Covid-19) outbreaks in some countries of the world. Some procedures taken to combat the coronavirus. We proposed the practice of physical activities during the quarantine period, and we showed their importance and their positive effects.

Keywords: COVID-19, psycholiqical impacts, stress, physical activities

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Authors: Armijos-Orellana Ana, González-Calle María, Maldonado-Matute Juan, Guerrero-Maxi Pedro

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Nowadays, the digital economy represents a fundamental element to guarantee economic and social development, whose importance increased significantly with the arrival of the COVID-19 pandemic. However, despite the benefits it offers, it can also be detrimental to those developing countries characterized by a wide digital divide. It is for this reason that the objective of this research was to identify and describe the main characteristics, benefits, and obstacles of the digital economy for Latin American countries. Through a bibliographic review, using the analytical-synthetic method in the period 1995-2021, it was determined that the digital economy could give way to structural changes, reduce inequality, and promote processes of social inclusion, as well as promote the construction and participatory development of organizational structures and institutional capacities in Latin American countries. However, the results showed that the digital economy is still incipient in the region and at least three factors are needed to establish it: joint work between academia, the business sector and the State, greater emphasis on learning and application of digital transformation and the creation of policies that encourage the creation of digital organizations.

Keywords: developing countries, digital divide, digital economy, digital literacy, digital transformation

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Authors: Zhaofeng Li, Jun Kang Chow, Yu-Hsing Wang

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This paper attempts to bridge the soil properties and the mechanical response of soil in the discrete element method (DEM) simulation. The artificial neural network (ANN) was therefore adopted, aiming to reproduce the stress-strain-volumetric response when soil properties are given. 31 biaxial shearing tests with varying soil parameters (e.g., initial void ratio and interparticle friction coefficient) were generated using the DEM simulations. Based on these 45 sets of training data, a three-layer neural network was established which can output the entire stress-strain-volumetric curve during the shearing process from the input soil parameters. Beyond the training data, 2 additional sets of data were generated to examine the validity of the network, and the stress-strain-volumetric curves for both cases were well reproduced using this network. Overall, the ANN was found promising in predicting the soil behavior and reducing repetitive simulation work.

Keywords: artificial neural network, discrete element method, soil properties, stress-strain-volumetric response

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Authors: A. Šapkauskienė, A. Mačerinskienė, R. Andrulienė, R. Bruzgė, S. Masteika, K. Driaunys

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The COVID-19 pandemic has affected not only world markets and economies but also the daily lives of customers and their payment habits. The pandemic has accelerated the digital transformation, so the role of technology will become even more important post-COVID. Although the popularity of cryptocurrencies has reached unprecedented heights, there are still obstacles, such as a lack of consumer experience and distrust of these technologies, so exploring the role of cryptocurrency and blockchain in the context of international travel becomes extremely important. Research on tourists’ intentions to use cryptocurrencies for payment purposes is limited due to the small number of research studies. To fill this research gap, an exploratory study based on the analysis of survey data was conducted. The purpose of the research is to explore how the behavior of tourists has changed making their financial transactions when paying for the tourism services in order to determine the intention to pay in cryptocurrencies. Behavioral intention can be examined as a dependent variable that is useful for the study of the acceptance of blockchain as cutting-edge technology. Therefore, this study examines the intention of travelers to use cryptocurrencies in electronic payments for tourism services. Several studies have shown that the intention to accept payments in a cryptocurrency is affected by the perceived usefulness of these payments and the perceived ease of use. The findings deepen our understanding of the readiness of service users to apply for blockchain-based payment in the tourism sector. The tourism industry has to focus not only on the technology but on consumers who can use cryptocurrencies, creating new possibilities and increasing business competitiveness. Based on research results, suggestions are made to guide future research on the use of cryptocurrencies by tourists in the tourism industry. Therefore, in line with the rapid expansion of virtual currency users, market capitalization, and payment in cryptographic currencies, it is necessary to explore the possibilities of implementing a blockchain-based system aiming to promote the use of services in the tourism sector as the most affected by the pandemic.

Keywords: behavioral intention, blockchain-based payment, cryptocurrency, tourism

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Authors: M. Moradi Dalini, M. R. Talebi

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This research revolves around a technical method according to combines econometric and multiobjective programming to select and obtain optimal solutions to management problems. It is taken for a generation that; it is important to analyze which combination of values of the explanatory variables -in an econometric method- would point to the simultaneous achievement of the best values of the response variables. In this case, if a certain degree of conflict is viewed among the response variables, we suggest a multiobjective method in order to the results obtained from a regression analysis. In fact, with the use of a multiobjective method, we will have the best decision about the conflicting relationship between the response variables and the optimal solution. The combined multiobjective programming and econometrics benefit is an assessment of a balanced “optimal” situation among them because a find of information can hardly be extracted just by econometric techniques.

Keywords: econometrics, multiobjective optimization, management problem, optimization

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Authors: John Ahluwalia

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As an affluent first-world nation, Canada took swift and comprehensive action during the outbreak of the SARS-CoV-2 (COVID-19) pandemic compared to other countries in the same socio-economic cohort. The United States has stumbled to overcome obstacles most developed nations have faced, which has led to significantly more per capita cases and deaths. The initial outbreaks of COVID-19 occurred in the US and Canada within days of each other and posed similar potentially catastrophic threats to public health, the economy, and governmental stability. On a macro level, events that take place in the US have a direct impact on Canada. For example, both countries tend to enter and exit economic recessions at approximately the same time, they are each other’s largest trading partners, and their currencies are inexorably linked. Why is it that Canada has not shared the same fate as the US (and many other nations) that have realized much worse outcomes relative to the COVID-19 pandemic? Variables intrinsic to Canada’s national infrastructure have been instrumental in the country’s efforts to flatten the curve of COVID-19 cases and deaths. Canada’s coordinated multi-level governmental effort has allowed it to create and enforce policies related to COVID-19 at both the national and provincial levels. Canada’s policy of universal healthcare is another variable. Health care and public health measures are enforced on a provincial level, and it is within each province’s jurisdiction to dictate standards for public safety based on scientific evidence. Rather than introducing confusion and the possibility of competition for resources such as PPE and vaccines, Canada’s multi-level chain of government authority has provided consistent policies supporting national public health and local delivery of medical care. This paper will demonstrate that the coordinated efforts on provincial and federal levels have been the linchpin in Canada’s relative success in containing the deadly spread of the COVID-19 virus.

Keywords: COVID-19, Canada, GIS, temporal analysis, ESRI

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Authors: K. Farheen, A. Munir

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Seismic response of the multi-storey buildings is created by the interaction of both the structure and underlying soil medium. The seismic design philosophy is incorporated using response modification factor 'R'. Current code based values of 'R' factor does not reflect the SSI problem as it is based on fixed base condition. In this study, the modified values of 'R' factor for moment resisting frame (MRF) considering SSI are evaluated. The response of structure with and without SSI has been compared using equivalent linear static and nonlinear static pushover analyses for 10-storied moment resisting frame building. The building is located in seismic zone 2B situated on different soils with shear wave velocity (Vₛ) of 300m/sec (SD) and 1200m/s (SB). Code based 'R' factor value for building frame system has been taken as 5.5. Soil medium is modelled using identical but mutually independent horizontal and vertical springs. It was found that the modified 'R' factor values have been decreased by 47% and 43% for soil SD and SB respectively as compared to that of code based 'R' factor.

Keywords: buildings, SSI, shear wave velocity, R factor

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Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

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Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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Authors: Mohammad H. Yarmohamadian, Reza Safdari, Nahid Tavakoli

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In recent years, many countries have suffered various natural disasters. Disaster response continues to face the challenges in health care sector in all countries. Information and communication management is a significant challenge in disaster scene. During the last decades, rapid advances in information technology have led to manage information effectively and improve communication in health care setting. Information technology is a vital solution for effective response to disasters and emergencies so that if an efficient ICT-based health information system is available, it will be highly valuable in such situation. Of that, mobile technology represents a nearly computing technology infrastructure that is accessible, convenient, inexpensive and easy to use. Most projects have not yet reached the deployment stage, but evaluation exercises show that mHealth should allow faster processing and transport of patients, improved accuracy of triage and better monitoring of unattended patients at a disaster scene. Since there is a high prevalence of cell phones among world population, it is expected the health care providers and managers to take measures for applying this technology for improvement patient safety and public health in disasters. At present there are challenges in the utilization of mhealth in disasters such as lack of structural and financial issues in our country. In this paper we will discuss about benefits and challenges of mhealth technology in disaster setting considering connectivity, usability, intelligibility, communication and teaching for implementing this technology for disaster response.

Keywords: information technology, mhealth, disaster, effective response

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Authors: Arkaprabha Bhattacharyya, Makarand Hastak

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The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: economic growth, infrastructure development, infrastructure projects, strategic investment

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Authors: Maisa Sales Gama Tobias, Humberto de Paiva Junior, Luciano Silva Brito, Rui António Rodrigues Ramos

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Waterway transport in the Amazon was the first means of access and occupation in the region. For the economic and social matter of high importance, still nowadays one of the main transport modes to several places in the region. To some places, still the only transport mode. With the advent of the pandemic, transport companies that already faced management challenges began to experience unprecedented structural changes and trends in trade and global supply chains. Thus, companies need operational reorganization to maintain the sustainability of the service under the penalty of loss of demand. Allied to this fact, it was observed that the demand presented behavior changes to adapt to this new moment. However, the lack of information about these changes makes it difficult to find solutions to maintain the quality of service. This work aimed to characterize the changes in the demand of waterway passengers through an empirical study with field research involving interviews with users and crew, on-board journeys, and visits to the waterway service company. The case study is the route Belém-Camara, on Marajó Island, in the state of Pará. This line is traditionally the only means of transport for this route, besides air transport on a much smaller scale. The collected data had a descriptive and analytical statistical treatment presented in this work. As the main result, the COVID-19 pandemic has caused significant changes, mainly in trip time and motives and, in the perception itself on service quality by part of the demand, with the increase of trip time and the feeling of insecurity. In conclusion, the service operator must review cost management and business survival strategies and tactics. The viability of the service and the social guarantee of transport proved to be threatened, putting at risk the service to the riverside populations.

Keywords: demand of waterway transport passengers, data analysis, COVID-19, amazonia

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Authors: Josua K. Junias, Fillemon N. Nangolo, Petrina T. Johaness

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The deterioration of pavement can lead to the formation of potholes, which cause the wheels of a vehicle to experience unusual and uneven movement. In addition, improper loading practices of heavy vehicles can result in dynamic loading of the pavement due to the vehicle's response to the irregular movement caused by the potholes. Previous studies have only focused on the effects of either the road's uneven surface or the asymmetrical loading of the vehicle, but not both. This study aimed to model the pavement's dynamic response to heavy vehicles under different loading configurations and wheel movements. A sample of 225 cases with symmetrical and asymmetrical loading and kinematic movements was used, and 27 validated 3D pavement-vehicle interactive models were developed using SIMWISE 4D. The study found that the type of kinematic movement experienced by the heavy vehicle affects the pavement's dynamic loading, with eccentrically loaded, asymmetrically kinematic heavy vehicles having a statistically significant impact. The study also suggests that the mass of the vehicle's suspension system plays a role in the pavement's dynamic loading.

Keywords: eccentricities, pavement dynamic loading, vertical displacement dynamic response, heavy vehicles

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Authors: Giselda Cristina Ferreira, Carlos Alberto Kamienski, Ana Lígia Scott

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The COVID-19 pandemic has enhanced the anti-vaccination movement in Brazil, supported by unscientific theories and false news and the possibility of wide communication through social networks such as Twitter, Facebook, and YouTube. The World Health Organization (WHO) classified the large volume of information on the subject against COVID-19 as an Infodemic. In this paper, we present a protocol to identify polarizing users (called polarizers) and study the profiles of Brazilian polarizers on Twitter (renamed to X some weeks ago). We analyzed polarizing interactions on Twitter (in Portuguese) to identify the main polarizers and how the conflicts they caused influenced the COVID-19 vaccination rate throughout the pandemic. This protocol uses data from this social network, graph theory, Java, and R-studio scripts to model and analyze the data. The information about the vaccination rate was obtained in a public database for the government called OpenDataSus. The results present the profiles of Twitter’s Polarizer (political position, gender, professional activity, immunization opinions). We observed that social and political events influenced the participation of these different profiles in conflicts and the vaccination rate.

Keywords: Twitter, polarization, vaccine, Brazil

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Authors: I. F. Ejim, F. L. Kamen

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Aims: In this experiment, algae oil extraction with a combination of n-hexane and ethanol was investigated. The effects of extraction solvent concentration, extraction time and temperature on the yield and quality of oil were studied using Response Surface Methodology (RSM). Experimental Design: Optimization of algae oil extraction using Box-Behnken design was used to generate 17 experimental runs in a three-factor-three-level design where oil yield, specific gravity, acid value and saponification value were evaluated as the response. Result: In this result, a minimum oil yield of 17% and maximum of 44% was realized. The optimum values for yield, specific gravity, acid value and saponification value from the overlay plot were 40.79%, 0.8788, 0.5056 mg KOH/g and 180.78 mg KOH/g respectively with desirability of 0.801. The maximum point prediction was yield 40.79% at solvent concentration 66.68 n-hexane, temperature of 40.0°C and extraction time of 4 hrs. Analysis of Variance (ANOVA) results showed that the linear and quadratic coefficient were all significant at p<0.05. The experiment was validated and results obtained were with the predicted values. Conclusion: Algae oil extraction was successfully optimized using RSM and its quality indicated it is suitable for many industrial uses.

Keywords: algae oil, response surface methodology, optimization, Box-Bohnken, extraction

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Authors: Rama Debbarma

Abstract:

The present study deals with the performance of Linear base isolation system to mitigate seismic response of structures characterized by random system parameters. This involves optimization of the tuning ratio and damping properties of the base isolation system considering uncertain system parameters. However, the efficiency of base isolator may reduce if it is not tuned to the vibrating mode it is designed to suppress due to unavoidable presence of system parameters uncertainty. With the aid of matrix perturbation theory and first order Taylor series expansion, the total probability concept is used to evaluate the unconditional response of the primary structures considering random system parameters. For this, the conditional second order information of the response quantities are obtained in random vibration framework using state space formulation. Subsequently, the maximum unconditional root mean square displacement of the primary structures is used as the objective function to obtain optimum damping parameters Numerical study is performed to elucidate the effect of parameters uncertainties on the optimization of parameters of linear base isolator and system performance.

Keywords: linear base isolator, earthquake, optimization, uncertain parameters

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Authors: Reda Dzingelevičienė, Vytautas Abromaitis, Nerijus Dzingelevičius, Kęstutis Baranauskis, Saulius Raugelė, Malgorzata Mlynska-Szultka, Sergej Suzdalev, Reza Pashaei, Sajjad Abbasi, Boguslaw Buszewski

Abstract:

A unique hybrid technology was developed for the removal of COVID-19 specific contaminants from wastewater. Reactor testing was performed using model water samples contaminated with COVID-19 pharmaceuticals and microplastics. Different hydraulic retention times, concentrations of pollutants and dissolved ozone were tested. Liquid Chromatography-Mass Spectrometry, solid phase extraction, surface area and porosity, analytical tools were used to monitor the treatment efficiency and remaining sorption capacity of the spent adsorbent. The combination of advanced oxidation and adsorption processes was found to be the most effective, with the highest 90-99% and 89-95% molnupiravir and microplastics contaminants removal efficiency from the model wastewater. The research has received funding from the European Regional Development Fund (project No 13.1.1-LMT-K-718-05-0014) under a grant agreement with the Research Council of Lithuania (LMTLT), and it was funded as part of the European Union’s measure in response to the COVID-19 pandemic.

Keywords: adsorption, hybrid reactor system, pharmaceuticals-microplastics, wastewater

Procedia PDF Downloads 63