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IntroductionDespite the importance of national-level public health agencies in times of a pandemic, there is limited comparative understanding of their must-have and forgotten pandemic-related communication topics. MethodsTo fill this gap in the literature, this article presents an analysis of COVID-related communication topics by national-level health agencies in Italy, Sweden, and the United States using the IDEA (Internalization, Distribution, Explanation, Action) model on crisis message framing. The public health agencies included in the study are the Italian National Institute of Health (Istituto Superiore di Sanita;ISS), the Public Health Agency of Sweden (Folkhalsomyndigheten), and the Center for Disease Control and Prevention (CDC) in the US. ResultsBased on these agencies' Twitter posts (n = 856) in the first 3 months of the pandemic, the article reveals a greater attention paid to action oriented (e.g., disease prevention) and explanatory messages (e.g., disease trends) than to distribution (e.g., transmission) and internalizing messages (e.g., risk factors) in all three countries. The study also highlights differences in terms of referrals to other communication channels and communication topics, especially in terms of these agencies' emphasis on individual risk factors (related to the risk of a person suffering from serious COVID-19-related health consequences) and social risk factors (related to the chance of an individual to become infected with COVID-19 because of the social context). DiscussionThe study's findings call for better incorporation of information that is directly relevant to the receivers (internalizing messages) by public health agencies.
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The topic of non-contact diagnosis became a hot topic during COVID-19 and online consultation gained popularity. In this research, a deep learning-based autonomous limb evaluation system is developed for online consultation and remote rehabilitation training for people with physical limitations. Its main goal is to collect and analyze information about limb states. The patient can evaluate the limb state at home using the mobile app, and the doctor can view the data and connect with the patient via the web's chat module to offer diagnostic opinions. Deep learning is used for the Start/End Attitude Determination Model and OpenCV for the limb and hand evaluation model, with the results being uploaded to the server. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.
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The impact of the COVID-19 pandemic on health care is vast and continuing to unfold. As much progress related to breast cancer has resulted from screening and public health measures, we analyzed the stage at which patients with breast cancer presented for surgical consultation from 2019 to 2021. From 2019 to 2021, retrospective analysis was performed on breast cancer patients, comparing differences in patient demographics and cancer stage at diagnosis pre- and post-recommendation (COVID-era) to postpone mammographic screening on March 26, 2020. Proportion analysis was performed to identify similar percentages for each stage, and a weighed stage severity score with sign test was crafted to compare overall stage for a given year. The study included 1107 breast cancer patients from breast cancer surgery registry. These groups were similar demographically. We performed analysis comparing pre-COVID and COVID-era stage severity score. This showed a statistically higher stage at presentation when comparing pre-COVID to COVID-era data (P = .0027). Additionally, we identified a higher rate of stage 3 at presentation or greater in the COVID-era with 7.79% pre-COVID vs 12.3% COVID-era (P = .016). We found that in comparing pre-COVID to COVID-era data that breast cancer patients presented with higher stages, in particular, stage 3 or higher stage disease. This analysis reveals the impact of COVID on the multidisciplinary treatment of breast cancer patients. Additional efforts are needed to address the stage migration, the disproportionate burden of disease, and the access to care.
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Scientific journals play a critical role in disseminating knowledge, and staying up to date with research findings in a particular field can be challenging given the vast number of journals and research topics available. Therefore, there is a need for researchers to occasionally summarize the main research topics in order to help fellow researchers navigate the contents more effectively. In this context, this article aims to review the research topics published in the Problems of Education in the 21st Century journal between 2018 and 2022. A total of 285 s were retrieved from the Web of Science database and analyzed to identify the most common research topics and the contributing countries. The top 10 research topics identified were self-efficacy, distance education, professional development, critical thinking, foreign language, thinking skills, Covid-19, academic achievement, emotional intelligence, and special education. The authors of the papers came from 62 countries, with most of the papers coming from Türkiye, South Africa, Indonesia, Brazil, Slovakia, Czech Republic, Malaysia, Sweden, Lithuania, and Serbia. In conclusion, this study highlights the relevance and diversity of research topics in the Problems of Education in the 21st Century journal, underscoring the need for a nuanced, context-specific approach to education research. The findings of this study have important implications for researchers, policymakers, and educators seeking to address the key challenges and opportunities facing education in the 21st century.
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Building ventilation significantly impacts healthy and safe indoor conditions preventing airborne virus spread between people. Therefore, ventilation strategy is a globally essential and health-promoting research topic. Previous studies showed the importance of sufficient ventilation for diluting the virus concentration and reducing the infection risk. The present study investigates the probability of coronavirus infection in the typical room calculated with the Wells Riley proposes recommendations for further research of indoor airflow effect on the virus transmission. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
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The outbreak of COVID-19 has impacted traditional teaching methods in schools, and blended teaching in the post-pandemic has gradually become a hot topic of research in higher education. Computational thinking, as one of the core literacies to be acquired in the 21st century, can help students realize the importance of computers as well as enable them to solve specific problems more effectively when facing real-life situations. The article takes the C language programming course as an example, analyzes the problems faced in teaching in the post-pandemic, introduces the concept of computational thinking and integrates it into all aspects of blended teaching design, pays attention to students' individual differences, and proposes a blended teaching model based on computational thinking and puts it into practice. The results show that this teaching model can improve students' learning performance, exercise students' computational thinking skills, and promote blended teaching reform and students' personalized development. © 2022 IEEE.
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In research and policies, the identification of trends as well as emerging topics and topics in decline is an important source of information for both academic and innovation management. Since at present policy analysis mostly employs qualitative research methods, the following article presents and assesses different approaches – trend analysis based on questionnaires, quantitative bibliometric surveys, the use of computer-linguistic approaches and machine learning and qualitative investigations. Against this backdrop, this article examines digital applications in cultural heritage and, in particular, built heritage via various investigative frameworks to identify topics of relevance and trendlines, mainly for European Union (EU)-based research and policies. Furthermore, this article exemplifies and assesses the specific opportunities and limitations of the different methodical approaches against the backdrop of data-driven vs. data-guided analytical frameworks. As its major findings, our study shows that both research and policies related to digital applications for cultural heritage are mainly driven by the availability of new technologies. Since policies focus on meta-topics such as digitisation, openness or automation, the research descriptors are more granular. In general, data-driven approaches are promising for identifying topics and trendlines and even predicting the development of near future trends. Conversely, qualitative approaches are able to answer "why” questions with regard to whether topics are emerging due to disruptive innovations or due to new terminologies or whether topics are becoming obsolete because they are common knowledge, as is the case for the term "internet”.
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With the developments of medical artificial intelligence (AI), meta-data analysis, intelligence-aided drug design and discovery, surgical robots and image-navigated precision treatments, intelligent medicine (IM) as a new era evolved from ancient medicine and biomedical medicine, has become an emerging topic and important criteria for clinical applications. It is fully characterized by fundamental research-driven, new-generation technique-directed as well as state-of-the-art paradigms for advanced disease diagnosis and therapy leading to an even broader future of modern medicine. As a fundamental subject and also a practice-oriented field, intelligent medicine is highly trans-disciplinary and cross-developed, which has emerged the knowledge of modern medicine, basic sciences and engineering. Basically, intelligent medicine has three domains of intelligent biomaterials, intelligent devices and intelligent techniques. Intelligent biomaterials derive from traditional biomedical materials, and currently are endowed with multiple functionalities for medical uses. For example, micro-/nanorobots, smart responsive biomaterials and digital drugs are representative intelligent biomaterials which have been already commercialized and applied to clinical uses. Intelligent devices, such as surgical robots, rehabilitation robots and medical powered exoskeleton, are an important majority in the family of intelligent medicine. Intelligent biomaterials and intelligent devices are more and more closely integrated with each other especially on the occasions of intelligence acquisition, remote transmission, AI-aided analysis and management. In comparison, intelligent techniques are internalized in the former two domains and are playing a critical role in the development of intelligent medicine. Representative intelligent techniques of telemedicine, image-navigated surgery, virtual/augmented reality and AI-assisted image analysis for early-stage disease assessments have been employed in nowadays clinical operations which to a large extent relieved medical labors. In the past decades, China has been in the leading groups compared to international colleagues in the arena of intelligent medicine, and a series of eminent research has been clinically translated for practical uses in China. For instance, the first 5G-aided remote surgery has been realized in Fujian Province in January 2019, which for the first time validated their applicability for human uses. The surgical robots have found China as the most vigorous market, and more than 10 famous Chinese companies are developing versatile surgical robots for both Chinese people and people all over the world. China also applied AI techniques to new drug developments especially in early 2020 when COVID-19 epidemic roared, and several active molecules and drug motifs have been discovered for early-stage COVID-19 screening and treatments. Based on the significance of intelligent medicine and its rapid developments in both basic research and industrials, this review summarized the comprehensive viewpoints of the Y6 Xiangshan Science Conferences titled with Fundamental Principles and Key Technologies of Intelligent Medicine, and gave an in-depth discussion on main perspectives of future developments of the integration of biomaterial and devices, the integration of bioinformatics and medical hardware, and the synergy of biotechnology and intelligence information. It is expected that this featuring article will further promote intelligent medicine to an even broader community not only for scientists but also for industrials, and in the long run embrace a perspective future for its blooming and rich contributions in China in the coming 5 years. © 2023 Chinese Academy of Sciences. All rights reserved.
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WHAT DOES IT MEAN TO SPEAK of "global Classics” in the "post-COVID era?” Reaching the post-COVID period may have eluded us, but the notion of a global Classics—Classics as it is received outside the West—has been a topic of serious interest in the field over the past decade, even in advance of the new opportunities for conferences and conversations across time zones made possible by Zoom and the virtual office.1 Paradoxically enough, the question of how to read—and interpret—the texts of the Classical tradition in a globalized world arises just as the field is facing critique from within, as texts once standard in university curricula are condemned for their historical use in the service of empire, expansion, ideology, and propping up hierarchies of class, race, and gender. At a 2019 conference on "Classics and Global Humanities” at the University of Ghana,2 (non-globalized) Classics' involvement in the ideologies of colonialism was openly acknowledged, but new frameworks were also suggested within which these texts could speak to topics relevant to the present, spurring readers to discuss such subjects as academic freedom and politics, race in the canon, citizenship and migration, globalization and education, and more.3 As Erin Mee (2010: 314) puts it in her review essay of Classics in Post-colonial Worlds and Crossroads in the Black Aegean: Oedipus, Antigone, and Dramas of the African Diaspora, "What better way to challenge colonialism (either before, during, or after the ‘official' period of colonization) than by using the very tools that colonial powers used to justify their cultural superiority and therefore their dominance?”4 Other voices agree: Here, then, "global Classics” strives to be truly global by cutting across social and economic status in its search for representative texts—representative, perhaps, of "the human condition,” to the extent that is possible. Unfortunately, the Yale-NUS liberal arts college (and its vibrant international student body with it) has just been shut down by policy makers at NUS: the challenges of teaching a broad-ranging core in a country without complete freedom of speech apparently proved to be too much.11 Here politics confronts the habits of mind of the liberal self, which is often prompted by the classical texts of any culture to ask questions about human beings' relationship to themselves and their society that do not mesh well with nationalism, autocracy, or the control of propaganda.
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The COVID-19 pandemic has had profound effects on the everyday behaviors of all patients. At the same time, the United States population is aging, and an increasing portion of traumatically injured patients are geriatric. Our study aims to examine the effects of the COVID-19 pandemic on the geriatric trauma population. We performed a retrospective review of the trauma database from our single institution level I trauma center examining pandemics impact on geriatric trauma demographics, mechanism of injury, injury severity, hospitalization characteristics, and alcohol use. Data during the pandemic was compared to the prior 3 years and controlled for seasonality. Statistical analysis demonstrated an increase in duration of mechanical ventilation and alcohol use during the pandemic while other factors remained stable. This shows the need for targeted alcohol assessment in the geriatric trauma population during periods of social isolation and additional research into the effects of the COVID-19 on trauma patients.
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The mission of WONCA Europe is the development of General Pratice / Family Medicine (GP/FM) discipline in Region Europe by addressing the current challenges of health and healthcare. The theme of this meeting is "Optimising the organisation of family medicine practice' to accomplish this vision. When we checked the meaning of "organisation' in the Webster dictionary, the words "forming a business for a particular purpose,' "certain order to be found or used easily' and the "process of planning' emerged and attracted our attention. The crucial discussion describing primary care (PC) organisation was based on the same concepts (if we summarise the words as needs, structure and delivery) after many years.Today the authors consolidated several frameworks and defined: (1) population needs;(2) organisation and structure of PC practices;(3) delivery of PC services and (4) patient and population health outcomes as the four domains and added connecting constructs to link the domains: accessibility, appropriateness, productivity, efficiency, effectiveness, equity and integration. Knowledge about the relationship between structure and process (including the interpersonal and societal exchange/performance of GP/FP) and outcome derives from the organisational, behavioural and healthcare sciences. So we need to partner with interprofessional and multisectoral teams to evaluate detailed research on PC organisation.In EGPRN-Istanbul, we hope we will discuss weaknesses and strengths, opportunities and threats of PC organisation in different conditions and develop many approaches during this meeting under the light of well-planned and applied trials or controlled observational studies, evidence, collaboration and collectivity.
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The port is the basic support for regional economic development and the global allocation of resources. With the rapid development of China's economy and growing ecological awareness, the assessment of port and regional efficiency has received unprecedented attention. In the current context of the COVID-19 pandemic, how the port and its region will be coordinated under the common goal of development has become a hot topic. In this study, the port subsystem (P-subsystem) and the regional subsystem (R-subsystem) are unified into the port–region system (PR system), and a new meta-frontier two-stage data envelopment analysis model is constructed to evaluate the P-subsystem efficiency and the environmental efficiency of the PR system. This research also measures the port–regional coordination level using the coordination index and explores the inefficiency of the PR system with the help of management improvement and technology improvement indices. Main results show that the overall efficiency of the Chinese PR system is increasing. The technological level of the PR system in coastal areas is close to the optimal level. The inefficiency of the Chinese PR system is mainly affected by management inefficiency. The coordination of regional and port development in China is also poor. Finally, on the basis of the research findings, this study provides targeted countermeasure suggestions to promote the efficiency enhancement and coordinated development of the PR system. © 2023 Elsevier Ltd
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Arguably, researching the trade and trafficking of natural resources, such as wildlife crime, environmental crime, trafficking of natural commodities, unregulated and unreported fishing, factory farming, human–wildlife conflict, to name a few examples, involves all four areas of threat. [...]research can be extremely emotionally taxing for both the researcher and research participants. [...]it offers the researcher an opportunity to think through potentially "risky”, dangerous, harmful, and ethically compromising fieldwork situations, while reflecting on their own positionality and protection of themselves, research participants, and data. [...]they are required to fill out risk assessments and complete specialized training for hostile environments. With increasing use of qualitative research methods within the wildlife trafficking research field, coupled with the growing importance of human–wildlife interactions exacerbated by the COVID-19 pandemic, this disparity in ethical regulations needs imminent addressing. [...]with the current emphasis on ‘decoloniality', an ethical review process could ensure that parachute social science is avoided, and equity and sustainable collaboration between stakeholders are foregrounded in the research.
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Various aspects of artificial intelligence (AI) have become of significant interest to academia and industry in recent times. To satisfy these academic and industrial interests, it is necessary to comprehensively investigate trends in AI-related changes of diverse areas. In this study, we identified and predicted emerging convergences with the help of AI-Associated research s collected from the SCOPUS database. The bidirectional encoder representations obtained via the transformers-based topic discovery technique were subsequently deployed to identify emerging topics related to AI. The topics discovered concern edge computing, biomedical algorithms, predictive defect maintenance, medical applications, fake news detection with block chain, explainable AI and COVID-19 applications. Their convergences were further analyzed based on the shortest path between topics to predict emerging convergences. Our findings indicated emerging AI convergences towards healthcare, manufacturing, legal applications, and marketing. These findings are expected to have policy implications for facilitating the convergences in diverse industries. Potentially, this study could contribute to the exploitation and adoption of AI-enabled convergences from a practical perspective. © 2023 Korean Society for Internet Information. All rights reserved.
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PurposeWork-family conflict is an important topic which had an evolution, starting from a static definition, where work and family domains were divided, to a more dynamic and complex balance. COVID-19 has influenced society and created a significant distress among families and working activity, and this topic has been characterised by a major interest, considering some old definitions where this balance was considered problematic but not as an enriching opportunity.Design/methodology/approachThe authors used SCOPUS to find all records mentioning work-family conflict, by considering book, article and review, excluding conference paper and considering only records written in English language. After a duplicated and not pertinent record removal, the authors obtained a number of 675 records. The authors considered 437 records from SCOPUS to create a cluster map.FindingsUsing SCOPUS and VOSviewer the authors have clustered 5 different areas, which are regrouped in next clusters considering keywords with most co-occurrence and significancy: Work-life balance and burnout gender cluster job stress and performance social and family support job satisfaction.Research limitations/implicationsCluster map is origined only by SCOPUS database.Originality/valueThis work aims to find a state of art about this topic, creating hypothesis where this problem has been exacerbated by 2020 due to important society modifications created by COVID-19, where recent evolution of work-family balance has been complicated by papers which come back to consider this balance as problematic.
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Blockchain is an emerging decentralized data collection, sharing, and storage technology, which have provided abundant transparent, secure, tamper-proof, secure, and robust ledger services for various real-world use cases. Recent years have witnessed notable developments of blockchain technology itself as well as blockchain-enabled applications. Most existing surveys limit the scopes on several particular issues of blockchain or applications, which are hard to depict the general picture of current giant blockchain ecosystem. In this paper, we investigate recent advances of both blockchain technology and its most active research topics in real-world applications. We first review the recent developments of consensus and storage mechanisms and communication schema in general blockchain systems. Then extensive literature review is conducted on blockchain-enabled Internet of Things (IoT), edge computing, federated learning, and several emerging applications including healthcare, COVID-19 pandemic, online social network, and supply chain, where detailed specific research topics are discussed in each. Finally, we discuss the future directions, challenges, and opportunities in both academia and industry. © 2020 Tsinghua University Press.
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Classifying whether collected information related to emerging topics and domains is fake/incorrect is not an easy task because we do not have enough labeled data in the domains. Given labeled data from source domains (e.g., gossip and health) and limited labeled data from a newly emerging target domain (e.g., COVID-19 and Ukraine war), simply applying knowledge learned from source domains to the target domain may not work well because of different data distribution. To solve the problem, in this paper, we propose an energy-based domain adaptation with active learning for early misinformation detection. Given three real world news datasets, we evaluate our proposed model against two baselines in both domain adaptation and the whole pipeline. Our model outperforms the baselines, improving at least 5% in the domain adaptation task and 10% in the whole pipeline, showing effectiveness of our proposed approach. © 2022 IEEE.
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Recent research on argumentative dialogues has focused on persuading people to take some action, changing their stance on the topic of discussion, or winning debates. In this work, we focus on argumentative dialogues that aim to open up (rather than change) people's minds to help them become more understanding to views that are unfamiliar or in opposition to their own convictions. To this end, we present a dataset of 183 argumentative dialogues about 3 controversial topics: veganism, Brexit and COVID-19 vaccination. The dialogues were collected using the Wizard of Oz approach, where wizards leverage a knowledge-base of arguments to converse with participants. Open-mindedness is measured before and after engaging in the dialogue using a questionnaire from the psychology literature, and success of the dialogue is measured as the change in the participant's stance towards those who hold opinions different to theirs. We evaluate two dialogue models: a Wikipedia-based and an argument-based model. We show that while both models perform closely in terms of opening up minds, the argument-based model is significantly better on other dialogue properties such as engagement and clarity. © 2022 Association for Computational Linguistics.
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The most common technique of analyzing data assembled to draw conclusions concerning the knowledge they contain, a lot of} with the utilization of specialized frameworks and programmes, is data examination. Researchers and professionals often use data analysis techniques and innovations to validate or, on the opposite hand, refute logical models, enabling organizations to form higher business decisions. Information analysis is turning into more and more popular in several fields, together with healthcare. Not solely will illustration play an enormous role in naturally displaying the results of knowledge analysis, however additionally throughout the whole method of collecting, cleaning, Associate in Nursing analyzing, and sharing information. this text outlines an approach for victimization Tableau as a business insight tool to represent and analyses aid data intelligently. Strategies: beginning with making the Tableau Work Space Individual ability 10.3, this analysis illustrates the foremost prevailing model-based technique of comprehending and visualizing Coronavirus data. © 2022 IEEE.