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Companies continuously produce several documents containing valuable information for users. However, querying these documents is challenging, mainly because of the heterogeneity and volume of documents available. In this work, we investigate the challenge of developing a Big Data Question Answering system, i.e., a system that provides a unified, reliable, and accurate way to query documents through naturally asked questions. We define a set of design principles and introduce BigQA, the first software reference architecture to meet these design principles. The architecture consists of high-level layers and is independent of programming language, technology, querying and answering algorithms. BigQA was validated through a pharmaceutical case study managing over 18k documents from Wikipedia articles and FAQ about Coronavirus. The results demonstrated the applicability of BigQA to real-world applications. In addition, we conducted 27 experiments on three open-domain datasets and compared the recall results of the well-established BM25, TF-IDF, and Dense Passage Retriever algorithms to find the most appropriate generic querying algorithm. According to the experiments, BM25 provided the highest overall performance. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
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The major goal of this study is to trace the emergence of SFC-related research across time, using a thematic map and a list of corresponding publications. In addition, this study aims to determine the author who has made the most significant contribution to this particular field. This study provides a comprehensive bibliometric analysis of the historical development and current trends in sustainable food consumption research, examining 2265 articles published between 1990 and 2023. Using the bibliometrics package of R Studio software version 4.2.1 and its Biblioshiny package, articles from the Scopus and Web of Science databases are examined. In the field of sustainable food consumption, we identify five distinct research phases: initial stagnation, infant growth, post-economic crisis, expanding phase and COVID-19 and post-pandemic. While research on broader sustainability topics can be traced back to the early 20th century, a very limited number of articles on sustainable food consumption was published in the 1990s. However, the number of publications increased incrementally over time, with a notable uptick in interest around 2015, and the subject was still being discussed in 2022. The emergence of the COVID-19 pandemic marked the beginning of the most recent phase of research, which analyzed the consumption patterns of consumers before and after the pandemic. Our study highlights key authors, documents and sources related to sustainable food consumption. The United States, Italy and the United Kingdom emerged as the most active contributors to the research on sustainable food consumption and were additionally the countries with the largest global market shares for organic products. Major sub-themes including organic food, food waste, sustainable development and food security, together with consumer behavior and organic products appeared as being the most researched sub-themes of recent times. The results of this study suggest that more research is related to sustainable food consumption in countries with a low organic food market share. In addition, the investigation of actual data on food waste, carbon footprints and greenhouse gas emissions resulting from food production and consumption is essential to gain holistic insights.
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The immunity (or vaccine) passport of the coronavirus pandemic, as a concept and object, is not unprecedented. This health and identity document features a history spanning over half-a-millennium and appearing across diverse geopolitical and sociocultural contexts. This article presents a documentary history of the immunity passport and its heterogeneous material instantiations, uses and effects across divergent historical settings. It illuminates how the immunity passport has helped shaped identities and public health, as well as impacted individual and institutional agency, during health crises. Four historical cases are explored, including the plagues ravaging the Renaissance Mediterranean region, the 1665 Great Plague of London, the yellow fever outbreaks in the antebellum slave-era southern USA and the chronic cholera conditions confronting colonial-era British India. Although disparate, these historical cases share the immunity passport as a non-pharmaceutical intervention into their respective health crises that played important roles in people's lives during these troubled times.
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Featured ApplicationThe research has a potential application in the field of fake news detection. By using the feature extraction technique, TwIdw, proposed in this paper, more relevant and informative features can be extracted from the text data, which can lead to an enhancement in the accuracy of the classification models employed in these tasks.This research proposes a novel technique for fake news classification using natural language processing (NLP) methods. The proposed technique, TwIdw (Term weight–inverse document weight), is used for feature extraction and is based on TfIdf, with the term frequencies replaced by the depth of the words in documents. The effectiveness of the TwIdw technique is compared to another feature extraction method—basic TfIdf. Classification models were created using the random forest and feedforward neural networks, and within those, three different datasets were used. The feedforward neural network method with the KaiDMML dataset showed an increase in accuracy of up to 3.9%. The random forest method with TwIdw was not as successful as the neural network method and only showed an increase in accuracy with the KaiDMML dataset (1%). The feedforward neural network, on the other hand, showed an increase in accuracy with the TwIdw technique for all datasets. Precision and recall measures also confirmed good results, particularly for the neural network method. The TwIdw technique has the potential to be used in various NLP applications, including fake news classification and other NLP classification problems.
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Collecting material related to the COVID-19 pandemic is one of the essential works of public humanities. Within this context, the community archive project titled "????????@????(Corona Archive @ Kansai University)" began as a digital public history practice. However, promoting public humanities, which has not yet taken root in Japan, has been met with various challenges. Introducing the Corona Archive @ Kansai University, this chapter answers the following questions: What are the challenges in engaging the public in public humanities activities in Japan? How can public humanities practitioners ensure that public humanities take root in Japan? How should public humanities practitioners communicate and disseminate this work?. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022, corrected publication 2023.
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PurposeHow to extract useful information from a very large volume of literature is a great challenge for librarians. Topic modeling technique, which is a machine learning algorithm to uncover latent thematic structures from large collections of documents, is a widespread approach in literature analysis, especially with the rapid growth of academic literature. In this paper, a comparison of topic modeling based literature analysis has been done using full texts and s of articles.Design/methodology/approachThe authors conduct a comparison study of topic modeling on full-text paper and corresponding to assess the influence of the different types of documents been used as input for topic modeling. In particular, the authors use the large volumes of COVID-19 research literature as a case study for topic modeling based literature analysis. The authors illustrate the research topics, research trends and topic similarity of COVID-19 research by using Latent Dirichlet allocation (LDA) and topic visualization method.FindingsThe authors found 14 research topics for COVID-19 research. The authors also found that the topic similarity between using full-text paper and corresponding is higher when more documents are analyzed.Originality/valueFirst, this study contributes to the literature analysis approach. The comparison study can help us understand the influence of the different types of documents on the results of topic modeling analysis. Second, the authors present an overview of COVID-19 research by summarizing 14 research topics for it. This automated literature analysis can help specialists in the health and medical domain or other people to quickly grasp the structured morphology of the current studies for COVID-19.
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Open-retrieval question answering systems are generally trained and tested on large datasets in well-established domains. However, low-resource settings such as new and emerging domains would especially benefit from reliable question answering systems. Furthermore, multilingual and cross-lingual resources in emergent domains are scarce, leading to few or no such systems. In this paper, we demonstrate a cross-lingual open-retrieval question answering system for the emergent domain of COVID-19. Our system adopts a corpus of scientific articles to ensure that retrieved documents are reliable. To address the scarcity of cross-lingual training data in emergent domains, we present a method utilizing automatic translation, alignment, and filtering to produce English-to-all datasets. We show that a deep semantic retriever greatly benefits from training on our English-to-all data and significantly outperforms a BM25 baseline in the cross-lingual setting. We illustrate the capabilities of our system with examples and release all code necessary to train and deploy such a system1 © 2023 Association for Computational Linguistics.
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The COVID-19 pandemic has had a significant impact on railway services, such as restrictions on transport services, introduction of strict anti-pandemic measures at railway stations, and a ban on free travel. This study simulated passenger flow at the Bratislava railway station before and during the COVID-19 pandemic. This study provides an overview of the number of tickets sold, average waiting time of passengers, and time spent by passengers at ticket windows during peak and off-peak hours. The mass-service theory was used as the operational research method. In addition, the user interface of the AnyLogic simulation programme and practical results of the passenger flow simulations at the Bratislava railway station are discussed. The simulation results showed that passenger movement at the railway station was neither synchronised nor systematic. This concurred with the measures implemented during the pandemic that were considered unacceptable. New methods for selling travel documents at Slovak railway stations were proposed, which contribute to better spatial organisation of the stations, faster customer service at ticket windows, and negating infection risks.
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Research findings have been widely used as evidence for policy-making. The internationalisation of research activities has been increasing in recent decades, particularly during the COVID-19 pandemic. Previous studies have revealed that international research collaboration can enhance the academic impact of research. However, the effects that international research collaboration exerts on the policy impact of research are still unknown. This study aims to examine the effects of international research collaboration on the policy impact of research (as measured by the number of citations in policy documents) using a causal inference approach. Research articles published by the journal Lancet between 2000 and 2019 were selected as the study sample (n = 6098). The number of policy citations of each article was obtained from Overton, the largest database of policy citations. Propensity score matching analysis, which takes a causal inference approach, was used to examine the dataset. Four other matching methods and alternative datasets of different sizes were used to test the robustness of the results. The results of this study reveal that international research collaboration has significant and positive effects on the policy impact of research (coefficient = 4.323, p < 0.001). This study can provide insight to researchers, research institutions and grant funders for improving the policy impact of research. © The Author(s) 2023.
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Physical documents may easily be converted into digital versions in the modern digital era by employing scanning software and the internet. The day when this activity needed printers and scanners is long gone. Nowadays, even our smartphones and cameras may be used to quickly convert paper documents into digital ones. This is especially useful in the wake of the COVID-19 pandemic, where the ability to share and access documents online is more important than ever. This study proposes an application for illiterate people to quickly translate scanned papers or photos into their native language and save them in a digital format. The Application makes use of image processing methods and has capabilities including PDF conversion, image colour adjustment, cropping, and Optical Character Recognition (OCR). A user-friendly application, developed using the Flutter Framework and programmed in Python and Dart, serves as the interface for the system. The proposed application is cross-platform and works with a variety of gadgets. This method intends to increase accessibility and productivity for illiterate people in the digital age by integrating image processing with language translation. © 2023 IEEE.
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Visualization is integral to investigating information hidden in data and providing users with intuitive feedback for decision-making. No matter the field a data set describes, inspecting the data visually will yield fruitful insights into the trends and statistics. Over the past calendar year, COVID-19 vaccines have become increasingly available for much of the population. However, the CDC (Centers for Disease Control and Prevention) fails to consider multiple sets of pandemic data in a side-by-side view and synchronize multiple key factors in one web page, limiting medical professionals and individuals to seeing, comparing, and interacting with complete data visualization. To analyze the coronavirus and vaccination data collected from multiple sources, effectively displaying them is critically important for interpreting the pandemic transmission pattern and vaccine efficiency. This paper presents new algorithms for innovative data visualizations that provide users with intuitive feedback and enable them to see a complete story of where the data is concerned. The information derived from our developed web-based data visualization will aid healthcare professionals and everyday citizens in moving forward as the pandemic progresses. © 2023 IEEE.
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PurposeThe COVID-19 pandemic has had a significant and worldwide influence on healthcare delivery, and it has significantly increased the pace at which digital technology is being used. Blockchain, one of these developing digital technologies, is distinguished by a number of properties. This study focuses on a blockchain-enabled healthcare supply chain. The purpose of this work is to investigate how blockchain technology (BCT) benefits the performance of healthcare supply chain management (HSCM).Design/methodology/approachThe present study is based on the empirical research. Blockchain Technology (BCT), Healthcare Sustainable Supply Chain Practices (HSSCP), Healthcare Supply Chain Performance (HSCP) and Stakeholders' Involvement (SI) practices are identified from the literature review and hypotheses are framed to check their interrelationship. For testing of hypothesis, a questionnaire was developed. Data collection was done by healthcare professionals via Google docs. The IBM SPSS version 22.0 was used to analyze the data and IBM SPSS AMOS 22.0 software was used for the development of structural modal. The data was collected through the Google form from the stakeholders of healthcare sector and analyzed through Structural Equation Modelling.FindingsThis research is focused on adoption of BCT enabled Healthcare Sustainable Supply Chain to improve HSCP. From the result, it had been found that BCT is positively effecting the stakeholder's involvement (SI) and HSSCP practices. Cumulatively, they positively impact the performance of HSCP. From this study, it is found that adoption of BCT enabled Healthcare Sustainable Supply Chain succours to combat COVID-19 situation.Originality/valueThis study attempts to show the potential benefits of the adoption of BCT enabled HSSCP to improve HSCP.
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This study aims to explore the potential for tourist scams that have occurred in the tourism industry. This research uses a bibliometric system. The data source comes from Scopus and SINTA indexed papers. The number of documents used is 110 papers. Based on the results of the study shows that there are 28 tourist scam schemes. Of the 28 schemes, price scams are the most common schemes in 48 papers. Other methods, such as corruption (38 documents), service scams (34 articles), fake products/souvenirs (23 articles), and food scams (30 papers). Meanwhile, in Indonesia, there were 17 tourist scam schemes found.
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La eficacia de las estrategias de la administración pública se ha medido en la forma en que manejan las pandemias y los efectos en cadena que se producen en el medio ambiente o la sociedad, y en este caso, en el abastecimiento de agua rural en México en tiempos de pandemia. El acceso al agua en las zonas rurales de México y cómo el gobierno ha manejado el aumento de la demanda durante las pandemias se exploran mediante una revisión sistemática de 51 documentos. El sistema de agua de México está por debajo de la media y es necesario realizar más inversiones en los planes de gestión comunitaria. Se requiere la participación de la ciudadanía en el desarrollo de esquemas de gestión comunitaria para encontrar una solución a la demanda y oferta cambiantes.Alternate :The efficacy of public administration strategies has been gauged on how they handle pandemics and the knock-on effects that occur on the environment or society, and in this case, in the rural water supply in Mexico in times of pandemics. Water access in rural Mexico and how the government has managed the rise in demand during pandemics are explored using a systematic review into 51 documents. Mexico's water system is below par and there is a need for more investments to be pumped into community management schemes. The involvement of the public in the development of community management schemes is necessary to find a solution to the changing demand and supply.
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The impact of the Covid-19 pandemic demonstrated the importance of urban forests for human well-being at a time of tight constraints, when large forests close to urban areas were in high demand. Increased use affects the management of territories. Urban forests play an important role in providing ecosystem services. Urban forests show a close link between ecosystem services and forest functions. A literature review was carried out, exploring the ecosystem services and specific urban forest services provided by such territories. This article examines the experience of the Ogres Zilie kalni during the Covid-19 pandemic, taking into account the peculiar functions of urban forests. Different types of recreation that take place in the Ogres Zilie kalni, and their impact on park management are discussed. The aim of the article is to analyse and present the challenges of urban forest governance and management under the influence of Covid-19, looking through the functions of urban forests. Taking into account the classifications of ecosystem services available in Zilie kalni, zoning and assessment of the territory have been carried out. Cartographic material has been created based on practical experience and employee interviews.The practical experience of territory management gained during Covid-19 is important and should be taken into account in the future development of green spaces, respecting the new habits of visitors potentially affected by the pandemic, where one of the most important proposals is to develop more small localised recreation areas on smaller
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The coronavirus disease 2019 pandemic has tested the response capacity of the international community. This article analyses the due diligence principle and the various international legal instruments that restate it in an assessment of the possible actions that states could have taken to avoid or, at least, contain the initial outbreak of the pandemic.
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This article explores the lived daily experiences of street vendors operating along the Main North 1 Road in the CBD of Maseru, Lesotho. This exploration considers how street vendors access and negotiate a claim for the right to the street. The challenges confronting these vendors in their daily hustling, including COVID-19 restrictions, are also examined. A narrative inquiry research design informs this article with data collected from interviews with purposively selected street vendors from Maseru. This primary data was triangulated with document analysis to increase the validity of the findings. The findings highlight strategies employed by vendors in Maseru that include integrating with the formal enterprises, diversifying their trades, resisting and frustrating certain decisions by the local authorities, and contributing to urban blight. A framework for interrogating and understanding street vending and its nuances is postulated based on the findings from Maseru. The article strongly appeals to the authorities to find more benign ways of integrating street vending into the production of cities. © 2023, The Author(s).
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PurposeThe COVID-19 pandemic has disrupted the supply chains, and this brought researchers and practitioners to think about more on circular supply chains (CSC). The CSC concept has been discussed in the literature more than a decade. This study aims to find out the theoretical roots of CSC by analyzing scholarly articles in literature.Design/methodology/approachThis paper uses document cocitation analysis for reaching this aim. After retrieving data from Web of Science database, this paper explores data set by considering used references of these publications and clusters them based on their title terms and visualizes them by using cosine similarity index.FindingsThis paper concludes that CSC is mainly discussed along with sustainability, sustainable supply chains and green supply chains, where the focus is integrating circular economy principles to supply chain management (SCM). On the other hand, although resiliency is an essential characteristic of SCM, contribution of CSC to supply chain resilience is neglected in the literature.Research limitations/implicationsCSC will gain importance in near future to increase national/firm productivity, and findings of this paper will give researchers insights for furthering their studies.Social implicationsTo avoid supply chain and market collapse caused by natural disruptions, supply chain resilience is of paramount importance. According to the findings of this paper, the authors believe that business resilience in COVID-19-restricted environment may have exit point by using circular perspective.Originality/valueThe importance of CSC has increased due to the disruptions caused by the COVID-19 pandemic. Therefore, this unique study was undertaken to investigate the evolution of this crucial topic with evidence from the literature through a cocitation analysis.
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PurposeUsing science mapping analysis approach and co-word analysis, the present study explores and visualizes research fields and thematic evolution of the coronavirus. Based on this method, one can get a picture of the real content of the themes in the mentioned thematic area and identify the main minor and emerging themes.Design/methodology/approachThis study was conducted based on co-word science mapping analysis under a longitudinal study (from 1988 to 2020). The collection of documents in this study was further divided into three subperiods: 1988–1998, 1999–2009 and 2010–2020. In order to perform science mapping analysis based on co-word bibliographic networks, SciMAT was utilized as a bibliometric tool. Moreover, WoS, PubMed and Scopus bibliographic databases were used to download all records.FindingsIn this study, strategic diagrams were demonstrated for the coronavirus research for a chronological period to assess the most relevant themes. Each diagram depended on the sum of documents linked to each research topic. In the first period (1988–1998), the most centralizations were on virology and evaluation of coronavirus structure and its structural and nonstructural proteins. In the second period (1999–2009), with due attention to high population density in eastern Asia and the increasing number of people affected with the new generation of coronavirus (named severe acute respiratory syndrome virus or SARS virus), publications have been concentrated on "antiviral activity.” In the third period (2010–2020), there was a tendency to investigate clinical syndromes, and most of the publications and citations were about hot topics like "severe acute respiratory syndrome,” "coronavirus” and "respiratory tract disease.” Scientometric analysis of the field of coronavirus can be regarded as a roadmap for future research and policymaking in this important area.Originality/valueThe originality of this research can be considered in two ways. First, the strategic diagrams of coronavirus are drawn in four thematic areas including motor cluster, basic and transversal cluster, highly developed cluster and emerging and declining cluster. Second, COVID-19 is mentioned as a hot topic of research.
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Behavioural non-pharmaceutical interventions (NPIs) (e.g., mask wearing, quarantine, restriction on gatherings, physical distancing) have been used to interrupt transmission of COVID-19 and to reduce the impacts of the pandemic. The aim of this scoping review was to document the efficacy of behavioural NPIs to positively influence COVID-19 outcomes. Following PRISMA guidelines, a systematic search was conducted of PubMed, ScienceDirect, Psych INFO, Medline, CINAHL and Scopus for studies published between January 2020 and February 2023. Seventy -seven studies were eligible to be included in the review. Majority of the studies were conducted in high-income countries, with fewer studies in low- or middle-income countries. School closure, mask wearing, and non-essential business closure and shelter-in-place orders were the most prevalent NPIs investigated. School closure and mask wearing reported high effectiveness while shelter-in-place orders reported less effectiveness. Shelter-in-place orders when used in conjunction with other measures, did not enhance effectiveness. Public event bans, physical distancing, handwashing, and travel restrictions were largely effective, while the effectiveness of gathering restrictions depended on the limitation on numbers. Early implementation was associated with a higher effectiveness in reducing COVID-19 cases and deaths, the use of behavioural NPIs in combinations was reported to yield more effective results. Moreover, behavioural NPIs were reported to be dependent on their consistent use and were difficult behaviours to maintain, highlighting the need for behavioural change. This review highlighted the effectiveness of behavioural NPIs to positively influence COVID-19 reduction outcomes. Further research to promote country- and context-specific documents that will enhance the effectiveness of behavioural NPIs.